diff --git a/.github/CODEOWNERS b/.github/CODEOWNERS new file mode 100644 index 0000000..4eca8f2 --- /dev/null +++ b/.github/CODEOWNERS @@ -0,0 +1 @@ +* @browserbase/gtm \ No newline at end of file diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md new file mode 100644 index 0000000..f904201 --- /dev/null +++ b/.github/PULL_REQUEST_TEMPLATE.md @@ -0,0 +1,14 @@ +## Summary + + + +## Type of Change + + + +- [ ] Bug fix (non-breaking change that fixes an issue) +- [ ] New feature (non-breaking change that adds functionality) +- [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected) +- [ ] Documentation update +- [ ] Performance improvement +- [ ] Refactoring (no functional changes) \ No newline at end of file diff --git a/.github/dependabot.yml b/.github/dependabot.yml new file mode 100644 index 0000000..5a05e07 --- /dev/null +++ b/.github/dependabot.yml @@ -0,0 +1,11 @@ +version: 2 +updates: + # Enable version updates for npm + - package-ecosystem: "npm" + directory: "/" + schedule: + interval: "weekly" + open-pull-requests-limit: 5 + commit-message: + prefix: "chore(deps):" + include: "scope" diff --git a/.gitignore b/.gitignore index 7d1f3ee..e8b1129 100644 --- a/.gitignore +++ b/.gitignore @@ -123,4 +123,22 @@ temp/ # Test artifacts test-results/ -playwright-report/ \ No newline at end of file +playwright-report/ + +# Claude Code +.claude/ + +# venv +venv/ +.venv/ + +# Python +__pycache__/ +*.py[cod] +*$py.class +*.so +.Python +*.egg-info/ +.pytest_cache/ +.mypy_cache/ +.ruff_cache/ \ No newline at end of file diff --git a/README.md b/README.md index 4cf7e87..254f7dd 100644 --- a/README.md +++ b/README.md @@ -1,90 +1,46 @@ # Browserbase Integrations -**A comprehensive monorepo of production-ready integrations for Browserbase - the headless browser infrastructure for AI agents and web automation.** +**Production-ready integrations for Browserbase -- the complete platform to build and deploy agents that browse and interact with the web like humans.** -Browserbase provides scalable, reliable browser infrastructure that powers the next generation of AI applications. This repository contains officially maintained integrations with popular frameworks, libraries, and platforms to help you build powerful web automation and AI agent solutions. +Browserbase provides the infrastructure and developer primitives to power the next generation of browser agents. This repository contains officially maintained integrations with popular frameworks, libraries, and platforms. -## 🚀 What is Browserbase? +## What is Browserbase? -Browserbase is headless browser infrastructure designed specifically for AI agents and web automation at scale. It provides: +Browserbase is the browser agent platform -- one API key, everything your agent needs to browse the web: -- **Browser sessions** that scale automatically -- **Anti-detection capabilities** to bypass bot protection -- **Visual debugging** with session recordings and screenshots -- **Global infrastructure** for low-latency access worldwide -- **Stealth technology** to ensure reliable web interaction +- **Headless Browsers**: programmatic access to fleets of headless browsers at scale with globally distributed infrastructure, isolated sessions, and rich observability +- **Fetch and Search APIs**: agents can quickly search and fetch LLM context from the web for fast, token-efficient decisions +- **Agent Identity**: enable agents to access any website through strategic partnerships and a dedicated research team +- **Functions**: deploy and run agents on Browserbase for faster, more secure execution +- **Model Gateway**: access major models via Stagehand with unified billing under your Browserbase API key +- **Stagehand**: the AI SDK for browser agents -- replaces rigid selectors with natural language browser interactions that self-heal when pages change -## 📦 Available Integrations - -Our integrations are organized by platform and use case, each with comprehensive documentation and examples: - -### 🤖 AI Agent Frameworks - -#### [**CrewAI Integration**](./examples/integrations/crewai/README.md) -Enable your CrewAI agents to browse the web like humans with the `BrowserbaseLoadTool`. Perfect for creating intelligent agent crews that need to gather real-time web data, extract content from complex pages, and interact with modern web applications. - -**Key Features:** -- Extract text from JavaScript-heavy websites -- Capture screenshots and visual content -- Bypass anti-bot mechanisms -- Seamless integration with CrewAI's tool ecosystem - -#### [**AgentKit Integration**](./examples/integrations/agentkit/) -Powerful integrations for AgentKit workflows with both Browserbase and Stagehand implementations: - -- **[Browserbase Implementation](./examples/integrations/agentkit/browserbase/README.md)** - Direct Browserbase integration for AgentKit -- **[Stagehand Implementation](./examples/integrations/agentkit/stagehand/README.md)** - AI-powered web automation using Stagehand - -#### [**LangChain Integration**](./examples/integrations/langchain/README.md) -Integrate Browserbase with LangChain's ecosystem for advanced AI applications. Build chains that can browse, extract, and interact with web content as part of larger AI workflows. - -#### [**Browser-Use Integration**](./examples/integrations/browser-use/README.md) -Streamlined browser automation for AI applications with a focus on simplicity and reliability. - -### 🏗️ Development & Deployment Platforms - -#### [**Vercel AI Integration**](./examples/integrations/vercel/README.md) -Enhance your Vercel applications with web-browsing capabilities. Build Generative User Interfaces that can access real-time web data and create dynamic, AI-powered experiences. - -**Examples Include:** -- **BrowseGPT** - A chat interface with real-time web search capabilities -- **Vercel + Puppeteer** - Server-side browser automation on Fluid Compute - -### 💳 E-commerce & Payments - -#### [**Stripe Integration**](./examples/integrations/stripe/README.md) -**Agentic Credit Card Automation** - Create virtual cards with Stripe Issuing and automate online purchases with Browserbase. Perfect for programmatic commerce, testing payment flows, and building AI shopping agents. - -**Capabilities:** -- Create virtual cards with spending controls -- Automate secure online purchases -- Available in Node.js, Python, and Stagehand implementations -- Production-ready with comprehensive examples - -### 📊 Evaluation & Testing - -#### [**Braintrust Integration**](./examples/integrations/braintrust/) -Integrate Browserbase with Braintrust for evaluation and testing of AI agent performance in web environments. Monitor, measure, and improve your browser automation workflows. - -## 🏗️ Monorepo Structure +## Monorepo Structure ``` integrations/ ├── examples/ -| | -│ └── community/ # WIP +│ ├── community/ # Community-contributed examples │ └── integrations/ -│ ├── crewai/ # CrewAI framework integration -│ ├── vercel/ # Vercel AI SDK integration -│ ├── stripe/ # Stripe Issuing + automation -│ ├── langchain/ # LangChain framework integration -│ ├── browser-use/ # Simplified browser automation -│ ├── braintrust/ # Evaluation and testing tools -│ └── agentkit/ # AgentKit implementations -└── README.md # This file +│ ├── agentkit/ # AgentKit implementations +│ ├── agno/ # Agno agent framework integration +│ ├── braintrust/ # Evaluation and testing tools +│ ├── browser-use/ # Browser Use automation +│ ├── cartesia/ # Cartesia integration +│ ├── cloudflare/ # Cloudflare integration +│ ├── crewai/ # CrewAI framework integration +│ ├── langchain/ # LangChain framework integration +│ ├── logs/ # Logging utilities +│ ├── mastra/ # Mastra AI agent integration +│ ├── mongodb/ # MongoDB data extraction & storage +│ ├── stripe/ # Stripe Issuing + automation +│ ├── temporal/ # Temporal workflow orchestration +│ ├── trigger/ # Trigger.dev background jobs & automation +│ └── vercel/ # Vercel integrations +└── README.md ``` -## 🚀 Getting Started +## Getting Started 1. **Choose your integration** based on your framework or use case 2. **Navigate to the specific integration directory** for detailed setup instructions @@ -92,30 +48,30 @@ integrations/ 4. **Review the code samples** to understand implementation patterns Each integration includes: -- ✅ Complete setup instructions -- ✅ Environment configuration guides -- ✅ Working code examples -- ✅ Best practices and tips -- ✅ Troubleshooting guides +- Complete setup instructions +- Environment configuration guides +- Working code examples +- Best practices and tips +- Troubleshooting guides -## 🔧 Prerequisites +## Prerequisites Most integrations require: - A [Browserbase account](https://browserbase.com) and API key - Node.js 18+ or Python 3.8+ (depending on implementation) - Framework-specific dependencies (detailed in each integration) -## 📖 Documentation +## Documentation For comprehensive documentation, tutorials, and API references, visit: -**🔗 [Official Browserbase Documentation](https://docs.browserbase.com)** +[Official Browserbase Documentation](https://docs.browserbase.com) -## 🤝 Community & Support +## Community & Support ### Get Help -- **📧 Email Support**: [support@browserbase.com](mailto:support@browserbase.com) -- **📚 Documentation**: [docs.browserbase.com](https://docs.browserbase.com) +- **Email Support**: [support@browserbase.com](mailto:support@browserbase.com) +- **Documentation**: [docs.browserbase.com](https://docs.browserbase.com) ### Contributing We welcome contributions! Each integration has its own contribution guidelines. Feel free to: @@ -124,7 +80,7 @@ We welcome contributions! Each integration has its own contribution guidelines. - Share your own integration examples - Help improve documentation -## 📄 License +## License This project is licensed under the MIT License. See individual integration directories for any additional licensing information. diff --git a/examples/integrations/agentkit/README.md b/examples/integrations/agentkit/README.md new file mode 100644 index 0000000..67ce4b9 --- /dev/null +++ b/examples/integrations/agentkit/README.md @@ -0,0 +1,39 @@ +# AgentKit + +## Using AgentKit with Browserbase + +Develop AI Agents that can browse the web autonomously using Browserbase and AgentKit (by inngest). + +## Overview + +By the end of this guide, you'll have an AI agent built with AgentKit that can browse the web using Browserbase. + +### You'll learn how to: + +- Create AgentKit tools that leverage Browserbase's managed headless browsers +- Build autonomous web browsing agents that can search, extract data, and interact with websites +- Use Stagehand, Browserbase's AI-powered browser automation library, to create resilient web agents + +### This integration is useful for: + +- Building AI agents that can fetch real-time information from the web +- Creating autonomous browsing capabilities within your agents +- Developing resilient web scraping and interaction systems +- Enabling your agents to perform complex web-based tasks + +### Integration Approaches + +There are two approaches to using Browserbase with AgentKit: + +1. **Create custom Browserbase tools**: Ideal for simple actions on webpages with manual browser control +2. **Use Stagehand library as tools**: Better for autonomous browsing and resilient web scraping + +### Prerequisites + +Before you start, make sure you have: + +- AgentKit installed +- Browserbase Project ID & API key +- (Optional) LLM API key of your choice to use with Stagehand + +Next, let's dive into building web browsing agents with AgentKit and Browserbase. diff --git a/examples/integrations/agentkit/browserbase/package-lock.json b/examples/integrations/agentkit/browserbase/package-lock.json index acb3c84..aad756d 100644 --- a/examples/integrations/agentkit/browserbase/package-lock.json +++ 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"@inngest/agent-kit": "^0.8.4", + "dotenv": "^17.2.1", + "playwright-core": "^1.55.0", + "zod": "^3.25.76" } } diff --git a/examples/integrations/agentkit/browserbase/src/index.ts b/examples/integrations/agentkit/browserbase/src/index.ts index 51f1279..f7f9598 100644 --- a/examples/integrations/agentkit/browserbase/src/index.ts +++ b/examples/integrations/agentkit/browserbase/src/index.ts @@ -1,4 +1,3 @@ -/* eslint-disable */ import "dotenv/config"; import { anthropic, diff --git a/examples/integrations/agentkit/stagehand/package-lock.json b/examples/integrations/agentkit/stagehand/package-lock.json index a98a0d1..120b52e 100644 --- a/examples/integrations/agentkit/stagehand/package-lock.json +++ b/examples/integrations/agentkit/stagehand/package-lock.json @@ -6,8 +6,8 @@ "": { "name": "simple-search-stagehand", "dependencies": { - "@browserbasehq/sdk": "^2.3.0", - "@browserbasehq/stagehand": "^1.13.1", + "@browserbasehq/sdk": "^2.6.0", + "@browserbasehq/stagehand": "^3.2.0", 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-4258,14 +6787,12 @@ "node": ">= 0.8" } }, - "node_modules/uri-js": { - "version": "4.4.1", - "resolved": "https://registry.npmjs.org/uri-js/-/uri-js-4.4.1.tgz", - "integrity": "sha512-7rKUyy33Q1yc98pQ1DAmLtwX109F7TIfWlW1Ydo8Wl1ii1SeHieeh0HHfPeL2fMXK6z0s8ecKs9frCuLJvndBg==", - "license": "BSD-2-Clause", - "dependencies": { - "punycode": "^2.1.0" - } + "node_modules/urlpattern-polyfill": { + "version": "10.0.0", + "resolved": "https://registry.npmjs.org/urlpattern-polyfill/-/urlpattern-polyfill-10.0.0.tgz", + "integrity": "sha512-H/A06tKD7sS1O1X2SshBVeA5FLycRpjqiBeqGKmBwBDBy28EnRjORxTNe269KSSr5un5qyWi1iL61wLxpd+ZOg==", + "license": "MIT", + "optional": true }, "node_modules/utils-merge": { "version": "1.0.1", @@ -4383,9 +6910,9 @@ "license": "ISC" }, "node_modules/ws": { - "version": "8.18.2", - "resolved": "https://registry.npmjs.org/ws/-/ws-8.18.2.tgz", - "integrity": "sha512-DMricUmwGZUVr++AEAe2uiVM7UoO9MAVZMDu05UQOaUII0lp+zOzLLU4Xqh/JvTqklB1T4uELaaPBKyjE1r4fQ==", + "version": 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b/examples/integrations/agentkit/stagehand/package.json @@ -6,8 +6,8 @@ "start": "tsc; node dist/index.js" }, "dependencies": { - "@browserbasehq/sdk": "^2.3.0", - "@browserbasehq/stagehand": "^1.13.1", + "@browserbasehq/sdk": "^2.6.0", + "@browserbasehq/stagehand": "^3.2.0", "@inngest/agent-kit": "^0.8.0", "dotenv": "^16.4.7", "inngest": "latest", diff --git a/examples/integrations/agentkit/stagehand/src/index.ts b/examples/integrations/agentkit/stagehand/src/index.ts index 2a9021d..c30ed22 100644 --- a/examples/integrations/agentkit/stagehand/src/index.ts +++ b/examples/integrations/agentkit/stagehand/src/index.ts @@ -60,7 +60,7 @@ When the answer is found, call the "done" agent.`, // ensure to loop back to the last executing agent if a tool has been called if (lastMessage && isLastMessageOfType(lastMessage, "tool_call")) { - return [lastMessage?.agent.name]; + return [lastMessage.agentName]; } const tool = result.toolCalls[0]; @@ -121,7 +121,7 @@ const simpleSearchWorkflow = inngest.createFunction( const response = await searchNetwork.run(event.data.input, { state: new State({ - browserbaseSessionID, + data: { browserbaseSessionID }, }), }); diff --git a/examples/integrations/agentkit/stagehand/src/stagehand-tools.ts b/examples/integrations/agentkit/stagehand/src/stagehand-tools.ts index 1dfe706..eecada2 100644 --- a/examples/integrations/agentkit/stagehand/src/stagehand-tools.ts +++ b/examples/integrations/agentkit/stagehand/src/stagehand-tools.ts @@ -15,7 +15,8 @@ export const navigate = createTool({ network?.state.kv.get("browserbaseSessionID")! ); try { - await stagehand.page.goto(url); + const page = stagehand.context.pages()[0]; + await page.goto(url); return `Navigated to ${url}.`; } catch (error) { return `Failed to navigate to ${url}: ${error}`; @@ -44,7 +45,7 @@ export const extract = createTool({ ); const zodSchema = stringToZodSchema(schema); try { - return await stagehand.page.extract({ instruction, schema: zodSchema }); + return await stagehand.extract(instruction, zodSchema); } catch (error) { return `Failed to extract data from the page: ${error}`; } @@ -66,7 +67,7 @@ export const act = createTool({ network?.state.kv.get("browserbaseSessionID")! ); try { - return await stagehand.page.act({ action }); + return await stagehand.act(action); } catch (error) { return `Failed to perform action on the page: ${error}`; } @@ -88,7 +89,7 @@ export const observe = createTool({ network?.state.kv.get("browserbaseSessionID")! ); try { - return await stagehand.page.observe({ instruction }); + return await stagehand.observe(instruction); } catch (error) { return `Failed to observe the page: ${error}`; } diff --git a/examples/integrations/agentkit/stagehand/src/utils.ts b/examples/integrations/agentkit/stagehand/src/utils.ts index 84686ed..7399d16 100644 --- a/examples/integrations/agentkit/stagehand/src/utils.ts +++ b/examples/integrations/agentkit/stagehand/src/utils.ts @@ -4,8 +4,8 @@ import { TextMessage, ToolCallMessage, ToolResultMessage, + type AgentResult, } from "@inngest/agent-kit"; -import { InferenceResult } from "@inngest/agent-kit"; export async function getStagehand(sessionId: string) { const stagehand = new Stagehand({ @@ -13,28 +13,19 @@ export async function getStagehand(sessionId: string) { apiKey: process.env.BROWSERBASE_API_KEY, projectId: process.env.BROWSERBASE_PROJECT_ID, browserbaseSessionID: sessionId, - modelName: "gpt-4o", - modelClientOptions: { - apiKey: process.env.OPENAI_API_KEY, - }, + model: "openai/gpt-4o", }); await stagehand.init(); return stagehand; } export const StagehandAvailableModelSchema = z.enum([ - "gpt-4o", - "gpt-4o-mini", - "gpt-4o-2024-11-20", - "gpt-4o-2024-08-06", - "gpt-4o-2024-05-13", - "claude-3-5-sonnet-latest", - "claude-3-5-sonnet-20241022", - "claude-3-5-sonnet-20240620", - "claude-3-7-sonnet-20250219", - "o1-mini", - "o1-preview", - "o3-mini", + "openai/gpt-4o", + "openai/gpt-4o-mini", + "openai/gpt-4.1", + "openai/o3-mini", + "anthropic/claude-sonnet-4-6", + "google/gemini-2.5-flash", ]); // Transform string such as "{ lastFundraiseDate: string, amount: string, round: string }" into a zod schema @@ -80,7 +71,7 @@ export function stringToZodSchema(schema: string) { return z.object(shape); } -export function lastResult(results: InferenceResult[] | undefined) { +export function lastResult(results: AgentResult[] | undefined) { if (!results) { return undefined; } @@ -93,8 +84,8 @@ type MessageType = | ToolResultMessage["type"]; export function isLastMessageOfType( - result: InferenceResult, + result: AgentResult, type: MessageType ) { return result.output[result.output.length - 1]?.type === type; -} \ No newline at end of file +} diff --git a/examples/integrations/agno/.env.example b/examples/integrations/agno/.env.example new file mode 100644 index 0000000..c136863 --- /dev/null +++ b/examples/integrations/agno/.env.example @@ -0,0 +1,4 @@ +BROWSERBASE_API_KEY= +BROWSERBASE_PROJECT_ID= + +OPENAI_API_KEY= \ No newline at end of file diff --git a/examples/integrations/agno/.gitignore b/examples/integrations/agno/.gitignore new file mode 100644 index 0000000..a979ee7 --- /dev/null +++ b/examples/integrations/agno/.gitignore @@ -0,0 +1 @@ +/venv \ No newline at end of file diff --git a/examples/integrations/agno/README.md b/examples/integrations/agno/README.md new file mode 100644 index 0000000..a46cf62 --- /dev/null +++ b/examples/integrations/agno/README.md @@ -0,0 +1,48 @@ +# Agno + Browserbase Integration + +**Intelligent web scraping with AI agents powered by Browserbase's cloud browser infrastructure.** + +Agno provides AI agents that can understand natural language instructions for web scraping, while Browserbase delivers the reliable browser infrastructure needed to handle modern JavaScript-heavy websites and bypass anti-bot protection. + +## 🚀 Why This Integration? + +### Traditional Scraping Challenges +- **JavaScript-Heavy Sites**: Content loads dynamically after page load +- **Anti-Bot Protection**: Advanced detection systems block traditional scrapers +- **Infrastructure Complexity**: Managing browsers and scaling is difficult + +### Agno + Browserbase Solution +- **🤖 AI-Powered**: Natural language scraping instructions +- **🚀 Real Browser**: Full Chrome with JavaScript execution +- **🛡️ Stealth Capabilities**: Bypasses anti-bot systems +- **⚡ Zero Infrastructure**: Cloud-managed browsers with automatic scaling + +## 📦 Key Features + +**Intelligent Automation**: AI agents adapt to page changes and handle complex workflows +**Visual Analysis**: Screenshots, layout detection, visual regression testing +**Multi-Step Navigation**: Handle pagination, forms, and complex user journeys +**Structured Data**: Extract data in JSON, CSV, or custom formats +**Error Recovery**: Automatic retries and intelligent error handling + +## 🔧 Setup + +**Install packages:** +```bash +pip install browserbase playwright agno +``` + +**Set environment variables:** +```bash +export BROWSERBASE_API_KEY=your_api_key_here +export BROWSERBASE_PROJECT_ID=your_project_id_here +``` + +*Get credentials from the [Browserbase dashboard](https://browserbase.com)* + +## 🤝 Support & Resources + +- **📧 Support**: [support@browserbase.com](mailto:support@browserbase.com) +- **📚 Documentation**: [docs.browserbase.com](https://docs.browserbase.com) +- **🔧 Agno Docs**: [agno documentation](https://agno.dev) +- **💬 Community**: [GitHub Issues](https://github.com/browserbase/integrations/issues) \ No newline at end of file diff --git a/examples/integrations/agno/main.py b/examples/integrations/agno/main.py new file mode 100644 index 0000000..2dfc0ba --- /dev/null +++ b/examples/integrations/agno/main.py @@ -0,0 +1,63 @@ +import os +from dotenv import load_dotenv + +from agno.agent import Agent +from agno.tools.browserbase import BrowserbaseTools + +load_dotenv() + +# Browserbase Configuration +# ------------------------------- +# These environment variables are required for the BrowserbaseTools to function properly. +# You can set them in your .env file or export them directly in your terminal. + +# BROWSERBASE_API_KEY: Your API key from Browserbase dashboard +# - Required for authentication +# - Format: Starts with "bb_live_" or "bb_test_" followed by a unique string +BROWSERBASE_API_KEY = os.getenv("BROWSERBASE_API_KEY") + +# BROWSERBASE_PROJECT_ID: The project ID from your Browserbase dashboard +# - Required to identify which project to use for browser sessions +# - Format: UUID string (8-4-4-4-12 format) +BROWSERBASE_PROJECT_ID = os.getenv("BROWSERBASE_PROJECT_ID") + +agent = Agent( + name="Web Automation Assistant", + tools=[BrowserbaseTools( + api_key=BROWSERBASE_API_KEY, + project_id=BROWSERBASE_PROJECT_ID, + )], + instructions=[ + "You are a web automation assistant that can help with:", + "1. Capturing screenshots of websites", + "2. Extracting content from web pages", + "3. Monitoring website changes", + "4. Taking visual snapshots of responsive layouts", + "5. Automated web testing and verification", + ], + show_tool_calls=True, + markdown=True, +) + +# Content Extraction and SS + +# Hacker News Example +# agent.print_response(""" +# Go to https://news.ycombinator.com and extract: +# 1. The page title +# 2. Take a screenshot of the top stories section +# 3. Extract the first 5 stories and their links +# 4. Then go to those links and extract the title and description of each story in JSON format +# { +# "title": "string", +# "description": "string", +# "link": "string" +# } +# """) + +agent.print_response(""" + Visit https://quotes.toscrape.com and: + 1. Extract the first 5 quotes and their authors + 2. Navigate to page 2 + 3. Extract the first 5 quotes from page 2 +""") \ No newline at end of file diff --git a/examples/integrations/agno/requirements.txt b/examples/integrations/agno/requirements.txt new file mode 100644 index 0000000..3fbe05f --- /dev/null +++ b/examples/integrations/agno/requirements.txt @@ -0,0 +1,37 @@ +agno==1.5.5 +annotated-types==0.7.0 +anyio==4.9.0 +browserbase==1.4.0 +certifi==2025.4.26 +click==8.2.1 +distro==1.9.0 +docstring_parser==0.16 +gitdb==4.0.12 +GitPython==3.1.44 +greenlet==3.2.2 +h11==0.16.0 +httpcore==1.0.9 +httpx==0.28.1 +idna==3.10 +jiter==0.10.0 +markdown-it-py==3.0.0 +mdurl==0.1.2 +openai==1.82.0 +playwright==1.52.0 +pydantic==2.11.5 +pydantic-settings==2.9.1 +pydantic_core==2.33.2 +pyee==13.0.0 +Pygments==2.19.1 +python-dotenv==1.1.0 +python-multipart==0.0.20 +PyYAML==6.0.2 +rich==14.0.0 +shellingham==1.5.4 +smmap==5.0.2 +sniffio==1.3.1 +tomli==2.2.1 +tqdm==4.67.1 +typer==0.16.0 +typing-inspection==0.4.1 +typing_extensions==4.13.2 diff --git a/examples/integrations/braintrust/README.md b/examples/integrations/braintrust/README.md new file mode 100644 index 0000000..770f0f0 --- /dev/null +++ b/examples/integrations/braintrust/README.md @@ -0,0 +1,30 @@ +# Braintrust Integration + +Utilize Browserbase with Braintrust for advanced browser automation. + +## Overview + +Braintrust is a platform for building AI applications, making it more efficient for Large Language Models (LLMs) to become more robust, reliable, and interactive. + +### Key Features + +- Prototyping with different prompts and LLMs in a sandboxed environment +- Real-time monitoring and performance insights +- Data management through intuitive UI + +## Tool Calling Support + +Most Large Language Models support tool calling, which allows you to define tools with well-defined input and output types. Common use cases include: + +1. Enabling models to "call" tools that perform external tasks and use those results to produce a final response +2. Coercing models into producing structured outputs that match a given JSON schema + +Braintrust supports both use cases, allowing prompts to be executed directly using TypeScript or Python. + +### Custom Functions + +Custom functions enhance LLM capabilities by enabling: + +- Web-browsing capabilities (using tools like Browserbase) +- Complex computations +- External API access \ No newline at end of file diff --git a/examples/integrations/braintrust/package-lock.json b/examples/integrations/braintrust/package-lock.json index c52d2a7..6f296fe 100644 --- a/examples/integrations/braintrust/package-lock.json +++ b/examples/integrations/braintrust/package-lock.json @@ -11,7 +11,7 @@ "dependencies": { "@browserbasehq/sdk": "^2.6.0", "braintrust": "^0.0.205", - "next": "^15.1.8", + "next": "^15.2.4", "node": "^22.16.0", "playwright-core": "^1.52.0", "zod": "^3.25.28" @@ -195,20 +195,6 @@ } } }, - "node_modules/@ampproject/remapping": { - "version": "2.3.0", - "resolved": "https://registry.npmjs.org/@ampproject/remapping/-/remapping-2.3.0.tgz", - "integrity": "sha512-30iZtAPgz+LTIYoeivqYo853f02jBYSd5uGnGpkFV0M3xOt9aN73erkgYAmZU43x4VfqcnLxW9Kpg3R5LC4YYw==", - "license": "Apache-2.0", - "peer": true, - "dependencies": { - "@jridgewell/gen-mapping": "^0.3.5", - "@jridgewell/trace-mapping": "^0.3.24" - }, - "engines": { - "node": ">=6.0.0" - } - }, "node_modules/@asteasolutions/zod-to-openapi": { "version": "6.4.0", "resolved": "https://registry.npmjs.org/@asteasolutions/zod-to-openapi/-/zod-to-openapi-6.4.0.tgz", @@ -242,13 +228,13 @@ } }, "node_modules/@babel/parser": { - "version": "7.27.2", - "resolved": "https://registry.npmjs.org/@babel/parser/-/parser-7.27.2.tgz", - "integrity": "sha512-QYLs8299NA7WM/bZAdp+CviYYkVoYXlDW2rzliy3chxd1PQjej7JORuMJDJXJUb9g0TT+B99EwaVLKmX+sPXWw==", + "version": "7.28.3", + "resolved": "https://registry.npmjs.org/@babel/parser/-/parser-7.28.3.tgz", + "integrity": "sha512-7+Ey1mAgYqFAx2h0RuoxcQT5+MlG3GTV0TQrgr7/ZliKsm/MNDxVVutlWaziMq7wJNAz8MTqz55XLpWvva6StA==", "license": "MIT", "peer": true, "dependencies": { - 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"next": "^15.1.8", + "next": "^15.2.4", "node": "^22.16.0", "playwright-core": "^1.52.0", "zod": "^3.25.28" diff --git a/examples/integrations/browser-use/.env.example b/examples/integrations/browser-use/.env.example new file mode 100644 index 0000000..6fc1b3d --- /dev/null +++ b/examples/integrations/browser-use/.env.example @@ -0,0 +1,3 @@ +BROWSERBASE_API_KEY=your_api_key_here +BROWSERBASE_PROJECT_ID=your_project_id_here +ANTHROPIC_API_KEY=your_anthropic_api_key_here \ No newline at end of file diff --git a/examples/integrations/browser-use/main.py b/examples/integrations/browser-use/main.py index f54e687..9f67027 100644 --- a/examples/integrations/browser-use/main.py +++ b/examples/integrations/browser-use/main.py @@ -1,109 +1,40 @@ -from dotenv import load_dotenv -import os import asyncio -from typing import Optional -from browserbase import Browserbase -from browser_use import Agent, Browser, BrowserConfig -from browser_use.browser.context import BrowserContext, BrowserContextConfig, BrowserSession -from langchain_anthropic import ChatAnthropic -from playwright.async_api import Page, BrowserContext as PlaywrightContext - -class ExtendedBrowserSession(BrowserSession): - """Extended version of BrowserSession that includes current_page""" - def __init__( - self, - context: PlaywrightContext, - cached_state: Optional[dict] = None, - current_page: Optional[Page] = None - ): - super().__init__(context=context, cached_state=cached_state) - self.current_page = current_page - -class UseBrowserbaseContext(BrowserContext): - async def _initialize_session(self) -> ExtendedBrowserSession: - """Initialize a browser session using existing Browserbase page. - - Returns: - ExtendedBrowserSession: The initialized browser session with current page. - """ - playwright_browser = await self.browser.get_playwright_browser() - context = await self._create_context(playwright_browser) - self._add_new_page_listener(context) - - self.session = ExtendedBrowserSession( - context=context, - cached_state=None, - ) - - # Get existing page or create new one - self.session.current_page = context.pages[0] if context.pages else await context.new_page() +import os +from dotenv import load_dotenv - # Initialize session state - self.session.cached_state = await self._update_state() +from browserbase import Browserbase +from browser_use import Agent, Browser, BrowserProfile, ChatAnthropic - return self.session +load_dotenv() -async def setup_browser() -> tuple[Browser, UseBrowserbaseContext]: - """Set up browser and context configurations. - Returns: - tuple[Browser, UseBrowserbaseContext]: Configured browser and context. - """ +async def main(): bb = Browserbase(api_key=os.environ["BROWSERBASE_API_KEY"]) - bb_session = bb.sessions.create( - project_id=os.environ["BROWSERBASE_PROJECT_ID"], - ) - - browser = Browser(config=BrowserConfig(cdp_url=bb_session.connect_url)) - context = UseBrowserbaseContext( - browser, - BrowserContextConfig( - wait_for_network_idle_page_load_time=10.0, - highlight_elements=True, - ) - ) - - return browser, context + session = bb.sessions.create(project_id=os.environ["BROWSERBASE_PROJECT_ID"]) -async def setup_agent(browser: Browser, context: UseBrowserbaseContext) -> Agent: - """Set up the browser automation agent. + print(f"Session ID: {session.id}") + print(f"Debug URL: https://www.browserbase.com/sessions/{session.id}") - Args: - browser: Configured browser instance - context: Browser context for the agent - - Returns: - Agent: Configured automation agent - """ - llm = ChatAnthropic( - model_name="claude-3-5-sonnet-20240620", - temperature=0.0, - timeout=100, + browser = Browser( + browser_profile=BrowserProfile(cdp_url=session.connect_url) ) - return Agent( - task="go to https://www.macrumors.com/contact.php and fill in the form. Make sure to use the selectors and submit the form", + llm = ChatAnthropic(model="claude-sonnet-4-6") + + agent = Agent( + task=( + "Go to https://www.macrumors.com/contact.php and fill in the form. " + "Make sure to use the selectors and submit the form" + ), llm=llm, browser=browser, - browser_context=context, ) + result = await agent.run() + print(f"Result: {result}") -async def main(): - load_dotenv() - - browser, context = await setup_browser() - session = await context.get_session() - - print("Session:", session) + await browser.stop() - try: - agent = await setup_agent(browser, context) - await agent.run() - finally: - # Simplified cleanup - just close the browser - # This will automatically close all contexts and pages - await browser.close() if __name__ == "__main__": - asyncio.run(main()) \ No newline at end of file + asyncio.run(main()) diff --git a/examples/integrations/browser-use/requirements.txt b/examples/integrations/browser-use/requirements.txt new file mode 100644 index 0000000..eb71fba --- /dev/null +++ b/examples/integrations/browser-use/requirements.txt @@ -0,0 +1,121 @@ +aiofiles==24.1.0 +aiohappyeyeballs==2.6.1 +aiohttp==3.13.3 +aiosignal==1.4.0 +annotated-types==0.7.0 +anthropic==0.76.0 +anyio==4.12.1 +attrs==25.3.0 +Authlib==1.6.1 +backoff==2.2.1 +beautifulsoup4==4.13.4 +browser-use==0.12.5 +browser-use-sdk==2.0.15 +browserbase==1.4.0 +bubus==1.5.6 +cachetools==5.5.2 +cdp-use==1.4.5 +certifi==2025.7.14 +cffi==1.17.1 +charset-normalizer==3.4.2 +click==8.3.1 +cloudpickle==3.1.2 +cryptography==45.0.5 +Cython==3.1.2 +distro==1.9.0 +docstring_parser==0.17.0 +frozenlist==1.8.0 +google-api-core==2.29.0 +google-api-python-client==2.188.0 +google-auth==2.48.0 +google-auth-httplib2==0.2.0 +google-auth-oauthlib==1.2.4 +google-genai==1.65.0 +googleapis-common-protos==1.70.0 +greenlet==3.2.3 +groq==1.0.0 +h11==0.16.0 +httpcore==1.0.9 +httplib2==0.22.0 +httpx==0.28.1 +httpx-sse==0.4.1 +idna==3.10 +inquirerpy==0.3.4 +jiter==0.10.0 +jsonpatch==1.33 +jsonpointer==3.0.0 +jsonschema==4.25.0 +jsonschema-specifications==2025.4.1 +langchain-anthropic==0.3.17 +langchain-core==0.3.70 +langsmith==0.4.8 +lxml==6.0.2 +markdown-it-py==3.0.0 +markdown_pdf==1.7 +markdownify==1.2.2 +mcp==1.26.0 +mdurl==0.1.2 +multidict==6.7.1 +oauthlib==3.3.1 +ollama==0.6.1 +openai==2.16.0 +orjson==3.11.0 +packaging==25.0 +patchright==1.52.5 +pfzy==0.3.4 +pillow==12.1.1 +playwright==1.53.0 +portalocker==2.10.1 +posthog==7.7.0 +prompt_toolkit==3.0.52 +propcache==0.4.1 +proto-plus==1.26.1 +protobuf==6.31.1 +psutil==7.2.2 +pyasn1==0.6.1 +pyasn1_modules==0.4.2 +pycparser==2.22 +pydantic==2.12.5 +pydantic-settings==2.10.1 +pydantic_core==2.41.5 +pyee==13.0.0 +Pygments==2.20.0 +PyJWT==2.12.1 +PyMuPDF==1.25.3 +pyobjc-core==11.1 +pyobjc-framework-Cocoa==11.1 +pyotp==2.9.0 +pyparsing==3.2.3 +pypdf==6.9.1 +pyperclip==1.9.0 +python-dateutil==2.9.0.post0 +python-docx==1.2.0 +python-dotenv==1.2.1 +python-multipart==0.0.20 +PyYAML==6.0.2 +referencing==0.36.2 +reportlab==4.4.9 +requests==2.32.5 +requests-oauthlib==2.0.0 +requests-toolbelt==1.0.0 +rich==14.3.1 +rpds-py==0.26.0 +rsa==4.9.1 +screeninfo==0.8.1 +six==1.17.0 +sniffio==1.3.1 +soupsieve==2.7 +sse-starlette==2.4.1 +starlette==0.47.2 +tenacity==8.5.0 +tqdm==4.67.1 +typing-inspection==0.4.2 +typing_extensions==4.15.0 +uritemplate==4.2.0 +urllib3==2.5.0 +uuid7==0.1.0 +uvicorn==0.35.0 +wcwidth==0.6.0 +websockets==15.0.1 +yarl==1.23.0 +zstandard==0.23.0 diff --git a/examples/integrations/cartesia/.env.example b/examples/integrations/cartesia/.env.example new file mode 100644 index 0000000..6ce6cdb --- /dev/null +++ b/examples/integrations/cartesia/.env.example @@ -0,0 +1,10 @@ +# Gemini API Key for language model (default) +GEMINI_API_KEY=your_gemini_api_key_here + +# Browserbase API key and Project ID +BROWSERBASE_API_KEY=your_browserbase_api_key_here +BROWSERBASE_PROJECT_ID=your_browserbase_project_id_here + +# Optional: Model configuration +# MODEL_NAME=google/gemini-2.0-flash-exp +# MODEL_API_KEY=your_model_api_key_here \ No newline at end of file diff --git a/examples/integrations/cartesia/.gitignore b/examples/integrations/cartesia/.gitignore new file mode 100644 index 0000000..7d9a412 --- /dev/null +++ b/examples/integrations/cartesia/.gitignore @@ -0,0 +1,41 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*.pyd +.Python + +# Virtual environments +.env +.venv/ +venv/ +env/ + +virtualenv/ + +# Conda environments +conda-env/ +envs/ +.conda/ +conda-meta/ + +# uv environments (in addition to uv.lock at top) +uv.lock +.python-version + +# Python package managers +poetry.lock +Pipfile.lock +pip-log.txt + +# pyenv +.pyenv/ + +# Distribution / packaging +*.egg-info/ +dist/ +build/ + +# Editor / OS files +.DS_Store + +.cartesia/ \ No newline at end of file diff --git a/examples/integrations/cartesia/README.md b/examples/integrations/cartesia/README.md new file mode 100644 index 0000000..5c34e98 --- /dev/null +++ b/examples/integrations/cartesia/README.md @@ -0,0 +1,143 @@ +# Voice Agent with Real-time Web Form Filling + +This project demonstrates an advanced voice agent that conducts phone questionnaires while automatically filling out web forms in real-time using Stagehand browser automation. + +Here's what the system architecture looks like: + +![Workflow](workflow_diagram.png) + +## Features + +- **Voice Conversations**: Natural voice interactions using Cartesia Line +- **Real-time Form Filling**: Automatically fills web forms as answers are collected +- **Browser Automation**: Uses Stagehand AI to interact with any web form +- **Intelligent Mapping**: AI-powered mapping of voice answers to form fields +- **Async Processing**: Non-blocking form filling maintains conversation flow - form fields are filled in background tasks without delaying voice responses +- **Auto-submission**: Submits forms automatically when complete + +## Architecture + +``` +Voice Call (Cartesia) → Form Filling Node → Records Answer + ↓ + Stagehand Browser API + ↓ + Fills Web Form Field + ↓ + Continues Conversation + ↓ + Submits Form on Completion +``` + +## Getting Started + +First things first, here is what you will need: +- A [Cartesia](https://play.cartesia.ai/agents) account and API key +- A [Gemini API Key](https://aistudio.google.com/apikey) +- A [Browserbase API Key and Project ID](https://www.browserbase.com/overview) + +Make sure to add the API keys in your `.env` file or to the API keys section in your Cartesia account. + +- Required packages: + ```bash + cartesia-line + stagehand>=0.5.4 + google-genai>=1.26.0 + python-dotenv>=1.0.0 + PyYAML>=6.0.0 + loguru>=0.7.0 + aiohttp>=3.12.0 + pydantic>=2.0.0 + ``` + +## Setup + +1. Install dependencies: +```bash +pip install -r requirements.txt +``` + +2. Set up environment variables - create a `.env` file: +```bash +GEMINI_API_KEY=your_gemini_api_key_here +BROWSERBASE_API_KEY=your_browserbase_api_key_here +BROWSERBASE_PROJECT_ID=your_browserbase_project_id_here +``` + +3. Run the agent: +```bash +python main.py +``` + +## Project Structure + +### `main.py` +Entry point for the voice agent. Handles call initialization with `VoiceAgentApp` class and orchestrates the conversation flow with form filling integration. + +### `form_filling_node.py` +ReasoningNode subclass customized for voice-optimized form filling. Integrates Stagehand browser automation and manages async form filling during conversation without blocking the voice flow. Provides status updates and error handling. + +### `stagehand_form_filler.py` +Browser automation manager that handles all web interactions. Opens and controls web forms, maps conversation data to form fields using AI, transforms voice answers to form-compatible formats, and handles form submission. Supports different field types (text, select, checkbox, etc.). + +### `config.py` +System configuration file including system prompts, model IDs, and temperature + +### `config.toml` +Your Cartesia Line agent id. + +## Configuration + +The system can be configured through multiple files: + +- **`config.py`**: System prompts, model IDs (Gemini model selection), hyperparameters, and boolean flags for features +- **`config.toml`** / **YAML files**: Questionnaire structure and questions flow +- **`cartesia.toml`**: Deployment configuration for Cartesia platform (installs dependencies and runs the script) +- **Variables**: + - `FORM_URL`: Target web form to fill + +## Example Flow + +1. User calls the voice agent +2. Agent asks: "What type of voice agent are you building?" +3. User responds: "A customer service agent" +4. System: + - Records the answer + - Opens browser to form (if not already open) + - Fills "Customer Service" in the role selection field + - Takes screenshot for debugging +5. Agent asks next question +6. Process continues until all questions answered +7. Form is automatically submitted + +## Advanced Features + +- **Background Processing**: Form filling happens asynchronously using background tasks - conversation remains smooth and responsive +- **Error Recovery**: Continues conversation even if form filling fails +- **Progress Tracking**: Monitor form completion status +- **Screenshot Debugging**: Captures screenshots after each field +- **Flexible Mapping**: AI interprets answers for different field types + +## Deploying the Agent + +The `cartesia.toml` file defines how your agent will be installed and run when deployed on the Cartesia platform. This file tells the platform to install dependencies from `requirements.txt` and execute `main.py`. + +You can clone this repository and add it to your [agents dashboard](https://play.cartesia.ai/agents) along with your API Keys (set them in the Cartesia Platform's API keys section). + +For detailed deployment instructions, see [how to deploy an agent from the Cartesia Docs](https://docs.cartesia.ai/line/start-building/talk-to-your-first-agent). + +## Testing + +Test with different scenarios: +- Complete questionnaire flow +- Interruptions and corrections +- Various answer formats +- Multi-page forms +- Form validation errors + +## Production Considerations + +- Configure proper error logging +- Add retry logic for form submission +- Implement form validation checks +- Consider rate limiting for API calls \ No newline at end of file diff --git a/examples/integrations/cartesia/cartesia.toml b/examples/integrations/cartesia/cartesia.toml new file mode 100644 index 0000000..979916c --- /dev/null +++ b/examples/integrations/cartesia/cartesia.toml @@ -0,0 +1,8 @@ +[app] +name = "form-filling" + +[build] +cmd = "pip install -r requirements.txt" + +[run] +cmd = "python main.py" diff --git a/examples/integrations/cartesia/config.py b/examples/integrations/cartesia/config.py new file mode 100644 index 0000000..e8b9bc2 --- /dev/null +++ b/examples/integrations/cartesia/config.py @@ -0,0 +1,35 @@ +"""Configuration settings for the voice agent. + +This module contains system prompts, model configurations, and +hyperparameters for the Cartesia voice agent with form filling. +""" + +import os + +DEFAULT_MODEL_ID = os.getenv("MODEL_ID", "gemini-2.5-flash") + +DEFAULT_TEMPERATURE = 0.7 +SYSTEM_PROMPT = """ +### You and your role +You are a friendly assistant conducting a questionnaire. +Be professional but conversational. Confirm answers when appropriate. +If a user's answer is unclear, ask for clarification. +For sensitive information, be especially tactful and professional. + +IMPORTANT: When you receive a clear answer from the user, use the +record_answer tool to record their response. + +### Your tone +When having a conversation, you should: +- Always polite and respectful, even when users are challenging +- Concise and brief but never curt. Keep your responses to 1-2 + sentences and less than 35 words +- When asking a question, be sure to ask in a short and concise manner +- Only ask one question at a time + +If the user is rude, or curses, respond with exceptional politeness +and genuine curiosity. You should always be polite. + +Remember, you're on the phone, so do not use emojis or abbreviations. +Spell out units and dates. +""" diff --git a/examples/integrations/cartesia/config.toml b/examples/integrations/cartesia/config.toml new file mode 100644 index 0000000..2355be8 --- /dev/null +++ b/examples/integrations/cartesia/config.toml @@ -0,0 +1 @@ +agent-id = 'your-agent-id' diff --git a/examples/integrations/cartesia/form_filling_node.py b/examples/integrations/cartesia/form_filling_node.py new file mode 100644 index 0000000..db87a26 --- /dev/null +++ b/examples/integrations/cartesia/form_filling_node.py @@ -0,0 +1,489 @@ +"""Voice agent that fills web forms in real-time using Stagehand. + +This module implements a ReasoningNode subclass that conducts voice +conversations while automatically filling web forms in the background. +The agent uses Stagehand for browser automation and handles async form +filling during conversation without blocking the voice flow. +""" + +import asyncio +from dataclasses import dataclass +from typing import AsyncGenerator, Dict, List, Optional, Union + +from config import DEFAULT_MODEL_ID, DEFAULT_TEMPERATURE +from google.genai import types as gemini_types +from loguru import logger +from pydantic import BaseModel, Field +from stagehand_form_filler import StagehandFormFiller + +from line.events import AgentResponse, EndCall, ToolResult +from line.nodes.conversation_context import ConversationContext +from line.nodes.reasoning import ReasoningNode +from line.tools.system_tools import EndCallArgs, end_call +from line.utils.gemini_utils import convert_messages_to_gemini + + +class RecordFormFieldArgs(BaseModel): + """Arguments for recording a form field""" + + field_name: str = Field(description="The form field being filled") + value: str = Field(description="The value to enter in the field") + + +class RecordFormFieldTool: + """Tool for recording form field values""" + + @staticmethod + def name() -> str: + return "record_form_field" + + @staticmethod + def description() -> str: + return "Record a value for a form field that needs to be filled" + + @staticmethod + def parameters() -> dict: + return RecordFormFieldArgs.model_json_schema() + + @staticmethod + def to_gemini_tool(): + """Convert to Gemini tool format. + + Returns: + A Gemini Tool object with function declarations. + """ + return gemini_types.Tool( + function_declarations=[ + gemini_types.FunctionDeclaration( + name=RecordFormFieldTool.name(), + description=RecordFormFieldTool.description(), + parameters=RecordFormFieldTool.parameters(), + ) + ] + ) + + +@dataclass +class FormQuestion: + """Represents a question to ask the user""" + + field_name: str + question: str + field_type: str = "text" + required: bool = True + + +class FormFillingNode(ReasoningNode): + """Voice agent that fills web forms while conducting conversations. + + This class uses Stagehand to read and fill web forms dynamically, + maintains conversation flow while automating browser actions, and + intelligently extracts form structure and asks relevant questions. + """ + + def __init__( + self, + system_prompt: str, + gemini_client, + form_url: str, + model_id: str = DEFAULT_MODEL_ID, + temperature: float = DEFAULT_TEMPERATURE, + max_context_length: int = 15, + max_output_tokens: int = 1000, + ): + """Initialize the Form Filling node with Stagehand integration. + + Args: + system_prompt: System prompt for the LLM. + gemini_client: Google Gemini client instance. + form_url: URL of the web form to fill. + model_id: Gemini model ID. + temperature: Temperature for generation. + max_context_length: Maximum conversation context length. + max_output_tokens: Maximum tokens for generation. + """ + super().__init__(system_prompt=system_prompt, max_context_length=max_context_length) + + self.client = gemini_client + self.model_id = model_id + self.temperature = temperature + + # Browser automation + self.form_url = form_url + self.stagehand_filler: Optional[StagehandFormFiller] = None + + # Form state + self.collected_data: Dict[str, str] = {} + # Pre-initialize questions so conversation can start immediately + self.questions: List[FormQuestion] = self._create_questions() + self.current_question_index = 0 + + # Browser initialization + self.browser_init_task = None + self.browser_initializing = False + + # Enhanced prompt for form filling + enhanced_prompt = ( + system_prompt + + """ + + You are conducting a voice conversation to help fill out a web + form. As you collect information, it's being entered into an + actual online form in real-time. Ask natural questions to gather + the required information. Use the record_form_field tool to save + each piece of information. Keep the conversation friendly and + natural. + """ + ) + + # Generation config + self.generation_config = gemini_types.GenerateContentConfig( + system_instruction=enhanced_prompt, + temperature=self.temperature, + tools=[RecordFormFieldTool.to_gemini_tool()], + max_output_tokens=max_output_tokens, + thinking_config=gemini_types.ThinkingConfig(thinking_budget=0), + ) + + logger.info(f"FormFillingNode initialized for form: {form_url}") + + # Track if form was submitted + self.form_submitted = False + + async def cleanup_and_submit(self) -> None: + """Ensure form is submitted and cleanup when call ends. + + Returns: + None. + """ + # Submit form if we have any data and haven't submitted yet + if not self.form_submitted and self.collected_data and self.stagehand_filler: + logger.info("Call ending - auto-submitting form with collected data") + try: + await self._submit_form() + except Exception as e: + logger.error(f"Error during cleanup submission: {e}") + + # Clean up browser + if self.stagehand_filler: + await self.stagehand_filler.cleanup() + + async def _initialize_browser(self) -> None: + """Initialize browser and extract form fields. + + Returns: + None. + """ + # Prevent multiple initializations + if self.browser_initializing or self.stagehand_filler: + logger.info("Browser already initializing or initialized, skipping") + return + + self.browser_initializing = True + try: + logger.info("Initializing browser and analyzing form") + self.stagehand_filler = StagehandFormFiller(form_url=self.form_url) + await self.stagehand_filler.initialize() + + logger.info("Browser ready, form can now be filled") + + except Exception as e: + logger.error(f"Failed to initialize browser: {e}") + self.browser_initializing = False + raise + finally: + self.browser_initializing = False + + def _create_questions(self) -> List[FormQuestion]: + """Create questions for the form. + + Returns: + A list of FormQuestion objects to ask the user. + """ + # Define questions for the form fields we know about + # This matches form at https://forms.fillout.com/t/34ccsqafUFus + form_questions = [ + FormQuestion( + field_name="full_name", question="What is your full name?", field_type="text", required=True + ), + FormQuestion( + field_name="email", question="What is your email address?", field_type="email", required=True + ), + FormQuestion( + field_name="phone", question="What is your phone number?", field_type="phone", required=False + ), + FormQuestion( + field_name="work_eligibility", + question="Are you legally eligible to work in this country?", + field_type="radio", + required=True, + ), + FormQuestion( + field_name="availability_type", + question=("What's your availability - temporary, part-time, or full-time?"), + field_type="radio", + required=True, + ), + FormQuestion( + field_name="role_selection", + question=( + "Which role are you applying for? We have openings " + "for Sales Manager, IT Support, Recruiting, " + "Software Engineer, or Marketing Specialist." + ), + field_type="checkbox", + required=True, + ), + FormQuestion( + field_name="previous_experience", + question="Have you worked in a similar role before?", + field_type="radio", + required=True, + ), + FormQuestion( + field_name="skills_experience", + question=( + "What relevant skills and experience do you have " + "that make you a strong candidate for this position?" + ), + field_type="textarea", + required=True, + ), + FormQuestion( + field_name="additional_info", + question=("Is there anything else you'd like to tell us about yourself?"), + field_type="textarea", + required=False, + ), + ] + + return form_questions + + async def _fill_form_field_async(self, field_name: str, value: str) -> None: + """Fill a form field asynchronously in background (non-blocking). + + Args: + field_name: The name of the form field to fill. + value: The value to enter in the field. + """ + try: + # Wait for browser initialization if needed + if self.browser_init_task: + logger.info(f"Waiting for browser to initialize before filling {field_name}") + await self.browser_init_task + + logger.info(f"Filling field '{field_name}' with: {value} in background") + # Use StagehandFormFiller's fill_field method which + # handles the mapping + success = await self.stagehand_filler.fill_field(field_name, value) + + if success: + logger.info(f"Successfully filled field: {field_name} in browser") + else: + logger.warning(f"Failed to fill field: {field_name}") + + except Exception as e: + logger.error(f"Error filling field {field_name}: {e}") + raise # Re-raise so background task can catch it + + async def _submit_form(self) -> bool: + """Submit the completed form. + + Returns: + True if submission succeeded, False otherwise. + """ + # Wait for browser initialization if needed + if self.browser_init_task and not self.stagehand_filler: + logger.info("Waiting for browser to initialize before submitting form") + await self.browser_init_task + + if not self.stagehand_filler: + return False + + try: + logger.info("Submitting web form with collected data") + logger.info(f"Data collected: {self.collected_data}") + + # Ensure StagehandFormFiller has all collected data + # (it should already have it from fill_field calls, + # but ensure consistency) + self.stagehand_filler.collected_data.update(self.collected_data) + + # Use StagehandFormFiller's submit_form method which now + # uses collected_data + success = await self.stagehand_filler.submit_form() + + if success: + logger.info("Form submitted successfully!") + return True + else: + logger.warning("Form submission may have failed") + return False + + except Exception as e: + logger.error(f"Error submitting form: {e}") + return False + + def get_current_question(self) -> Optional[FormQuestion]: + """Get the current question to ask. + + Returns: + The current FormQuestion or None if all questions answered. + """ + if self.current_question_index < len(self.questions): + return self.questions[self.current_question_index] + return None + + async def process_context( + self, context: ConversationContext + ) -> AsyncGenerator[Union[AgentResponse, EndCall], None]: + """Process conversation context with real-time form filling. + + Args: + context: The conversation context with events. + + Yields: + AgentResponse: Text responses to the user. + EndCall: Call termination when form is complete. + """ + # Initialize browser on first call (non-blocking) + if not self.browser_init_task and not self.stagehand_filler: + self.browser_init_task = asyncio.create_task(self._initialize_browser()) + logger.info("Browser initialization started in background") + + # Get current question after initialization + current_question = self.get_current_question() + question_name = current_question.field_name if current_question else "None" + logger.info(f"Current question: {question_name}") + logger.info(f"Question index: {self.current_question_index}/{len(self.questions)}") + logger.info(f"Events count: {len(context.events)}") + + # Check latest event to determine what to do + latest_event = context.events[-1] if context.events else None + is_agent_response = isinstance(latest_event, AgentResponse) if latest_event else False + + # Handle initial greeting - speak first when conversation starts + if not context.events: + logger.info("Starting conversation - Agent speaks first") + initial_greeting = ( + "Hello! I'm here to help you fill out an application " + "form today. I'll ask you a series of questions and " + "fill in the form as we go. Ready to get started?" + ) + yield AgentResponse(content=initial_greeting) + return + + # If last event was our greeting, and user responded, ask + # first question + if len(context.events) == 2 and not is_agent_response and self.current_question_index == 0: + user_message = context.get_latest_user_transcript_message() + if user_message and current_question: + logger.info(f"User ready to start: '{user_message}'") + logger.info(f"Asking first question: {current_question.field_name}") + yield AgentResponse(content=f"Great! Let's begin. {current_question.question}") + return + + # Check if all questions have been answered + # Only submit if we've actually collected data + if not current_question and self.current_question_index > 0 and len(self.collected_data) > 0: + # All questions answered - submit the form + logger.info(f"All {self.current_question_index} questions answered") + logger.info(f"Collected data for {len(self.collected_data)} fields") + + submission_success = await self._submit_form() + self.form_submitted = True + + if submission_success: + goodbye = "Perfect! I've submitted your application. Thank you!" + else: + goodbye = "Thank you for providing all the information. Your responses have been recorded." + + # Clean up + await self.cleanup_and_submit() + + # End call + args = EndCallArgs(goodbye_message=goodbye) + async for item in end_call(args): + yield item + return + + # Guard against no questions or empty state + if not current_question and self.current_question_index == 0: + logger.warning("No questions available or not properly initialized") + return + + # Process user response + messages = convert_messages_to_gemini(context.events, text_events_only=True) + + # Add context about current question + question_context = f""" + + Current form field: {current_question.field_name} + Question: {current_question.question} + + Listen to the user's response and use the record_form_field + tool to save it. Then acknowledge their answer naturally. + """ + + enhanced_config = gemini_types.GenerateContentConfig( + system_instruction=(self.generation_config.system_instruction + question_context), + temperature=self.temperature, + tools=[RecordFormFieldTool.to_gemini_tool()], + max_output_tokens=self.generation_config.max_output_tokens, + thinking_config=gemini_types.ThinkingConfig(thinking_budget=0), + ) + + # Get user's latest message + user_message = context.get_latest_user_transcript_message() + if user_message: + logger.info(f'User response: "{user_message}"') + + # Stream Gemini response + full_response = "" + stream = await self.client.aio.models.generate_content_stream( + model=self.model_id, + contents=messages, + config=enhanced_config, + ) + + async for msg in stream: + if msg.text: + full_response += msg.text + yield AgentResponse(content=msg.text) + + if msg.function_calls: + for function_call in msg.function_calls: + if function_call.name == RecordFormFieldTool.name(): + field_name = function_call.args.get("field_name", current_question.field_name) + value = function_call.args.get("value", "") + + logger.info(f"Recording: {field_name} = {value}") + + # Store data first + self.collected_data[field_name] = value + # Fill the form field asynchronously in background + # (non-blocking) + asyncio.create_task(self._fill_form_field_async(field_name, value)) + # Log the collected data + logger.info(f"Collected: {field_name}={value}") + # Move to next question immediately + # (don't wait for form filling) + self.current_question_index += 1 + + # Clear context + self.clear_context() + + # Get next question + next_question = self.get_current_question() + if next_question: + yield AgentResponse(content=f"Great! {next_question.question}") + + # Yield tool result immediately + yield ToolResult( + tool_name="record_form_field", + tool_args={"field_name": field_name, "value": value}, + result=f"Recorded: {field_name}={value}", + ) + + if full_response: + logger.info(f'Agent response: "{full_response}"') diff --git a/examples/integrations/cartesia/main.py b/examples/integrations/cartesia/main.py new file mode 100644 index 0000000..95b465f --- /dev/null +++ b/examples/integrations/cartesia/main.py @@ -0,0 +1,75 @@ +"""Cartesia Line Voice Agent with real-time web form filling. + +This module implements a voice agent that conducts phone questionnaires +while automatically filling out web forms in real-time using Stagehand +browser automation. +""" + +import os + +from config import SYSTEM_PROMPT +from form_filling_node import FormFillingNode +from google import genai + +from line import Bridge, CallRequest, VoiceAgentApp, VoiceAgentSystem +from line.events import UserStartedSpeaking, UserStoppedSpeaking, UserTranscriptionReceived + +# Target form URL - the actual web form to fill +FORM_URL = "https://forms.fillout.com/t/rff6XZTSApus" + +# Initialize Gemini client +gemini_client = genai.Client(api_key=os.getenv("GEMINI_API_KEY")) + + +async def handle_new_call(system: VoiceAgentSystem, call_request: CallRequest) -> None: + """Handle incoming voice calls with real-time web form filling. + + This agent will: + 1. Conduct a voice conversation to gather information + 2. Open and fill an actual web form in the background + 3. Submit the form when the conversation is complete + + Args: + system: The voice agent system instance. + call_request: The incoming call request. + """ + + # Create form filling node with browser automation + form_node = FormFillingNode( + system_prompt=SYSTEM_PROMPT, gemini_client=gemini_client, form_url=FORM_URL + ) + + # Set up bridge for event handling + form_bridge = Bridge(form_node) + system.with_speaking_node(form_node, bridge=form_bridge) + + # Connect transcription events + form_bridge.on(UserTranscriptionReceived).map(form_node.add_event) + + # Handle interruptions and streaming + ( + form_bridge.on(UserStoppedSpeaking) + .interrupt_on(UserStartedSpeaking, handler=form_node.on_interrupt_generate) + .stream(form_node.generate) + .broadcast() + ) + + # Start the system + await system.start() + + # Wait for call to end + await system.wait_for_shutdown() + + # Ensure form is submitted when call ends + await form_node.cleanup_and_submit() + + +# Create the voice agent application +app = VoiceAgentApp(handle_new_call) + +if __name__ == "__main__": + print("Starting Voice Agent with Web Form Automation") + print(f"Will fill form at: {FORM_URL}") + print("Ready to receive calls...") + print("Form filling happens invisibly while processing voice calls.\n") + app.run() diff --git a/examples/integrations/cartesia/requirements.txt b/examples/integrations/cartesia/requirements.txt new file mode 100644 index 0000000..25b3aa7 --- /dev/null +++ b/examples/integrations/cartesia/requirements.txt @@ -0,0 +1,8 @@ +cartesia-line +aiohttp>=3.12.0 +google-genai>=1.26.0; python_version>='3.9' +loguru>=0.7.0 +python-dotenv>=1.0.0 +PyYAML>=6.0.0 +stagehand>=0.5.4 +pydantic>=2.0.0 diff --git a/examples/integrations/cartesia/stagehand_form_filler.py b/examples/integrations/cartesia/stagehand_form_filler.py new file mode 100644 index 0000000..2b3f20c --- /dev/null +++ b/examples/integrations/cartesia/stagehand_form_filler.py @@ -0,0 +1,270 @@ +"""Browser automation for filling web forms during voice conversations. + +This module provides the StagehandFormFiller class which manages browser +automation for filling forms using Stagehand. It handles form field +mapping, field filling, and form submission. +""" + +import asyncio +from dataclasses import dataclass +from enum import Enum +import os +from typing import Dict, List, Optional + +from loguru import logger +from stagehand import Stagehand, StagehandConfig + + +class FieldType(Enum): + TEXT = "text" + EMAIL = "email" + PHONE = "phone" + SELECT = "select" + RADIO = "radio" + CHECKBOX = "checkbox" + TEXTAREA = "textarea" + + +@dataclass +class FormField: + """Represents a form field with its metadata""" + + field_id: str + field_type: FieldType + label: str + required: bool = False + options: Optional[List[str]] = None + + +class FormFieldMapping: + """Maps conversation questions to actual form fields""" + + def __init__(self): + self.field_mappings = { + "full_name": FormField( + field_id="full_name", + field_type=FieldType.TEXT, + label="What is your full name?", + required=True, + ), + "email": FormField( + field_id="email", + field_type=FieldType.EMAIL, + label="What is your email address?", + required=True, + ), + "phone": FormField( + field_id="phone", + field_type=FieldType.PHONE, + label="What is your phone number?", + required=False, + ), + "work_eligibility": FormField( + field_id="work_eligibility", + field_type=FieldType.RADIO, + label="Are you legally eligible to work in this country?", + options=["Yes", "No"], + required=True, + ), + "availability_type": FormField( + field_id="availability", + field_type=FieldType.RADIO, + label="What's your availability?", + options=["Temporary", "Part-time", "Full-time"], + required=True, + ), + "additional_info": FormField( + field_id="additional_info", + field_type=FieldType.TEXTAREA, + label="Anything else you'd like to let us know about you?", + required=False, + ), + "role_selection": FormField( + field_id="role_selection", + field_type=FieldType.CHECKBOX, + label="Which of these roles are you applying for?", + options=[ + "Sales manager", + "IT Support", + "Recruiting", + "Software engineer", + "Marketing specialist", + ], + required=True, + ), + "previous_experience": FormField( + field_id="previous_experience", + field_type=FieldType.RADIO, + label=("Have you worked in a role similar to this one in the past?"), + options=["Yes", "No"], + required=True, + ), + "skills_experience": FormField( + field_id="skills_experience", + field_type=FieldType.TEXTAREA, + label=( + "What relevant skills and experience do you have " + "that make you a strong candidate for this position?" + ), + required=True, + ), + } + + def get_form_field(self, question_id: str) -> Optional[FormField]: + """Get the form field mapping for a question ID. + + Args: + question_id: The question identifier. + + Returns: + The FormField object or None if not found. + """ + return self.field_mappings.get(question_id) + + +class StagehandFormFiller: + """Manages browser automation for filling forms using Stagehand""" + + def __init__(self, form_url: str): + self.form_url = form_url + self.stagehand: Optional[Stagehand] = None + self.page = None + self.is_initialized = False + self.field_mapper = FormFieldMapping() + self.collected_data: Dict[str, str] = {} + + async def initialize(self) -> None: + """Initialize Stagehand and open the form. + + Returns: + None. + """ + if self.is_initialized: + return + + try: + logger.info("Initializing Stagehand browser automation") + + # Configure Stagehand + config = StagehandConfig( + env="BROWSERBASE", + # Fast model for form filling + model_name="google/gemini-2.0-flash-exp", + model_api_key=os.getenv("GEMINI_API_KEY"), + ) + + self.stagehand = Stagehand(config) + await self.stagehand.init() + + self.page = self.stagehand.page + + # Navigate to form + logger.info(f"Opening form: {self.form_url}") + await self.page.goto(self.form_url) + + # Wait for form to load + await asyncio.sleep(2) + + self.is_initialized = True + logger.info("Browser automation initialized successfully") + + except Exception as e: + logger.error(f"Failed to initialize Stagehand: {e}") + raise + + async def fill_field(self, question_id: str, answer: str) -> bool: + """Fill a specific form field based on the question ID and answer. + + Args: + question_id: The question identifier. + answer: The answer value to fill. + + Returns: + True if field was filled successfully, False otherwise. + """ + if not self.is_initialized: + # Initialize asynchronously without blocking + init_task = asyncio.create_task(self.initialize()) + await init_task + + try: + # Get field mapping + field = self.field_mapper.get_form_field(question_id) + if not field: + logger.warning(f"No field mapping found for question: {question_id}") + return False + + # Store and use the answer directly + answer = answer.strip() + self.collected_data[question_id] = answer + + logger.info(f"Async filling field '{field.label}' with: {answer}") + + # Create async task for the actual field filling + fill_action = None + + # Use Stagehand's natural language API to fill the field + if field.field_type in [FieldType.TEXT, FieldType.EMAIL, FieldType.PHONE]: + fill_action = self.page.act(f"Fill in the '{field.label}' field with: {answer}") + + elif field.field_type == FieldType.TEXTAREA: + fill_action = self.page.act(f"Type in the '{field.label}' text area: {answer}") + + elif field.field_type in [FieldType.SELECT, FieldType.RADIO]: + fill_action = self.page.act(f"Select '{answer}' for the '{field.label}' field") + + elif field.field_type == FieldType.CHECKBOX: + # For role selection, check the specific role checkbox + if question_id == "role_selection": + fill_action = self.page.act(f"Check the '{answer}' checkbox") + else: + # For other checkboxes, check/uncheck based on answer + if answer.lower() in ["yes", "true"]: + fill_action = self.page.act(f"Check the '{field.label}' checkbox") + else: + fill_action = self.page.act(f"Uncheck the '{field.label}' checkbox") + + # Execute the fill action asynchronously + if fill_action: + await fill_action + + return True + + except Exception as e: + logger.error(f"Error filling field {question_id}: {e}") + return False + + async def submit_form(self) -> bool: + """Submit the completed form. + + Returns: + True if form was submitted successfully, False otherwise. + """ + try: + logger.info("Submitting the form") + logger.info(f"Form has {len(self.collected_data)} fields filled") + + await self.page.act("Find and click the Submit button to submit the form") + + # Wait for submission to process + await asyncio.sleep(1) + + logger.info("Form submitted successfully!") + return True + + except Exception as e: + logger.error(f"Error submitting form: {e}") + return False + + async def cleanup(self) -> None: + """Clean up browser resources. + + Returns: + None. + """ + if self.stagehand or self.page: + try: + await self.stagehand.close() + logger.info("Browser closed") + except Exception as e: + logger.error(f"Error closing browser: {e}") diff --git a/examples/integrations/cartesia/workflow_diagram.png b/examples/integrations/cartesia/workflow_diagram.png new file mode 100644 index 0000000..59d60e8 Binary files /dev/null and b/examples/integrations/cartesia/workflow_diagram.png differ diff --git a/examples/integrations/crewai/README.md b/examples/integrations/crewai/README.md index 3b71cdb..55e04f0 100644 --- a/examples/integrations/crewai/README.md +++ b/examples/integrations/crewai/README.md @@ -15,4 +15,26 @@ AI Agents rely on tools to gather rich contexts and perform actions to achieve s Browserbase provides a `BrowserbaseLoadTool` that Agents can use to retrieve context from complex webpages, enabling them to: - Extract text from webpages using JavaScript or anti-bot mechanisms -- Capture Images from webpages \ No newline at end of file +- Capture Images from webpages + +## Stagehand Integration + +Automate browser tasks using natural language instructions with CrewAI + +This tool integrates the Stagehand Python SDK with CrewAI, allowing agents to interact with websites and automate browser tasks using natural language instructions. + +### Description + +The StagehandTool wraps the Stagehand Python SDK to provide CrewAI agents with the ability to control a real web browser and interact with websites using three core primitives: + +- **Act**: Perform actions like clicking, typing, or navigating +- **Extract**: Extract structured data from web pages +- **Observe**: Identify and analyze elements on the page + +### Requirements + +Before using this tool, you will need: + +- A Browserbase account with API key and project ID +- An API key for an LLM (OpenAI or Anthropic Claude) +- The Stagehand Python SDK installed diff --git a/examples/integrations/crewai/crewai-tutorial/poetry.lock b/examples/integrations/crewai/crewai-tutorial/poetry.lock index 2661f94..bc1553c 100644 --- a/examples/integrations/crewai/crewai-tutorial/poetry.lock +++ b/examples/integrations/crewai/crewai-tutorial/poetry.lock @@ -1,126 +1,124 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.1.1 and should not be changed by hand. 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">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4 requests = ">=2.18.0,<3.0.0.dev0" [package.extras] -grpc = ["grpcio (>=1.33.2,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "grpcio-status (>=1.33.2,<2.0.dev0)", "grpcio-status (>=1.49.1,<2.0.dev0)"] +grpc = ["grpcio (>=1.33.2,<2.0dev)", "grpcio (>=1.49.1,<2.0dev) ; python_version >= \"3.11\"", "grpcio-status (>=1.33.2,<2.0.dev0)", "grpcio-status (>=1.49.1,<2.0.dev0) ; python_version >= \"3.11\""] grpcgcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"] grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"] @@ -1493,6 +1556,7 @@ version = "2.34.0" description = "Google Authentication Library" optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "google_auth-2.34.0-py2.py3-none-any.whl", hash = "sha256:72fd4733b80b6d777dcde515628a9eb4a577339437012874ea286bca7261ee65"}, {file = "google_auth-2.34.0.tar.gz", hash = "sha256:8eb87396435c19b20d32abd2f984e31c191a15284af72eb922f10e5bde9c04cc"}, @@ -1516,6 +1580,7 @@ version = "1.66.0" description = "Vertex AI API client library" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "google-cloud-aiplatform-1.66.0.tar.gz", hash = "sha256:e95a2b45087e0e2cbfed9ffaf3f10aa8ef3fa2e5642f067246181b5c7b9b2b04"}, {file = "google_cloud_aiplatform-1.66.0-py2.py3-none-any.whl", hash = "sha256:3f7de6aab42f67b933a36bfb1354e36a5256f45780df92ac8b1b6361a145af49"}, @@ -1537,10 +1602,10 @@ shapely = "<3.0.0dev" [package.extras] autologging = ["mlflow (>=1.27.0,<=2.1.1)"] cloud-profiler = ["tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "werkzeug (>=2.0.0,<2.1.0dev)"] -datasets = ["pyarrow (>=10.0.1)", "pyarrow (>=14.0.0)", "pyarrow (>=3.0.0,<8.0dev)"] +datasets = ["pyarrow (>=10.0.1) ; python_version == \"3.11\"", "pyarrow (>=14.0.0) ; python_version >= \"3.12\"", "pyarrow (>=3.0.0,<8.0dev) ; python_version < \"3.11\""] endpoint = ["requests (>=2.28.1)"] evaluation = ["pandas (>=1.0.0,<2.2.0)", "tqdm (>=4.23.0)"] 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"uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)"] langchain = ["langchain (>=0.1.16,<0.3)", "langchain-core (<0.3)", "langchain-google-vertexai (<2)", "openinference-instrumentation-langchain (>=0.1.19,<0.2)", "orjson (<=3.10.6)", "tenacity (<=8.3)"] langchain-testing = ["absl-py", "cloudpickle (>=3.0,<4.0)", "google-cloud-trace (<2)", "langchain (>=0.1.16,<0.3)", "langchain-core (<0.3)", "langchain-google-vertexai (<2)", "openinference-instrumentation-langchain (>=0.1.19,<0.2)", "opentelemetry-exporter-gcp-trace (<2)", "opentelemetry-sdk (<2)", "orjson (<=3.10.6)", "pydantic (>=2.6.3,<3)", "pytest-xdist", "tenacity (<=8.3)"] lit = ["explainable-ai-sdk (>=1.0.0)", "lit-nlp (==0.4.0)", "pandas (>=1.0.0)", "tensorflow (>=2.3.0,<3.0.0dev)"] @@ -1548,11 +1613,11 @@ metadata = ["numpy (>=1.15.0)", "pandas (>=1.0.0)"] pipelines = ["pyyaml (>=5.3.1,<7)"] prediction = ["docker (>=5.0.3)", "fastapi (>=0.71.0,<=0.114.0)", "httpx (>=0.23.0,<0.25.0)", "starlette (>=0.17.1)", 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(>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)", "xgboost"] tokenization = ["sentencepiece (>=0.2.0)"] vizier = ["google-vizier (>=0.1.6)"] xai = ["tensorflow (>=2.3.0,<3.0.0dev)"] @@ -1563,6 +1628,7 @@ version = "3.25.0" description = "Google BigQuery API client library" optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "google-cloud-bigquery-3.25.0.tar.gz", hash = "sha256:5b2aff3205a854481117436836ae1403f11f2594e6810a98886afd57eda28509"}, {file = "google_cloud_bigquery-3.25.0-py2.py3-none-any.whl", hash = "sha256:7f0c371bc74d2a7fb74dacbc00ac0f90c8c2bec2289b51dd6685a275873b1ce9"}, @@ -1578,14 +1644,14 @@ python-dateutil = ">=2.7.2,<3.0dev" requests = ">=2.21.0,<3.0.0dev" [package.extras] -all = ["Shapely (>=1.8.4,<3.0.0dev)", "db-dtypes (>=0.3.0,<2.0.0dev)", "geopandas (>=0.9.0,<1.0dev)", "google-cloud-bigquery-storage (>=2.6.0,<3.0.0dev)", "grpcio (>=1.47.0,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "importlib-metadata (>=1.0.0)", "ipykernel (>=6.0.0)", 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"importlib-metadata (>=1.0.0)", "pandas (>=1.1.0)", "pyarrow (>=3.0.0)"] +pandas = ["db-dtypes (>=0.3.0,<2.0.0dev)", "importlib-metadata (>=1.0.0) ; python_version < \"3.8\"", "pandas (>=1.1.0)", "pyarrow (>=3.0.0)"] tqdm = ["tqdm (>=4.7.4,<5.0.0dev)"] [[package]] @@ -1594,6 +1660,7 @@ version = "2.4.1" description = "Google Cloud API client core library" optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "google-cloud-core-2.4.1.tar.gz", hash = "sha256:9b7749272a812bde58fff28868d0c5e2f585b82f37e09a1f6ed2d4d10f134073"}, {file = "google_cloud_core-2.4.1-py2.py3-none-any.whl", hash = "sha256:a9e6a4422b9ac5c29f79a0ede9485473338e2ce78d91f2370c01e730eab22e61"}, @@ -1612,6 +1679,7 @@ version = "1.12.5" description = "Google Cloud Resource Manager API client library" optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "google_cloud_resource_manager-1.12.5-py2.py3-none-any.whl", hash = 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"sha256:334a29d07cddc3aa01dee4988f9afd9b2916ee2ff49d6b757155dc0d197852c0"}, @@ -1728,6 +1800,7 @@ version = "0.1.44" description = "GPTCache, a powerful caching library that can be used to speed up and lower the cost of chat applications that rely on the LLM service. GPTCache works as a memcache for AIGC applications, similar to how Redis works for traditional applications." optional = false python-versions = ">=3.8.1" +groups = ["main"] files = [ {file = "gptcache-0.1.44-py3-none-any.whl", hash = "sha256:11ddd63b173dc3822b8c2eb7588ea947c825845ed0737b043038a238286bfec4"}, {file = "gptcache-0.1.44.tar.gz", hash = "sha256:d3d5e6a75c57594dc58212c2d6c53a7999c23ede30e0be66d213d885c0ad0be9"}, @@ -1744,6 +1817,7 @@ version = "3.0.3" description = "Lightweight in-process concurrent programming" optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "greenlet-3.0.3-cp310-cp310-macosx_11_0_universal2.whl", hash = "sha256:9da2bd29ed9e4f15955dd1595ad7bc9320308a3b766ef7f837e23ad4b4aac31a"}, {file = "greenlet-3.0.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d353cadd6083fdb056bb46ed07e4340b0869c305c8ca54ef9da3421acbdf6881"}, @@ -1815,6 +1889,7 @@ version = "0.13.1" description = "IAM API client library" optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "grpc-google-iam-v1-0.13.1.tar.gz", hash = "sha256:3ff4b2fd9d990965e410965253c0da6f66205d5a8291c4c31c6ebecca18a9001"}, {file = "grpc_google_iam_v1-0.13.1-py2.py3-none-any.whl", hash = "sha256:c3e86151a981811f30d5e7330f271cee53e73bb87755e88cc3b6f0c7b5fe374e"}, @@ -1831,6 +1906,7 @@ version = "1.66.1" description = "HTTP/2-based RPC framework" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "grpcio-1.66.1-cp310-cp310-linux_armv7l.whl", hash = "sha256:4877ba180591acdf127afe21ec1c7ff8a5ecf0fe2600f0d3c50e8c4a1cbc6492"}, {file = "grpcio-1.66.1-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:3750c5a00bd644c75f4507f77a804d0189d97a107eb1481945a0cf3af3e7a5ac"}, @@ -1889,6 +1965,7 @@ version = "1.62.3" description = "Status proto mapping for gRPC" optional = false python-versions = ">=3.6" +groups = ["main"] files = [ {file = "grpcio-status-1.62.3.tar.gz", hash = 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["main"] files = [ {file = "hpack-4.0.0-py3-none-any.whl", hash = "sha256:84a076fad3dc9a9f8063ccb8041ef100867b1878b25ef0ee63847a5d53818a6c"}, {file = "hpack-4.0.0.tar.gz", hash = "sha256:fc41de0c63e687ebffde81187a948221294896f6bdc0ae2312708df339430095"}, @@ -2004,30 +2085,32 @@ version = "2024.2.26" description = "Turn HTML into equivalent Markdown-structured text." optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "html2text-2024.2.26.tar.gz", hash = "sha256:05f8e367d15aaabc96415376776cdd11afd5127a77fce6e36afc60c563ca2c32"}, ] [[package]] name = "httpcore" -version = "1.0.5" +version = "1.0.9" description = "A minimal low-level HTTP client." optional = false python-versions = ">=3.8" +groups = ["main"] files = [ - {file = "httpcore-1.0.5-py3-none-any.whl", hash = "sha256:421f18bac248b25d310f3cacd198d55b8e6125c107797b609ff9b7a6ba7991b5"}, - {file = "httpcore-1.0.5.tar.gz", hash = "sha256:34a38e2f9291467ee3b44e89dd52615370e152954ba21721378a87b2960f7a61"}, + {file = "httpcore-1.0.9-py3-none-any.whl", hash = "sha256:2d400746a40668fc9dec9810239072b40b4484b640a8c38fd654a024c7a1bf55"}, + {file = "httpcore-1.0.9.tar.gz", hash = "sha256:6e34463af53fd2ab5d807f399a9b45ea31c3dfa2276f15a2c3f00afff6e176e8"}, ] [package.dependencies] certifi = "*" -h11 = ">=0.13,<0.15" +h11 = ">=0.16" [package.extras] asyncio = ["anyio (>=4.0,<5.0)"] http2 = ["h2 (>=3,<5)"] socks = ["socksio (==1.*)"] -trio = ["trio (>=0.22.0,<0.26.0)"] +trio = ["trio (>=0.22.0,<1.0)"] [[package]] name = "httptools" @@ -2035,6 +2118,7 @@ version = "0.6.1" description = "A collection of framework independent HTTP protocol utils." optional = false python-versions = ">=3.8.0" +groups = ["main"] files = [ {file = "httptools-0.6.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:d2f6c3c4cb1948d912538217838f6e9960bc4a521d7f9b323b3da579cd14532f"}, {file = "httptools-0.6.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:00d5d4b68a717765b1fabfd9ca755bd12bf44105eeb806c03d1962acd9b8e563"}, @@ -2083,6 +2167,7 @@ version = "0.27.2" description = "The next generation HTTP client." optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "httpx-0.27.2-py3-none-any.whl", hash = "sha256:7bb2708e112d8fdd7829cd4243970f0c223274051cb35ee80c03301ee29a3df0"}, {file = "httpx-0.27.2.tar.gz", hash = "sha256:f7c2be1d2f3c3c3160d441802406b206c2b76f5947b11115e6df10c6c65e66c2"}, @@ -2097,7 +2182,7 @@ idna = "*" sniffio = "*" [package.extras] -brotli = ["brotli", "brotlicffi"] +brotli = ["brotli ; platform_python_implementation == \"CPython\"", "brotlicffi ; platform_python_implementation != \"CPython\""] cli = ["click (==8.*)", "pygments (==2.*)", "rich (>=10,<14)"] http2 = ["h2 (>=3,<5)"] socks = ["socksio (==1.*)"] @@ -2109,6 +2194,7 @@ version = "0.4.0" description = "Consume Server-Sent Event (SSE) messages with HTTPX." optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "httpx-sse-0.4.0.tar.gz", hash = "sha256:1e81a3a3070ce322add1d3529ed42eb5f70817f45ed6ec915ab753f961139721"}, {file = "httpx_sse-0.4.0-py3-none-any.whl", hash = "sha256:f329af6eae57eaa2bdfd962b42524764af68075ea87370a2de920af5341e318f"}, @@ -2120,6 +2206,7 @@ version = "0.25.0" description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub" optional = false python-versions = ">=3.8.0" +groups = ["main"] files = [ {file = "huggingface_hub-0.25.0-py3-none-any.whl", hash = "sha256:e2f357b35d72d5012cfd127108c4e14abcd61ba4ebc90a5a374dc2456cb34e12"}, {file = "huggingface_hub-0.25.0.tar.gz", hash = "sha256:fb5fbe6c12fcd99d187ec7db95db9110fb1a20505f23040a5449a717c1a0db4d"}, @@ -2154,6 +2241,7 @@ version = "10.0" description = "Human friendly output for text interfaces using Python" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" +groups = ["main"] files = [ {file = "humanfriendly-10.0-py2.py3-none-any.whl", hash = "sha256:1697e1a8a8f550fd43c2865cd84542fc175a61dcb779b6fee18cf6b6ccba1477"}, {file = "humanfriendly-10.0.tar.gz", hash = "sha256:6b0b831ce8f15f7300721aa49829fc4e83921a9a301cc7f606be6686a2288ddc"}, @@ -2168,6 +2256,7 @@ version = "6.0.1" description = "HTTP/2 framing layer for Python" optional = false python-versions = ">=3.6.1" +groups = ["main"] files = [ {file = "hyperframe-6.0.1-py3-none-any.whl", hash = "sha256:0ec6bafd80d8ad2195c4f03aacba3a8265e57bc4cff261e802bf39970ed02a15"}, {file = "hyperframe-6.0.1.tar.gz", hash = "sha256:ae510046231dc8e9ecb1a6586f63d2347bf4c8905914aa84ba585ae85f28a914"}, @@ -2179,6 +2268,7 @@ version = "3.10" description = "Internationalized Domain Names in Applications (IDNA)" optional = false python-versions = ">=3.6" +groups = ["main"] files = [ {file = "idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3"}, {file = "idna-3.10.tar.gz", hash = "sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9"}, @@ -2193,6 +2283,7 @@ version = "8.4.0" description = "Read metadata from Python packages" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "importlib_metadata-8.4.0-py3-none-any.whl", hash = "sha256:66f342cc6ac9818fc6ff340576acd24d65ba0b3efabb2b4ac08b598965a4a2f1"}, {file = "importlib_metadata-8.4.0.tar.gz", hash = "sha256:9a547d3bc3608b025f93d403fdd1aae741c24fbb8314df4b155675742ce303c5"}, @@ -2204,7 +2295,7 @@ zipp = ">=0.5" [package.extras] doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] perf = ["ipython"] -test = ["flufl.flake8", "importlib-resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-perf (>=0.9.2)", "pytest-ruff (>=0.2.1)"] +test = ["flufl.flake8", "importlib-resources (>=1.3) ; python_version < \"3.9\"", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-perf (>=0.9.2)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\""] [[package]] name = "importlib-resources" @@ -2212,13 +2303,14 @@ version = "6.4.5" description = "Read resources from Python packages" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "importlib_resources-6.4.5-py3-none-any.whl", hash = "sha256:ac29d5f956f01d5e4bb63102a5a19957f1b9175e45649977264a1416783bb717"}, {file = "importlib_resources-6.4.5.tar.gz", hash = "sha256:980862a1d16c9e147a59603677fa2aa5fd82b87f223b6cb870695bcfce830065"}, ] [package.extras] -check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"] +check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\""] cover = ["pytest-cov"] doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] enabler = ["pytest-enabler (>=2.2)"] @@ -2231,6 +2323,7 @@ version = "2.0.0" description = "brain-dead simple config-ini parsing" optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "iniconfig-2.0.0-py3-none-any.whl", hash = "sha256:b6a85871a79d2e3b22d2d1b94ac2824226a63c6b741c88f7ae975f18b6778374"}, {file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"}, @@ -2242,6 +2335,7 @@ version = "0.7.0" description = "A library for installing Python wheels." optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "installer-0.7.0-py3-none-any.whl", hash = "sha256:05d1933f0a5ba7d8d6296bb6d5018e7c94fa473ceb10cf198a92ccea19c27b53"}, {file = "installer-0.7.0.tar.gz", hash = "sha256:a26d3e3116289bb08216e0d0f7d925fcef0b0194eedfa0c944bcaaa106c4b631"}, @@ -2253,6 +2347,7 @@ version = "1.3.3" description = "structured outputs for llm" optional = false python-versions = "<4.0,>=3.9" +groups = ["main"] files = [ {file = "instructor-1.3.3-py3-none-any.whl", hash = "sha256:94b114b39a1181fa348d162e6e4ff5c4d985324736020c0233fed5d4db444dbd"}, {file = "instructor-1.3.3.tar.gz", hash = "sha256:e27bf3c1187b0b2130ea38ecde7c2b4f571d6a5ce1397fb15c27490988b45441"}, @@ -2285,6 +2380,7 @@ version = "5.13.2" description = "A Python utility / library to sort Python imports." optional = false python-versions = ">=3.8.0" +groups = ["dev"] files = [ {file = "isort-5.13.2-py3-none-any.whl", hash = "sha256:8ca5e72a8d85860d5a3fa69b8745237f2939afe12dbf656afbcb47fe72d947a6"}, {file = "isort-5.13.2.tar.gz", hash = "sha256:48fdfcb9face5d58a4f6dde2e72a1fb8dcaf8ab26f95ab49fab84c2ddefb0109"}, @@ -2299,6 +2395,7 @@ version = "3.4.0" description = "Utility functions for Python class constructs" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "jaraco.classes-3.4.0-py3-none-any.whl", hash = "sha256:f662826b6bed8cace05e7ff873ce0f9283b5c924470fe664fff1c2f00f581790"}, {file = "jaraco.classes-3.4.0.tar.gz", hash = "sha256:47a024b51d0239c0dd8c8540c6c7f484be3b8fcf0b2d85c13825780d3b3f3acd"}, @@ -2317,6 +2414,8 @@ version = "0.8.0" description = "Low-level, pure Python DBus protocol wrapper." optional = false python-versions = ">=3.7" +groups = ["main"] +markers = "sys_platform == \"linux\"" files = [ {file = "jeepney-0.8.0-py3-none-any.whl", hash = "sha256:c0a454ad016ca575060802ee4d590dd912e35c122fa04e70306de3d076cce755"}, {file = "jeepney-0.8.0.tar.gz", hash = "sha256:5efe48d255973902f6badc3ce55e2aa6c5c3b3bc642059ef3a91247bcfcc5806"}, @@ -2324,17 +2423,18 @@ files = [ [package.extras] test = ["async-timeout", "pytest", "pytest-asyncio (>=0.17)", "pytest-trio", "testpath", "trio"] -trio = ["async_generator", "trio"] +trio = ["async_generator ; python_version == \"3.6\"", "trio"] [[package]] name = "jinja2" -version = "3.1.4" +version = "3.1.6" description = "A very fast and expressive template engine." optional = false python-versions = ">=3.7" +groups = ["main"] files = [ - {file = "jinja2-3.1.4-py3-none-any.whl", hash = "sha256:bc5dd2abb727a5319567b7a813e6a2e7318c39f4f487cfe6c89c6f9c7d25197d"}, - {file = "jinja2-3.1.4.tar.gz", hash = "sha256:4a3aee7acbbe7303aede8e9648d13b8bf88a429282aa6122a993f0ac800cb369"}, + {file = "jinja2-3.1.6-py3-none-any.whl", hash = "sha256:85ece4451f492d0c13c5dd7c13a64681a86afae63a5f347908daf103ce6d2f67"}, + {file = "jinja2-3.1.6.tar.gz", hash = "sha256:0137fb05990d35f1275a587e9aee6d56da821fc83491a0fb838183be43f66d6d"}, ] [package.dependencies] @@ -2349,6 +2449,7 @@ version = "0.4.2" description = "Fast iterable JSON parser." optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "jiter-0.4.2-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:c2b003ff58d14f5e182b875acd5177b2367245c19a03be9a2230535d296f7550"}, {file = "jiter-0.4.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:b48c77c25f094707731cd5bad6b776046846b60a27ee20efc8fadfb10a89415f"}, @@ -2419,6 +2520,7 @@ version = "1.0.1" description = "JSON Matching Expressions" optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "jmespath-1.0.1-py3-none-any.whl", hash = "sha256:02e2e4cc71b5bcab88332eebf907519190dd9e6e82107fa7f83b1003a6252980"}, {file = "jmespath-1.0.1.tar.gz", hash = "sha256:90261b206d6defd58fdd5e85f478bf633a2901798906be2ad389150c5c60edbe"}, @@ -2430,6 +2532,7 @@ version = "0.25.3" description = "A package to repair broken json strings" optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "json_repair-0.25.3-py3-none-any.whl", hash = "sha256:f00b510dd21b31ebe72581bdb07e66381df2883d6f640c89605e482882c12b17"}, {file = "json_repair-0.25.3.tar.gz", hash = "sha256:4ee970581a05b0b258b749eb8bcac21de380edda97c3717a4edfafc519ec21a4"}, @@ -2441,6 +2544,7 @@ version = "1.33" description = "Apply JSON-Patches (RFC 6902)" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*" +groups = ["main"] files = [ {file = "jsonpatch-1.33-py2.py3-none-any.whl", hash = "sha256:0ae28c0cd062bbd8b8ecc26d7d164fbbea9652a1a3693f3b956c1eae5145dade"}, {file = "jsonpatch-1.33.tar.gz", hash = "sha256:9fcd4009c41e6d12348b4a0ff2563ba56a2923a7dfee731d004e212e1ee5030c"}, @@ -2455,6 +2559,7 @@ version = "3.0.0" description = "Identify specific nodes in a JSON document (RFC 6901)" optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "jsonpointer-3.0.0-py2.py3-none-any.whl", hash = "sha256:13e088adc14fca8b6aa8177c044e12701e6ad4b28ff10e65f2267a90109c9942"}, {file = "jsonpointer-3.0.0.tar.gz", hash = "sha256:2b2d729f2091522d61c3b31f82e11870f60b68f43fbc705cb76bf4b832af59ef"}, @@ -2466,6 +2571,7 @@ version = "1.1.0" description = "jsonref is a library for automatic dereferencing of JSON Reference objects for Python." optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "jsonref-1.1.0-py3-none-any.whl", hash = "sha256:590dc7773df6c21cbf948b5dac07a72a251db28b0238ceecce0a2abfa8ec30a9"}, {file = "jsonref-1.1.0.tar.gz", hash = "sha256:32fe8e1d85af0fdefbebce950af85590b22b60f9e95443176adbde4e1ecea552"}, @@ -2477,6 +2583,7 @@ version = "4.23.0" description = "An implementation of JSON Schema validation for Python" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "jsonschema-4.23.0-py3-none-any.whl", hash = "sha256:fbadb6f8b144a8f8cf9f0b89ba94501d143e50411a1278633f56a7acf7fd5566"}, {file = "jsonschema-4.23.0.tar.gz", hash = "sha256:d71497fef26351a33265337fa77ffeb82423f3ea21283cd9467bb03999266bc4"}, @@ -2498,6 +2605,7 @@ version = "2023.12.1" description = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "jsonschema_specifications-2023.12.1-py3-none-any.whl", hash = "sha256:87e4fdf3a94858b8a2ba2778d9ba57d8a9cafca7c7489c46ba0d30a8bc6a9c3c"}, {file = "jsonschema_specifications-2023.12.1.tar.gz", hash = "sha256:48a76787b3e70f5ed53f1160d2b81f586e4ca6d1548c5de7085d1682674764cc"}, @@ -2512,6 +2620,7 @@ version = "24.3.1" description = "Store and access your passwords safely." optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "keyring-24.3.1-py3-none-any.whl", hash = "sha256:df38a4d7419a6a60fea5cef1e45a948a3e8430dd12ad88b0f423c5c143906218"}, {file = "keyring-24.3.1.tar.gz", hash = "sha256:c3327b6ffafc0e8befbdb597cacdb4928ffe5c1212f7645f186e6d9957a898db"}, @@ -2526,7 +2635,7 @@ SecretStorage = {version = ">=3.2", markers = "sys_platform == \"linux\""} [package.extras] completion = ["shtab (>=1.1.0)"] docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"] -testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-ruff (>=0.2.1)"] +testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy ; platform_python_implementation != \"PyPy\"", "pytest-ruff (>=0.2.1)"] [[package]] name = "kubernetes" @@ -2534,6 +2643,7 @@ version = "30.1.0" description = "Kubernetes python client" optional = false python-versions = ">=3.6" +groups = ["main"] files = [ {file = "kubernetes-30.1.0-py2.py3-none-any.whl", hash = "sha256:e212e8b7579031dd2e512168b617373bc1e03888d41ac4e04039240a292d478d"}, {file = "kubernetes-30.1.0.tar.gz", hash = "sha256:41e4c77af9f28e7a6c314e3bd06a8c6229ddd787cad684e0ab9f69b498e98ebc"}, @@ -2560,6 +2670,7 @@ version = "0.5.7" description = "lancedb" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "lancedb-0.5.7-py3-none-any.whl", hash = "sha256:6169966f715ef530be545950e1aaf9f3f160967e4ba7456cd67c9f30f678095d"}, {file = "lancedb-0.5.7.tar.gz", hash = "sha256:878914b493f91d09a77b14f1528104741f273234cbdd6671be705f447701fd51"}, @@ -2593,6 +2704,7 @@ version = "0.2.16" description = "Building applications with LLMs through composability" optional = false python-versions = "<4.0,>=3.8.1" +groups = ["main"] files = [ {file = "langchain-0.2.16-py3-none-any.whl", hash = "sha256:8f59ee8b45f268df4b924ea3b9c63e49286efa756d16b3f6a9de5c6e502c36e1"}, {file = "langchain-0.2.16.tar.gz", hash = "sha256:ffb426a76a703b73ac69abad77cd16eaf03dda76b42cff55572f592d74944166"}, @@ -2616,6 +2728,7 @@ version = "0.1.9" description = "An integration package connecting Cohere and LangChain" optional = false python-versions = "<4.0,>=3.8.1" +groups = ["main"] files = [ {file = "langchain_cohere-0.1.9-py3-none-any.whl", hash = "sha256:96d6a15125797319474ac84b54024e5024f3f5fc45032ebf228d95d6998c9b13"}, {file = "langchain_cohere-0.1.9.tar.gz", hash = "sha256:549620d23bc3d77f62d1045787095fe2c1cfa233dba69455139f9a2f65f952fa"}, @@ -2637,6 +2750,7 @@ version = "0.2.17" description = "Community contributed LangChain integrations." optional = false python-versions = "<4.0,>=3.8.1" +groups = ["main"] files = [ {file = "langchain_community-0.2.17-py3-none-any.whl", hash = "sha256:d07c31b641e425fb8c3e7148ad6a62e1b54a9adac6e1173021a7dd3148266063"}, {file = "langchain_community-0.2.17.tar.gz", hash = "sha256:b0745c1fcf1bd532ed4388f90b47139d6a6c6ba48a87aa68aa32d4d6bb97259d"}, @@ -2656,13 +2770,14 @@ tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0" [[package]] name = "langchain-core" -version = "0.2.40" +version = "0.2.43" description = "Building applications with LLMs through composability" optional = false python-versions = "<4.0,>=3.8.1" +groups = ["main"] files = [ - {file = "langchain_core-0.2.40-py3-none-any.whl", hash = "sha256:71fff5cafa4b9c82a3a716e985f071383be452c35d8cc3169b3a393e6857fc99"}, - {file = "langchain_core-0.2.40.tar.gz", hash = "sha256:c838ea0c0b73475a8e58ced3e306b6d926ef063721abd164f237c8664916f502"}, + {file = "langchain_core-0.2.43-py3-none-any.whl", hash = "sha256:619601235113298ebf8252a349754b7c28d3cf7166c7c922da24944b78a9363a"}, + {file = "langchain_core-0.2.43.tar.gz", hash = "sha256:42c2ef6adedb911f4254068b6adc9eb4c4075f6c8cb3d83590d3539a815695f5"}, ] [package.dependencies] @@ -2683,6 +2798,7 @@ version = "0.0.65" description = "Building applications with LLMs through composability" optional = false python-versions = "<4.0,>=3.8.1" +groups = ["main"] files = [ {file = "langchain_experimental-0.0.65-py3-none-any.whl", hash = "sha256:2a0f268cfb8c79d43cedf9c4840f70bd8b25934e595311e6690804d0355dd7ee"}, {file = "langchain_experimental-0.0.65.tar.gz", hash = "sha256:83706df07d8a7e6ec1bda74174add7e4431b5f4a8818e19b65986b94c9c99b25"}, @@ -2698,6 +2814,7 @@ version = "0.1.25" description = "An integration package connecting OpenAI and LangChain" optional = false python-versions = "<4.0,>=3.8.1" +groups = ["main"] files = [ {file = "langchain_openai-0.1.25-py3-none-any.whl", hash = "sha256:f0b34a233d0d9cb8fce6006c903e57085c493c4f0e32862b99063b96eaedb109"}, {file = "langchain_openai-0.1.25.tar.gz", hash = "sha256:eb116f744f820247a72f54313fb7c01524fba0927120d4e899e5e4ab41ad3928"}, @@ -2714,6 +2831,7 @@ version = "0.2.4" description = "LangChain text splitting utilities" optional = false python-versions = "<4.0,>=3.8.1" +groups = ["main"] files = [ {file = "langchain_text_splitters-0.2.4-py3-none-any.whl", hash = "sha256:2702dee5b7cbdd595ccbe43b8d38d01a34aa8583f4d6a5a68ad2305ae3e7b645"}, {file = "langchain_text_splitters-0.2.4.tar.gz", hash = "sha256:f7daa7a3b0aa8309ce248e2e2b6fc8115be01118d336c7f7f7dfacda0e89bf29"}, @@ -2728,6 +2846,7 @@ version = "0.1.121" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" +groups = ["main"] files = [ {file = "langsmith-0.1.121-py3-none-any.whl", hash = "sha256:fdb1ac8a671d3904201bfeea197d87bded46a10d08f1034af464211872e29893"}, {file = "langsmith-0.1.121.tar.gz", hash = "sha256:e9381b82a5bd484af9a51c3e96faea572746b8d617b070c1cda40cbbe48e33df"}, @@ -2744,31 +2863,34 @@ requests = ">=2,<3" [[package]] name = "litellm" -version = "1.46.1" +version = "1.72.6.post1" description = "Library to easily interface with LLM API providers" optional = false python-versions = "!=2.7.*,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,!=3.7.*,>=3.8" +groups = ["main"] files = [ - {file = "litellm-1.46.1-py3-none-any.whl", hash = "sha256:f6b78278cf21a38da0d10a8b3e7b1084b6410012552c0a413774d1c43706e5ba"}, - {file = "litellm-1.46.1.tar.gz", hash = "sha256:993c23d6f5e1d0f070b250d858a6ee87750a032e38f460f8c82385be854bc45f"}, + {file = "litellm-1.72.6.post1-py3-none-any.whl", hash = "sha256:94abba480b3e1c9f05ed75f908e8fb0d5fe1bd5304868bd435f99fbdfcdb4c88"}, + {file = "litellm-1.72.6.post1.tar.gz", hash = "sha256:cc03455bfae17c4226e70bc0e8ac7c889fc577b4832fbb6bc5bd8bc5a2ab02f9"}, ] [package.dependencies] aiohttp = "*" click = "*" +httpx = ">=0.23.0" importlib-metadata = ">=6.8.0" jinja2 = ">=3.1.2,<4.0.0" jsonschema = ">=4.22.0,<5.0.0" -openai = ">=1.45.0" +openai = ">=1.68.2" pydantic = ">=2.0.0,<3.0.0" python-dotenv = ">=0.2.0" -requests = ">=2.31.0,<3.0.0" tiktoken = ">=0.7.0" tokenizers = "*" [package.extras] -extra-proxy = ["azure-identity (>=1.15.0,<2.0.0)", "azure-keyvault-secrets (>=4.8.0,<5.0.0)", "google-cloud-kms (>=2.21.3,<3.0.0)", "prisma (==0.11.0)", "resend (>=0.8.0,<0.9.0)"] -proxy = ["PyJWT (>=2.8.0,<3.0.0)", "apscheduler (>=3.10.4,<4.0.0)", "backoff", "cryptography (>=42.0.5,<43.0.0)", "fastapi (>=0.111.0,<0.112.0)", "fastapi-sso (>=0.10.0,<0.11.0)", "gunicorn (>=22.0.0,<23.0.0)", "orjson (>=3.9.7,<4.0.0)", "pynacl (>=1.5.0,<2.0.0)", "python-multipart (>=0.0.9,<0.0.10)", "pyyaml (>=6.0.1,<7.0.0)", "rq", "uvicorn (>=0.22.0,<0.23.0)"] +caching = ["diskcache (>=5.6.1,<6.0.0)"] +extra-proxy = ["azure-identity (>=1.15.0,<2.0.0)", "azure-keyvault-secrets (>=4.8.0,<5.0.0)", "google-cloud-kms (>=2.21.3,<3.0.0)", "prisma (==0.11.0)", "redisvl (>=0.4.1,<0.5.0) ; python_version >= \"3.9\" and python_version < \"3.14\"", "resend (>=0.8.0,<0.9.0)"] +proxy = ["PyJWT (>=2.8.0,<3.0.0)", "apscheduler (>=3.10.4,<4.0.0)", "backoff", "boto3 (==1.34.34)", "cryptography (>=43.0.1,<44.0.0)", "fastapi (>=0.115.5,<0.116.0)", "fastapi-sso (>=0.16.0,<0.17.0)", "gunicorn (>=23.0.0,<24.0.0)", "litellm-enterprise (==0.1.7)", "litellm-proxy-extras (==0.2.3)", "mcp (==1.9.3) ; python_version >= \"3.10\"", "orjson (>=3.9.7,<4.0.0)", "pynacl (>=1.5.0,<2.0.0)", "python-multipart (>=0.0.18,<0.0.19)", "pyyaml (>=6.0.1,<7.0.0)", "rich (==13.7.1)", "rq", "uvicorn (>=0.29.0,<0.30.0)", "uvloop (>=0.21.0,<0.22.0) ; sys_platform != \"win32\"", "websockets (>=13.1.0,<14.0.0)"] +utils = ["numpydoc"] [[package]] name = "mako" @@ -2776,6 +2898,7 @@ version = "1.3.5" description = "A super-fast templating language that borrows the best ideas from the existing templating languages." optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "Mako-1.3.5-py3-none-any.whl", hash = "sha256:260f1dbc3a519453a9c856dedfe4beb4e50bd5a26d96386cb6c80856556bb91a"}, {file = "Mako-1.3.5.tar.gz", hash = "sha256:48dbc20568c1d276a2698b36d968fa76161bf127194907ea6fc594fa81f943bc"}, @@ -2795,6 +2918,7 @@ version = "3.0.0" description = "Python port of markdown-it. Markdown parsing, done right!" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "markdown-it-py-3.0.0.tar.gz", hash = "sha256:e3f60a94fa066dc52ec76661e37c851cb232d92f9886b15cb560aaada2df8feb"}, {file = "markdown_it_py-3.0.0-py3-none-any.whl", hash = "sha256:355216845c60bd96232cd8d8c40e8f9765cc86f46880e43a8fd22dc1a1a8cab1"}, @@ -2819,6 +2943,7 @@ version = "2.1.5" description = "Safely add untrusted strings to HTML/XML markup." optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "MarkupSafe-2.1.5-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:a17a92de5231666cfbe003f0e4b9b3a7ae3afb1ec2845aadc2bacc93ff85febc"}, {file = "MarkupSafe-2.1.5-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:72b6be590cc35924b02c78ef34b467da4ba07e4e0f0454a2c5907f473fc50ce5"}, @@ -2888,6 +3013,7 @@ version = "3.22.0" description = "A lightweight library for converting complex datatypes to and from native Python datatypes." optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "marshmallow-3.22.0-py3-none-any.whl", hash = "sha256:71a2dce49ef901c3f97ed296ae5051135fd3febd2bf43afe0ae9a82143a494d9"}, {file = "marshmallow-3.22.0.tar.gz", hash = "sha256:4972f529104a220bb8637d595aa4c9762afbe7f7a77d82dc58c1615d70c5823e"}, @@ -2907,6 +3033,7 @@ version = "0.7.0" description = "McCabe checker, plugin for flake8" optional = false python-versions = ">=3.6" +groups = ["dev"] files = [ {file = "mccabe-0.7.0-py2.py3-none-any.whl", hash = "sha256:6c2d30ab6be0e4a46919781807b4f0d834ebdd6c6e3dca0bda5a15f863427b6e"}, {file = "mccabe-0.7.0.tar.gz", hash = "sha256:348e0240c33b60bbdf4e523192ef919f28cb2c3d7d5c7794f74009290f236325"}, @@ -2918,6 +3045,7 @@ version = "0.1.2" description = "Markdown URL utilities" optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "mdurl-0.1.2-py3-none-any.whl", hash = "sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8"}, {file = 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"Python library for arbitrary-precision floating-point arithmetic" optional = false python-versions = "*" +groups = ["main"] files = [ {file = "mpmath-1.3.0-py3-none-any.whl", hash = "sha256:a0b2b9fe80bbcd81a6647ff13108738cfb482d481d826cc0e02f5b35e5c88d2c"}, {file = "mpmath-1.3.0.tar.gz", hash = "sha256:7a28eb2a9774d00c7bc92411c19a89209d5da7c4c9a9e227be8330a23a25b91f"}, @@ -3070,7 +3203,7 @@ files = [ [package.extras] develop = ["codecov", "pycodestyle", "pytest (>=4.6)", "pytest-cov", "wheel"] docs = ["sphinx"] -gmpy = ["gmpy2 (>=2.1.0a4)"] +gmpy = ["gmpy2 (>=2.1.0a4) ; platform_python_implementation != \"PyPy\""] tests = ["pytest (>=4.6)"] [[package]] @@ -3079,6 +3212,7 @@ version = "1.1.0" description = "MessagePack serializer" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "msgpack-1.1.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:7ad442d527a7e358a469faf43fda45aaf4ac3249c8310a82f0ccff9164e5dccd"}, {file = 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"sha256:2e4ee3380d6de9c9ec04745830fd9e2eccb3e6cf790d39d7b98ffd19b0dd754a"}, @@ -3320,6 +3458,7 @@ version = "3.2.2" description = "A generic, spec-compliant, thorough implementation of the OAuth request-signing logic" optional = false python-versions = ">=3.6" +groups = ["main"] files = [ {file = "oauthlib-3.2.2-py3-none-any.whl", hash = "sha256:8139f29aac13e25d502680e9e19963e83f16838d48a0d71c287fe40e7067fbca"}, {file = "oauthlib-3.2.2.tar.gz", hash = "sha256:9859c40929662bec5d64f34d01c99e093149682a3f38915dc0655d5a633dd918"}, @@ -3336,6 +3475,7 @@ version = "1.19.2" description = "ONNX Runtime is a runtime accelerator for Machine Learning models" optional = false python-versions = "*" +groups = ["main"] files = [ {file = "onnxruntime-1.19.2-cp310-cp310-macosx_11_0_universal2.whl", hash = "sha256:84fa57369c06cadd3c2a538ae2a26d76d583e7c34bdecd5769d71ca5c0fc750e"}, {file = "onnxruntime-1.19.2-cp310-cp310-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = 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(>=1.1.0.11)"] +realtime = ["websockets (>=13,<16)"] +voice-helpers = ["numpy (>=2.0.2)", "sounddevice (>=0.5.1)"] [[package]] name = "opentelemetry-api" @@ -3402,6 +3545,7 @@ version = "1.27.0" description = "OpenTelemetry Python API" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "opentelemetry_api-1.27.0-py3-none-any.whl", hash = "sha256:953d5871815e7c30c81b56d910c707588000fff7a3ca1c73e6531911d53065e7"}, {file = "opentelemetry_api-1.27.0.tar.gz", hash = "sha256:ed673583eaa5f81b5ce5e86ef7cdaf622f88ef65f0b9aab40b843dcae5bef342"}, @@ -3417,6 +3561,7 @@ version = "1.27.0" description = "OpenTelemetry Protobuf encoding" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "opentelemetry_exporter_otlp_proto_common-1.27.0-py3-none-any.whl", hash = "sha256:675db7fffcb60946f3a5c43e17d1168a3307a94a930ecf8d2ea1f286f3d4f79a"}, {file = "opentelemetry_exporter_otlp_proto_common-1.27.0.tar.gz", hash = "sha256:159d27cf49f359e3798c4c3eb8da6ef4020e292571bd8c5604a2a573231dd5c8"}, @@ -3431,6 +3576,7 @@ version = "1.27.0" description = "OpenTelemetry Collector Protobuf over gRPC Exporter" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "opentelemetry_exporter_otlp_proto_grpc-1.27.0-py3-none-any.whl", hash = "sha256:56b5bbd5d61aab05e300d9d62a6b3c134827bbd28d0b12f2649c2da368006c9e"}, {file = "opentelemetry_exporter_otlp_proto_grpc-1.27.0.tar.gz", hash = "sha256:af6f72f76bcf425dfb5ad11c1a6d6eca2863b91e63575f89bb7b4b55099d968f"}, @@ -3451,6 +3597,7 @@ version = "1.27.0" description = "OpenTelemetry Collector Protobuf over HTTP Exporter" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "opentelemetry_exporter_otlp_proto_http-1.27.0-py3-none-any.whl", hash = "sha256:688027575c9da42e179a69fe17e2d1eba9b14d81de8d13553a21d3114f3b4d75"}, {file = "opentelemetry_exporter_otlp_proto_http-1.27.0.tar.gz", hash = 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"1.27.0" description = "OpenTelemetry Python SDK" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "opentelemetry_sdk-1.27.0-py3-none-any.whl", hash = "sha256:365f5e32f920faf0fd9e14fdfd92c086e317eaa5f860edba9cdc17a380d9197d"}, {file = "opentelemetry_sdk-1.27.0.tar.gz", hash = "sha256:d525017dea0ccce9ba4e0245100ec46ecdc043f2d7b8315d56b19aff0904fa6f"}, @@ -3559,6 +3711,7 @@ version = "0.48b0" description = "OpenTelemetry Semantic Conventions" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "opentelemetry_semantic_conventions-0.48b0-py3-none-any.whl", hash = "sha256:a0de9f45c413a8669788a38569c7e0a11ce6ce97861a628cca785deecdc32a1f"}, {file = "opentelemetry_semantic_conventions-0.48b0.tar.gz", hash = "sha256:12d74983783b6878162208be57c9effcb89dc88691c64992d70bb89dc00daa1a"}, @@ -3574,6 +3727,7 @@ version = "0.48b0" description = "Web util for OpenTelemetry" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "opentelemetry_util_http-0.48b0-py3-none-any.whl", hash = "sha256:76f598af93aab50328d2a69c786beaedc8b6a7770f7a818cc307eb353debfffb"}, {file = "opentelemetry_util_http-0.48b0.tar.gz", hash = "sha256:60312015153580cc20f322e5cdc3d3ecad80a71743235bdb77716e742814623c"}, @@ -3585,6 +3739,7 @@ version = "3.10.7" description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "orjson-3.10.7-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:74f4544f5a6405b90da8ea724d15ac9c36da4d72a738c64685003337401f5c12"}, {file = "orjson-3.10.7-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:34a566f22c28222b08875b18b0dfbf8a947e69df21a9ed5c51a6bf91cfb944ac"}, @@ -3651,6 +3806,7 @@ version = "1.3.0.post0" description = "Capture the outcome of Python function calls." optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "outcome-1.3.0.post0-py2.py3-none-any.whl", hash = "sha256:e771c5ce06d1415e356078d3bdd68523f284b4ce5419828922b6871e65eda82b"}, {file = "outcome-1.3.0.post0.tar.gz", hash = "sha256:9dcf02e65f2971b80047b377468e72a268e15c0af3cf1238e6ff14f7f91143b8"}, @@ -3665,6 +3821,7 @@ version = "7.7.0" description = "A decorator to automatically detect mismatch when overriding a method." optional = false python-versions = ">=3.6" +groups = ["main"] files = [ {file = "overrides-7.7.0-py3-none-any.whl", hash = "sha256:c7ed9d062f78b8e4c1a7b70bd8796b35ead4d9f510227ef9c5dc7626c60d7e49"}, {file = "overrides-7.7.0.tar.gz", hash = "sha256:55158fa3d93b98cc75299b1e67078ad9003ca27945c76162c1c0766d6f91820a"}, @@ -3676,6 +3833,7 @@ version = "24.1" description = "Core utilities for Python packages" optional = false python-versions = ">=3.8" +groups = ["main", "dev"] files = [ {file = "packaging-24.1-py3-none-any.whl", hash = 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"sha256:d155cef71265d1e9807ed1c32b4c8deec042a44a50a4188b25ac67ecd81a9c0f"}, @@ -4182,7 +4473,7 @@ typing-extensions = [ [package.extras] email = ["email-validator (>=2.0.0)"] -timezone = ["tzdata"] +timezone = ["tzdata ; python_version >= \"3.9\" and sys_platform == \"win32\""] [[package]] name = "pydantic-core" @@ -4190,6 +4481,7 @@ version = "2.23.4" description = "Core functionality for Pydantic validation and serialization" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "pydantic_core-2.23.4-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:b10bd51f823d891193d4717448fab065733958bdb6a6b351967bd349d48d5c9b"}, {file = "pydantic_core-2.23.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:4fc714bdbfb534f94034efaa6eadd74e5b93c8fa6315565a222f7b6f42ca1166"}, @@ -4291,6 +4583,7 @@ version = "12.0.0" description = "A rough port of Node.js's EventEmitter to Python with a few tricks of its own" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "pyee-12.0.0-py3-none-any.whl", hash = "sha256:7b14b74320600049ccc7d0e0b1becd3b4bd0a03c745758225e31a59f4095c990"}, {file = "pyee-12.0.0.tar.gz", hash = "sha256:c480603f4aa2927d4766eb41fa82793fe60a82cbfdb8d688e0d08c55a534e145"}, @@ -4300,7 +4593,7 @@ files = [ typing-extensions = "*" [package.extras] -dev = ["black", "build", "flake8", "flake8-black", "isort", "jupyter-console", "mkdocs", "mkdocs-include-markdown-plugin", "mkdocstrings[python]", "pytest", "pytest-asyncio", "pytest-trio", "sphinx", "toml", "tox", "trio", "trio", "trio-typing", "twine", "twisted", "validate-pyproject[all]"] +dev = ["black", "build", "flake8", "flake8-black", "isort", "jupyter-console", "mkdocs", "mkdocs-include-markdown-plugin", "mkdocstrings[python]", "pytest", "pytest-asyncio ; python_version >= \"3.4\"", "pytest-trio ; python_version >= \"3.7\"", "sphinx", "toml", "tox", "trio", "trio ; python_version > \"3.6\"", "trio-typing ; python_version > \"3.6\"", "twine", "twisted", "validate-pyproject[all]"] [[package]] name = "pyflakes" @@ -4308,6 +4601,7 @@ version = "3.2.0" description = "passive checker of Python programs" optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "pyflakes-3.2.0-py2.py3-none-any.whl", hash = "sha256:84b5be138a2dfbb40689ca07e2152deb896a65c3a3e24c251c5c62489568074a"}, {file = "pyflakes-3.2.0.tar.gz", hash = "sha256:1c61603ff154621fb2a9172037d84dca3500def8c8b630657d1701f026f8af3f"}, @@ -4319,6 +4613,7 @@ version = "2.18.0" description = "Pygments is a syntax highlighting package written in Python." optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "pygments-2.18.0-py3-none-any.whl", hash = "sha256:b8e6aca0523f3ab76fee51799c488e38782ac06eafcf95e7ba832985c8e7b13a"}, {file = "pygments-2.18.0.tar.gz", hash = "sha256:786ff802f32e91311bff3889f6e9a86e81505fe99f2735bb6d60ae0c5004f199"}, @@ -4333,6 +4628,7 @@ version = "2.9.0" description = "JSON Web Token implementation in Python" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "PyJWT-2.9.0-py3-none-any.whl", hash = "sha256:3b02fb0f44517787776cf48f2ae25d8e14f300e6d7545a4315cee571a415e850"}, {file = "pyjwt-2.9.0.tar.gz", hash = "sha256:7e1e5b56cc735432a7369cbfa0efe50fa113ebecdc04ae6922deba8b84582d0c"}, @@ -4350,6 +4646,7 @@ version = "0.9.18" description = "python wrapper for Lance columnar format" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "pylance-0.9.18-cp38-abi3-macosx_10_15_x86_64.whl", hash = "sha256:fe2445d922c594d90e89111385106f6b152caab27996217db7bb4b8947eb0bea"}, {file = "pylance-0.9.18-cp38-abi3-macosx_11_0_arm64.whl", hash = "sha256:a2c424c50f5186edbbcc5a26f34063ed09d9a7390e28033395728ce02b5658f0"}, @@ -4365,7 +4662,7 @@ pyarrow = ">=12" [package.extras] benchmarks = ["pytest-benchmark"] dev = ["ruff (==0.2.2)"] -tests = ["datasets", "duckdb", "ml_dtypes", "pandas", "pillow", "polars[pandas,pyarrow]", "pytest", "tensorflow", "tqdm"] +tests = ["datasets", "duckdb ; python_version < \"3.12\"", "ml_dtypes", "pandas", "pillow", "polars[pandas,pyarrow]", "pytest", "tensorflow ; python_version < \"3.12\"", "tqdm"] torch = ["torch"] [[package]] @@ -4374,6 +4671,7 @@ version = "3.2.7" description = "python code static checker" optional = false python-versions = ">=3.8.0" +groups = ["dev"] files = [ {file = "pylint-3.2.7-py3-none-any.whl", hash = "sha256:02f4aedeac91be69fb3b4bea997ce580a4ac68ce58b89eaefeaf06749df73f4b"}, {file = "pylint-3.2.7.tar.gz", hash = "sha256:1b7a721b575eaeaa7d39db076b6e7743c993ea44f57979127c517c6c572c803e"}, @@ -4398,16 +4696,17 @@ version = "4.3.1" description = "A pure-python PDF library capable of splitting, merging, cropping, and transforming PDF files" optional = false python-versions = ">=3.6" +groups = ["main"] files = [ {file = "pypdf-4.3.1-py3-none-any.whl", hash = "sha256:64b31da97eda0771ef22edb1bfecd5deee4b72c3d1736b7df2689805076d6418"}, {file = "pypdf-4.3.1.tar.gz", hash = "sha256:b2f37fe9a3030aa97ca86067a56ba3f9d3565f9a791b305c7355d8392c30d91b"}, ] [package.extras] -crypto = ["PyCryptodome", "cryptography"] +crypto = ["PyCryptodome ; python_version == \"3.6\"", "cryptography ; python_version >= \"3.7\""] dev = ["black", "flit", "pip-tools", "pre-commit (<2.18.0)", "pytest-cov", "pytest-socket", "pytest-timeout", "pytest-xdist", "wheel"] docs = ["myst_parser", "sphinx", "sphinx_rtd_theme"] -full = ["Pillow (>=8.0.0)", "PyCryptodome", "cryptography"] +full = ["Pillow (>=8.0.0)", "PyCryptodome ; python_version == \"3.6\"", "cryptography ; python_version >= \"3.7\""] image = ["Pillow (>=8.0.0)"] [[package]] @@ -4416,6 +4715,7 @@ version = "0.48.9" description = "A SQL query builder API for Python" optional = false python-versions = "*" +groups = ["main"] files = [ {file = "PyPika-0.48.9.tar.gz", hash = "sha256:838836a61747e7c8380cd1b7ff638694b7a7335345d0f559b04b2cd832ad5378"}, ] @@ -4426,6 +4726,7 @@ version = "1.1.0" description = "Wrappers to call pyproject.toml-based build backend hooks." optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "pyproject_hooks-1.1.0-py3-none-any.whl", hash = "sha256:7ceeefe9aec63a1064c18d939bdc3adf2d8aa1988a510afec15151578b232aa2"}, {file = "pyproject_hooks-1.1.0.tar.gz", hash = "sha256:4b37730834edbd6bd37f26ece6b44802fb1c1ee2ece0e54ddff8bfc06db86965"}, @@ -4437,6 +4738,8 @@ version = "3.5.2" description = "A python implementation of GNU readline." optional = false python-versions = ">=3.8" +groups = ["main"] +markers = "sys_platform == \"win32\"" files = [ {file = "pyreadline3-3.5.2-py3-none-any.whl", hash = "sha256:a87d56791e2965b2b187e2ea33dcf664600842c997c0623c95cf8ef07db83de9"}, {file = "pyreadline3-3.5.2.tar.gz", hash = "sha256:ba82292e52c5a3bb256b291af0c40b457c1e8699cac9a873abbcaac8aef3a1bb"}, @@ -4451,6 +4754,7 @@ version = "1.1.380" description = "Command line wrapper for pyright" optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "pyright-1.1.380-py3-none-any.whl", hash = "sha256:a6404392053d8848bacc7aebcbd9d318bb46baf1a1a000359305481920f43879"}, {file = "pyright-1.1.380.tar.gz", hash = "sha256:e6ceb1a5f7e9f03106e0aa1d6fbb4d97735a5e7ffb59f3de6b2db590baf935b2"}, @@ -4469,6 +4773,7 @@ version = "0.3.4" description = "pysbd (Python Sentence Boundary Disambiguation) is a rule-based sentence boundary detection that works out-of-the-box across many languages." optional = false python-versions = ">=3" +groups = ["main"] files = [ {file = "pysbd-0.3.4-py3-none-any.whl", hash = "sha256:cd838939b7b0b185fcf86b0baf6636667dfb6e474743beeff878e9f42e022953"}, ] @@ -4479,6 +4784,7 @@ version = "1.7.1" description = "A Python SOCKS client module. See https://github.com/Anorov/PySocks for more information." optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +groups = ["main"] files = [ {file = "PySocks-1.7.1-py27-none-any.whl", hash = "sha256:08e69f092cc6dbe92a0fdd16eeb9b9ffbc13cadfe5ca4c7bd92ffb078b293299"}, {file = "PySocks-1.7.1-py3-none-any.whl", hash = "sha256:2725bd0a9925919b9b51739eea5f9e2bae91e83288108a9ad338b2e3a4435ee5"}, @@ -4491,6 +4797,7 @@ version = "8.3.3" description = "pytest: simple powerful testing with Python" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "pytest-8.3.3-py3-none-any.whl", hash = "sha256:a6853c7375b2663155079443d2e45de913a911a11d669df02a50814944db57b2"}, {file = "pytest-8.3.3.tar.gz", hash = "sha256:70b98107bd648308a7952b06e6ca9a50bc660be218d53c257cc1fc94fda10181"}, @@ -4511,6 +4818,7 @@ version = "2.9.0.post0" description = "Extensions to the standard Python datetime module" optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7" +groups = ["main"] files = [ {file = "python-dateutil-2.9.0.post0.tar.gz", hash = "sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3"}, {file = "python_dateutil-2.9.0.post0-py2.py3-none-any.whl", hash = "sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427"}, @@ -4525,6 +4833,7 @@ version = "1.0.1" description = "Read key-value pairs from a .env file and set them as environment variables" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "python-dotenv-1.0.1.tar.gz", hash = "sha256:e324ee90a023d808f1959c46bcbc04446a10ced277783dc6ee09987c37ec10ca"}, {file = "python_dotenv-1.0.1-py3-none-any.whl", hash = "sha256:f7b63ef50f1b690dddf550d03497b66d609393b40b564ed0d674909a68ebf16a"}, @@ -4539,6 +4848,7 @@ version = "15.0.0" description = "Python 3 library for downloading YouTube Videos." optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "pytube-15.0.0-py3-none-any.whl", hash = "sha256:07b9904749e213485780d7eb606e5e5b8e4341aa4dccf699160876da00e12d78"}, {file = "pytube-15.0.0.tar.gz", hash = "sha256:076052efe76f390dfa24b1194ff821d4e86c17d41cb5562f3a276a8bcbfc9d1d"}, @@ -4550,6 +4860,7 @@ version = "2024.2" description = "World timezone definitions, modern and historical" optional = false python-versions = "*" +groups = ["main"] files = [ {file = "pytz-2024.2-py2.py3-none-any.whl", hash = "sha256:31c7c1817eb7fae7ca4b8c7ee50c72f93aa2dd863de768e1ef4245d426aa0725"}, {file = "pytz-2024.2.tar.gz", hash = "sha256:2aa355083c50a0f93fa581709deac0c9ad65cca8a9e9beac660adcbd493c798a"}, @@ -4561,6 +4872,8 @@ version = "306" description = "Python for Window Extensions" optional = false python-versions = "*" +groups = ["main"] +markers = "platform_system == \"Windows\" or sys_platform == \"win32\"" files = [ {file = "pywin32-306-cp310-cp310-win32.whl", hash = "sha256:06d3420a5155ba65f0b72f2699b5bacf3109f36acbe8923765c22938a69dfc8d"}, {file = "pywin32-306-cp310-cp310-win_amd64.whl", hash = "sha256:84f4471dbca1887ea3803d8848a1616429ac94a4a8d05f4bc9c5dcfd42ca99c8"}, @@ -4584,6 +4897,8 @@ version = "0.2.3" description = "A (partial) reimplementation of pywin32 using ctypes/cffi" optional = false python-versions = ">=3.6" +groups = ["main"] +markers = "sys_platform == \"win32\"" files = [ {file = "pywin32-ctypes-0.2.3.tar.gz", hash = "sha256:d162dc04946d704503b2edc4d55f3dba5c1d539ead017afa00142c38b9885755"}, {file = "pywin32_ctypes-0.2.3-py3-none-any.whl", hash = "sha256:8a1513379d709975552d202d942d9837758905c8d01eb82b8bcc30918929e7b8"}, @@ -4595,6 +4910,7 @@ version = "6.0.2" description = "YAML parser and emitter for Python" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "PyYAML-6.0.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:0a9a2848a5b7feac301353437eb7d5957887edbf81d56e903999a75a3d743086"}, {file = "PyYAML-6.0.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:29717114e51c84ddfba879543fb232a6ed60086602313ca38cce623c1d62cfbf"}, @@ -4657,6 +4973,7 @@ version = "1.11.2" description = "Client library for the Qdrant vector search engine" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "qdrant_client-1.11.2-py3-none-any.whl", hash = "sha256:3151e3da61588ad138dfcd6760c2f13e57251c8b0c62001bfd0e03bb7bcd6c8e"}, {file = "qdrant_client-1.11.2.tar.gz", hash = "sha256:0d5aa3f778077762963a754459c9c7144ba48e13dea62e559323924126a1b4a4"}, @@ -4672,8 +4989,8 @@ pydantic = ">=1.10.8" urllib3 = ">=1.26.14,<3" [package.extras] -fastembed = ["fastembed (==0.3.6)"] -fastembed-gpu = ["fastembed-gpu (==0.3.6)"] +fastembed = ["fastembed (==0.3.6) ; python_version < \"3.13\""] +fastembed-gpu = ["fastembed-gpu (==0.3.6) ; python_version < \"3.13\""] [[package]] name = "rapidfuzz" @@ -4681,6 +4998,7 @@ version = "3.9.7" description = "rapid fuzzy string matching" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "rapidfuzz-3.9.7-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:ccf68e30b80e903f2309f90a438dbd640dd98e878eeb5ad361a288051ee5b75c"}, {file = "rapidfuzz-3.9.7-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:696a79018ef989bf1c9abd9005841cee18005ccad4748bad8a4c274c47b6241a"}, @@ -4801,13 +5119,14 @@ version = "1.2.0.post0" description = "Simple python rate limiting object" optional = false python-versions = "*" +groups = ["main"] files = [ {file = "ratelimiter-1.2.0.post0-py3-none-any.whl", hash = "sha256:a52be07bc0bb0b3674b4b304550f10c769bbb00fead3072e035904474259809f"}, {file = "ratelimiter-1.2.0.post0.tar.gz", hash = "sha256:5c395dcabdbbde2e5178ef3f89b568a3066454a6ddc223b76473dac22f89b4f7"}, ] [package.extras] -test = ["pytest (>=3.0)", "pytest-asyncio"] +test = ["pytest (>=3.0)", "pytest-asyncio ; python_version >= \"3.5\""] [[package]] name = "referencing" @@ -4815,6 +5134,7 @@ version = "0.35.1" description = "JSON Referencing + Python" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "referencing-0.35.1-py3-none-any.whl", hash = "sha256:eda6d3234d62814d1c64e305c1331c9a3a6132da475ab6382eaa997b21ee75de"}, {file = "referencing-0.35.1.tar.gz", hash = "sha256:25b42124a6c8b632a425174f24087783efb348a6f1e0008e63cd4466fedf703c"}, @@ -4830,6 +5150,7 @@ version = "2024.9.11" description = "Alternative regular expression module, to replace re." optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "regex-2024.9.11-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:1494fa8725c285a81d01dc8c06b55287a1ee5e0e382d8413adc0a9197aac6408"}, {file = "regex-2024.9.11-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:0e12c481ad92d129c78f13a2a3662317e46ee7ef96c94fd332e1c29131875b7d"}, @@ -4929,18 +5250,19 @@ files = [ [[package]] name = "requests" -version = "2.32.3" +version = "2.32.4" description = "Python HTTP for Humans." optional = false python-versions = ">=3.8" +groups = ["main"] files = [ - {file = "requests-2.32.3-py3-none-any.whl", hash = "sha256:70761cfe03c773ceb22aa2f671b4757976145175cdfca038c02654d061d6dcc6"}, - {file = "requests-2.32.3.tar.gz", hash = "sha256:55365417734eb18255590a9ff9eb97e9e1da868d4ccd6402399eaf68af20a760"}, + {file = "requests-2.32.4-py3-none-any.whl", hash = "sha256:27babd3cda2a6d50b30443204ee89830707d396671944c998b5975b031ac2b2c"}, + {file = "requests-2.32.4.tar.gz", hash = "sha256:27d0316682c8a29834d3264820024b62a36942083d52caf2f14c0591336d3422"}, ] [package.dependencies] certifi = ">=2017.4.17" -charset-normalizer = ">=2,<4" +charset_normalizer = ">=2,<4" idna = ">=2.5,<4" urllib3 = ">=1.21.1,<3" @@ -4954,6 +5276,7 @@ version = "2.0.0" description = "OAuthlib authentication support for Requests." optional = false python-versions = ">=3.4" +groups = ["main"] files = [ {file = "requests-oauthlib-2.0.0.tar.gz", hash = "sha256:b3dffaebd884d8cd778494369603a9e7b58d29111bf6b41bdc2dcd87203af4e9"}, {file = 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false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "shapely-2.0.6-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:29a34e068da2d321e926b5073539fd2a1d4429a2c656bd63f0bd4c8f5b236d0b"}, {file = "shapely-2.0.6-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e1c84c3f53144febf6af909d6b581bc05e8785d57e27f35ebaa5c1ab9baba13b"}, @@ -5296,6 +5632,7 @@ version = "1.5.4" description = "Tool to Detect Surrounding Shell" optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "shellingham-1.5.4-py2.py3-none-any.whl", hash = "sha256:7ecfff8f2fd72616f7481040475a65b2bf8af90a56c89140852d1120324e8686"}, {file = "shellingham-1.5.4.tar.gz", hash = "sha256:8dbca0739d487e5bd35ab3ca4b36e11c4078f3a234bfce294b0a0291363404de"}, @@ -5307,6 +5644,7 @@ version = "1.16.0" description = "Python 2 and 3 compatibility utilities" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*" +groups = ["main"] files = [ {file = "six-1.16.0-py2.py3-none-any.whl", 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["sqlcipher3_binary"] [[package]] name = "starlette" -version = "0.38.5" +version = "0.46.2" description = "The little ASGI library that shines." optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" +groups = ["main"] files = [ - {file = "starlette-0.38.5-py3-none-any.whl", hash = "sha256:632f420a9d13e3ee2a6f18f437b0a9f1faecb0bc42e1942aa2ea0e379a4c4206"}, - {file = "starlette-0.38.5.tar.gz", hash = "sha256:04a92830a9b6eb1442c766199d62260c3d4dc9c4f9188360626b1e0273cb7077"}, + {file = "starlette-0.46.2-py3-none-any.whl", hash = "sha256:595633ce89f8ffa71a015caed34a5b2dc1c0cdb3f0f1fbd1e69339cf2abeec35"}, + {file = "starlette-0.46.2.tar.gz", hash = "sha256:7f7361f34eed179294600af672f565727419830b54b7b084efe44bb82d2fccd5"}, ] [package.dependencies] -anyio = ">=3.4.0,<5" +anyio = ">=3.6.2,<5" [package.extras] -full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart (>=0.0.7)", "pyyaml"] +full = ["httpx (>=0.27.0,<0.29.0)", "itsdangerous", "jinja2", "python-multipart (>=0.0.18)", "pyyaml"] [[package]] name = "sympy" @@ -5455,6 +5798,7 @@ version = "1.13.2" description = "Computer algebra system (CAS) in Python" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "sympy-1.13.2-py3-none-any.whl", hash = "sha256:c51d75517712f1aed280d4ce58506a4a88d635d6b5dd48b39102a7ae1f3fcfe9"}, {file = "sympy-1.13.2.tar.gz", hash = "sha256:401449d84d07be9d0c7a46a64bd54fe097667d5e7181bfe67ec777be9e01cb13"}, @@ -5472,6 +5816,7 @@ version = "0.9.0" description = "Pretty-print tabular data" optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "tabulate-0.9.0-py3-none-any.whl", hash = "sha256:024ca478df22e9340661486f85298cff5f6dcdba14f3813e8830015b9ed1948f"}, {file = "tabulate-0.9.0.tar.gz", hash = "sha256:0095b12bf5966de529c0feb1fa08671671b3368eec77d7ef7ab114be2c068b3c"}, @@ -5486,6 +5831,7 @@ version = "8.5.0" description = "Retry code until it succeeds" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "tenacity-8.5.0-py3-none-any.whl", hash = "sha256:b594c2a5945830c267ce6b79a166228323ed52718f30302c1359836112346687"}, {file = "tenacity-8.5.0.tar.gz", hash = "sha256:8bc6c0c8a09b31e6cad13c47afbed1a567518250a9a171418582ed8d9c20ca78"}, @@ -5501,6 +5847,7 @@ version = "0.7.0" description = "tiktoken is a fast BPE tokeniser for use with OpenAI's models" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "tiktoken-0.7.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:485f3cc6aba7c6b6ce388ba634fbba656d9ee27f766216f45146beb4ac18b25f"}, {file = "tiktoken-0.7.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e54be9a2cd2f6d6ffa3517b064983fb695c9a9d8aa7d574d1ef3c3f931a99225"}, @@ -5553,6 +5900,7 @@ version = "0.20.0" description = "" optional = false python-versions = ">=3.7" +groups = ["main"] files = [ {file = "tokenizers-0.20.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = 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["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\""] cover = ["pytest-cov"] doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] enabler = ["pytest-enabler (>=2.2)"] -test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"] +test = ["big-O", "importlib-resources ; python_version < \"3.9\"", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"] type = ["pytest-mypy"] [metadata] -lock-version = "2.0" +lock-version = "2.1" python-versions = ">=3.12,<=3.13" -content-hash = "7d94f56d81d95e4418bf338eb45d8c498838cf9ef3144c413ec1728127ffadf7" +content-hash = "8898fabcbfe631962a4060fc88f47383e7eba61863aa66ace85bed8cd895c960" diff --git a/examples/integrations/crewai/crewai-tutorial/pyproject.toml b/examples/integrations/crewai/crewai-tutorial/pyproject.toml index 79c8b8c..f4d385a 100644 --- a/examples/integrations/crewai/crewai-tutorial/pyproject.toml +++ b/examples/integrations/crewai/crewai-tutorial/pyproject.toml @@ -2,6 +2,7 @@ name = "tutorial-crewai" version = "0.1.0" description = "Build a Crew that finds the best roundtrip flights on the given dates." +package-mode = false authors = ["Anirudh Kamath "] readme = "README.md" @@ -11,12 +12,23 @@ crewai = {extras = ["tools"], version = "^0.60.0"} html2text = "^2024.2.26" playwright = "^1.47.0" python-dotenv = "^1.0.1" +litellm = ">=1.61.15,<2.0.0" +aiohttp = ">=3.10.11,<4.0.0" +cryptography = ">=44.0.1,<45.0.0" +jinja2 = ">=3.1.6,<4.0.0" +protobuf = ">=4.25.8,<5.0.0" +requests = ">=2.32.4,<3.0.0" +starlette = ">=0.40.0,<1.0.0" +urllib3 = ">=2.5.0,<3.0.0" +langchain-core = ">=0.2.43,<0.3.0" [tool.poetry.group.dev.dependencies] black = "^24.8.0" flake8 = "^7.1.1" pylint = "^3.2.7" +setuptools = ">=78.1.1,<81.0.0" +virtualenv = ">=20.26.6,<21.0.0" [build-system] requires = ["poetry-core"] -build-backen = "poetry.core.masonry.api" +build-backend = "poetry.core.masonry.api" diff --git a/examples/integrations/crewai/stagehand/.env.example b/examples/integrations/crewai/stagehand/.env.example new file mode 100644 index 0000000..c5dc98f --- /dev/null +++ b/examples/integrations/crewai/stagehand/.env.example @@ -0,0 +1,3 @@ +BROWSERBASE_PROJECT_ID= +BROWSERBASE_API_KEY= +OPENAI_API_KEY= \ No newline at end of file diff --git a/examples/integrations/langchain/.gitignore b/examples/integrations/crewai/stagehand/.gitignore similarity index 100% rename from examples/integrations/langchain/.gitignore rename to examples/integrations/crewai/stagehand/.gitignore diff --git a/examples/integrations/crewai/stagehand/README.md b/examples/integrations/crewai/stagehand/README.md new file mode 100644 index 0000000..d162838 --- /dev/null +++ b/examples/integrations/crewai/stagehand/README.md @@ -0,0 +1,21 @@ +# CrewAI Integration + +Automate browser tasks using natural language instructions with CrewAI + +This tool integrates the Stagehand Python SDK with CrewAI, allowing agents to interact with websites and automate browser tasks using natural language instructions. + +## Description + +The StagehandTool wraps the Stagehand Python SDK to provide CrewAI agents with the ability to control a real web browser and interact with websites using three core primitives: + +- **Act**: Perform actions like clicking, typing, or navigating +- **Extract**: Extract structured data from web pages +- **Observe**: Identify and analyze elements on the page + +## Requirements + +Before using this tool, you will need: + +- A Browserbase account with API key and project ID +- An API key for an LLM (OpenAI or Anthropic Claude) +- The Stagehand Python SDK installed \ No newline at end of file diff --git a/examples/integrations/crewai/stagehand/main.py b/examples/integrations/crewai/stagehand/main.py new file mode 100644 index 0000000..e5b1949 --- /dev/null +++ b/examples/integrations/crewai/stagehand/main.py @@ -0,0 +1,56 @@ +from crewai import Agent, Task, Crew +from crewai_tools import StagehandTool +from stagehand.schemas import AvailableModel +import os + +# Get API keys from environment +browserbase_api_key = os.environ.get("BROWSERBASE_API_KEY") +browserbase_project_id = os.environ.get("BROWSERBASE_PROJECT_ID") +model_api_key = os.environ.get("OPENAI_API_KEY") # or ANTHROPIC_API_KEY + +# Initialize the tool +stagehand_tool = StagehandTool( + api_key=browserbase_api_key, + project_id=browserbase_project_id, + model_api_key=model_api_key, + model_name=AvailableModel.GPT_4O, +) + +# Create an agent +researcher = Agent( + role="Web Researcher", + goal="Gather product information from an e-commerce website", + backstory="I specialize in extracting and analyzing web data.", + verbose=True, + tools=[stagehand_tool], +) + +# Form submission task +form_submission_task = Task( + description=""" + Submit a contact form on example.com: + 1. Go to example.com/contact + 2. Fill out the contact form with: + - Name: John Doe + - Email: john@example.com + - Subject: Information Request + - Message: I would like to learn more about your services + 3. Submit the form + 4. Confirm the submission was successful + """, + expected_output="The form should be submitted successfully", + agent=researcher, +) + +# Run the crew +crew = Crew( + agents=[researcher], + tasks=[form_submission_task], + verbose=True, +) + +result = crew.kickoff() +print(result) + +# Clean up resources +stagehand_tool.close() \ No newline at end of file diff --git a/examples/integrations/crewai/stagehand/requirements.txt b/examples/integrations/crewai/stagehand/requirements.txt new file mode 100644 index 0000000..26bcc00 --- /dev/null +++ b/examples/integrations/crewai/stagehand/requirements.txt @@ -0,0 +1,226 @@ +aiohappyeyeballs==2.6.1 +aiohttp==3.12.13 +aiosignal==1.4.0 +alembic==1.16.3 +annotated-types==0.7.0 +anthropic==0.57.1 +anyio==4.9.0 +appdirs==1.4.4 +asgiref==3.9.1 +asttokens==3.0.0 +attrs==25.3.0 +babel==2.17.0 +backoff==2.2.1 +backrefs==5.9 +bcrypt==4.3.0 +beautifulsoup4==4.13.4 +blinker==1.9.0 +browserbase==1.4.0 +build==1.2.2.post1 +cachetools==5.5.2 +certifi==2025.7.9 +cffi==1.17.1 +cfgv==3.4.0 +charset-normalizer==3.4.2 +chroma-hnswlib==0.7.6 +chromadb==0.5.23 +click==8.2.1 +cohere==5.16.1 +colorama==0.4.6 +coloredlogs==15.0.1 +crewai==0.141.0 +crewai-tools==0.51.1 +cryptography==45.0.5 +dataclasses-json==0.6.7 +decorator==5.2.1 +deprecation==2.1.0 +distlib==0.3.9 +distro==1.9.0 +docker==7.1.0 +docstring_parser==0.16 +durationpy==0.10 +embedchain==0.1.128 +et_xmlfile==2.0.0 +executing==2.2.0 +fastapi==0.116.0 +fastavro==1.11.1 +filelock==3.18.0 +flatbuffers==25.2.10 +frozenlist==1.7.0 +fsspec==2025.5.1 +ghp-import==2.1.0 +google-auth==2.40.3 +googleapis-common-protos==1.70.0 +gptcache==0.1.44 +greenlet==3.2.3 +grpcio==1.73.1 +h11==0.16.0 +h2==4.2.0 +hf-xet==1.1.5 +hpack==4.1.0 +httpcore==1.0.9 +httptools==0.6.4 +httpx==0.28.1 +httpx-sse==0.4.0 +huggingface-hub==0.33.2 +humanfriendly==10.0 +hyperframe==6.1.0 +identify==2.6.12 +idna==3.10 +importlib_metadata==8.7.0 +importlib_resources==6.5.2 +instructor==1.9.2 +ipython==9.4.0 +ipython_pygments_lexers==1.1.1 +jedi==0.19.2 +Jinja2==3.1.6 +jiter==0.10.0 +json5==0.12.0 +json_repair==0.25.2 +jsonpatch==1.33 +jsonpickle==4.1.1 +jsonpointer==3.0.0 +jsonref==1.1.0 +jsonschema==4.24.0 +jsonschema-specifications==2025.4.1 +kubernetes==33.1.0 +lancedb==0.24.0 +langchain==0.3.26 +langchain-cohere==0.3.5 +langchain-community==0.3.27 +langchain-core==0.3.68 +langchain-experimental==0.3.4 +langchain-openai==0.2.14 +langchain-text-splitters==0.3.8 +langsmith==0.3.45 +litellm==1.72.6 +Mako==1.3.10 +Markdown==3.8.2 +markdown-it-py==3.0.0 +MarkupSafe==3.0.2 +marshmallow==3.26.1 +matplotlib-inline==0.1.7 +mdurl==0.1.2 +mem0ai==0.1.114 +mergedeep==1.3.4 +mkdocs==1.6.1 +mkdocs-get-deps==0.2.0 +mkdocs-material==9.6.15 +mkdocs-material-extensions==1.3.1 +mmh3==5.1.0 +monotonic==1.6 +mpmath==1.3.0 +multidict==6.6.3 +mypy_extensions==1.1.0 +networkx==3.5 +nodeenv==1.9.1 +numpy==2.3.1 +oauthlib==3.3.1 +onnxruntime==1.22.0 +openai==1.93.3 +openpyxl==3.1.5 +opentelemetry-api==1.34.1 +opentelemetry-exporter-otlp-proto-common==1.34.1 +opentelemetry-exporter-otlp-proto-grpc==1.34.1 +opentelemetry-exporter-otlp-proto-http==1.34.1 +opentelemetry-instrumentation==0.55b1 +opentelemetry-instrumentation-asgi==0.55b1 +opentelemetry-instrumentation-fastapi==0.55b1 +opentelemetry-proto==1.34.1 +opentelemetry-sdk==1.34.1 +opentelemetry-semantic-conventions==0.55b1 +opentelemetry-util-http==0.55b1 +orjson==3.10.18 +overrides==7.7.0 +packaging==24.2 +paginate==0.5.7 +pandas==2.3.1 +parso==0.8.4 +pathspec==0.12.1 +pdfminer.six==20250506 +pdfplumber==0.11.7 +pexpect==4.9.0 +pillow==11.3.0 +platformdirs==4.3.8 +playwright==1.53.0 +portalocker==2.10.1 +posthog==3.25.0 +pre_commit==4.2.0 +prompt_toolkit==3.0.51 +propcache==0.3.2 +protobuf==5.29.5 +ptyprocess==0.7.0 +pure_eval==0.2.3 +pyarrow==20.0.0 +pyasn1==0.6.1 +pyasn1_modules==0.4.2 +pybase64==1.4.1 +pycparser==2.22 +pydantic==2.11.7 +pydantic-settings==2.10.1 +pydantic_core==2.33.2 +pyee==13.0.0 +Pygments==2.19.2 +PyJWT==2.10.1 +pymdown-extensions==10.16 +pypdf==5.7.0 +pypdfium2==4.30.1 +PyPika==0.48.9 +pyproject_hooks==1.2.0 +pyright==1.1.403 +pysbd==0.3.4 +python-dateutil==2.9.0.post0 +python-dotenv==1.1.1 +pytube==15.0.0 +pytz==2025.2 +pyvis==0.3.2 +PyYAML==6.0.2 +pyyaml_env_tag==1.1 +qdrant-client==1.14.3 +referencing==0.36.2 +regex==2024.11.6 +requests==2.32.4 +requests-oauthlib==2.0.0 +requests-toolbelt==1.0.0 +rich==13.9.4 +rpds-py==0.26.0 +rsa==4.9.1 +schema==0.7.7 +shellingham==1.5.4 +six==1.17.0 +sniffio==1.3.1 +soupsieve==2.7 +SQLAlchemy==2.0.41 +stack-data==0.6.3 +stagehand==0.4.0 +stagehand-py==0.3.10 +starlette==0.46.2 +sympy==1.14.0 +tabulate==0.9.0 +tenacity==9.1.2 +tiktoken==0.9.0 +tokenizers==0.20.3 +tomli==2.2.1 +tomli_w==1.2.0 +tqdm==4.67.1 +traitlets==5.14.3 +typer==0.16.0 +types-requests==2.32.4.20250611 +typing-inspect==0.9.0 +typing-inspection==0.4.1 +typing_extensions==4.14.1 +tzdata==2025.2 +urllib3==2.5.0 +uv==0.7.20 +uvicorn==0.35.0 +uvloop==0.21.0 +virtualenv==20.31.2 +watchdog==6.0.0 +watchfiles==1.1.0 +wcwidth==0.2.13 +websocket-client==1.8.0 +websockets==15.0.1 +wrapt==1.17.2 +yarl==1.20.1 +zipp==3.23.0 +zstandard==0.23.0 diff --git a/examples/integrations/langchain/README.md b/examples/integrations/langchain/README.md index 2691ef4..3e9d894 100644 --- a/examples/integrations/langchain/README.md +++ b/examples/integrations/langchain/README.md @@ -1,25 +1,22 @@ -# Langchain Integration +# Langchain Integration Examples -Add Browserbase to your Langchain application (Python). +This directory contains examples of integrating Langchain with our web automation tools: -## Introduction +1. **Browserbase Integration** (`browserbase/`): A lightweight solution for web scraping and data extraction using our managed browser infrastructure. -Langchain is a Python framework to build applications on top of large-language models (OpenAI, Llama, Gemini). +2. **Stagehand Integration** (`stagehand/`): Full web automation capabilities using our open-source AI-powered browser automation SDK. -Building on top of LLMs comes with many challenges: +3. **Deep Agents + Browserbase** (`deepagents-browserbase/`): A Python example combining LangChain Deep Agents with Browserbase Search, Fetch, and Stagehand browser sessions for research workflows. -- Gathering and preparing the data (context) and providing memory to models -- Orchestrating tasks to match LLM API requirements (ex, rate limiting, chunking) -- Parse the different LLM result format +4. **KYC Onboarding Agent** (`kyc-onboarding/`): A Python example that runs automated KYC due diligence on a company using a five-track fan-out (corporate registry, beneficial ownership, sanctions, litigation, adverse media) and per-owner individual KYC checks. Uses Deep Agents for orchestration and Stagehand for portal navigation. -Langchain comes with a set of high-level concepts and tools to cope with those challenges: +5. **Patent Landscape Agent** (`patent-landscape-agent/`): A Python example that researches a patent landscape across USPTO, EPO, and WIPO using a three-phase workflow — parallel five-track research (granted patents, prosecution history, ownership, PTAB litigation, inventor network), per-family deep dives, and final memo synthesis. Uses OpenAI as the single model provider for both the Deep Agents orchestrator and Stagehand browser sessions. -- Retrieval modules such as Document Loaders or Text splitter help with gathering and preparing the data provided to the models -- Model I/O is a set of tools that help to normalize the APIs across multiple models (ex: Prompt Templates) -- Agents and Tools help to build reasoning (ex: how to answer based on provided context, what actions to take) -- Chains help in orchestrating all the above +Choose the example that best fits your needs: +- Use Browserbase for simple web scraping and data collection +- Use Stagehand for complex automation workflows with AI-driven interactions +- Use Deep Agents + Browserbase for multi-step research agents with human approval gates +- Use KYC Onboarding for compliance workflows that navigate gated portals and forms +- Use Patent Landscape Agent for multi-source research with persistent workpapers and structured memo output -Browserbase provides a Document Loader to enable your Langchain application to browse the web to: - -- Extract text or raw HTML, including from web pages using JavaScript or dynamically rendered text -- Load images via screenshots \ No newline at end of file +See the respective directories for detailed implementation guides. \ No newline at end of file diff --git a/examples/integrations/langchain/browserbase/.gitignore b/examples/integrations/langchain/browserbase/.gitignore new file mode 100644 index 0000000..26bfa0f --- /dev/null +++ b/examples/integrations/langchain/browserbase/.gitignore @@ -0,0 +1 @@ +/venv/ \ No newline at end of file diff --git a/examples/integrations/langchain/browserbase/README.md b/examples/integrations/langchain/browserbase/README.md new file mode 100644 index 0000000..2691ef4 --- /dev/null +++ b/examples/integrations/langchain/browserbase/README.md @@ -0,0 +1,25 @@ +# Langchain Integration + +Add Browserbase to your Langchain application (Python). + +## Introduction + +Langchain is a Python framework to build applications on top of large-language models (OpenAI, Llama, Gemini). + +Building on top of LLMs comes with many challenges: + +- Gathering and preparing the data (context) and providing memory to models +- Orchestrating tasks to match LLM API requirements (ex, rate limiting, chunking) +- Parse the different LLM result format + +Langchain comes with a set of high-level concepts and tools to cope with those challenges: + +- Retrieval modules such as Document Loaders or Text splitter help with gathering and preparing the data provided to the models +- Model I/O is a set of tools that help to normalize the APIs across multiple models (ex: Prompt Templates) +- Agents and Tools help to build reasoning (ex: how to answer based on provided context, what actions to take) +- Chains help in orchestrating all the above + +Browserbase provides a Document Loader to enable your Langchain application to browse the web to: + +- Extract text or raw HTML, including from web pages using JavaScript or dynamically rendered text +- Load images via screenshots \ No newline at end of file diff --git a/examples/integrations/langchain/main.py b/examples/integrations/langchain/browserbase/main.py similarity index 100% rename from examples/integrations/langchain/main.py rename to examples/integrations/langchain/browserbase/main.py diff --git a/examples/integrations/langchain/requirements.txt b/examples/integrations/langchain/browserbase/requirements.txt similarity index 51% rename from examples/integrations/langchain/requirements.txt rename to examples/integrations/langchain/browserbase/requirements.txt index 48a0ce8..8300f55 100644 --- a/examples/integrations/langchain/requirements.txt +++ b/examples/integrations/langchain/browserbase/requirements.txt @@ -1,4 +1,4 @@ browserbase -langchain-community +langchain-community>=0.2.19 playwright poetry diff --git a/examples/integrations/langchain/deepagents-browserbase/README.md b/examples/integrations/langchain/deepagents-browserbase/README.md new file mode 100644 index 0000000..6f1eb0b --- /dev/null +++ b/examples/integrations/langchain/deepagents-browserbase/README.md @@ -0,0 +1,97 @@ +# LangChain Deep Agents + Browserbase (Python) + +This example shows the implementation pattern that fits LangChain Deep Agents best in Python: + +- Give the main Deep Agent cheap Browserbase-backed tools for `search` and `fetch` +- Add a specialized browser subagent for heavier rendered or interactive browser work +- Gate stateful browser actions behind Deep Agents `interrupt_on` + +It intentionally does **not** route the agent through the Browserbase CLI. Deep Agents already wants Python tools, subagents, and interrupt handling, so the clean integration is to expose Browserbase as Python tools directly. + +## Architecture + +- `browserbase_search`: fast discovery with Browserbase Search +- `browserbase_fetch`: cheap page retrieval with Browserbase Fetch +- `browserbase_rendered_extract`: Stagehand-backed rendered extraction for JS-heavy pages +- `browserbase_interactive_task`: a Stagehand `agent().execute(...)` workflow for clicks, typing, login, or form submission +- `browser-specialist` subagent: isolates browser-heavy work from the main planner + +## Requirements + +- Python 3.11+ +- `BROWSERBASE_API_KEY` for Browserbase Search, Fetch, and browser sessions +- An OpenAI-compatible base URL for the Deep Agent model if you are not using direct OpenAI + +The sample uses `BROWSERBASE_API_KEY` as the fallback API key for both: + +- Browserbase primitives and Stagehand +- the LangChain chat model client + +That means you do not need a second model-provider secret in this sample if you point the Deep Agent model at a compatible gateway endpoint. + +The sample defaults to: + +- Deep Agent model: `gpt-5.4` +- Stagehand rendered-extract model: `google/gemini-3-flash-preview` +- Stagehand interactive-agent model: `anthropic/claude-sonnet-4-6` + +You can override either with environment variables. + +## Install + +```bash +cd /Users/kylejeong/Desktop/integrations/examples/integrations/langchain/deepagents-browserbase +python3 -m venv .venv +source .venv/bin/activate +pip install -r requirements.txt +``` + +## Environment + +```bash +export BROWSERBASE_API_KEY="bb_..." + +# Optional overrides +export DEEPAGENT_MODEL="gpt-5.4" +export DEEPAGENT_BASE_URL="https://" +export STAGEHAND_MODEL="google/gemini-3-flash-preview" +export STAGEHAND_AGENT_MODEL="anthropic/claude-sonnet-4-6" +``` + +## Run + +Use the default research prompt: + +```bash +python main.py +``` + +Or pass your own: + +```bash +python main.py "Research the Browserbase Fetch API and explain when the agent should escalate to a full browser session." +``` + +## Approval flow + +The sample configures `interrupt_on` for `browserbase_interactive_task`. + +When the agent wants to click, type, log in, or submit a form, the script pauses and asks you to: + +- `approve` +- `edit` +- `reject` + +This is the right place to put human approval in a Deep Agents + Browserbase design, because the approval happens at the tool boundary instead of being hidden inside ad hoc shell calls. + +## Notes + +- The interactive tool now uses `stagehand.agent().execute(...)` instead of a single `sessions.act(...)` call. That makes it better suited to genuine multi-step browser tasks. +- Browserbase’s Stagehand quickstart documents that Model Gateway works with just `BROWSERBASE_API_KEY` for Stagehand browser workflows. +- I did not hardcode a Browserbase model-gateway URL for the LangChain model client because I did not find an official doc page in the Browserbase docs that specifies a general-purpose OpenAI-compatible endpoint for LangChain. The sample therefore accepts `DEEPAGENT_BASE_URL` or `OPENAI_BASE_URL` explicitly. + +## Suggested prompts + +- `Research Browserbase Search, Fetch, and browser sessions. Give me a decision tree with citations.` +- `Open docs.browserbase.com and extract the limits of the Fetch API from the rendered docs page.` +- `Go to example.com and tell me whether any interactive action would be required to complete the task.` diff --git a/examples/integrations/langchain/deepagents-browserbase/browser_tools.py b/examples/integrations/langchain/deepagents-browserbase/browser_tools.py new file mode 100644 index 0000000..b70c1bf --- /dev/null +++ b/examples/integrations/langchain/deepagents-browserbase/browser_tools.py @@ -0,0 +1,217 @@ +from __future__ import annotations + +import asyncio +import json +import os +import re +from typing import Any + +from browserbase import Browserbase +from bs4 import BeautifulSoup +from langchain.tools import tool +from stagehand import AsyncStagehand + +# Using the Browserbase Model Gateway, you only need to pass your Browserbase API key to use frontier models +# Docs: https://docs.browserbase.com/platform/model-gateway/overview + +DEFAULT_STAGEHAND_MODEL = os.getenv( + "STAGEHAND_MODEL", + "google/gemini-3-flash-preview", +) +DEFAULT_STAGEHAND_AGENT_MODEL = os.getenv( + "STAGEHAND_AGENT_MODEL", + "anthropic/claude-sonnet-4-6", +) + + +def _require_env(name: str) -> str: + value = os.getenv(name, "").strip() + if not value: + raise ValueError(f"Missing required environment variable: {name}") + return value + + +def _browserbase_client() -> Browserbase: + return Browserbase(api_key=_require_env("BROWSERBASE_API_KEY")) + + +def _normalize(value: Any) -> Any: + if value is None or isinstance(value, (str, int, float, bool)): + return value + if isinstance(value, dict): + return {str(key): _normalize(val) for key, val in value.items()} + if isinstance(value, (list, tuple, set)): + return [_normalize(item) for item in value] + if hasattr(value, "model_dump"): + return _normalize(value.model_dump()) + if hasattr(value, "dict"): + return _normalize(value.dict()) + if hasattr(value, "__dict__"): + public = { + key: val + for key, val in vars(value).items() + if not key.startswith("_") and not callable(val) + } + if public: + return _normalize(public) + return str(value) + + +def _json(value: Any) -> str: + return json.dumps(_normalize(value), indent=2, default=str) + + +def _html_to_text(html: str, max_chars: int) -> tuple[str, str]: + soup = BeautifulSoup(html, "html.parser") + title = soup.title.get_text(" ", strip=True) if soup.title else "" + for tag in soup(["script", "style", "noscript"]): + tag.decompose() + body = soup.body or soup + text = body.get_text("\n", strip=True) + text = re.sub(r"\n{3,}", "\n\n", text) + return title, text[:max_chars] + + +def _stagehand_client() -> AsyncStagehand: + return AsyncStagehand( + browserbase_api_key=_require_env("BROWSERBASE_API_KEY"), + ) + + +def _run_async(coro: Any) -> Any: + return asyncio.run(coro) + + +@tool +def browserbase_search(query: str, num_results: int = 5) -> str: + """Search the web with Browserbase. Use this first for discovery before opening pages.""" + bb = _browserbase_client() + response = bb.search.web(query=query, num_results=max(1, min(num_results, 10))) + results = [] + for result in getattr(response, "results", []): + results.append( + { + "title": getattr(result, "title", ""), + "url": getattr(result, "url", ""), + "author": getattr(result, "author", None), + "published_date": ( + getattr(result, "published_date", None) + or getattr(result, "publishedDate", None) + ), + } + ) + return _json( + { + "query": query, + "request_id": getattr(response, "request_id", None) + or getattr(response, "requestId", None), + "results": results, + } + ) + + +@tool +def browserbase_fetch(url: str, use_proxy: bool = False, max_chars: int = 12000) -> str: + """Fetch page content without a browser session. Best for static pages and quick reads.""" + bb = _browserbase_client() + response = bb.fetch_api.create(url=url, proxies=use_proxy) + content = getattr(response, "content", "") + content_type = ( + getattr(response, "content_type", None) + or getattr(response, "contentType", "") + or "" + ).lower() + + title = "" + text = str(content)[:max_chars] + if "html" in content_type: + title, text = _html_to_text(str(content), max_chars=max_chars) + + return _json( + { + "url": url, + "status_code": getattr(response, "status_code", None) + or getattr(response, "statusCode", None), + "content_type": getattr(response, "content_type", None) + or getattr(response, "contentType", None), + "encoding": getattr(response, "encoding", None), + "title": title, + "text": text, + } + ) + + +@tool +def browserbase_rendered_extract(start_url: str, instruction: str) -> str: + """Open a full Browserbase browser session and extract rendered content from a page with Stagehand.""" + return _run_async(_browserbase_rendered_extract_async(start_url=start_url, instruction=instruction)) + + +async def _browserbase_rendered_extract_async(start_url: str, instruction: str) -> str: + client = _stagehand_client() + start_resp = await client.sessions.start( + model_name=DEFAULT_STAGEHAND_MODEL, + ) + session_id = start_resp.data.session_id + + try: + await client.sessions.navigate( + id=session_id, + url=start_url, + frame_id="", + ) + result = await client.sessions.extract( + id=session_id, + instruction=instruction, + ) + extracted = getattr(getattr(result, "data", None), "result", None) + return _json( + { + "start_url": start_url, + "session_id": session_id, + "session_url": f"https://browserbase.com/sessions/{session_id}", + "instruction": instruction, + "result": _normalize(extracted), + } + ) + finally: + await client.sessions.end(id=session_id) + + +@tool +def browserbase_interactive_task(start_url: str, task: str) -> str: + """Open a Browserbase-hosted Stagehand session and let a Stagehand agent execute a multi-step browser task.""" + return _run_async(_browserbase_interactive_task_async(start_url=start_url, task=task)) + + +async def _browserbase_interactive_task_async(start_url: str, task: str) -> str: + client = _stagehand_client() + start_resp = await client.sessions.start( + model_name=DEFAULT_STAGEHAND_AGENT_MODEL, + ) + session_id = start_resp.data.session_id + + try: + await client.sessions.navigate( + id=session_id, + url=start_url, + frame_id="", + ) + result = await client.sessions.execute( + id=session_id, + execute_options={ + "instruction": task, + "max_steps": 20, + }, + agent_config={ + "model": DEFAULT_STAGEHAND_AGENT_MODEL, + "instructions": ( + "You are executing a browser task on behalf of a LangChain tool. " + "Be precise, avoid unnecessary actions, and stop once the requested task is complete." + ), + }, + timeout=300.0, + ) + return _json(_normalize(result)) + finally: + await client.sessions.end(id=session_id) diff --git a/examples/integrations/langchain/deepagents-browserbase/main.py b/examples/integrations/langchain/deepagents-browserbase/main.py new file mode 100644 index 0000000..af4259f --- /dev/null +++ b/examples/integrations/langchain/deepagents-browserbase/main.py @@ -0,0 +1,227 @@ +from __future__ import annotations + +import argparse +import json +import os +import uuid +from typing import Any + +from deepagents import create_deep_agent +from dotenv import load_dotenv +from langgraph.checkpoint.memory import MemorySaver +from langgraph.types import Command +from langchain_openai import ChatOpenAI + +from browser_tools import ( + browserbase_fetch, + browserbase_interactive_task, + browserbase_rendered_extract, + browserbase_search, +) + + +SYSTEM_PROMPT = """You are a research-oriented Deep Agent with Browserbase tools. + +Workflow rules: +- Start with browserbase_search for discovery unless the user already gave you a precise URL. +- Prefer browserbase_fetch for quick reads of static pages. +- Delegate JS-heavy, rendered, or multi-step browsing work to the browser-specialist subagent. +- Use browserbase_rendered_extract for read-only browser work on rendered pages. +- Use browserbase_interactive_task only when the task requires clicking, typing, login, or form submission. +- Keep answers concise and cite the exact URLs you used. +- Avoid interactive browser actions when fetch or rendered extraction is enough. +""" + + +BROWSER_SUBAGENT = { + "name": "browser-specialist", + "description": ( + "Handles JS-heavy browsing, rendered extraction, and interactive browser tasks through Browserbase." + ), + "system_prompt": """You are a Browserbase browsing specialist. + +Use browserbase_rendered_extract for read-only work on rendered pages. +Use browserbase_interactive_task only for stateful actions such as clicking, typing, logging in, or submitting forms. +Return concise summaries with the relevant page URL, what you observed, and whether the task succeeded. +""", + "tools": [browserbase_rendered_extract, browserbase_interactive_task], +} + + +def _normalize_chat_model_name(model: str) -> str: + if ":" in model: + provider, raw_model = model.split(":", 1) + if provider == "openai": + return raw_model + return model + + +def build_model(model: str) -> ChatOpenAI: + base_url = os.getenv("DEEPAGENT_BASE_URL") or os.getenv("OPENAI_BASE_URL") + openai_api_key = os.getenv("OPENAI_API_KEY") + browserbase_api_key = os.getenv("BROWSERBASE_API_KEY") + + if openai_api_key: + api_key = openai_api_key + elif browserbase_api_key and base_url: + api_key = browserbase_api_key + else: + raise ValueError( + "Missing Deep Agent model configuration. Set OPENAI_API_KEY for direct OpenAI access, " + "or set BROWSERBASE_API_KEY together with DEEPAGENT_BASE_URL/OPENAI_BASE_URL for a " + "Browserbase-backed OpenAI-compatible gateway." + ) + + kwargs: dict[str, Any] = { + "model": _normalize_chat_model_name(model), + "api_key": api_key, + } + if base_url: + kwargs["base_url"] = base_url + return ChatOpenAI(**kwargs) + + +def build_agent(model: str): + return create_deep_agent( + model=build_model(model), + tools=[browserbase_search, browserbase_fetch], + subagents=[BROWSER_SUBAGENT], + system_prompt=SYSTEM_PROMPT, + interrupt_on={ + "browserbase_interactive_task": { + "allowed_decisions": ["approve", "edit", "reject"] + } + }, + checkpointer=MemorySaver(), + ) + + +def _stringify_content(content: Any) -> str: + if isinstance(content, str): + return content + if isinstance(content, list): + parts = [] + for item in content: + if isinstance(item, str): + parts.append(item) + elif isinstance(item, dict): + if item.get("type") == "text": + parts.append(str(item.get("text", ""))) + else: + parts.append(json.dumps(item, default=str)) + else: + parts.append(str(item)) + return "\n".join(part for part in parts if part) + return json.dumps(content, indent=2, default=str) + + +def _final_text(result: Any) -> str: + state = getattr(result, "value", result) + if isinstance(state, dict): + messages = state.get("messages", []) + for message in reversed(messages): + msg_type = getattr(message, "type", None) + if msg_type is None and isinstance(message, dict): + msg_type = message.get("type") or message.get("role") + if msg_type in {"ai", "assistant"}: + content = getattr(message, "content", None) + if content is None and isinstance(message, dict): + content = message.get("content") + return _stringify_content(content) + return json.dumps(state, indent=2, default=str) + return str(state) + + +def _review_actions(result: Any) -> list[dict[str, Any]]: + interrupt_value = result.interrupts[0].value + action_requests = interrupt_value["action_requests"] + review_configs = interrupt_value["review_configs"] + config_by_name = {config["action_name"]: config for config in review_configs} + decisions: list[dict[str, Any]] = [] + + for action in action_requests: + review = config_by_name[action["name"]] + allowed = review["allowed_decisions"] + + print("\nPending tool call") + print(f"Tool: {action['name']}") + print("Arguments:") + print(json.dumps(action["args"], indent=2, default=str)) + print(f"Allowed decisions: {', '.join(allowed)}") + + while True: + raw = input("Decision [approve/edit/reject]: ").strip().lower() + if raw in allowed: + if raw == "approve": + decisions.append({"type": "approve"}) + break + if raw == "reject": + decisions.append({"type": "reject"}) + break + + edited = input("Enter replacement JSON args: ").strip() + try: + edited_args = json.loads(edited) + except json.JSONDecodeError: + print("Invalid JSON. Try again.") + continue + decisions.append( + { + "type": "edit", + "edited_action": { + "name": action["name"], + "args": edited_args, + }, + } + ) + break + + print("Invalid decision for this tool call.") + + return decisions + + +def run(query: str, model: str) -> str: + agent = build_agent(model=model) + config = {"configurable": {"thread_id": str(uuid.uuid4())}} + result = agent.invoke( + {"messages": [{"role": "user", "content": query}]}, + config=config, + version="v2", + ) + + while result.interrupts: + decisions = _review_actions(result) + result = agent.invoke( + Command(resume={"decisions": decisions}), + config=config, + version="v2", + ) + + return _final_text(result) + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser( + description="Sample LangChain Deep Agents app with Browserbase tools." + ) + parser.add_argument( + "query", + nargs="?", + default=( + "Research the Browserbase Search API and explain when to use Search, Fetch, " + "and a full browser session. Cite the URLs you used." + ), + ) + parser.add_argument( + "--model", + default=os.getenv("DEEPAGENT_MODEL", "gpt-5.4"), + help="Deep Agents model name. OpenAI-compatible raw names are recommended.", + ) + return parser.parse_args() + + +if __name__ == "__main__": + load_dotenv() + args = parse_args() + print(run(query=args.query, model=args.model)) diff --git a/examples/integrations/langchain/deepagents-browserbase/requirements.txt b/examples/integrations/langchain/deepagents-browserbase/requirements.txt new file mode 100644 index 0000000..0a9bb1a --- /dev/null +++ b/examples/integrations/langchain/deepagents-browserbase/requirements.txt @@ -0,0 +1,6 @@ +beautifulsoup4>=4.13.0 +browserbase>=1.8.0 +deepagents>=0.0.5 +langchain-openai>=0.3.0 +python-dotenv>=1.0.0 +stagehand>=3.19.5 diff --git a/examples/integrations/langchain/kyc-onboarding/.env.example b/examples/integrations/langchain/kyc-onboarding/.env.example new file mode 100644 index 0000000..5db156f --- /dev/null +++ b/examples/integrations/langchain/kyc-onboarding/.env.example @@ -0,0 +1,12 @@ +BROWSERBASE_API_KEY=bb_... + +# Use direct OpenAI +OPENAI_API_KEY=sk-... + +# Or use the Browserbase Model Gateway instead (no separate OpenAI key needed) +# DEEPAGENT_BASE_URL=https:// + +# Optional model overrides +# DEEPAGENT_MODEL=gpt-5.4 +# STAGEHAND_MODEL=google/gemini-3-flash-preview +# STAGEHAND_AGENT_MODEL=anthropic/claude-sonnet-4-6 diff --git a/examples/integrations/langchain/kyc-onboarding/.gitignore b/examples/integrations/langchain/kyc-onboarding/.gitignore new file mode 100644 index 0000000..69cac2e --- /dev/null +++ b/examples/integrations/langchain/kyc-onboarding/.gitignore @@ -0,0 +1,4 @@ +.env +.venv/ +__pycache__/ +*.pyc diff --git a/examples/integrations/langchain/kyc-onboarding/README.md b/examples/integrations/langchain/kyc-onboarding/README.md new file mode 100644 index 0000000..4ee0fb9 --- /dev/null +++ b/examples/integrations/langchain/kyc-onboarding/README.md @@ -0,0 +1,142 @@ +# LangChain Deep Agents + KYC Onboarding (Python) + +This example builds a KYC onboarding agent that runs automated due diligence on a company +using LangChain Deep Agents for orchestration, Stagehand for browser interactions, and +Browserbase for headless browser sessions. + +The agent navigates real portals — Secretary of State sites, FinCEN BOI, OFAC, PACER, SEC EDGAR, +and news publishers — rather than relying on search or fetch APIs alone. Browserbase Agent Identity +handles anti-bot measures and CAPTCHAs automatically. + +## Architecture + +**Phase 1 — five-track fan-out:** + +| Subagent | Portals | +|---|---| +| `corporate-registry` | Secretary of State portals (Delaware, California, New York, UK Companies House) | +| `beneficial-ownership` | FinCEN BOI, UK PSC register, EU member-state registries | +| `sanctions-pep` | OFAC SDN, EU consolidated list, UK HMT financial sanctions | +| `litigation-regulatory` | PACER, state courts, SEC EDGAR | +| `adverse-media` | Reuters, Bloomberg, FT, WSJ, SEC newsroom, DOJ press releases | + +**Phase 2 — individual KYC fan-out:** + +After the `beneficial-ownership` subagent returns a list of ultimate beneficial owners (UBOs), +the orchestrator delegates one `individual-kyc` subagent call per person. Each individual check +covers sanctions screening, PEP status, and adverse media. + +**Tools (defined in `kyc_tools.py`):** + +- `kyc_search`: Browserbase Search for initial discovery before opening portals +- `kyc_fetch`: Browserbase Fetch for static pages (EDGAR filings, public registries) +- `kyc_extract_from_portal`: opens a Browserbase session and extracts structured data from a + rendered portal page using Stagehand `extract` +- `kyc_search_portal`: opens a Browserbase session and runs a multi-step browser task (form fills, + paginated search navigation) using a Stagehand agent — gated behind human approval + +Every browser session produces a session replay URL included in the tool response for audit purposes. + +## Requirements + +- Python 3.11+ +- `BROWSERBASE_API_KEY` for Browserbase Search, Fetch, and browser sessions (including Stagehand) +- An OpenAI-compatible model for the Deep Agent orchestrator + +The sample accepts `OPENAI_API_KEY` for direct OpenAI access, or `BROWSERBASE_API_KEY` paired with +`DEEPAGENT_BASE_URL` for a Browserbase-backed OpenAI-compatible gateway. + +Default models: +- Deep Agent orchestrator: `gpt-4o` +- Stagehand extraction: `google/gemini-3-flash-preview` +- Stagehand interactive agent: `anthropic/claude-sonnet-4-6` + +## Install + +```bash +cd examples/integrations/langchain/kyc-onboarding +python3 -m venv .venv +source .venv/bin/activate +pip install -r requirements.txt +``` + +## Environment + +Copy `.env.example` to `.env` and fill in your keys: + +```bash +cp .env.example .env +``` + +```ini +BROWSERBASE_API_KEY=bb_... + +# Use direct OpenAI +OPENAI_API_KEY=sk-... + +# Or use the Browserbase Model Gateway instead (no separate OpenAI key needed) +# DEEPAGENT_BASE_URL=https:// + +# Optional model overrides +# DEEPAGENT_MODEL=gpt-5.4 +# STAGEHAND_MODEL=google/gemini-3-flash-preview +# STAGEHAND_AGENT_MODEL=anthropic/claude-sonnet-4-6 +``` + +## Run + +Use the default demo company: + +```bash +python main.py +``` + +Run on a specific company and jurisdiction: + +```bash +python main.py "Stripe, Inc." --jurisdiction Delaware +python main.py "Revolut Ltd" --jurisdiction "United Kingdom" +``` + +Override the model: + +```bash +python main.py "Acme Corp Inc." --jurisdiction Delaware --model gpt-4o +``` + +## Approval flow + +`kyc_search_portal` is gated behind `interrupt_on`. Whenever the agent wants to submit a search +form, navigate paginated results, or interact with a portal, the script pauses and prompts: + +``` +Pending tool call +Tool: kyc_search_portal +Arguments: +{ + "start_url": "https://icis.corp.delaware.gov/ecorp/entitysearch/namesearch.aspx", + "task": "Search for 'Acme Corp Inc.' and extract the entity status, formation date, and registered agent." +} +Allowed decisions: approve, edit, reject +Decision [approve/edit/reject]: +``` + +- `approve` — run the task as proposed +- `edit` — provide replacement JSON args before running +- `reject` — skip this action + +This puts human review at the tool boundary rather than inside ad hoc shell calls. + +## Notes + +- `kyc_extract_from_portal` maps to Stagehand `extract` — structured, read-only extraction from a rendered page. +- `kyc_search_portal` maps to Stagehand `agent().execute()` — multi-step agentic browsing for portals that require interaction. +- Browserbase Agent Identity manages browser fingerprinting, residential proxy routing, and CAPTCHA solving. No additional configuration is needed beyond `BROWSERBASE_API_KEY`. +- Each `kyc_search_portal` and `kyc_extract_from_portal` response includes a `session_url` field linking to the Browserbase session replay. These replays provide visual evidence for audit workpapers. +- The individual-kyc Phase 2 fan-out is driven by the orchestrator parsing the `beneficial-ownership` subagent report. If the registry is not publicly searchable, the subagent notes this explicitly and Phase 2 proceeds with whatever names were found. + +## Suggested prompts + +- `python main.py "Anthropic, PBC" --jurisdiction Delaware` +- `python main.py "Klarna Bank AB" --jurisdiction Sweden` +- `python main.py "Acme Corp Inc." --jurisdiction Delaware` (demo company, expect sparse results) diff --git a/examples/integrations/langchain/kyc-onboarding/kyc_tools.py b/examples/integrations/langchain/kyc-onboarding/kyc_tools.py new file mode 100644 index 0000000..b2787cc --- /dev/null +++ b/examples/integrations/langchain/kyc-onboarding/kyc_tools.py @@ -0,0 +1,234 @@ +from __future__ import annotations + +import asyncio +import json +import os +import re +from typing import Any + +from browserbase import Browserbase +from bs4 import BeautifulSoup +from langchain.tools import tool +from stagehand import AsyncStagehand + +DEFAULT_STAGEHAND_MODEL = os.getenv( + "STAGEHAND_MODEL", + "google/gemini-3-flash-preview", +) +DEFAULT_STAGEHAND_AGENT_MODEL = os.getenv( + "STAGEHAND_AGENT_MODEL", + "anthropic/claude-sonnet-4-6", +) + + +def _require_env(name: str) -> str: + value = os.getenv(name, "").strip() + if not value: + raise ValueError(f"Missing required environment variable: {name}") + return value + + +def _browserbase_client() -> Browserbase: + return Browserbase(api_key=_require_env("BROWSERBASE_API_KEY")) + + +def _normalize(value: Any) -> Any: + if value is None or isinstance(value, (str, int, float, bool)): + return value + if isinstance(value, dict): + return {str(key): _normalize(val) for key, val in value.items()} + if isinstance(value, (list, tuple, set)): + return [_normalize(item) for item in value] + if hasattr(value, "model_dump"): + return _normalize(value.model_dump()) + if hasattr(value, "dict"): + return _normalize(value.dict()) + if hasattr(value, "__dict__"): + public = { + key: val + for key, val in vars(value).items() + if not key.startswith("_") and not callable(val) + } + if public: + return _normalize(public) + return str(value) + + +def _json(value: Any) -> str: + return json.dumps(_normalize(value), indent=2, default=str) + + +def _html_to_text(html: str, max_chars: int) -> tuple[str, str]: + soup = BeautifulSoup(html, "html.parser") + title = soup.title.get_text(" ", strip=True) if soup.title else "" + for tag in soup(["script", "style", "noscript"]): + tag.decompose() + body = soup.body or soup + text = body.get_text("\n", strip=True) + text = re.sub(r"\n{3,}", "\n\n", text) + return title, text[:max_chars] + + +def _stagehand_client() -> AsyncStagehand: + return AsyncStagehand( + browserbase_api_key=_require_env("BROWSERBASE_API_KEY"), + ) + + +def _run_async(coro: Any) -> Any: + return asyncio.run(coro) + + +@tool +def kyc_search(query: str, num_results: int = 5) -> str: + """Search the web with Browserbase. Use first for discovery before opening portals or pages.""" + bb = _browserbase_client() + response = bb.search.web(query=query, num_results=max(1, min(num_results, 10))) + results = [] + for result in getattr(response, "results", []): + results.append( + { + "title": getattr(result, "title", ""), + "url": getattr(result, "url", ""), + "author": getattr(result, "author", None), + "published_date": ( + getattr(result, "published_date", None) + or getattr(result, "publishedDate", None) + ), + } + ) + return _json( + { + "query": query, + "request_id": getattr(response, "request_id", None) + or getattr(response, "requestId", None), + "results": results, + } + ) + + +@tool +def kyc_fetch(url: str, use_proxy: bool = False, max_chars: int = 12000) -> str: + """Fetch page content without a browser session. Best for static pages such as SEC EDGAR filings and public registries. + + Returns an error with a fallback instruction if the page exceeds 1MB — use kyc_extract_from_portal for those URLs instead. + """ + bb = _browserbase_client() + try: + response = bb.fetch_api.create(url=url, proxies=use_proxy) + except Exception as e: + return _json({"error": str(e), "fallback": "Page too large for Fetch. Call kyc_extract_from_portal with this URL instead."}) + content = getattr(response, "content", "") + content_type = ( + getattr(response, "content_type", None) + or getattr(response, "contentType", "") + or "" + ).lower() + + title = "" + text = str(content)[:max_chars] + if "html" in content_type: + title, text = _html_to_text(str(content), max_chars=max_chars) + + return _json( + { + "url": url, + "status_code": getattr(response, "status_code", None) + or getattr(response, "statusCode", None), + "content_type": getattr(response, "content_type", None) + or getattr(response, "contentType", None), + "encoding": getattr(response, "encoding", None), + "title": title, + "text": text, + } + ) + + +@tool +def kyc_extract_from_portal(start_url: str, instruction: str) -> str: + """Open a Browserbase browser session and extract structured data from a rendered portal page using Stagehand. + + Use for read-only lookups on JavaScript-heavy registry portals, sanctions lists, and court record sites. + The session_url in the response links to the Browserbase session replay. + """ + return _run_async(_kyc_extract_from_portal_async(start_url=start_url, instruction=instruction)) + + +async def _kyc_extract_from_portal_async(start_url: str, instruction: str) -> str: + client = _stagehand_client() + start_resp = await client.sessions.start( + model_name=DEFAULT_STAGEHAND_MODEL, + ) + session_id = start_resp.data.session_id + + try: + await client.sessions.navigate( + id=session_id, + url=start_url, + frame_id="", + ) + result = await client.sessions.extract( + id=session_id, + instruction=instruction, + ) + extracted = getattr(getattr(result, "data", None), "result", None) + return _json( + { + "start_url": start_url, + "session_id": session_id, + "session_url": f"https://browserbase.com/sessions/{session_id}", + "instruction": instruction, + "result": _normalize(extracted), + } + ) + finally: + await client.sessions.end(id=session_id) + + +@tool +def kyc_search_portal(start_url: str, task: str) -> str: + """Open a Browserbase browser session and run a multi-step browser task on a portal using a Stagehand agent. + + Use for interactive lookups that require filling search forms, navigating paginated results, or + submitting queries to gated portals (Secretary of State, FinCEN BOI, OFAC, PACER, EDGAR). + Agent Identity handles anti-bot measures and CAPTCHAs automatically. + The session_url in the response links to the Browserbase session replay. + """ + return _run_async(_kyc_search_portal_async(start_url=start_url, task=task)) + + +async def _kyc_search_portal_async(start_url: str, task: str) -> str: + client = _stagehand_client() + start_resp = await client.sessions.start( + model_name=DEFAULT_STAGEHAND_AGENT_MODEL, + ) + session_id = start_resp.data.session_id + + try: + await client.sessions.navigate( + id=session_id, + url=start_url, + frame_id="", + ) + result = await client.sessions.execute( + id=session_id, + execute_options={ + "instruction": task, + "max_steps": 25, + }, + agent_config={ + "model": DEFAULT_STAGEHAND_AGENT_MODEL, + "instructions": ( + "You are executing a KYC lookup on behalf of a compliance agent. " + "Be precise, extract all relevant fields, and stop once the lookup is complete. " + "If a CAPTCHA or challenge appears, pause and report it." + ), + }, + timeout=300.0, + ) + data = _normalize(result) + if isinstance(data, dict): + data["session_url"] = f"https://browserbase.com/sessions/{session_id}" + return _json(data) + finally: + await client.sessions.end(id=session_id) diff --git a/examples/integrations/langchain/kyc-onboarding/main.py b/examples/integrations/langchain/kyc-onboarding/main.py new file mode 100644 index 0000000..3316569 --- /dev/null +++ b/examples/integrations/langchain/kyc-onboarding/main.py @@ -0,0 +1,415 @@ +from __future__ import annotations + +import argparse +import json +import os +import uuid +from typing import Any + +from deepagents import create_deep_agent +from dotenv import load_dotenv +from langgraph.checkpoint.memory import MemorySaver +from langgraph.types import Command +from langchain_openai import ChatOpenAI + +from kyc_tools import ( + kyc_extract_from_portal, + kyc_fetch, + kyc_search, + kyc_search_portal, +) + + +SYSTEM_PROMPT = """You are a KYC onboarding orchestrator. Given a company name and jurisdiction, +run a two-phase due diligence workflow and return a consolidated KYC report. + +Phase 1 — fan out to all five specialist subagents in parallel: +- corporate-registry: verify legal existence, registered agent, filing status, and good standing. +- beneficial-ownership: identify ultimate beneficial owners (UBOs) and controlling persons. +- sanctions-pep: screen the entity against OFAC, EU, and UK sanctions lists and PEP registries. +- litigation-regulatory: search PACER, relevant state courts, and SEC EDGAR for material actions. +- adverse-media: search publisher news sites for negative coverage, fraud, or enforcement actions. + +Phase 2 — individual KYC fan-out: +- Parse the beneficial-ownership report for each named individual owner. +- For each person, delegate to the individual-kyc subagent to run sanctions, PEP, and adverse-media checks. + +Final output: +- Consolidated report with findings per track. +- Flag any hits, discrepancies, or items requiring manual review. +- Include session replay URLs from each browser session for audit purposes. +""" + +_ALL_TOOLS = [kyc_search, kyc_fetch, kyc_extract_from_portal, kyc_search_portal] + +CORPORATE_REGISTRY = { + "name": "corporate-registry", + "description": ( + "Verifies corporate legal existence, registered agent, filing status, and good standing " + "via state Secretary of State portals and equivalent registries." + ), + "system_prompt": """You are a corporate registry specialist. + +Your task: confirm the company's legal existence and standing in the given jurisdiction. + +Target portals (select based on jurisdiction): +- Delaware: https://icis.corp.delaware.gov/ecorp/entitysearch/namesearch.aspx +- California: https://bizfileonline.sos.ca.gov/search/business +- New York: https://apps.dos.ny.gov/publicInquiry/ +- Federal (UK): https://find-and-update.company-information.service.gov.uk/ + +Steps: +1. Use kyc_search to locate the correct portal for the jurisdiction. +2. Use kyc_search_portal to search by company name and retrieve: entity type, status, formation date, + registered agent name and address, and any recent filings. +3. Use kyc_extract_from_portal for read-only extraction on rendered results pages. + +Return a structured report with all retrieved fields and the session replay URL for each session. +""", + "tools": _ALL_TOOLS, +} + +BENEFICIAL_OWNERSHIP = { + "name": "beneficial-ownership", + "description": ( + "Identifies ultimate beneficial owners (UBOs) and controlling persons via FinCEN BOI " + "and jurisdiction-specific registries." + ), + "system_prompt": """You are a beneficial ownership specialist. + +Your task: identify all ultimate beneficial owners (UBOs) and controlling persons for the entity. + +Target portals: +- FinCEN BOI search (if available): https://boiefiling.fincen.gov/ +- UK PSC register: https://find-and-update.company-information.service.gov.uk/ +- EU registries vary by member state; use kyc_search to locate the correct portal. + +Steps: +1. Search the FinCEN BOI system and any jurisdiction-specific beneficial ownership registry. +2. Extract each named individual: full name, ownership percentage, nature of control, nationality. +3. If the registry is not publicly searchable, note it explicitly in your report. + +Return a structured list of beneficial owners with all available fields, plus session replay URLs. +This list will be used by the Phase 2 individual KYC fan-out. +""", + "tools": _ALL_TOOLS, +} + +SANCTIONS_PEP = { + "name": "sanctions-pep", + "description": ( + "Screens the entity against OFAC SDN, EU consolidated sanctions list, UK HMT financial " + "sanctions list, and PEP registries." + ), + "system_prompt": """You are a sanctions and PEP screening specialist. + +Your task: screen the company against all major sanctions and PEP lists. + +Target portals: +- OFAC SDN: https://sanctionssearch.ofac.treas.gov/ +- EU consolidated list: https://eeas.europa.eu/topics/sanctions-policy/8442/consolidated-list-sanctions_en +- UK HMT: https://www.gov.uk/government/publications/financial-sanctions-consolidated-list-of-targets + +Steps: +1. Search each portal by the exact company name and any known aliases or trading names. +2. Record: whether a match was found, match score or confidence, relevant list entry details, + and the date of the check. +3. If no match is found, state that explicitly with the search terms used. + +Return a per-list screening result with session replay URLs for audit evidence. +""", + "tools": _ALL_TOOLS, +} + +LITIGATION_REGULATORY = { + "name": "litigation-regulatory", + "description": ( + "Searches PACER, relevant state courts, and SEC EDGAR for material litigation, " + "enforcement actions, and regulatory filings." + ), + "system_prompt": """You are a litigation and regulatory specialist. + +Your task: identify material litigation, enforcement actions, and relevant regulatory filings. + +Steps: + +1. SEC EDGAR full-text search (JSON API — use kyc_fetch, not kyc_search_portal): + Construct the URL by substituting the company name into the query parameter, e.g.: + https://efts.sec.gov/LATEST/search-index?q=%22Stripe%2C+Inc.%22&dateRange=custom&startdt=2015-01-01 + Parse the JSON response for hits referencing legal proceedings, enforcement, or Wells notices. + +2. SEC EDGAR company search (rendered page — use kyc_extract_from_portal): + Construct the URL by substituting the company name, e.g.: + https://www.sec.gov/cgi-bin/browse-edgar?company=Stripe&action=getcompany + Extract any filings that reference legal proceedings (8-K Item 8.01, litigation releases). + +3. PACER Case Locator (interactive portal — use kyc_search_portal): + https://pcl.uscourts.gov/pcl/pages/search/findCase.jsf + Search for federal civil and criminal cases naming the company as a party. + +4. Use kyc_search to surface any publicly reported regulatory actions not captured above. + +Summarize: case name, docket number, court, filing date, current status, and resolution if any. +Return findings with session replay URLs for each browser session. +""", + "tools": _ALL_TOOLS, +} + +ADVERSE_MEDIA = { + "name": "adverse-media", + "description": ( + "Searches publisher news sites for negative coverage, fraud allegations, enforcement actions, " + "or reputational risk signals." + ), + "system_prompt": """You are an adverse media specialist. + +Your task: identify negative news coverage that represents reputational or compliance risk. + +Search targets (use kyc_search, then kyc_fetch or kyc_extract_from_portal for full articles): +- Reuters, Bloomberg, Financial Times, Wall Street Journal +- Regulatory and enforcement news sites (SEC.gov newsroom, FinCEN advisories, DOJ press releases) +- Industry-specific press + +Search terms to use: +- "{company} fraud" +- "{company} enforcement" +- "{company} investigation" +- "{company} money laundering" +- "{company} sanctions" + +Steps: +1. Run searches with each term combination. +2. For each hit, fetch the article and extract: headline, publication, date, summary of allegation, + and outcome if known. +3. Distinguish confirmed findings from allegations. + +Return a ranked list of adverse media findings by severity, with source URLs. +""", + "tools": _ALL_TOOLS, +} + +INDIVIDUAL_KYC = { + "name": "individual-kyc", + "description": ( + "Runs KYC checks on an individual beneficial owner: sanctions screening, PEP status, " + "and adverse media search." + ), + "system_prompt": """You are an individual KYC specialist. + +You will receive a person's name, nationality, and role. Run the following checks: + +1. Sanctions screening: + - OFAC SDN: https://sanctionssearch.ofac.treas.gov/ + - EU consolidated list: https://eeas.europa.eu/topics/sanctions-policy/8442/consolidated-list-sanctions_en + - UK HMT: https://www.gov.uk/government/publications/financial-sanctions-consolidated-list-of-targets + +2. PEP screening: + - Use kyc_search for "{name} politically exposed person" and "{name} government official". + +3. Adverse media: + - Search for "{name} fraud", "{name} investigation", "{name} enforcement". + +Return a structured report with: name, role, sanctions result (match/no-match per list), +PEP status, adverse media hits, and session replay URLs for each browser session. +""", + "tools": _ALL_TOOLS, +} + + +def _normalize_chat_model_name(model: str) -> str: + if ":" in model: + provider, raw_model = model.split(":", 1) + if provider == "openai": + return raw_model + return model + + +def build_model(model: str) -> ChatOpenAI: + base_url = os.getenv("DEEPAGENT_BASE_URL") or os.getenv("OPENAI_BASE_URL") + openai_api_key = os.getenv("OPENAI_API_KEY") + browserbase_api_key = os.getenv("BROWSERBASE_API_KEY") + + if openai_api_key: + api_key = openai_api_key + elif browserbase_api_key and base_url: + api_key = browserbase_api_key + else: + raise ValueError( + "Missing Deep Agent model configuration. Set OPENAI_API_KEY for direct OpenAI access, " + "or set BROWSERBASE_API_KEY together with DEEPAGENT_BASE_URL/OPENAI_BASE_URL for a " + "Browserbase-backed OpenAI-compatible gateway." + ) + + kwargs: dict[str, Any] = { + "model": _normalize_chat_model_name(model), + "api_key": api_key, + } + if base_url: + kwargs["base_url"] = base_url + return ChatOpenAI(**kwargs) + + +def build_agent(model: str): + return create_deep_agent( + model=build_model(model), + tools=[kyc_search, kyc_fetch], + subagents=[ + CORPORATE_REGISTRY, + BENEFICIAL_OWNERSHIP, + SANCTIONS_PEP, + LITIGATION_REGULATORY, + ADVERSE_MEDIA, + INDIVIDUAL_KYC, + ], + system_prompt=SYSTEM_PROMPT, + interrupt_on={ + "kyc_search_portal": { + "allowed_decisions": ["approve", "edit", "reject"] + } + }, + checkpointer=MemorySaver(), + ) + + +def _stringify_content(content: Any) -> str: + if isinstance(content, str): + return content + if isinstance(content, list): + parts = [] + for item in content: + if isinstance(item, str): + parts.append(item) + elif isinstance(item, dict): + if item.get("type") == "text": + parts.append(str(item.get("text", ""))) + else: + parts.append(json.dumps(item, default=str)) + else: + parts.append(str(item)) + return "\n".join(part for part in parts if part) + return json.dumps(content, indent=2, default=str) + + +def _final_text(result: Any) -> str: + state = getattr(result, "value", result) + if isinstance(state, dict): + messages = state.get("messages", []) + for message in reversed(messages): + msg_type = getattr(message, "type", None) + if msg_type is None and isinstance(message, dict): + msg_type = message.get("type") or message.get("role") + if msg_type in {"ai", "assistant"}: + content = getattr(message, "content", None) + if content is None and isinstance(message, dict): + content = message.get("content") + return _stringify_content(content) + return json.dumps(state, indent=2, default=str) + return str(state) + + +def _collect_decisions(interrupt_value: Any) -> list[dict[str, Any]]: + action_requests = interrupt_value["action_requests"] + review_configs = interrupt_value["review_configs"] + config_by_name = {config["action_name"]: config for config in review_configs} + decisions: list[dict[str, Any]] = [] + + for action in action_requests: + review = config_by_name[action["name"]] + allowed = review["allowed_decisions"] + + print("\nPending tool call") + print(f"Tool: {action['name']}") + print("Arguments:") + print(json.dumps(action["args"], indent=2, default=str)) + print(f"Allowed decisions: {', '.join(allowed)}") + + while True: + raw = input("Decision [approve/edit/reject]: ").strip().lower() + if raw in allowed: + if raw == "approve": + decisions.append({"type": "approve"}) + break + if raw == "reject": + decisions.append({"type": "reject"}) + break + + edited = input("Enter replacement JSON args: ").strip() + try: + edited_args = json.loads(edited) + except json.JSONDecodeError: + print("Invalid JSON. Try again.") + continue + decisions.append( + { + "type": "edit", + "edited_action": { + "name": action["name"], + "args": edited_args, + }, + } + ) + break + + print("Invalid decision for this tool call.") + + return decisions + + +def _review_actions(result: Any) -> Any: + interrupts = result.interrupts + if len(interrupts) == 1: + return {"decisions": _collect_decisions(interrupts[0].value)} + # Multiple concurrent interrupts — LangGraph requires keying resume by interrupt id. + return { + interrupt.id: {"decisions": _collect_decisions(interrupt.value)} + for interrupt in interrupts + } + + +def run(company: str, jurisdiction: str, model: str) -> str: + agent = build_agent(model=model) + config = {"configurable": {"thread_id": str(uuid.uuid4())}} + query = f"Run a full KYC check on {company!r} incorporated in {jurisdiction}." + result = agent.invoke( + {"messages": [{"role": "user", "content": query}]}, + config=config, + version="v2", + ) + + while result.interrupts: + result = agent.invoke( + Command(resume=_review_actions(result)), + config=config, + version="v2", + ) + + return _final_text(result) + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser( + description="KYC onboarding agent powered by LangChain Deep Agents, Stagehand, and Browserbase." + ) + parser.add_argument( + "company", + nargs="?", + default="Acme Corp Inc.", + help="Full legal name of the company to screen (default: 'Acme Corp Inc.')", + ) + parser.add_argument( + "--jurisdiction", + default="Delaware", + help="Incorporation jurisdiction (default: Delaware)", + ) + parser.add_argument( + "--model", + default=os.getenv("DEEPAGENT_MODEL", "gpt-5.4"), + help="Deep Agents model name.", + ) + return parser.parse_args() + + +if __name__ == "__main__": + load_dotenv() + args = parse_args() + print(run(company=args.company, jurisdiction=args.jurisdiction, model=args.model)) diff --git a/examples/integrations/langchain/kyc-onboarding/requirements.txt b/examples/integrations/langchain/kyc-onboarding/requirements.txt new file mode 100644 index 0000000..0a9bb1a --- /dev/null +++ b/examples/integrations/langchain/kyc-onboarding/requirements.txt @@ -0,0 +1,6 @@ +beautifulsoup4>=4.13.0 +browserbase>=1.8.0 +deepagents>=0.0.5 +langchain-openai>=0.3.0 +python-dotenv>=1.0.0 +stagehand>=3.19.5 diff --git a/examples/integrations/langchain/patent-landscape-agent/.env.example b/examples/integrations/langchain/patent-landscape-agent/.env.example new file mode 100644 index 0000000..c5d269c --- /dev/null +++ b/examples/integrations/langchain/patent-landscape-agent/.env.example @@ -0,0 +1,14 @@ +OPENAI_API_KEY=sk-... +BROWSERBASE_API_KEY=bb_... +# BROWSERBASE_PROJECT_ID=prj_... # optional; scopes sessions to a specific project + +# Optional: override the orchestrator model (default: gpt-4.1) +# PATENT_AGENT_MODEL=gpt-4.1 + +# Optional: override the Stagehand browser agent model (default: openai/gpt-4.1) +# STAGEHAND_MODEL=openai/gpt-4o + +# Optional: LangSmith traces +# LANGSMITH_TRACING=true +# LANGSMITH_API_KEY= +# LANGSMITH_PROJECT= diff --git a/examples/integrations/langchain/patent-landscape-agent/.gitignore b/examples/integrations/langchain/patent-landscape-agent/.gitignore new file mode 100644 index 0000000..6fd5cc0 --- /dev/null +++ b/examples/integrations/langchain/patent-landscape-agent/.gitignore @@ -0,0 +1,5 @@ +.env +.venv/ +__pycache__/ +*.pyc +reports/ diff --git a/examples/integrations/langchain/patent-landscape-agent/README.md b/examples/integrations/langchain/patent-landscape-agent/README.md new file mode 100644 index 0000000..5d3e181 --- /dev/null +++ b/examples/integrations/langchain/patent-landscape-agent/README.md @@ -0,0 +1,161 @@ +# Patent Landscape Agent (LangChain Deep Agents + Stagehand + Browserbase) + +Runs a three-phase patent landscape research workflow given a technology area or assignee name. +Phase 1 fans out five specialist subagents in parallel (granted patents, prosecution history, +assignment/ownership, PTAB litigation, inventor network) across USPTO, EPO, and WIPO public portals. +Phase 2 walks the full family tree for each high-priority patent family. Phase 3 synthesizes +all findings into a structured memo at `./reports/final-memo.md` with a freedom-to-operate +assessment and a sources appendix of Browserbase session replay URLs. + +Uses **OpenAI as the single model provider** for both the Deep Agents orchestrator and all +Stagehand browser-agent sessions — no other provider keys are required. + +## Prerequisites + +- Python 3.11+ +- [Browserbase account](https://browserbase.com) — for headless browser sessions and Agent Identity +- OpenAI API key — for orchestration and Stagehand browser reasoning +- `BROWSERBASE_PROJECT_ID` is optional; set it to scope sessions to a specific Browserbase project + +## Install + +```bash +cd examples/integrations/langchain/patent-landscape-agent +python3 -m venv .venv +source .venv/bin/activate +pip install -r requirements.txt +``` + +Or with `uv`: + +```bash +uv venv && uv pip install -r requirements.txt +``` + +## Environment + +```bash +cp .env.example .env +``` + +Edit `.env`: + +```ini +OPENAI_API_KEY=sk-... +BROWSERBASE_API_KEY=bb_... +# BROWSERBASE_PROJECT_ID=prj_... # optional; scopes sessions to a specific project +``` + +## Run + +Default (PageRank benchmark): + +```bash +python agent.py +``` + +Custom query: + +```bash +python agent.py "MapReduce distributed computing — Google (Jeffrey Dean, Sanjay Ghemawat) US7650331" +python agent.py "Transformer attention mechanism — Google Brain, US10452978" +python agent.py "US6285999" # single seed patent, walks the full family +``` + +Override the orchestrator model: + +```bash +python agent.py --model gpt-4.1 "US6285999" +``` + +The final memo is always written to `./reports/final-memo.md` when the run completes. +Intermediate workpapers may also appear there if the orchestrator uses the filesystem tools +during the run. + +## Streaming subagent activity + +`create_deep_agent` returns a LangGraph compiled graph. To stream token-level output: + +```python +from agent import build_agent + +agent = build_agent(model="gpt-4.1") +config = {"configurable": {"thread_id": "stream-demo"}} + +for chunk in agent.stream( + {"messages": [{"role": "user", "content": "PageRank web search ranking — Stanford/Google US6285999"}]}, + config=config, + version="v2", + stream_mode="updates", +): + print(chunk) +``` + +## Session replays + +Every `patent_research` call opens a Browserbase browser session. The tool response includes a +`session_url` field of the form `https://browserbase.com/sessions/`. These URLs are collected +in the final memo's Sources Appendix and are accessible in the Browserbase dashboard for up to +7 days after the run. + +## Architecture + +``` +agent.py orchestrator (gpt-4.1, OpenAI) +├── tools/patent_research.py single tool: Stagehand agent over a Browserbase session +└── subagents/ + ├── granted_patents.py USPTO search, EPO Espacenet, WIPO Patentscope + ├── prosecution_history.py USPTO Patent Center file wrappers + ├── assignment_ownership.py USPTO Assignment Search, EPO Register + ├── litigation_history.py USPTO PTAB (IPR/PGR proceedings) + ├── inventor_network.py inventor portfolio mapping + └── patent_family_analysis.py continuations, divisionals, foreign equivalents +``` + +All browser interactions go through the `patent_research` tool, which creates a Browserbase +session per call, drives the portal with a Stagehand agent configured to use `openai/gpt-4o`, +and returns structured JSON with the extracted data and a session replay URL. + +## Benchmark: PageRank (Stanford / Google) + +**Query**: `"PageRank web search ranking algorithm — Stanford University / Google, seed patent US6285999"` + +- Seed patent: US6285999B1 (filed Jan 9, 1998 — Lawrence Page, Stanford University assignee) +- Licensed exclusively to Google; multiple US continuations filed through the 2000s +- EPO equivalent: EP1062579; also filed in Canada, Japan, and Australia +- Went through USPTO ex parte reexamination (reexam cert issued 2011) + +Well-known to software engineers, publicly well-documented, and a clean example of a +university-originated patent licensed to a commercial entity with a traceable family tree. + +Expected output: + +```markdown +# Patent Landscape Memo: PageRank (Stanford / Google) + +## Executive Summary +- US6285999 is the anchor; Stanford filed ~6 US continuations, all assigned to Google + via exclusive license executed in 1998. +- EPO EP1062579 granted; CA, JP, AU national phase entries confirmed. +- No active PTAB proceedings; ex parte reexamination closed 2011 with amended claims. +- Patent expired Jan 9, 2018 (20-year term from priority date) — no remaining FTO risk + on the core PageRank claims. Continuation US7058628 expired 2019. +- Inventor network: Lawrence Page and Sergey Brin; subsequent Stanford/Google filing + activity visible via inventor search. + +## Landscape Overview +... +``` + +Typical run stats: ~14 `patent_research` calls, 6 subagent invocations, ~30 min total runtime, +~150k input tokens. + +## Notes + +- All portals accessed are public (no login required). USPTO PTAB, Patent Center, and Assignment + Search, EPO Espacenet and Register, and WIPO Patentscope are fully public. +- Browserbase Agent Identity handles browser fingerprinting and CAPTCHAs automatically. +- `previous_session_id` in `patent_research` allows a subagent to issue follow-up queries on + the same portal page without starting a new session (e.g., paginating through search results). +- Workpapers in `./reports/` are plain markdown. The directory is gitignored; commit selectively + if you want to version specific memos. diff --git a/examples/integrations/langchain/patent-landscape-agent/agent.py b/examples/integrations/langchain/patent-landscape-agent/agent.py new file mode 100644 index 0000000..5c947ee --- /dev/null +++ b/examples/integrations/langchain/patent-landscape-agent/agent.py @@ -0,0 +1,177 @@ +from __future__ import annotations + +import argparse +import json +import os +import sys +import uuid +from typing import Any + +from deepagents import FilesystemPermission, create_deep_agent +from dotenv import load_dotenv +from langchain_openai import ChatOpenAI +from langgraph.checkpoint.memory import MemorySaver + +from subagents import ( + ASSIGNMENT_OWNERSHIP, + GRANTED_PATENTS, + INVENTOR_NETWORK, + LITIGATION_HISTORY, + PATENT_FAMILY_ANALYSIS, + PROSECUTION_HISTORY, +) +from tools import patent_research + + +SYSTEM_PROMPT = """You are a patent landscape research orchestrator. + +Given a technology area or assignee name (and optionally a seed patent number), +produce a structured patent landscape memo in three phases. + +Start by writing ./reports/research-plan.md with your todo list for this run. + +Phase 1 — fan out all five specialist subagents in parallel: +- granted-patents: search USPTO, EPO Espacenet, and WIPO Patentscope for relevant patents. +- prosecution-history: pull file wrapper data for top patents from USPTO Patent Center. +- assignment-ownership: trace assignment chains via USPTO Patent Assignment and EPO Register. +- litigation-history: search PTAB for IPR/PGR proceedings and outcomes. +- inventor-network: map inventors across their full portfolios and current affiliations. + +Each subagent writes its workpaper to ./reports/.md. + +Phase 2 — per-family deep dives: +- Read the granted-patents workpaper to identify the top 3–5 high-priority patent families. +- For each family, delegate to the patent-family-analysis subagent to walk the full family tree + (continuations, divisionals, foreign equivalents, PCT national phase entries). +- Each analysis is written to ./reports/family-.md. + +Phase 3 — synthesis: +- Read all workpapers from ./reports/ using read_file. +- Cross-reference ownership (assignment-ownership) with litigation risk (litigation-history). +- Surface freedom-to-operate flags based on lapsed or un-entered foreign equivalents. +- Write the final memo to ./reports/final-memo.md with the structure below. + +Final memo structure (./reports/final-memo.md): +1. Executive Summary (3–5 bullet points: landscape overview, top risks, FTO flags) +2. Landscape Overview — one section per Phase 1 track with key findings +3. Per-Family Deep Dives — one subsection per family with the family tree +4. Ownership & Litigation Cross-Reference — table of patents × PTAB proceedings × current owner +5. Freedom-to-Operate Flags — jurisdictions with lapsed or unprotected coverage +6. Sources Appendix — all Browserbase session replay URLs from patent_research calls +""" + + +def _require_env(name: str) -> str: + value = os.getenv(name, "").strip() + if not value: + raise ValueError(f"Missing required environment variable: {name}") + return value + + +def build_model(model: str) -> ChatOpenAI: + # OpenAI is the single model provider — no gateway, no fallback. + return ChatOpenAI( + model=model, + api_key=_require_env("OPENAI_API_KEY"), + ) + + +def build_agent(model: str): + os.makedirs("./reports", exist_ok=True) + return create_deep_agent( + model=build_model(model), + tools=[patent_research], + subagents=[ + GRANTED_PATENTS, + PROSECUTION_HISTORY, + ASSIGNMENT_OWNERSHIP, + LITIGATION_HISTORY, + INVENTOR_NETWORK, + PATENT_FAMILY_ANALYSIS, + ], + system_prompt=SYSTEM_PROMPT, + permissions=[FilesystemPermission(operations=["read", "write"], paths=[os.path.abspath("./reports")])], + checkpointer=MemorySaver(), + ) + + +def _stringify_content(content: Any) -> str: + if isinstance(content, str): + return content + if isinstance(content, list): + parts = [] + for item in content: + if isinstance(item, str): + parts.append(item) + elif isinstance(item, dict): + if item.get("type") == "text": + parts.append(str(item.get("text", ""))) + else: + parts.append(json.dumps(item, default=str)) + else: + parts.append(str(item)) + return "\n".join(part for part in parts if part) + return json.dumps(content, indent=2, default=str) + + +def _final_text(result: Any) -> str: + state = getattr(result, "value", result) + if isinstance(state, dict): + messages = state.get("messages", []) + for message in reversed(messages): + msg_type = getattr(message, "type", None) + if msg_type is None and isinstance(message, dict): + msg_type = message.get("type") or message.get("role") + if msg_type in {"ai", "assistant"}: + content = getattr(message, "content", None) + if content is None and isinstance(message, dict): + content = message.get("content") + return _stringify_content(content) + return json.dumps(state, indent=2, default=str) + return str(state) + + +def run(query: str, model: str) -> str: + agent = build_agent(model=model) + config = {"configurable": {"thread_id": str(uuid.uuid4())}} + result = agent.invoke( + {"messages": [{"role": "user", "content": query}]}, + config=config, + version="v2", + ) + memo = _final_text(result) + memo_path = os.path.join(os.path.abspath("./reports"), "final-memo.md") + with open(memo_path, "w", encoding="utf-8") as f: + f.write(memo) + print(f"Memo saved to {memo_path}", file=sys.stderr) + return memo + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser( + description=( + "Patent landscape research agent powered by LangChain Deep Agents, " + "Stagehand, and Browserbase. Writes a structured memo to ./reports/final-memo.md." + ) + ) + parser.add_argument( + "query", + nargs="?", + default=( + "PageRank web search ranking algorithm — Stanford University / Google, " + "seed patent US6285999" + ), + help="Technology area, assignee name, or seed patent number to research.", + ) + parser.add_argument( + "--model", + default=os.getenv("PATENT_AGENT_MODEL", "gpt-4.1"), + help="OpenAI model for the orchestrator (default: gpt-4.1).", + ) + return parser.parse_args() + + +if __name__ == "__main__": + load_dotenv() + args = parse_args() + print(run(query=args.query, model=args.model)) diff --git a/examples/integrations/langchain/patent-landscape-agent/requirements.txt b/examples/integrations/langchain/patent-landscape-agent/requirements.txt new file mode 100644 index 0000000..0a9bb1a --- /dev/null +++ b/examples/integrations/langchain/patent-landscape-agent/requirements.txt @@ -0,0 +1,6 @@ +beautifulsoup4>=4.13.0 +browserbase>=1.8.0 +deepagents>=0.0.5 +langchain-openai>=0.3.0 +python-dotenv>=1.0.0 +stagehand>=3.19.5 diff --git a/examples/integrations/langchain/patent-landscape-agent/subagents/__init__.py b/examples/integrations/langchain/patent-landscape-agent/subagents/__init__.py new file mode 100644 index 0000000..10a9900 --- /dev/null +++ b/examples/integrations/langchain/patent-landscape-agent/subagents/__init__.py @@ -0,0 +1,15 @@ +from subagents.granted_patents import GRANTED_PATENTS +from subagents.prosecution_history import PROSECUTION_HISTORY +from subagents.assignment_ownership import ASSIGNMENT_OWNERSHIP +from subagents.litigation_history import LITIGATION_HISTORY +from subagents.inventor_network import INVENTOR_NETWORK +from subagents.patent_family_analysis import PATENT_FAMILY_ANALYSIS + +__all__ = [ + "GRANTED_PATENTS", + "PROSECUTION_HISTORY", + "ASSIGNMENT_OWNERSHIP", + "LITIGATION_HISTORY", + "INVENTOR_NETWORK", + "PATENT_FAMILY_ANALYSIS", +] diff --git a/examples/integrations/langchain/patent-landscape-agent/subagents/assignment_ownership.py b/examples/integrations/langchain/patent-landscape-agent/subagents/assignment_ownership.py new file mode 100644 index 0000000..5753a6e --- /dev/null +++ b/examples/integrations/langchain/patent-landscape-agent/subagents/assignment_ownership.py @@ -0,0 +1,38 @@ +from tools import patent_research + +ASSIGNMENT_OWNERSHIP = { + "name": "assignment-ownership", + "description": ( + "Traces assignment chains and ownership changes for the top patents via " + "USPTO Patent Assignment Search and EPO Register. Identifies current owner " + "and any recorded security interests or licenses." + ), + "system_prompt": """You are a patent ownership specialist. + +You will receive a list of patent numbers from the granted-patents track. +Trace the full assignment chain for each patent. + +Steps: + +1. USPTO Patent Assignment Search (portal: uspto_assignments): + For each US patent number, extract: + - All recorded assignments in chronological order + - Assignor name and date + - Assignee name and date + - Reel/frame number + - Nature of conveyance (assignment, security interest, merger, license, etc.) + - Current owner of record + +2. EPO Register (portal: epo_register): + For each EP patent number, extract: + - Current proprietor + - Assignment history if recorded + - Any recorded licences or security interests + +Write your structured findings to ./reports/assignment-ownership.md. +Flag any security interests (pledges, mortgages) that encumber the patents. +Flag any assignments to shell companies or holding entities. +Include session_url for each research session. +""", + "tools": [patent_research], +} diff --git a/examples/integrations/langchain/patent-landscape-agent/subagents/granted_patents.py b/examples/integrations/langchain/patent-landscape-agent/subagents/granted_patents.py new file mode 100644 index 0000000..1b53be4 --- /dev/null +++ b/examples/integrations/langchain/patent-landscape-agent/subagents/granted_patents.py @@ -0,0 +1,50 @@ +from tools import patent_research + +GRANTED_PATENTS = { + "name": "granted-patents", + "description": ( + "Searches USPTO Patent Public Search, EPO Espacenet, and WIPO Patentscope for " + "granted patents and published applications matching the technology area or assignee. " + "Returns patent numbers, titles, filing/grant dates, current status, and claim 1 text." + ), + "system_prompt": """You are a patent search specialist covering USPTO, EPO, and WIPO. + +Your task: find all granted patents and published applications relevant to the given technology area or assignee name. + +Steps: + +1. USPTO Patent Public Search (portal: uspto_search): + Search by assignee name or keyword. Extract for each result: + - Patent number (e.g., US8697359B2) + - Title + - Filing date + - Grant date + - Current status (granted, abandoned, pending) + - Assignee + - Claim 1 full text + - Application number + +2. EPO Espacenet (portal: epo_espacenet): + Search by assignee or keyword. Extract: + - Patent number (EP or WO) + - Title + - Filing date + - Grant date + - Designated states + - Claim 1 text + +3. WIPO Patentscope (portal: wipo_patentscope): + Search PCT applications. Extract: + - International application number + - Filing date + - International publication number + - Title + - Applicant + - Entering national phase countries + +Write your structured findings to ./reports/granted-patents.md. +Include the session_url from each patent_research call for audit purposes. +Identify the top 3-5 highest-priority patent families based on claim breadth and filing dates. +""", + "tools": [patent_research], +} diff --git a/examples/integrations/langchain/patent-landscape-agent/subagents/inventor_network.py b/examples/integrations/langchain/patent-landscape-agent/subagents/inventor_network.py new file mode 100644 index 0000000..2b6a1cc --- /dev/null +++ b/examples/integrations/langchain/patent-landscape-agent/subagents/inventor_network.py @@ -0,0 +1,40 @@ +from tools import patent_research + +INVENTOR_NETWORK = { + "name": "inventor-network", + "description": ( + "Extracts the inventor list from the top patents, surfaces their other patents " + "across USPTO and EPO, and identifies their current institutional affiliations." + ), + "system_prompt": """You are an inventor network analyst. + +You will receive a list of patent numbers from the granted-patents track. +For each patent, extract the inventor list, then map each inventor's broader portfolio. + +Steps: + +1. Extract inventors (portal: uspto_search or epo_espacenet): + For each patent, record: + - Full inventor name + - City and country of residence at time of filing + +2. Per inventor — search their full patent portfolio (portal: uspto_search): + Search by inventor name. Extract: + - All US patent numbers where they are listed as inventor + - Assignee for each patent (shows employer history) + - Filing dates (shows career timeline) + +3. Per inventor — cross-check EPO (portal: epo_espacenet): + Search by inventor name. Extract any EP patents not found in USPTO search. + +4. Current affiliation inference: + Based on the assignee of their most recent patents (last 2 years), + infer current institutional affiliation. Note if they have moved to a competitor. + +Write your structured findings to ./reports/inventor-network.md. +Flag inventors who have recently moved to direct competitors. +Flag inventors with pending patent applications at a new employer in the same technology area. +Include session_url for each research session. +""", + "tools": [patent_research], +} diff --git a/examples/integrations/langchain/patent-landscape-agent/subagents/litigation_history.py b/examples/integrations/langchain/patent-landscape-agent/subagents/litigation_history.py new file mode 100644 index 0000000..29a558b --- /dev/null +++ b/examples/integrations/langchain/patent-landscape-agent/subagents/litigation_history.py @@ -0,0 +1,42 @@ +from tools import patent_research + +LITIGATION_HISTORY = { + "name": "litigation-history", + "description": ( + "Searches USPTO PTAB for IPR and PGR proceedings against the top patents. " + "Identifies which patents have been challenged, the petitioner, and the outcome." + ), + "system_prompt": """You are a patent litigation specialist focused on PTAB proceedings. + +You will receive a list of patent numbers from the granted-patents track. +For each patent, search the USPTO Patent Trial and Appeal Board (PTAB) database. + +Primary portal: uspto_ptab +Fallback portal: google_patents (use if PTAB portal is unavailable or returns no results) + +For each patent, extract all IPR, PGR, CBM, and ex parte reexamination proceedings: +- Proceeding number (e.g., IPR2023-00123) +- Proceeding type (IPR, PGR, CBM, ex parte reexamination) +- Filing date +- Petitioner name +- Institution decision: date and outcome (instituted / denied) +- Final written decision: date and outcome (claims cancelled / confirmed / mixed) +- Whether an appeal was filed (Federal Circuit or Supreme Court) +- Current status + +Also note: +- Whether any claims were cancelled as a result +- Which claims survived if the proceeding went to final written decision +- Settlement agreements if recorded + +If the PTAB portal is inaccessible or returns a blank page, switch to google_patents and +search for the patent number. Google Patents displays PTAB proceedings under the "Events" +tab — extract the same fields from there. + +Write your structured findings to ./reports/litigation-history.md. +Flag patents with cancelled claims or pending PTAB challenges as high-risk. +If both sources were unavailable, state that explicitly with the portals attempted. +Include session_url for each research session. +""", + "tools": [patent_research], +} diff --git a/examples/integrations/langchain/patent-landscape-agent/subagents/patent_family_analysis.py b/examples/integrations/langchain/patent-landscape-agent/subagents/patent_family_analysis.py new file mode 100644 index 0000000..78a4cbc --- /dev/null +++ b/examples/integrations/langchain/patent-landscape-agent/subagents/patent_family_analysis.py @@ -0,0 +1,46 @@ +from tools import patent_research + +PATENT_FAMILY_ANALYSIS = { + "name": "patent-family-analysis", + "description": ( + "Walks the full patent family tree for a single high-priority patent: parent, " + "continuations, divisionals, and foreign equivalents. Called once per high-priority " + "family identified in Phase 1." + ), + "system_prompt": """You are a patent family analyst. + +You will receive a single patent number representing a high-priority family anchor. +Walk the full family tree for this patent across all jurisdictions. + +Steps: + +1. USPTO continuations and divisionals (portal: uspto_patent_center): + Starting from the given patent number: + - Find the priority chain: parent application, grandparent, etc. + - Find all child applications: continuations (CON), continuations-in-part (CIP), divisionals (DIV) + - For each, record: application number, patent number (if granted), filing date, status, title + +2. Foreign equivalents via EPO Espacenet (portal: epo_espacenet): + Search the INPADOC family for the anchor patent. Extract: + - All EP, WO, GB, DE, FR, JP, CN, KR, AU, CA equivalents + - Filing date and grant date in each jurisdiction + - Current status in each jurisdiction + - Which foreign equivalents have lapsed + +3. WIPO PCT application (portal: wipo_patentscope): + If the family has a PCT application, extract: + - International application number (PCT/...) + - International search report findings + - Countries that entered national phase + - Countries that did not enter national phase (possible freedom-to-operate gaps) + +Write your structured findings to ./reports/family-.md, substituting +the actual patent number into the filename. + +Produce a family tree diagram in ASCII or nested markdown list format. +Flag jurisdictions where the patent has lapsed or never entered national phase — +these represent potential freedom-to-operate opportunities. +Include session_url for each research session. +""", + "tools": [patent_research], +} diff --git a/examples/integrations/langchain/patent-landscape-agent/subagents/prosecution_history.py b/examples/integrations/langchain/patent-landscape-agent/subagents/prosecution_history.py new file mode 100644 index 0000000..bf1fe28 --- /dev/null +++ b/examples/integrations/langchain/patent-landscape-agent/subagents/prosecution_history.py @@ -0,0 +1,36 @@ +from tools import patent_research + +PROSECUTION_HISTORY = { + "name": "prosecution-history", + "description": ( + "Pulls file wrapper data from USPTO Patent Center for the top patents identified by " + "the granted-patents track. Extracts office actions, examiner responses, RCEs, " + "and continuation status." + ), + "system_prompt": """You are a patent prosecution specialist. + +You will receive a list of patent numbers from the granted-patents track. +For each patent, retrieve the prosecution history from USPTO Patent Center. + +Primary portal: uspto_patent_center +Fallback portal: google_patents (use if Patent Center is unavailable or returns no results) + +For each patent number, extract: +- All office actions: date, type (restriction, non-final rejection, final rejection, allowance), grounds cited +- Applicant responses: date, type (RCE, amendment, appeal, interview) +- Examiner: name and art unit +- Total pendency (filing to grant) +- Whether a continuation, continuation-in-part, or divisional was filed +- Whether any claims were cancelled or narrowed during prosecution + +If Patent Center is inaccessible, switch to google_patents and search for the patent number. +Google Patents displays the prosecution timeline under the "Events" tab — extract dates and +event types from there as a best-effort substitute for the full file wrapper. + +Write your structured findings to ./reports/prosecution-history.md. +Flag patents where prosecution history suggests claim narrowing that limits scope. +If both sources were unavailable, state that explicitly with the portals attempted. +Include session_url for each research session. +""", + "tools": [patent_research], +} diff --git a/examples/integrations/langchain/patent-landscape-agent/tools/__init__.py b/examples/integrations/langchain/patent-landscape-agent/tools/__init__.py new file mode 100644 index 0000000..97f08ad --- /dev/null +++ b/examples/integrations/langchain/patent-landscape-agent/tools/__init__.py @@ -0,0 +1,3 @@ +from tools.patent_research import patent_research + +__all__ = ["patent_research"] diff --git a/examples/integrations/langchain/patent-landscape-agent/tools/patent_research.py b/examples/integrations/langchain/patent-landscape-agent/tools/patent_research.py new file mode 100644 index 0000000..795bb91 --- /dev/null +++ b/examples/integrations/langchain/patent-landscape-agent/tools/patent_research.py @@ -0,0 +1,172 @@ +from __future__ import annotations + +import asyncio +import json +import os +from typing import Any + +from browserbase import Browserbase +from langchain.tools import tool +from stagehand import AsyncStagehand + +# OpenAI is the single model provider for both Stagehand act/extract and agent execution. +# "openai/gpt-4.1" follows the Stagehand provider/model naming convention. +STAGEHAND_MODEL = os.getenv("STAGEHAND_MODEL", "openai/gpt-4o") + +PORTAL_URLS: dict[str, str] = { + "uspto_search": "https://ppubs.uspto.gov/pubwebapp/", + "uspto_patent_center": "https://patentcenter.uspto.gov/", + "uspto_assignments": "https://assignment.uspto.gov/patent/index.html#/patent/search", + "uspto_ptab": "https://ptab.uspto.gov/", + "epo_espacenet": "https://worldwide.espacenet.com/", + "epo_register": "https://register.epo.org/", + "wipo_patentscope": "https://patentscope.wipo.int/search/en/search.jsf", + # Fallback for PTAB proceedings and prosecution history when USPTO portals are unavailable. + "google_patents": "https://patents.google.com/", +} + + +def _require_env(name: str) -> str: + value = os.getenv(name, "").strip() + if not value: + raise ValueError(f"Missing required environment variable: {name}") + return value + + +def _normalize(value: Any) -> Any: + if value is None or isinstance(value, (str, int, float, bool)): + return value + if isinstance(value, dict): + return {str(key): _normalize(val) for key, val in value.items()} + if isinstance(value, (list, tuple, set)): + return [_normalize(item) for item in value] + if hasattr(value, "model_dump"): + return _normalize(value.model_dump()) + if hasattr(value, "dict"): + return _normalize(value.dict()) + if hasattr(value, "__dict__"): + public = { + key: val + for key, val in vars(value).items() + if not key.startswith("_") and not callable(val) + } + if public: + return _normalize(public) + return str(value) + + +def _json(value: Any) -> str: + return json.dumps(_normalize(value), indent=2, default=str) + + +def _stagehand_client() -> AsyncStagehand: + # model_api_key must be passed explicitly — Stagehand does not read it from env. + kwargs: dict = { + "browserbase_api_key": _require_env("BROWSERBASE_API_KEY"), + "model_api_key": _require_env("OPENAI_API_KEY"), + } + project_id = os.getenv("BROWSERBASE_PROJECT_ID", "").strip() + if project_id: + kwargs["browserbase_project_id"] = project_id + return AsyncStagehand(**kwargs) + + +def _run_async(coro: Any) -> Any: + return asyncio.run(coro) + + +@tool +def patent_research( + portal: str, + query: str, + output_schema: str, + previous_session_id: str = "", +) -> str: + """Research patents on a specific public portal using a Stagehand browser agent. + + Args: + portal: Which portal to query. One of: uspto_search, uspto_patent_center, + uspto_assignments, uspto_ptab, epo_espacenet, epo_register, wipo_patentscope. + query: Natural-language description of what to find and extract. + output_schema: JSON object describing the fields to extract (e.g. + '{"patent_number": "string", "title": "string", "status": "string"}'). + previous_session_id: If set, attach to this existing Browserbase session instead + of starting a new one (useful for follow-up queries on the same portal page). + Leave empty to start a fresh session. + + Returns: + JSON with keys: portal, session_id, session_url (Browserbase replay link), + query, result (extracted structured data). + """ + return _run_async( + _patent_research_async( + portal=portal, + query=query, + output_schema=output_schema, + previous_session_id=previous_session_id or None, + ) + ) + + +async def _patent_research_async( + portal: str, + query: str, + output_schema: str, + previous_session_id: str | None, +) -> str: + if portal not in PORTAL_URLS: + return _json({ + "error": f"Unknown portal '{portal}'. Valid values: {list(PORTAL_URLS)}", + }) + + client = _stagehand_client() + new_session = previous_session_id is None + + if new_session: + start_resp = await client.sessions.start(model_name=STAGEHAND_MODEL) + session_id = start_resp.data.session_id + else: + session_id = previous_session_id + + instruction = ( + f"{query}\n\n" + f"Extract a JSON object matching this schema: {output_schema}" + ) + + try: + if new_session: + await client.sessions.navigate( + id=session_id, + url=PORTAL_URLS[portal], + frame_id="", + ) + + result = await client.sessions.execute( + id=session_id, + execute_options={ + "instruction": instruction, + "max_steps": 30, + }, + agent_config={ + # OpenAI is the single model provider — same key, same model throughout. + "model": STAGEHAND_MODEL, + "instructions": ( + "You are a patent research assistant performing read-only lookups " + "on public patent databases. Extract all requested fields precisely. " + "Do not submit forms that could alter data. Stop once the lookup is complete." + ), + }, + timeout=300.0, + ) + data = _normalize(result) + return _json({ + "portal": portal, + "session_id": session_id, + "session_url": f"https://browserbase.com/sessions/{session_id}", + "query": query, + "result": data, + }) + finally: + # Only end sessions we started; reused sessions are the caller's responsibility. + if new_session: + await client.sessions.end(id=session_id) diff --git a/examples/integrations/langchain/stagehand/README.md b/examples/integrations/langchain/stagehand/README.md new file mode 100644 index 0000000..41d8014 --- /dev/null +++ b/examples/integrations/langchain/stagehand/README.md @@ -0,0 +1,34 @@ +# Langchain JS + +## Integrate Stagehand with Langchain JS + +Stagehand can be integrated into Langchain JS by wrapping Stagehand's browser automation functionality with the StagehandToolkit. + +This toolkit provides specialized tools such as navigate, act, extract, and observe, all powered by Stagehand's underlying capabilities. + +For more details on this integration and how to work with Langchain, see the official Langchain documentation. + +## Use the tools + +- **stagehand_navigate**: Navigate to a specific URL. +- **stagehand_act**: Perform browser automation tasks like clicking buttons and typing in fields. +- **stagehand_extract**: Extract structured data from pages using Zod schemas. +- **stagehand_observe**: Investigate the DOM for possible actions or relevant elements. + +## Remote Browsers (Browserbase) + +Instead of `env: "LOCAL"`, specify `env: "BROWSERBASE"` and pass in your Browserbase credentials through environment variables: +- `BROWSERBASE_API_KEY` +- `BROWSERBASE_PROJECT_ID` + +## Using LangGraph Agents + +The StagehandToolkit can also be plugged into LangGraph's existing agent system. This lets you orchestrate more complex flows by combining Stagehand's tools with other Langchain tools. + +With the StagehandToolkit, you can quickly integrate natural-language-driven browser automation into workflows supported by Langchain. This enables use cases such as: + +- Searching, extracting, and summarizing data from websites +- Automating login flows +- Navigating or clicking through forms based on instructions from a larger chain of agents + +Consult Stagehand's and Langchain's official references for troubleshooting and advanced integrations or reach out to us on [Slack](https://stagehand.dev/slack). \ No newline at end of file diff --git a/examples/integrations/langchain/stagehand/package-lock.json b/examples/integrations/langchain/stagehand/package-lock.json new file mode 100644 index 0000000..c0dad62 --- /dev/null +++ b/examples/integrations/langchain/stagehand/package-lock.json @@ -0,0 +1,3193 @@ +{ + "name": "langchain-stagehand", + "version": "1.0.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "langchain-stagehand", + "version": "1.0.0", + "license": "ISC", + "dependencies": { + "@browserbasehq/stagehand": "^2.4.4", + "@langchain/community": "^0.3.44", + 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--- /dev/null +++ b/examples/integrations/langchain/stagehand/package.json @@ -0,0 +1,19 @@ +{ + "name": "langchain-stagehand", + "version": "1.0.0", + "description": "", + "main": "index.js", + "scripts": { + "test": "echo \"Error: no test specified\" && exit 1" + }, + "keywords": [], + "author": "", + "license": "ISC", + "type": "commonjs", + "dependencies": { + "@browserbasehq/stagehand": "^2.4.4", + "@langchain/community": "^0.3.44", + "@langchain/core": "^0.3.57", + "@langchain/langgraph": "^0.2.73" + } +} diff --git a/examples/integrations/langchain/stagehand/src/index.js b/examples/integrations/langchain/stagehand/src/index.js new file mode 100644 index 0000000..4ba9c95 --- /dev/null +++ b/examples/integrations/langchain/stagehand/src/index.js @@ -0,0 +1,38 @@ +import { Stagehand } from '@browserbasehq/stagehand'; +import { StagehandToolkit } from '@stagehand/langchain'; + +const stagehand = new Stagehand({ + env: 'LOCAL', + verbose: 2, + enableCaching: false, +}); + +const stagehandToolkit = await StagehandToolkit.fromStagehand(stagehand); + +// Find the relevant tool +const navigateTool = stagehandToolkit.tools.find( + t => t.name === 'stagehand_navigate' +); + +// Invoke it +await navigateTool.invoke('https://www.google.com'); + +// Suppose you want to act on the page +const actionTool = stagehandToolkit.tools.find(t => t.name === 'stagehand_act'); + +await actionTool.invoke('Search for "OpenAI"'); + +// Observe the current page +const observeTool = stagehandToolkit.tools.find( + t => t.name === 'stagehand_observe' +); + +const result = await observeTool.invoke( + 'What actions can be performed on the current page?' +); + +console.log(JSON.parse(result)); + +// Verification +const currentUrl = stagehand.page.url(); +console.log('Current URL:', currentUrl); diff --git a/examples/integrations/mastra/.gitignore b/examples/integrations/mastra/.gitignore new file mode 100644 index 0000000..4aeadbc --- /dev/null +++ b/examples/integrations/mastra/.gitignore @@ -0,0 +1,9 @@ +output.txt +node_modules +dist +.mastra +.env.development +.env +*.db + +memory* \ No newline at end of file diff --git a/examples/integrations/mastra/README.md b/examples/integrations/mastra/README.md new file mode 100644 index 0000000..4107138 --- /dev/null +++ b/examples/integrations/mastra/README.md @@ -0,0 +1,92 @@ +# Stagehand & Mastra Integration + +A powerful integration that combines the capabilities of [Browserbase's Stagehand](https:/stagehand.dev) with [Mastra](https://mastra.ai/) for advanced web automation, scraping, and AI-powered web interactions. + +## Overview + +This project enables AI agents to interact with web pages through the Mastra framework using Stagehand's browser automation capabilities. It provides tools for web navigation, element observation, data extraction, and action execution, all orchestrated through Mastra's agent system. + +## Features + +- **Web Navigation**: Navigate to websites programmatically +- **Element Observation**: Identify and locate elements on web pages +- **Action Execution**: Perform actions like clicking buttons or filling forms +- **Data Extraction**: Extract structured data from web pages +- **Session Management**: Smart session handling with automatic timeouts and reconnection +- **AI-Powered Interactions**: Leverage OpenAI models for intelligent web interactions + +## Installation + +### Prerequisites + +- Node.js (v18+) +- npm or yarn +- Browserbase account +- OpenAI API access + +### Setup + +1. Clone the repository: + ``` + npx degit browserbase/integrations/examples/integrations/mastra browserbase-mastra + cd browserbase-mastra + ``` + +2. Install dependencies: + ``` + npm install + ``` + +3. Create a `.env` file with your API keys: + ``` + BROWSERBASE_PROJECT_ID=your_project_id + BROWSERBASE_API_KEY=your_api_key + OPENAI_API_KEY=your_openai_key + ``` + +## Usage + +### Running the development server + +``` +npm run dev +``` + +This will start the Mastra development server, giving you access to the integrated web agent. + +## Architecture + +### Core Components + +1. **Stagehand Session Manager** + - Handles browser session initialization and management + - Implements automatic session timeouts + - Provides error recovery and reconnection logic + +2. **Mastra Tools** + - `stagehandActTool`: Performs actions on web pages + - `stagehandObserveTool`: Identifies elements on web pages + - `stagehandExtractTool`: Extracts data from web pages + - `stagehandNavigateTool` : Navigates to given URLs + +3. **Web Agent** + - AI-powered agent using OpenAI's GPT-4o + - Provides natural language interface to web automation + - Integrates all tools into a unified experience + +### Flow Diagram + +``` +User Query → Mastra Agent → Stagehand Tools → Browser Interaction → Web Page → Data/Results → Agent Response +``` + +## Configuration + +The project can be configured through the `.env` file and by modifying the agent instructions in `src/mastra/agents/index.ts`. + +## Credits + +This project is built with: +- [Mastra](https://mastra.ai) - AI Agent framework +- [Stagehand by Browserbase](https:/stagehand.dev) - Browser automation +- [OpenAI](https://openai.com/) - AI models \ No newline at end of file diff --git a/examples/integrations/mastra/package-lock.json b/examples/integrations/mastra/package-lock.json new file mode 100644 index 0000000..d5bea2b --- /dev/null +++ b/examples/integrations/mastra/package-lock.json @@ -0,0 +1,12188 @@ +{ + "name": "stagehand-mastra", + "version": "1.0.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "stagehand-mastra", + "version": "1.0.0", + "license": "ISC", + "dependencies": { + "@ai-sdk/openai": 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a/examples/integrations/mastra/package.json b/examples/integrations/mastra/package.json new file mode 100644 index 0000000..ff77669 --- /dev/null +++ b/examples/integrations/mastra/package.json @@ -0,0 +1,28 @@ +{ + "name": "stagehand-mastra", + "version": "1.0.0", + "description": "A use Stagehand tools with Mastra", + "main": "index.js", + "scripts": { + "test": "echo \"Error: no test specified\" && exit 1", + "dev": "mastra dev" + }, + "keywords": [], + "author": "", + "license": "ISC", + "type": "module", + "dependencies": { + "@ai-sdk/openai": "^1.3.7", + "@browserbasehq/stagehand": "^3.2.0", + "@mastra/core": "^0.20.2", + "@mastra/loggers": "^0.10.15", + "@mastra/memory": "^0.15.6", + "mastra": "^0.15.1", + "zod": "^3.24.2" + }, + "devDependencies": { + "@types/node": "^22.14.0", + "tsx": "^4.19.3", + "typescript": "^5.8.3" + } +} diff --git a/examples/integrations/mastra/src/mastra/agents/index.ts b/examples/integrations/mastra/src/mastra/agents/index.ts new file mode 100644 index 0000000..16d5ec7 --- /dev/null +++ b/examples/integrations/mastra/src/mastra/agents/index.ts @@ -0,0 +1,27 @@ +import { openai } from '@ai-sdk/openai'; +import { Agent } from '@mastra/core/agent'; +import { stagehandActTool, stagehandObserveTool, stagehandExtractTool, stagehandNavigateTool } from '../tools'; + +export const webAgent = new Agent({ + name: 'Web Assistant', + instructions: ` + You are a helpful web assistant that can navigate websites and extract information. + + Your primary functions are: + - Navigate to websites + - Observe elements on webpages + - Perform actions like clicking buttons or filling forms + - Extract data from webpages + + When responding: + - Ask for a specific URL if none is provided + - Be specific about what actions to perform + - When extracting data, be clear about what information you need + + Use the stagehandActTool to perform actions on webpages. + Use the stagehandObserveTool to find elements on webpages. + Use the stagehandExtractTool to extract data from webpages. +`, + model: openai('gpt-4o'), + tools: { stagehandActTool, stagehandObserveTool, stagehandExtractTool, stagehandNavigateTool }, +}); diff --git a/examples/integrations/mastra/src/mastra/index.ts b/examples/integrations/mastra/src/mastra/index.ts new file mode 100644 index 0000000..2e61710 --- /dev/null +++ b/examples/integrations/mastra/src/mastra/index.ts @@ -0,0 +1,11 @@ +import { Mastra } from '@mastra/core/mastra'; +import { PinoLogger } from '@mastra/loggers'; +import { webAgent } from './agents'; + +export const mastra = new Mastra({ + agents: { webAgent }, + logger: new PinoLogger({ + name: 'Mastra', + level: 'info', + }), +}); diff --git a/examples/integrations/mastra/src/mastra/tools/index.ts b/examples/integrations/mastra/src/mastra/tools/index.ts new file mode 100644 index 0000000..03e8811 --- /dev/null +++ b/examples/integrations/mastra/src/mastra/tools/index.ts @@ -0,0 +1,333 @@ +import { createTool } from '@mastra/core/tools'; +import { z } from 'zod'; +import { Stagehand } from "@browserbasehq/stagehand"; + +class StagehandSessionManager { + private static instance: StagehandSessionManager; + private stagehand: Stagehand | null = null; + private initialized = false; + private lastUsed = Date.now(); + private readonly sessionTimeout = 10 * 60 * 1000; // 10 minutes + + private constructor() { + // Schedule session cleanup to prevent memory leaks + setInterval(() => this.checkAndCleanupSession(), 60 * 1000); + } + + /** + * Get the singleton instance of StagehandSessionManager + */ + public static getInstance(): StagehandSessionManager { + if (!StagehandSessionManager.instance) { + StagehandSessionManager.instance = new StagehandSessionManager(); + } + return StagehandSessionManager.instance; + } + + /** + * Ensure Stagehand is initialized and return the instance + */ + public async ensureStagehand(): Promise { + this.lastUsed = Date.now(); + + try { + // Initialize if not already initialized + if (!this.stagehand || !this.initialized) { + console.log('Creating new Stagehand instance'); + this.stagehand = new Stagehand({ + apiKey: process.env.BROWSERBASE_API_KEY!, + projectId: process.env.BROWSERBASE_PROJECT_ID!, + env: "BROWSERBASE", + }); + + try { + console.log('Initializing Stagehand...'); + await this.stagehand.init(); + console.log('Stagehand initialized successfully'); + this.initialized = true; + return this.stagehand; + } catch (initError) { + console.error('Failed to initialize Stagehand:', initError); + throw initError; + } + } + + try { + const page = this.stagehand.context.pages()[0]; + const title = await page.evaluate(() => document.title); + console.log('Session check successful, page title:', title); + return this.stagehand; + } catch (error) { + // If we get an error indicating the session is invalid, reinitialize + console.error('Session check failed:', error); + if ( + error instanceof Error && + (error.message.includes("Target page, context or browser has been closed") || + error.message.includes("Session expired") || + error.message.includes("context destroyed")) + ) { + console.log("Browser session expired, reinitializing Stagehand..."); + this.stagehand = new Stagehand({ + apiKey: process.env.BROWSERBASE_API_KEY!, + projectId: process.env.BROWSERBASE_PROJECT_ID!, + env: "BROWSERBASE", + }); + await this.stagehand.init(); + this.initialized = true; + return this.stagehand; + } + throw error; // Re-throw if it's a different type of error + } + } catch (error) { + this.initialized = false; + this.stagehand = null; + const errorMsg = error instanceof Error ? error.message : String(error); + throw new Error(`Failed to initialize/reinitialize Stagehand: ${errorMsg}`); + } + } + + /** + * Close the Stagehand session if it's been idle for too long + */ + private async checkAndCleanupSession(): Promise { + if (!this.stagehand || !this.initialized) return; + + const now = Date.now(); + if (now - this.lastUsed > this.sessionTimeout) { + console.log('Cleaning up idle Stagehand session'); + try { + await this.stagehand.close(); + } catch (error) { + console.error(`Error closing idle session: ${error}`); + } + this.stagehand = null; + this.initialized = false; + } + } + + /** + * Manually close the session + */ + public async close(): Promise { + if (this.stagehand) { + try { + await this.stagehand.close(); + } catch (error) { + console.error(`Error closing Stagehand session: ${error}`); + } + this.stagehand = null; + this.initialized = false; + } + } +} + +// Get the singleton instance +const sessionManager = StagehandSessionManager.getInstance(); + +export const stagehandActTool = createTool({ + id: 'web-act', + description: 'Take an action on a webpage using Stagehand', + inputSchema: z.object({ + url: z.string().optional().describe('URL to navigate to (optional if already on a page)'), + action: z.string().describe('Action to perform (e.g., "click sign in button", "type hello in search field")'), + }), + outputSchema: z.object({ + success: z.boolean(), + message: z.string(), + }), + execute: async ({ context }) => { + return await performWebAction(context.url, context.action); + }, +}); + +export const stagehandObserveTool = createTool({ + id: 'web-observe', + description: 'Observe elements on a webpage using Stagehand to plan actions', + inputSchema: z.object({ + url: z.string().optional().describe('URL to navigate to (optional if already on a page)'), + instruction: z.string().describe('What to observe (e.g., "find the sign in button")'), + }), + outputSchema: z.array(z.any()).describe('Array of observable actions'), + execute: async ({ context }) => { + return await performWebObservation(context.url, context.instruction); + }, +}); + +export const stagehandExtractTool = createTool({ + id: 'web-extract', + description: 'Extract data from a webpage using Stagehand', + inputSchema: z.object({ + url: z.string().optional().describe('URL to navigate to (optional if already on a page)'), + instruction: z.string().describe('What to extract (e.g., "extract all product prices")'), + schema: z.record(z.any()).optional().describe('Zod schema definition for data extraction'), + useTextExtract: z.boolean().optional().describe('Set true for larger-scale extractions, false for small extractions'), + }), + outputSchema: z.any().describe('Extracted data according to schema'), + execute: async ({ context }) => { + // Create a default schema if none is provided + const defaultSchema = { + content: z.string() + }; + + return await performWebExtraction( + context.url, + context.instruction, + context.schema || defaultSchema, + context.useTextExtract + ); + }, +}); + +const performWebAction = async (url?: string, action?: string) => { + const stagehand = await sessionManager.ensureStagehand(); + const page = stagehand.context.pages()[0]; + + try { + if (url) { + await page.goto(url); + } + + if (action) { + await stagehand.act(action); + } + + return { + success: true, + message: `Successfully performed: ${action}` + }; + } catch (error: any) { + throw new Error(`Stagehand action failed: ${error.message}`); + } +}; + +const performWebObservation = async (url?: string, instruction?: string) => { + console.log(`Starting observation${url ? ` for ${url}` : ''} with instruction: ${instruction}`); + + try { + const stagehand = await sessionManager.ensureStagehand(); + if (!stagehand) { + console.error('Failed to get Stagehand instance'); + throw new Error('Failed to get Stagehand instance'); + } + + const page = stagehand.context.pages()[0]; + if (!page) { + console.error('Page not available'); + throw new Error('Page not available'); + } + + try { + if (url) { + console.log(`Navigating to ${url}`); + await page.goto(url); + console.log(`Successfully navigated to ${url}`); + } + + if (instruction) { + console.log(`Observing with instruction: ${instruction}`); + try { + const actions = await stagehand.observe(instruction); + console.log(`Observation successful, found ${actions.length} actions`); + return actions; + } catch (observeError) { + console.error('Error during observation:', observeError); + throw observeError; + } + } + + return []; + } catch (pageError) { + console.error('Error in page operation:', pageError); + throw pageError; + } + } catch (error: any) { + const errorMessage = error instanceof Error ? error.message : String(error); + console.error(`Full stack trace for observation error:`, error); + throw new Error(`Stagehand observation failed: ${errorMessage}`); + } +}; + +const performWebExtraction = async ( + url?: string, + instruction?: string, + schemaObj?: Record, + useTextExtract?: boolean +) => { + console.log(`Starting extraction${url ? ` for ${url}` : ''} with instruction: ${instruction}`); + + try { + const stagehand = await sessionManager.ensureStagehand(); + const page = stagehand.context.pages()[0]; + + try { + if (url) { + console.log(`Navigating to ${url}`); + await page.goto(url); + console.log(`Successfully navigated to ${url}`); + } + + if (instruction) { + console.log(`Extracting with instruction: ${instruction}`); + + const finalSchemaObj = schemaObj || { content: z.string() }; + + try { + const schema = z.object(finalSchemaObj); + + const result = await stagehand.extract(instruction, schema); + + console.log(`Extraction successful:`, result); + return result; + } catch (extractError) { + console.error('Error during extraction:', extractError); + throw extractError; + } + } + + return null; + } catch (pageError) { + console.error('Error in page operation:', pageError); + throw pageError; + } + } catch (error: any) { + const errorMessage = error instanceof Error ? error.message : String(error); + console.error(`Full stack trace for extraction error:`, error); + throw new Error(`Stagehand extraction failed: ${errorMessage}`); + } +}; + +// Add a navigation tool for convenience +export const stagehandNavigateTool = createTool({ + id: 'web-navigate', + description: 'Navigate to a URL in the browser', + inputSchema: z.object({ + url: z.string().describe('URL to navigate to'), + }), + outputSchema: z.object({ + success: z.boolean(), + title: z.string().optional(), + currentUrl: z.string().optional(), + }), + execute: async ({ context }) => { + try { + const stagehand = await sessionManager.ensureStagehand(); + + const page = stagehand.context.pages()[0]; + await page.goto(context.url); + + const title = await page.evaluate(() => document.title); + const currentUrl = await page.evaluate(() => window.location.href); + + return { + success: true, + title, + currentUrl + }; + } catch (error: any) { + return { + success: false, + message: `Navigation failed: ${error.message}` + }; + } + }, +}); diff --git a/examples/integrations/mastra/tsconfig.json b/examples/integrations/mastra/tsconfig.json new file mode 100644 index 0000000..910778e --- /dev/null +++ b/examples/integrations/mastra/tsconfig.json @@ -0,0 +1,20 @@ +{ + "compilerOptions": { + "target": "ES2022", + "module": "ES2022", + "moduleResolution": "bundler", + "esModuleInterop": true, + "forceConsistentCasingInFileNames": true, + "strict": true, + "skipLibCheck": true, + "outDir": "dist" + }, + "include": [ + "src/**/*" + ], + "exclude": [ + "node_modules", + "dist", + ".mastra" + ] +} diff --git a/examples/integrations/mongodb/README.md b/examples/integrations/mongodb/README.md new file mode 100644 index 0000000..124f893 --- /dev/null +++ b/examples/integrations/mongodb/README.md @@ -0,0 +1,203 @@ +# Browserbase + Stagehand MongoDB Integration + +A comprehensive web scraping integration that uses Stagehand to extract structured data from e-commerce websites and store it in MongoDB for analysis. Available in both **Python** and **TypeScript**. + +## 🚀 Choose Your Language + + + + + + +
+ +### 🐍 **Python Version** +**`📁 python/`** + +Perfect for data scientists and Python developers who want: +- **Rich terminal output** with beautiful tables and progress indicators +- **Pydantic models** for robust data validation +- **Async/await** support for high-performance scraping +- **pymongo** for MongoDB operations +- Simple single-file architecture + +**[→ Get Started with Python](python/README.md)** + +```bash +cd python/ +pip install -r requirements.txt +python main.py +``` + + + +### 📘 **TypeScript Version** +**`📁 typescript/`** + +Ideal for JavaScript/Node.js developers who prefer: +- **Type safety** with full TypeScript support +- **Zod schemas** for runtime validation +- **Modern ES modules** and clean architecture +- **MongoDB native driver** with full typing +- Modular, well-structured codebase + +**[→ Get Started with TypeScript](typescript/README.md)** + +```bash +cd typescript/ +npm install +npm start +``` + +
+ +## 🌟 Features (Both Versions) + +- **🌐 Intelligent Web Scraping**: Uses Stagehand's AI-powered extraction +- **🗄️ MongoDB Storage**: Persistent data storage with proper indexing +- **📊 Data Analysis**: Built-in queries and reporting +- **🛡️ Error Handling**: Robust error handling and recovery +- **⚡ Performance**: Optimized for speed and reliability +- **🔍 Schema Validation**: Type-safe data models + +## 📋 What It Does + +Both versions perform the same core functionality: + +1. **🔌 Connect** to MongoDB and set up collections with proper indexes +2. **📊 Scrape** Amazon product listings using Stagehand's AI extraction +3. **🔍 Extract** detailed product information including: + - Product names, prices, ratings + - Categories, descriptions, specifications + - Review counts and availability +4. **💾 Store** all data in MongoDB with validated schemas +5. **📈 Analyze** the data with built-in reporting: + - Collection statistics + - Products by category + - Top-rated products + +## 🛠️ Prerequisites + +**For Both Versions:** +- MongoDB installed locally or MongoDB Atlas account +- Stagehand API key + +**Python Version:** +- Python 3.8+ + +**TypeScript Version:** +- Node.js 16+ +- npm or pnpm + +## 🚦 Quick Start + +### Python Quick Start +```bash +# Navigate to Python version +cd examples/integrations/mongodb/python + +# Install dependencies +pip install -r requirements.txt + +# Set up environment +cp env.example .env +# Edit .env with your MongoDB URI and Stagehand API key + +# Run the scraper +python main.py +``` + +### TypeScript Quick Start +```bash +# Navigate to TypeScript version +cd examples/integrations/mongodb/typescript + +# Install dependencies +npm install + +# Set up environment +cp .env.example .env +# Edit .env with your MongoDB URI and Stagehand API key + +# Run the scraper +npm start +``` + +## 📊 Sample Output + +Both versions provide rich, colorful output showing the scraping progress: + +``` +🤘 Welcome to Stagehand MongoDB Scraper! + +🔌 Connecting to MongoDB... +✅ Connected to MongoDB +⚙️ Creating indexes... +✅ Index creation completed + +📊 Starting to scrape product listing... +✅ Scraped 16 products from category: Laptops + +📊 Scraping details for product 1/3: MacBook Pro M3 +✅ Scraped detailed information for: MacBook Pro M3 + +📊 Running Data Analysis +┌─────────────────┬───────┐ +│ Collection │ Count │ +├─────────────────┼───────┤ +│ PRODUCTS │ 19 │ +│ PRODUCT_LISTS │ 1 │ +└─────────────────┴───────┘ + +🎉 Scraping completed successfully! +``` + +## 🏗️ Architecture + +Both versions follow the same architectural patterns: + +- **MongoDB Manager**: Handles database connections, indexing, and operations +- **Product Scraper**: Manages web scraping using Stagehand +- **Data Models**: Structured schemas for products and product lists +- **Data Analyzer**: Provides insights and reporting on collected data + +## 🔧 Configuration + +Both versions support: +- **Browserbase** cloud browsers for scalability +- **Environment-based** configuration +- **Flexible MongoDB** connection options + +## 📚 Documentation + +- **[Python Version Documentation](python/README.md)** - Detailed Python setup and usage +- **[TypeScript Version Documentation](typescript/README.md)** - Complete TypeScript guide +- **[Stagehand Documentation](https://docs.stagehand.dev/)** - Learn more about Stagehand +- **[MongoDB Documentation](https://docs.mongodb.com/)** - MongoDB setup and operations + +## 🤝 Contributing + +Both versions are actively maintained and welcome contributions: +- Bug reports and feature requests +- Code improvements and optimizations +- Documentation enhancements +- Additional data analysis features + +## 📄 License + +MIT License - feel free to use in your projects! + +## 🙏 Acknowledgements + +- **[Stagehand](https://docs.stagehand.dev/)** - AI-powered web scraping +- **[MongoDB](https://www.mongodb.com/)** - Flexible document database +- **[Pydantic](https://pydantic.dev/)** (Python) - Data validation +- **[Zod](https://zod.dev/)** (TypeScript) - Schema validation + +--- + +## 🤘 Ready to Start? + +Choose your preferred language and dive in: + +**🐍 [Python Version →](python/README.md)** | **📘 [TypeScript Version →](typescript/README.md)** diff --git a/examples/integrations/mongodb/python/.gitignore b/examples/integrations/mongodb/python/.gitignore new file mode 100644 index 0000000..df099fc --- /dev/null +++ b/examples/integrations/mongodb/python/.gitignore @@ -0,0 +1,2 @@ +.env +/venv \ No newline at end of file diff --git a/examples/integrations/mongodb/python/README.md b/examples/integrations/mongodb/python/README.md new file mode 100644 index 0000000..dfa0d95 --- /dev/null +++ b/examples/integrations/mongodb/python/README.md @@ -0,0 +1,226 @@ +# Stagehand MongoDB Scraper (Python) + +A Python web scraping project that uses Stagehand to extract structured data from e-commerce websites and store it in MongoDB for analysis. + +## Features + +- **🌐 Web Scraping**: Uses Stagehand (built on Playwright) for intelligent web scraping +- **🧠 AI-Powered Extraction**: Extracts structured product data using AI-powered instructions +- **🗄️ MongoDB Storage**: Stores scraped data in MongoDB for persistence and querying +- **✅ Schema Validation**: Uses Pydantic for schema validation and type safety +- **🛡️ Error Handling**: Robust error handling to prevent crashes during scraping +- **📊 Data Analysis**: Built-in MongoDB queries for data analysis with beautiful tables +- **🎨 Rich Output**: Colorful console output with progress indicators + +## Prerequisites + +- Python 3.8 or higher +- MongoDB installed locally or MongoDB Atlas account +- Stagehand API key + +## Installation + +1. Navigate to the Python directory: + ```bash + cd examples/integrations/mongodb/python + ``` + +2. Install dependencies: + ```bash + pip install -r requirements.txt + ``` + +3. Set up environment variables: + ```bash + # Copy the example environment file + cp env.example .env + + # Edit .env with your actual values + # MONGO_URI=mongodb://localhost:27017 + # DB_NAME=scraper_db + # STAGEHAND_API_KEY=your_stagehand_api_key_here + ``` + +## Usage + +1. Start MongoDB locally: + ```bash + mongod + ``` + +2. Run the scraper: + ```bash + python main.py + ``` + +3. The script will: + - 🔌 Connect to MongoDB and create necessary indexes + - 📊 Scrape product listings from Amazon laptops category + - 🔍 Extract detailed information for the first 3 products + - 💾 Store all data in MongoDB with proper schemas + - 📈 Run analysis queries showing: + - Collection document counts + - Products grouped by category + - Top-rated products (4+ stars) + +## Project Structure + +``` +python/ +├── main.py # Main application with all functionality +├── requirements.txt # Python dependencies +├── env.example # Example environment variables +└── README.md # This file +``` + +## Data Models + +The project uses Pydantic models for data validation: + +### Product Model +```python +class Product(BaseModel): + url: str + date_scraped: datetime + name: str + price: str + rating: Optional[float] = None + category: Optional[str] = None + id: Optional[str] = None + currency: Optional[str] = None + image_url: Optional[str] = None + review_count: Optional[int] = None + description: Optional[str] = None + specs: Optional[Dict[str, Any]] = None +``` + +### ProductList Model +```python +class ProductList(BaseModel): + products: List[Product] + category: Optional[str] = None + date_scraped: datetime + total_products: Optional[int] = None + page: Optional[int] = None + website_name: Optional[str] = None +``` + +## MongoDB Collections + +Data is stored in the following MongoDB collections: + +- **`products`**: Individual product information with indexes on: + - `rating` (ascending) + - `category` (ascending) + - `url` (ascending, unique) + - `date_scraped` (descending) + +- **`product_lists`**: Lists of products from category pages with indexes on: + - `category` (ascending) + - `date_scraped` (descending) + +## Configuration + +The application supports both local and Browserbase environments: + +```python +# Local browser (default) +config = StagehandConfig( + api_key=os.getenv('STAGEHAND_API_KEY'), + env="LOCAL", + verbose=1 +) + +# Browserbase (cloud browsers) +config = StagehandConfig( + api_key=os.getenv('STAGEHAND_API_KEY'), + env="BROWSERBASE", + verbose=1 +) +``` + +## Key Classes + +### MongoDBManager +Handles all MongoDB operations including: +- Connection management +- Index creation +- Data storage and retrieval +- Aggregation queries + +### ProductScraper +Handles web scraping using Stagehand: +- Product list scraping from category pages +- Detailed product information extraction +- Rate limiting and error handling + +### DataAnalyzer +Provides data analysis and reporting: +- Collection statistics +- Category-based analysis +- Top-rated product reports + +## Error Handling + +The application includes comprehensive error handling: +- MongoDB connection errors +- Web scraping failures +- Data validation errors +- Graceful cleanup on exit + +## Example Output + +``` +🤘 Welcome to Stagehand MongoDB Scraper! + +🔌 Connecting to MongoDB... +✅ Connected to MongoDB +⚙️ Creating indexes... +✅ Created index rating_idx on products +✅ Index creation completed + +📊 Starting to scrape product listing from: https://www.amazon.com/s?k=laptops +✅ Scraped 16 products from category: Laptops + +📊 Running Data Analysis +┏━━━━━━━━━━━━━━━┳━━━━━━━┓ +┃ Collection ┃ Count ┃ +┡━━━━━━━━━━━━━━━╇━━━━━━━┩ +│ PRODUCTS │ 19 │ +│ PRODUCT_LISTS │ 1 │ +└───────────────┴───────┘ + +🎉 Scraping and MongoDB operations completed successfully! +``` + +## Troubleshooting + +### MongoDB Connection Issues +- Ensure MongoDB is running: `mongod` +- Check connection string in `.env` file +- Verify database permissions + +### Stagehand API Issues +- Verify API key in `.env` file +- Check Stagehand service status +- Review rate limiting settings + +### Dependencies Issues +```bash +# Reinstall dependencies +pip install --upgrade -r requirements.txt + +# For Playwright browser issues +playwright install +``` + +## License + +MIT + +## Acknowledgements + +- [Stagehand](https://docs.stagehand.dev/) - Powerful web scraping with AI +- [MongoDB](https://www.mongodb.com/) - Flexible document database +- [Pydantic](https://pydantic.dev/) - Data validation using Python type hints +- [Rich](https://rich.readthedocs.io/) - Beautiful terminal output \ No newline at end of file diff --git a/examples/integrations/mongodb/python/env.example b/examples/integrations/mongodb/python/env.example new file mode 100644 index 0000000..c74b767 --- /dev/null +++ b/examples/integrations/mongodb/python/env.example @@ -0,0 +1,10 @@ +# MongoDB Configuration +MONGO_URI=mongodb://localhost:27017 +DB_NAME=scraper_db + +# Stagehand Configuration +MODEL_API_KEY=your_model_api_key_here + +# Optional: Browserbase Configuration (if using BROWSERBASE env) +BROWSERBASE_API_KEY=your_browserbase_api_key_here +BROWSERBASE_PROJECT_ID=your_browserbase_project_id_here \ No newline at end of file diff --git a/examples/integrations/mongodb/python/main.py b/examples/integrations/mongodb/python/main.py new file mode 100644 index 0000000..80820f2 --- /dev/null +++ b/examples/integrations/mongodb/python/main.py @@ -0,0 +1,577 @@ +import os +import asyncio +import logging +from datetime import datetime +from typing import List, Dict, Any, Optional + +from pydantic import BaseModel +from pymongo import MongoClient, IndexModel, ASCENDING, DESCENDING +from pymongo.errors import DuplicateKeyError +from stagehand import Stagehand +from stagehand.schemas import AvailableModel +from rich.console import Console +from rich.panel import Panel +from rich.table import Table +from dotenv import load_dotenv + +# Load environment variables +load_dotenv() + +# Initialize rich console for better output +console = Console() + +# ========== MongoDB Configuration ========== +MONGO_URI = os.getenv('MONGO_URI', 'mongodb://localhost:27017') +DB_NAME = os.getenv('DB_NAME', 'scraper_db') + +# ========== Pydantic Models (Schema Definitions) ========== +class Product(BaseModel): + """Product model for e-commerce websites""" + url: str + date_scraped: datetime + name: str + price: str + rating: Optional[float] = None + category: Optional[str] = None + id: Optional[str] = None + currency: Optional[str] = None + image_url: Optional[str] = None + review_count: Optional[int] = None + description: Optional[str] = None + specs: Optional[Dict[str, Any]] = None + +class ProductList(BaseModel): + """Product list model for results from category pages""" + products: List[Product] + category: Optional[str] = None + date_scraped: datetime + total_products: Optional[int] = None + page: Optional[int] = None + website_name: Optional[str] = None + +# Schema for extraction (without date_scraped since that's added later) +class ProductExtraction(BaseModel): + """Schema for extracting product data from pages""" + name: str + price: str + url: str + rating: Optional[float] = None + reviewCount: Optional[int] = None + description: Optional[str] = None + specs: Optional[Dict[str, Any]] = None + +class ProductListExtraction(BaseModel): + """Schema for extracting product list data from category pages""" + products: List[ProductExtraction] + category: str + totalProducts: Optional[int] = None + + +# ========== MongoDB Connection and Operations ========== +class MongoDBManager: + """Handles MongoDB connections and operations""" + + def __init__(self, uri: str, db_name: str): + self.uri = uri + self.db_name = db_name + self.client = None + self.db = None + + # Collection names + self.COLLECTIONS = { + 'PRODUCTS': 'products', + 'PRODUCT_LISTS': 'product_lists' + } + + # Index definitions + self.INDEXES = { + self.COLLECTIONS['PRODUCTS']: [ + IndexModel([("rating", ASCENDING)], name="rating_idx"), + IndexModel([("category", ASCENDING)], name="category_idx"), + IndexModel([("url", ASCENDING)], name="url_idx", unique=True), + IndexModel([("date_scraped", DESCENDING)], name="date_scraped_idx") + ], + self.COLLECTIONS['PRODUCT_LISTS']: [ + IndexModel([("category", ASCENDING)], name="category_idx"), + IndexModel([("date_scraped", DESCENDING)], name="date_scraped_idx") + ] + } + + async def connect(self): + """Connect to MongoDB""" + try: + console.print("🔌 Connecting to MongoDB...", style="blue") + self.client = MongoClient(self.uri) + + # Test connection + self.client.admin.command('ismaster') + self.db = self.client[self.db_name] + + console.print("✅ Connected to MongoDB", style="green") + + # Create indexes + await self._create_indexes() + + except Exception as e: + console.print(f"❌ Error connecting to MongoDB: {e}", style="red") + raise + + async def _create_indexes(self): + """Create indexes for all collections""" + console.print("⚙️ Creating indexes...", style="blue") + + for collection_name, indexes in self.INDEXES.items(): + try: + collection = self.db[collection_name] + + # Create indexes + for index in indexes: + try: + collection.create_index( + index.document['key'], + name=index.document.get('name'), + unique=index.document.get('unique', False), + background=True + ) + console.print(f"✅ Created index {index.document.get('name')} on {collection_name}", style="green") + except DuplicateKeyError: + console.print(f"⚠️ Index {index.document.get('name')} already exists on {collection_name}", style="yellow") + + except Exception as e: + console.print(f"❌ Error creating indexes for {collection_name}: {e}", style="red") + + console.print("✅ Index creation completed", style="green") + + async def store_data(self, collection_name: str, data): + """Store data in MongoDB collection""" + try: + collection = self.db[collection_name] + + if isinstance(data, list): + # Check if list is empty + if not data: + console.print(f"⚠️ No data to store in {collection_name} (empty list)", style="yellow") + return + + # Convert Pydantic models to dict (using model_dump for Pydantic v2) + documents = [item.model_dump() if hasattr(item, 'model_dump') else item for item in data] + + # Handle duplicate key errors gracefully + try: + result = collection.insert_many(documents, ordered=False) + console.print(f"✅ Stored {len(result.inserted_ids)} documents in {collection_name}", style="green") + except DuplicateKeyError as e: + # Count successful inserts + inserted = len(documents) - len(e.details.get('writeErrors', [])) + if inserted > 0: + console.print(f"✅ Stored {inserted} new documents in {collection_name} (skipped {len(e.details.get('writeErrors', []))} duplicates)", style="green") + else: + console.print(f"⚠️ All {len(documents)} documents already exist in {collection_name}", style="yellow") + else: + # Convert Pydantic model to dict (using model_dump for Pydantic v2) + document = data.model_dump() if hasattr(data, 'model_dump') else data + + # Handle duplicate key errors gracefully + try: + result = collection.insert_one(document) + console.print(f"✅ Stored document in {collection_name}", style="green") + except DuplicateKeyError: + console.print(f"⚠️ Document already exists in {collection_name} (skipped duplicate)", style="yellow") + + except DuplicateKeyError: + # Already handled above + pass + except Exception as e: + console.print(f"❌ Error storing data in {collection_name}: {e}", style="red") + raise + + async def find_data(self, collection_name: str, query: Dict = None): + """Find documents in MongoDB collection""" + try: + collection = self.db[collection_name] + query = query or {} + documents = list(collection.find(query)) + return documents + except Exception as e: + console.print(f"❌ Error finding data in {collection_name}: {e}", style="red") + raise + + async def aggregate_data(self, collection_name: str, pipeline: List[Dict]): + """Aggregate data in MongoDB collection""" + try: + collection = self.db[collection_name] + results = list(collection.aggregate(pipeline)) + return results + except Exception as e: + console.print(f"❌ Error aggregating data in {collection_name}: {e}", style="red") + raise + + async def get_collection_count(self, collection_name: str) -> int: + """Get document count for a collection""" + try: + collection = self.db[collection_name] + return collection.count_documents({}) + except Exception as e: + console.print(f"❌ Error getting count for {collection_name}: {e}", style="red") + return 0 + + def close(self): + """Close MongoDB connection""" + if self.client: + self.client.close() + console.print("🔌 MongoDB connection closed", style="blue") + +# ========== Web Scraping Functions ========== +class ProductScraper: + """Handles web scraping operations using Stagehand""" + + def __init__(self, stagehand: Stagehand, mongodb: MongoDBManager): + self.stagehand = stagehand + self.page = stagehand.page + self.mongodb = mongodb + + async def scrape_product_list(self, category_url: str) -> ProductList: + """Scrape a product list from an Amazon category page""" + console.print(f"📊 Starting to scrape product listing from: {category_url}", style="blue") + + # Navigate to Amazon homepage first + await self.page.goto('https://www.amazon.com') + await self.page.wait_for_timeout(2000) + + # Then navigate to the category page + await self.page.goto(category_url) + + # Wait for products to load + await self.page.wait_for_selector('[data-component-type="s-search-result"]', timeout=10000) + await self.page.wait_for_timeout(2000) + + # Scroll to load more products + await self.page.evaluate(""" + () => { + window.scrollTo(0, document.body.scrollHeight / 2); + } + """) + await self.page.wait_for_timeout(1000) + + await self.page.evaluate(""" + () => { + window.scrollTo(0, document.body.scrollHeight); + } + """) + await self.page.wait_for_timeout(1000) + + # Extract product data using Stagehand with better error handling + console.print("🔍 Extracting product data with AI...", style="blue") + + try: + # Use Pydantic BaseModel schema as per documentation + extraction_result = await self.page.extract( + """Extract all product information from this Amazon category page. For each product, extract: + - name: ONLY the main product title/name (e.g., "HP 14 Laptop" or "Dell Inspiron 15") + - price: The current price (if available) + - url: The actual clickable link/href to the product detail page (NOT the product name) + - rating: The star rating (if available) + - reviewCount: Number of reviews (if available) + - description: The detailed product description with features, specifications, and details (e.g., "Intel Celeron N4020, 4 GB RAM, 64 GB Storage, 14-inch Micro-edge HD Display, Windows 11 Home, Thin & Portable, 4K Graphics, One Year of Microsoft 365") + - specs: Technical specifications as a dictionary/object with key-value pairs like {"RAM": "16GB", "Storage": "512GB SSD", "Processor": "Intel i7", "Screen": "15.6 inch"} (if available) + + IMPORTANT: + - The 'url' field must contain the actual product link/href, not the product name. + - The 'name' field should be SHORT and concise (just the brand and model). + - The 'description' field should contain the DETAILED product information, features, and specifications. + - For 'specs', extract any technical details you can see and structure them as key-value pairs. + - DO NOT put promotional text like "1K+ bought" or "Limited time deal" in the description field.""", + schema=ProductListExtraction + ) + + # Handle the result - should be a ProductListExtraction object directly + if isinstance(extraction_result, ProductListExtraction): + extraction_data = extraction_result + console.print(f"✅ Extraction successful: {len(extraction_result.products)} products found", style="green") + elif hasattr(extraction_result, 'data'): + # Debug: print the raw data to understand what we're getting + console.print(f"🔍 DEBUG: Raw data type: {type(extraction_result.data)}", style="cyan") + console.print(f"🔍 DEBUG: Raw data (first 300 chars): {str(extraction_result.data)[:300]}...", style="cyan") + + # Check if data is a string that needs parsing or if it's the raw data we need + if isinstance(extraction_result.data, str): + try: + import json + parsed_data = json.loads(extraction_result.data) + # Create ProductListExtraction from parsed JSON + extraction_data = ProductListExtraction(**parsed_data) + console.print(f"✅ Extraction successful (parsed JSON): {len(extraction_data.products)} products found", style="green") + except (json.JSONDecodeError, Exception) as e: + console.print(f"⚠️ Failed to parse JSON extraction data: {e}", style="yellow") + extraction_data = ProductListExtraction(products=[], category="Unknown") + elif isinstance(extraction_result.data, ProductListExtraction): + extraction_data = extraction_result.data + console.print(f"✅ Extraction successful: {len(extraction_result.data.products)} products found", style="green") + elif isinstance(extraction_result.data, dict): + # Try to create ProductListExtraction from dict + try: + extraction_data = ProductListExtraction(**extraction_result.data) + console.print(f"✅ Extraction successful (from dict): {len(extraction_data.products)} products found", style="green") + except Exception as e: + console.print(f"⚠️ Failed to create ProductListExtraction from dict: {e}", style="yellow") + extraction_data = ProductListExtraction(products=[], category="Unknown") + else: + console.print(f"⚠️ Unexpected data type: {type(extraction_result.data)}", style="yellow") + extraction_data = ProductListExtraction(products=[], category="Unknown") + else: + console.print("⚠️ Extraction completed but no products found", style="yellow") + extraction_data = ProductListExtraction(products=[], category="Unknown") + + except Exception as e: + console.print(f"⚠️ AI extraction failed: {str(e)[:100]}...", style="yellow") + extraction_data = ProductListExtraction(products=[], category="Unknown") + + # Process the extracted data + current_time = datetime.now() + timestamp = int(current_time.timestamp()) + products = [] + + # Handle both ProductListExtraction object and dict formats + if isinstance(extraction_data, ProductListExtraction): + products_list = extraction_data.products + category = extraction_data.category + total_products = extraction_data.totalProducts + else: + products_list = extraction_data.get('products', []) + category = extraction_data.get('category', 'Unknown') + total_products = extraction_data.get('totalProducts') + + for i, product_data in enumerate(products_list): + try: + if isinstance(product_data, ProductExtraction): + # Validate and fix URL if it's actually the product name + extracted_url = product_data.url + if not extracted_url.startswith(('http://', 'https://', '/')): + # If URL doesn't look like a URL, create a proper one + extracted_url = f"{category_url}#product-{i}" + console.print(f"⚠️ Fixed invalid URL for: {product_data.name[:50]}...", style="yellow") + + unique_url = f"{extracted_url}?scraped_at={timestamp}&index={i}" + product = Product( + url=unique_url, + date_scraped=current_time, + name=product_data.name, + price=product_data.price, + rating=product_data.rating, + review_count=product_data.reviewCount, + description=product_data.description, + specs=product_data.specs + ) + else: + # If it's a dictionary, validate and fix URL + base_url = product_data.get('url', category_url) + if not base_url.startswith(('http://', 'https://', '/')): + # If URL doesn't look like a URL, create a proper one + base_url = f"{category_url}#product-{i}" + console.print(f"⚠️ Fixed invalid URL for: {product_data.get('name', 'Unknown')[:50]}...", style="yellow") + + unique_url = f"{base_url}?scraped_at={timestamp}&index={i}" + product = Product( + url=unique_url, + date_scraped=current_time, + name=product_data['name'], + price=product_data['price'], + rating=product_data.get('rating'), + review_count=product_data.get('reviewCount'), + description=product_data.get('description'), + specs=product_data.get('specs') + ) + products.append(product) + console.print(f"✅ Processed: {product.name[:50]}...", style="green") + except Exception as e: + console.print(f"⚠️ Error processing product: {e}", style="yellow") + console.print(f"Product data: {product_data}", style="yellow") + + # Create the product list object + product_list = ProductList( + products=products, + category=category, + date_scraped=current_time, + total_products=total_products or len(products), + website_name="Amazon" + ) + + # Create sample products if extraction failed completely + if not products: + console.print("⚠️ No products were successfully extracted. Creating sample products for demonstration...", style="yellow") + console.print(" • This might be due to Amazon's anti-bot measures", style="yellow") + console.print(" • Changes in Amazon's page structure", style="yellow") + console.print(" • Network issues or timeouts", style="yellow") + console.print(" • Geographic restrictions", style="yellow") + + # Create sample products for demonstration + sample_products = [ + {"name": "Premium Laptop Pro", "price": "$1,299.99", "rating": 4.5}, + {"name": "Laptop Ultra Performance", "price": "$899.99", "rating": 4.3}, + {"name": "Budget Laptop Essential", "price": "$499.99", "rating": 4.1}, + {"name": "Gaming Laptop Elite", "price": "$1,599.99", "rating": 4.7}, + {"name": "Portable Laptop Lite", "price": "$699.99", "rating": 4.2} + ] + + # Use current timestamp for unique URLs + for i, sample in enumerate(sample_products[:3]): # Create 3 sample products + product = Product( + url=f"{category_url}&sample_product={i+1}&ts={timestamp}", + date_scraped=current_time, + name=sample["name"], + price=sample["price"], + rating=sample["rating"] + ) + products.append(product) + console.print(f"📝 Created sample: {product.name}", style="cyan") + + # Store the data in MongoDB + await self.mongodb.store_data(self.mongodb.COLLECTIONS['PRODUCT_LISTS'], product_list) + if products: # Only store products if we have any + await self.mongodb.store_data(self.mongodb.COLLECTIONS['PRODUCTS'], products) + + console.print(f"✅ Scraped {len(products)} products from category: {product_list.category}", style="green") + return product_list + + +# ========== Data Analysis Functions ========== +class DataAnalyzer: + """Handles data analysis and reporting""" + + def __init__(self, mongodb: MongoDBManager): + self.mongodb = mongodb + + async def run_analysis(self): + """Run comprehensive data analysis""" + console.print("\n📊 Running Data Analysis", style="bold blue") + + # 1. Collection counts + await self._show_collection_counts() + + # 2. Products by category + await self._show_products_by_category() + + # 3. Top rated products + await self._show_top_rated_products() + + console.print("\n✅ Data analysis completed!", style="bold green") + + async def _show_collection_counts(self): + """Show document counts for each collection""" + console.print("\n📊 Collection Counts:", style="yellow") + + table = Table() + table.add_column("Collection", style="cyan") + table.add_column("Count", style="green") + + for name, collection in self.mongodb.COLLECTIONS.items(): + count = await self.mongodb.get_collection_count(collection) + table.add_row(name, str(count)) + + console.print(table) + + async def _show_products_by_category(self): + """Show products grouped by category""" + console.print("\n📊 Products by Category:", style="yellow") + + pipeline = [ + {"$group": {"_id": "$category", "count": {"$sum": 1}}}, + {"$sort": {"count": -1}} + ] + + results = await self.mongodb.aggregate_data( + self.mongodb.COLLECTIONS['PRODUCTS'], + pipeline + ) + + if results: + table = Table() + table.add_column("Category", style="cyan") + table.add_column("Count", style="green") + + for item in results: + category = item['_id'] or "Unknown" + count = item['count'] + table.add_row(category, str(count)) + + console.print(table) + else: + console.print("No category data found", style="yellow") + + async def _show_top_rated_products(self): + """Show highest rated products""" + console.print("\n📊 Top Rated Products (4+ stars):", style="yellow") + + # Count highly rated products + highly_rated = await self.mongodb.find_data( + self.mongodb.COLLECTIONS['PRODUCTS'], + {"rating": {"$gte": 4}} + ) + + console.print(f"Found {len(highly_rated)} highly rated products", style="blue") + + if highly_rated: + table = Table() + table.add_column("Name", style="cyan", max_width=40) + table.add_column("Price", style="green") + table.add_column("Rating", style="yellow") + table.add_column("Category", style="magenta") + + for product in highly_rated[:10]: # Show top 10 + table.add_row( + product.get('name', 'N/A')[:37] + "..." if len(product.get('name', '')) > 40 else product.get('name', 'N/A'), + product.get('price', 'N/A'), + str(product.get('rating', 'N/A')), + product.get('category', 'Unknown') + ) + + console.print(table) + +# ========== Main Application ========== +async def main(): + """Main application function""" + try: + # Initialize MongoDB + mongodb = MongoDBManager(MONGO_URI, DB_NAME) + await mongodb.connect() + + # Initialize Stagehand with proper config overrides + stagehand = Stagehand( + env="BROWSERBASE", + model_name=AvailableModel.CLAUDE_3_7_SONNET_LATEST, + model_api_key=os.getenv("MODEL_API_KEY"), + verbose=1, + dom_settle_timeout_ms=30000 + ) + await stagehand.init() + + # Initialize scraper + scraper = ProductScraper(stagehand, mongodb) + + # Define category URL + category_url = "https://www.amazon.com/s?k=laptops" + + # Scrape product listing + product_list = await scraper.scrape_product_list(category_url) + + + # Run data analysis + analyzer = DataAnalyzer(mongodb) + await analyzer.run_analysis() + + console.print("\n🎉 Scraping and MongoDB operations completed successfully!", style="bold green") + + except Exception as e: + console.print(f"❌ Error during execution: {e}", style="red") + raise + finally: + # Cleanup + if 'stagehand' in locals(): + await stagehand.close() + if 'mongodb' in locals(): + mongodb.close() + +# ========== Entry Point ========== +if __name__ == "__main__": + # Run the main function + asyncio.run(main()) \ No newline at end of file diff --git a/examples/integrations/mongodb/python/requirements.txt b/examples/integrations/mongodb/python/requirements.txt new file mode 100644 index 0000000..21e3685 --- /dev/null +++ b/examples/integrations/mongodb/python/requirements.txt @@ -0,0 +1,6 @@ +stagehand>=0.3.0 +pymongo>=4.6.0 +pydantic>=2.0.0 +python-dotenv>=1.0.0 +colorama>=0.4.6 +rich>=13.0.0 \ No newline at end of file diff --git a/examples/integrations/mongodb/typescript/.cursorrules b/examples/integrations/mongodb/typescript/.cursorrules new file mode 100644 index 0000000..fe68bca --- /dev/null +++ b/examples/integrations/mongodb/typescript/.cursorrules @@ -0,0 +1,140 @@ +# Stagehand Project + +This is a project that uses Stagehand, which amplifies Playwright with `act`, `extract`, and `observe` added to the Page class. + +`Stagehand` is a class that provides config, a `StagehandPage` object via `stagehand.page`, and a `StagehandContext` object via `stagehand.context`. + +`Page` is a class that extends the Playwright `Page` class and adds `act`, `extract`, and `observe` methods. +`Context` is a class that extends the Playwright `BrowserContext` class. + +Use the following rules to write code for this project. + +- To take an action on the page like "click the sign in button", use Stagehand `act` like this: + +```typescript +await page.act("Click the sign in button"); +``` + +- To plan an instruction before taking an action, use Stagehand `observe` to get the action to execute. + +```typescript +const [action] = await page.observe("Click the sign in button"); +``` + +- The result of `observe` is an array of `ObserveResult` objects that can directly be used as params for `act` like this: + + ```typescript + const [action] = await page.observe("Click the sign in button"); + await page.act(action); + ``` + +- When writing code that needs to extract data from the page, use Stagehand `extract`. Explicitly pass the following params by default: + +```typescript +const { someValue } = await page.extract({ + instruction: the instruction to execute, + schema: z.object({ + someValue: z.string(), + }), // The schema to extract +}); +``` + +## Initialize + +```typescript +import { Stagehand } from "@browserbasehq/stagehand"; +import StagehandConfig from "./stagehand.config"; + +const stagehand = new Stagehand(StagehandConfig); +await stagehand.init(); + +const page = stagehand.page; // Playwright Page with act, extract, and observe methods +const context = stagehand.context; // Playwright BrowserContext +``` + +## Act + +You can cache the results of `observe` and use them as params for `act` like this: + +```typescript +const instruction = "Click the sign in button"; +const cachedAction = await getCache(instruction); + +if (cachedAction) { + await page.act(cachedAction); +} else { + try { + const results = await page.observe(instruction); + await setCache(instruction, results); + await page.act(results[0]); + } catch (error) { + await page.act(instruction); // If the action is not cached, execute the instruction directly + } +} +``` + +Be sure to cache the results of `observe` and use them as params for `act` to avoid unexpected DOM changes. Using `act` without caching will result in more unpredictable behavior. + +Act `action` should be as atomic and specific as possible, i.e. "Click the sign in button" or "Type 'hello' into the search input". +AVOID actions that are more than one step, i.e. "Order me pizza" or "Type in the search bar and hit enter". + +## Extract + +If you are writing code that needs to extract data from the page, use Stagehand `extract`. + +```typescript +const signInButtonText = await page.extract("extract the sign in button text"); +``` + +You can also pass in params like an output schema in Zod, and a flag to use text extraction: + +```typescript +const data = await page.extract({ + instruction: "extract the sign in button text", + schema: z.object({ + text: z.string(), + }), +}); +``` + +`schema` is a Zod schema that describes the data you want to extract. To extract an array, make sure to pass in a single object that contains the array, as follows: + +```typescript +const data = await page.extract({ + instruction: "extract the text inside all buttons", + schema: z.object({ + text: z.array(z.string()), + }), + useTextExtract: true, // Set true for larger-scale extractions (multiple paragraphs), or set false for small extractions (name, birthday, etc) +}); +``` + +## Agent + +Use the `agent` method to automonously execute larger tasks like "Get the stock price of NVDA" + +```typescript +// Navigate to a website +await stagehand.page.goto("https://www.google.com"); + +const agent = stagehand.agent({ + // You can use either OpenAI or Anthropic + provider: "openai", + // The model to use (claude-3-7-sonnet-20250219 or claude-3-5-sonnet-20240620 for Anthropic) + model: "computer-use-preview", + + // Customize the system prompt + instructions: `You are a helpful assistant that can use a web browser. + Do not ask follow up questions, the user will trust your judgement.`, + + // Customize the API key + options: { + apiKey: process.env.OPENAI_API_KEY, + }, +}); + +// Execute the agent +await agent.execute( + "Apply for a library card at the San Francisco Public Library" +); +``` diff --git a/examples/integrations/mongodb/typescript/.env.example b/examples/integrations/mongodb/typescript/.env.example new file mode 100644 index 0000000..c810410 --- /dev/null +++ b/examples/integrations/mongodb/typescript/.env.example @@ -0,0 +1,15 @@ +# MongoDB Connection + +# Local MongoDB instance +# MONGO_URI=mongodb://localhost:27017 + +# MongoDB Atlas connection string format: +# MONGO_URI=mongodb+srv://:@.mongodb.net/?retryWrites=true&w=majority + +# Database name +DB_NAME=scraper_db + +BROWSERBASE_PROJECT_ID="YOUR_BROWSERBASE_PROJECT_ID" +BROWSERBASE_API_KEY="YOUR_BROWSERBASE_API_KEY" +OPENAI_API_KEY="THIS_IS_OPTIONAL_WITH_ANTHROPIC_KEY" +ANTHROPIC_API_KEY="THIS_IS_OPTIONAL_WITH_OPENAI_KEY" \ No newline at end of file diff --git a/examples/integrations/mongodb/typescript/.gitignore b/examples/integrations/mongodb/typescript/.gitignore new file mode 100644 index 0000000..b9151e0 --- /dev/null +++ b/examples/integrations/mongodb/typescript/.gitignore @@ -0,0 +1,7 @@ +.env +node_modules +tmp +downloads +.DS_Store +dist +cache.json \ No newline at end of file diff --git a/examples/integrations/mongodb/typescript/LICENSE b/examples/integrations/mongodb/typescript/LICENSE new file mode 100644 index 0000000..a4b1230 --- /dev/null +++ b/examples/integrations/mongodb/typescript/LICENSE @@ -0,0 +1,7 @@ +Copyright 2025 Browserbase, Inc + +Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. \ No newline at end of file diff --git a/examples/integrations/mongodb/typescript/README.md b/examples/integrations/mongodb/typescript/README.md new file mode 100644 index 0000000..df318f8 --- /dev/null +++ b/examples/integrations/mongodb/typescript/README.md @@ -0,0 +1,99 @@ +# Stagehand MongoDB Scraper + +A web scraping project that uses Stagehand to extract structured data from e-commerce websites and store it in MongoDB for analysis. + +## Features + +- **Web Scraping**: Uses Stagehand (built on Playwright) for intelligent web scraping +- **Data Extraction**: Extracts structured product data using AI-powered instructions +- **MongoDB Storage**: Stores scraped data in MongoDB for persistence and querying +- **Schema Validation**: Uses Zod for schema validation and TypeScript interfaces +- **Error Handling**: Robust error handling to prevent crashes during scraping +- **Data Analysis**: Built-in MongoDB queries for data analysis + +## Prerequisites + +- Node.js 16 or higher +- MongoDB installed locally or MongoDB Atlas account +- Stagehand API key + +## Installation + +1. Clone the repository: + ``` + git clone + cd stagehand-mongodb-scraper + ``` + +2. Install dependencies: + ``` + npm install + ``` + +3. Set up environment variables: + ``` + # Create a .env file with the following variables + MONGO_URI=mongodb://localhost:27017 + DB_NAME=scraper_db + ``` + +## Usage + +1. Start MongoDB locally: + ``` + mongod + ``` + +2. Run the scraper: + ``` + npm start + ``` + +3. The script will: + - Scrape product listings from Amazon + - Extract detailed information for the first 3 products + - Extract reviews for each product + - Store all data in MongoDB + - Run analysis queries on the collected data showing: + - Collection counts + - Products by category + - Top-rated products + +## Project Structure + +The project has a simple structure with a single file containing all functionality: + +- `index.ts`: Contains the complete implementation including: + - MongoDB connection and data operations + - Schema definitions + - Scraping functions + - Data analysis + - Main execution logic +- `stagehand.config.js`: Stagehand configuration +- `.env.example`: Example environment variables + +## Data Models + +The project uses the following data models: + +- **Product**: Individual product information +- **ProductList**: List of products from a category page +- **Review**: Product reviews + +## MongoDB Collections + +Data is stored in the following MongoDB collections: + +- **products**: Individual product information +- **product_lists**: Lists of products from category pages +- **reviews**: Product reviews + +## License + +MIT + +## Acknowledgements + +- [Stagehand](https://docs.stagehand.dev/) for the powerful web scraping capabilities +- [MongoDB](https://www.mongodb.com/) for the flexible document database +- [Zod](https://zod.dev/) for runtime schema validation diff --git a/examples/integrations/mongodb/typescript/index.ts b/examples/integrations/mongodb/typescript/index.ts new file mode 100644 index 0000000..28748c5 --- /dev/null +++ b/examples/integrations/mongodb/typescript/index.ts @@ -0,0 +1,546 @@ +import { Stagehand, type Page } from "@browserbasehq/stagehand"; +import StagehandConfig from "./stagehand.config.js"; +import chalk from "chalk"; +import boxen from "boxen"; +import { z } from "zod"; +import { MongoServerError } from "mongodb"; +import { MongoClient, Db, Document } from 'mongodb'; + +/** + * 🤘 Welcome to Stagehand! Thanks so much for trying us out! + * 🛠️ CONFIGURATION: stagehand.config.ts will help you configure Stagehand + * + * 📝 Check out our docs for more fun use cases, like building agents + * https://docs.stagehand.dev/ + * + * 💬 If you have any feedback, reach out to us on Slack! + * https://stagehand.dev/slack + * + * 📚 You might also benefit from the docs for Zod, Browserbase, and Playwright: + * - https://zod.dev/ + * - https://docs.browserbase.com/ + * - https://playwright.dev/docs/intro + */ + +// ========== MongoDB Connection Configuration ========== +const MONGO_URI = process.env.MONGO_URI || 'mongodb://localhost:27017'; +const DB_NAME = process.env.DB_NAME || 'scraper_db'; + +let client: MongoClient | null = null; +let db: Db | null = null; + +// ========== Schema Definitions ========== +// Product schema for e-commerce websites +const ProductSchema = z.object({ + url: z.string(), + dateScraped: z.date(), + name: z.string(), + price: z.string(), + rating: z.number().optional(), + category: z.string().optional(), + id: z.string().optional(), + currency: z.string().optional(), + imageUrl: z.string().optional(), + reviewCount: z.number().optional(), + description: z.string().optional(), + specs: z.record(z.any()).optional() +}) satisfies z.ZodType; + +// Product list schema for results from category pages +const ProductListSchema = z.object({ + products: z.array(ProductSchema), + category: z.string().optional(), + dateScraped: z.date(), + totalProducts: z.number().optional(), + page: z.number().optional(), + websiteName: z.string().optional() +}) satisfies z.ZodType; + +// Types are inferred from the schemas +export type Product = z.infer; +export type ProductList = z.infer; + +// Collection names for MongoDB +const COLLECTIONS = { + PRODUCTS: 'products', + PRODUCT_LISTS: 'product_lists' +} as const; + +// Index definitions for MongoDB collections +interface IndexDefinition { + key: { [key: string]: number }; + name: string; + unique?: boolean; +} + +const INDEXES = { + [COLLECTIONS.PRODUCTS]: [ + { key: { rating: 1 }, name: 'rating_idx' } as IndexDefinition, + { key: { category: 1 }, name: 'category_idx' } as IndexDefinition, + { key: { url: 1 }, name: 'url_idx', unique: true } as IndexDefinition, + { key: { dateScraped: -1 }, name: 'dateScraped_idx' } as IndexDefinition + ], + [COLLECTIONS.PRODUCT_LISTS]: [ + { key: { category: 1 }, name: 'category_idx' } as IndexDefinition, + { key: { dateScraped: -1 }, name: 'dateScraped_idx' } as IndexDefinition + ] +} as const; + +// Check and create indexes for all collections +async function createIndexes(db: Db): Promise { + console.log(chalk.blue('⚙️ Starting index creation...')); + + // First create all collections if they don't exist + for (const collectionName of Object.keys(INDEXES)) { + try { + await db.createCollection(collectionName); + console.log(chalk.green(`✅ Created collection: ${collectionName}`)); + } catch (error) { + if (error instanceof MongoServerError && error.code === 48) { + console.log(chalk.yellow(`⚠️ Collection ${collectionName} already exists`)); + } else { + console.error(chalk.red(`❌ Error creating collection ${collectionName}:`), error); + throw error; + } + } + } + + // Now create indexes for each collection + for (const [collectionName, indexes] of Object.entries(INDEXES)) { + console.log(chalk.blue(`⚙️ Processing indexes for collection: ${collectionName}`)); + const collection = db.collection(collectionName); + + for (const index of indexes) { + try { + console.log(chalk.blue(`⚙️ Creating index ${index.name} on ${collectionName} with keys:`, index.key)); + const existingIndexes = await collection.listIndexes().toArray(); + const indexExists = existingIndexes.some(idx => idx.name === index.name); + + if (indexExists) { + console.log(chalk.yellow(`⚠️ Index ${index.name} already exists on ${collectionName}`)); + } else { + await collection.createIndex(index.key, { + name: index.name, + unique: index.unique || false, + background: false + }); + console.log(chalk.green(`✅ Created index ${index.name} on ${collectionName}`)); + } + } catch (error) { + console.error(chalk.red(`❌ Error creating index ${index.name} on ${collectionName}:`), error); + } + } + } + + // Verify indexes were created + for (const [collectionName, indexes] of Object.entries(INDEXES)) { + const collection = db.collection(collectionName); + const existingIndexes = await collection.listIndexes().toArray(); + console.log(chalk.blue(`Indexes for ${collectionName}:`)); + console.log(existingIndexes); + } + + console.log(chalk.green('✅ Index creation completed')); +} + +// ========== MongoDB Utility Functions ========== +/** + * Connects to MongoDB + */ +async function connectToMongo(): Promise { + if (client) { + console.log('Using existing MongoDB connection'); + return client.db(DB_NAME); + } + + try { + console.log('Connecting to MongoDB...'); + client = new MongoClient(MONGO_URI); + await client.connect(); + + console.log('Connected to MongoDB'); + + // Verify if database exists + const adminDb = client.db('admin'); + const databases = await adminDb.admin().listDatabases(); + const dbExists = databases.databases?.some((db: { name: string }) => db.name === DB_NAME) ?? false; + + if (!dbExists) { + console.log(chalk.blue(`⚙️ Creating database: ${DB_NAME}`)); + // Create a collection to trigger database creation + const db = client.db(DB_NAME); + await db.createCollection(COLLECTIONS.PRODUCTS); + console.log(chalk.green(`✅ Database ${DB_NAME} created successfully`)); + } else { + console.log(chalk.yellow(`⚠️ Database ${DB_NAME} already exists`)); + } + + const db = client.db(DB_NAME); + + // Create indexes for all collections + console.log('Creating indexes...'); + await createIndexes(db); + console.log('Indexes created successfully'); + + return db; + } catch (error) { + console.error('Error connecting to MongoDB:', error); + throw error; + } +} + +/** + * Closes the MongoDB connection + */ +async function closeMongo(): Promise { + if (client) { + await client.close(); + console.log('MongoDB connection closed'); + client = null; + db = null; + } +} + +/** + * Stores data in a MongoDB collection + */ +async function storeData(collectionName: string, data: T | T[]): Promise { + const db = await connectToMongo(); + + // Ensure collection exists + try { + await db.createCollection(collectionName); + console.log(chalk.green(`✅ Created collection: ${collectionName}`)); + } catch (error) { + if (error instanceof MongoServerError && error.code === 48) { + console.log(chalk.yellow(`⚠️ Collection ${collectionName} already exists`)); + } else { + console.error(chalk.red(`❌ Error creating collection ${collectionName}:`), error); + throw error; + } + } + + const collection = db.collection(collectionName); + + try { + if (Array.isArray(data)) { + await collection.insertMany(data as Document[]); + } else { + await collection.insertOne(data as Document); + } + console.log(chalk.green(`✅ Stored data in ${collectionName}`)); + } catch (error) { + console.error(chalk.red(`❌ Error storing data in ${collectionName}:`), error); + throw error; + } +} + +/** + * Finds documents in a MongoDB collection + */ +async function findData(collectionName: string, query = {}): Promise { + const database = await connectToMongo(); + const collection = database.collection(collectionName); + + try { + const documents = await collection.find(query).toArray(); + return documents as T[]; + } catch (error) { + console.error(`Error finding data in ${collectionName}:`, error); + throw error; + } +} + +/** + * Aggregates data in a MongoDB collection + */ +async function aggregateData( + collectionName: string, + pipeline: object[] +): Promise { + const database = await connectToMongo(); + const collection = database.collection(collectionName); + + try { + const results = await collection.aggregate(pipeline).toArray(); + return results as T[]; + } catch (error) { + console.error(`Error aggregating data in ${collectionName}:`, error); + throw error; + } +} + +// ========== Scraping Functions ========== +/** + * Scrapes a product list from an Amazon category page + */ +async function scrapeProductList( + page: Page, + categoryUrl: string, + stagehand: Stagehand, +): Promise { + // Navigate to Amazon homepage first + await page.goto('https://www.amazon.com'); + await page.waitForTimeout(2000); + + // Then navigate to the category page + await page.goto(categoryUrl); + + // Wait for products to load + await page.waitForSelector('[data-component-type="s-search-result"]', { timeout: 10000 }); + await page.waitForTimeout(2000); + + // Scroll to load more products + await page.evaluate(() => { + window.scrollTo(0, document.body.scrollHeight / 2); + }); + await page.waitForTimeout(1000); + await page.evaluate(() => { + window.scrollTo(0, document.body.scrollHeight); + }); + await page.waitForTimeout(1000); + + const listSchema = z.object({ + products: z.array( + z.object({ + name: z.string(), + price: z.string(), + url: z.string(), + rating: z.number().optional(), + reviewCount: z.number().optional(), + }), + ), + category: z.string(), + totalProducts: z.number().optional(), + }); + + const data = await stagehand.extract( + "Extract all product information from this Amazon category page, including product names, prices, URLs, ratings", + listSchema, + ); + + const products = data.products.map((product: (typeof data.products)[number]) => ({ + ...product, + dateScraped: new Date(), + })); + + // Create the product list object + const productList: ProductList = { + products: products, + category: data.category, + dateScraped: new Date(), + totalProducts: products.length, + websiteName: "Amazon" + }; + + // Store the data in MongoDB + await storeData(COLLECTIONS.PRODUCT_LISTS, productList); + await storeData(COLLECTIONS.PRODUCTS, products); + + return productList; +} + +/** + * Scrapes detailed information for a single product + */ +async function scrapeProductDetails( + page: Page, + productUrl: string, + stagehand: Stagehand, +): Promise { + await page.goto(productUrl); + + // Wait for the page to load + await page.waitForTimeout(2000); + + // Scroll down to load more content + await page.evaluate(() => { + window.scrollTo(0, document.body.scrollHeight / 3); + }); + await page.waitForTimeout(1000); + await page.evaluate(() => { + window.scrollTo(0, document.body.scrollHeight * 2 / 3); + }); + await page.waitForTimeout(1000); + + const product = await stagehand.extract( + "Extract detailed product information from this Amazon product page, including name, price, description, specifications, brand, category, image URL, rating, review count, and availability", + ProductSchema.omit({ dateScraped: true }), + ); + + // Add additional data + const completeProduct: Product = { + ...product, + url: productUrl, + dateScraped: new Date(), + }; + + // Store the data in MongoDB + await storeData(COLLECTIONS.PRODUCTS, completeProduct); + + return completeProduct; +} + +// ========== Data Analysis Functions ========== +/** + * Run queries on the collected data + */ +async function runQueries(): Promise { + try { + // Connect to MongoDB + await connectToMongo(); + console.log(chalk.blue("🔌 Connected to MongoDB")); + + // Define types for MongoDB query results + interface CategoryCount { + _id: string | null; + count: number; + } + + // 1. Get total counts for each collection using MongoDB's native countDocuments + console.log(chalk.yellow("\n📊 Collection Counts:")); + if (!db) throw new Error('MongoDB connection not established'); + for (const [name, collection] of Object.entries(COLLECTIONS)) { + const count = await db.collection(collection).countDocuments(); + console.log(`${chalk.green(name)}: ${count} documents`); + } + + // 2. Products by category + console.log(chalk.yellow("\n📊 Products by Category:")); + const productsByCategory = await aggregateData( + COLLECTIONS.PRODUCTS, + [ + { $group: { _id: "$category", count: { $sum: 1 } } }, + { $sort: { count: -1 } } + ] + ); + + console.table( + productsByCategory.map(item => ({ + Category: item._id || "Unknown", + Count: item.count + })) + ); + + // 3. Find highest rated products + console.log(chalk.yellow("\n📊 Top Rated Products:")); + // First get the count of highly rated products + if (!db) throw new Error('MongoDB connection not established'); + const count = await db.collection(COLLECTIONS.PRODUCTS).countDocuments({ rating: { $gte: 4 } }); + console.log(chalk.yellow(`Found ${count} highly rated products (4+ stars)`)); + + // Only fetch and display the products if there are any + if (count > 0) { + const highestRatedProducts = await findData( + COLLECTIONS.PRODUCTS, + { rating: { $gte: 4 } } + ); + console.table( + highestRatedProducts.map((product: any) => ({ + Name: product.name, + Price: product.price, + Rating: product.rating, + Category: product.category || "Unknown" + })) + ); + } + + console.log(chalk.green("\n✅ Queries completed successfully!")); + } catch (error) { + console.error(chalk.red("❌ Error running queries:"), error); + } +} + +// ========== Main Function ========== +async function main({ + page, + stagehand, +}: { + page: Page; + stagehand: Stagehand; +}) { + try { + // Connect to MongoDB + const db = await connectToMongo(); + + // Verify indexes were created + console.log(chalk.blue('Verifying indexes...')); + for (const [collectionName, indexes] of Object.entries(INDEXES)) { + const collection = db.collection(collectionName); + const existingIndexes = await collection.listIndexes().toArray(); + console.log(chalk.blue(`Indexes for ${collectionName}:`)); + console.log(existingIndexes); + } + + // Define the category URL for Amazon electronics + const categoryUrl = "https://www.amazon.com/s?k=laptops"; + + console.log(chalk.blue("📊 Starting to scrape product listing...")); + + // Scrape product listing + const productList = await scrapeProductList(page, categoryUrl, stagehand); + console.log(chalk.green(`✅ Scraped ${productList.products.length} products from category: ${productList.category}`)); + + // Scrape detailed information for the first 3 products + const productsToScrape = productList.products.slice(0, 3); + + for (const [index, product] of productsToScrape.entries()) { + console.log(chalk.blue(`📊 Scraping details for product ${index + 1}/${productsToScrape.length}: ${product.name}`)); + + try { + // Scrape product details + const detailedProduct = await scrapeProductDetails(page, product.url, stagehand); + console.log(chalk.green(`✅ Scraped detailed information for: ${detailedProduct.name}`)); + + // Wait between requests to avoid rate limiting + await page.waitForTimeout(2000); + } catch (error) { + console.error(chalk.red(`❌ Error scraping product ${product.name}:`), error); + } + } + + // Run queries on the collected data + await runQueries(); + + console.log(chalk.green("🎉 Scraping and MongoDB operations completed successfully!")); + } catch (error) { + console.error(chalk.red("❌ Error during scraping:"), error); + } finally { + // Close MongoDB connection + await closeMongo(); + } +} + +// ========== Entry Point ========== +async function run() { + const stagehand = new Stagehand({ + ...StagehandConfig, + }); + await stagehand.init(); + + if (StagehandConfig.env === "BROWSERBASE" && stagehand.browserbaseSessionID) { + console.log( + boxen( + `View this session live in your browser: \n${chalk.blue( + `https://browserbase.com/sessions/${stagehand.browserbaseSessionID}`, + )}`, + { + title: "Browserbase", + padding: 1, + margin: 3, + }, + ), + ); + } + + const page = stagehand.context.pages()[0]; + + await main({ + page, + stagehand, + }); + + await stagehand.close(); +} + +run(); diff --git a/examples/integrations/mongodb/typescript/package-lock.json b/examples/integrations/mongodb/typescript/package-lock.json new file mode 100644 index 0000000..b8f305f --- /dev/null +++ b/examples/integrations/mongodb/typescript/package-lock.json @@ -0,0 +1,5287 @@ +{ + "name": "mongodb", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "mongodb", + "hasInstallScript": true, + "dependencies": { + "@browserbasehq/sdk": 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b/examples/integrations/mongodb/typescript/package.json new file mode 100644 index 0000000..422b758 --- /dev/null +++ b/examples/integrations/mongodb/typescript/package.json @@ -0,0 +1,24 @@ +{ + "name": "mongodb", + "type": "module", + "scripts": { + "build": "tsc", + "start": "tsx index.ts", + "postinstall": "playwright install" + }, + "dependencies": { + "@browserbasehq/sdk": "^2.6.0", + "@browserbasehq/stagehand": "^3.2.0", + "@playwright/test": "^1.49.1", + "boxen": "^8.0.1", + "chalk": "^5.3.0", + "dotenv": "^16.4.7", + "mongodb": "^6.16.0", + "zod": "^3.25.76" + }, + "devDependencies": { + "tsx": "^4.19.2", + "typescript": "^5.0.0" + }, + "packageManager": "pnpm@9.15.0+sha512.76e2379760a4328ec4415815bcd6628dee727af3779aaa4c914e3944156c4299921a89f976381ee107d41f12cfa4b66681ca9c718f0668fa0831ed4c6d8ba56c" +} diff --git a/examples/integrations/mongodb/typescript/stagehand.config.ts b/examples/integrations/mongodb/typescript/stagehand.config.ts new file mode 100644 index 0000000..bc1f09d --- /dev/null +++ b/examples/integrations/mongodb/typescript/stagehand.config.ts @@ -0,0 +1,34 @@ +import type { V3Options } from "@browserbasehq/stagehand"; +import dotenv from "dotenv"; + +dotenv.config(); + +const StagehandConfig: V3Options = { + verbose: 1, + domSettleTimeout: 30_000, + + model: "anthropic/claude-sonnet-4-6", + + env: "LOCAL", + apiKey: process.env.BROWSERBASE_API_KEY, + projectId: process.env.BROWSERBASE_PROJECT_ID, + browserbaseSessionID: undefined, + browserbaseSessionCreateParams: { + projectId: process.env.BROWSERBASE_PROJECT_ID!, + browserSettings: { + blockAds: true, + viewport: { + width: 1024, + height: 768, + }, + }, + }, + localBrowserLaunchOptions: { + viewport: { + width: 1024, + height: 768, + }, + }, +}; + +export default StagehandConfig; diff --git a/examples/integrations/mongodb/typescript/tsconfig.json b/examples/integrations/mongodb/typescript/tsconfig.json new file mode 100644 index 0000000..2b269c1 --- /dev/null +++ b/examples/integrations/mongodb/typescript/tsconfig.json @@ -0,0 +1,17 @@ +{ + "compilerOptions": { + "target": "ES2022", + "module": "NodeNext", + "moduleResolution": "NodeNext", + "outDir": "./dist", + "rootDir": "./", + "strict": true, + "esModuleInterop": true, + "skipLibCheck": true, + "forceConsistentCasingInFileNames": true, + "allowImportingTsExtensions": false, + "noEmit": false + }, + "include": ["*.ts", "api", "examples/run.ts"], + "exclude": ["node_modules", "dist"] +} diff --git a/examples/integrations/mongodb/typescript/utils.ts b/examples/integrations/mongodb/typescript/utils.ts new file mode 100644 index 0000000..4708ce8 --- /dev/null +++ b/examples/integrations/mongodb/typescript/utils.ts @@ -0,0 +1,142 @@ +import type { + Action, + ObserveResult, + Page, + Stagehand, +} from "@browserbasehq/stagehand"; +import boxen from "boxen"; +import chalk from "chalk"; +import fs from "fs/promises"; +import { z } from "zod"; + +export function announce(message: string, title?: string) { + console.log( + boxen(message, { + padding: 1, + margin: 3, + title: title || "Stagehand", + }), + ); +} + +export function getEnvVar(name: string, required = true): string | undefined { + const value = process.env[name]; + if (!value && required) { + throw new Error(`${name} not found in environment variables`); + } + return value; +} + +export function validateZodSchema(schema: z.ZodTypeAny, data: unknown) { + try { + schema.parse(data); + return true; + } catch { + return false; + } +} + +export async function drawObserveOverlay(page: Page, results: ObserveResult) { + const xpathList = results.map((result: Action) => result.selector); + + const validXpaths = xpathList.filter((xpath) => xpath !== "xpath="); + + await page.evaluate((selectors) => { + selectors.forEach((selector) => { + let element; + if (selector.startsWith("xpath=")) { + const xpath = selector.substring(6); + element = document.evaluate( + xpath, + document, + null, + XPathResult.FIRST_ORDERED_NODE_TYPE, + null, + ).singleNodeValue; + } else { + element = document.querySelector(selector); + } + + if (element instanceof HTMLElement) { + const overlay = document.createElement("div"); + overlay.setAttribute("stagehandObserve", "true"); + const rect = element.getBoundingClientRect(); + overlay.style.position = "absolute"; + overlay.style.left = rect.left + "px"; + overlay.style.top = rect.top + "px"; + overlay.style.width = rect.width + "px"; + overlay.style.height = rect.height + "px"; + overlay.style.backgroundColor = "rgba(255, 255, 0, 0.3)"; + overlay.style.pointerEvents = "none"; + overlay.style.zIndex = "10000"; + document.body.appendChild(overlay); + } + }); + }, validXpaths); +} + +export async function clearOverlays(page: Page) { + await page.evaluate(() => { + const elements = document.querySelectorAll('[stagehandObserve="true"]'); + elements.forEach((el) => { + const parent = el.parentNode; + while (el.firstChild) { + parent?.insertBefore(el.firstChild, el); + } + parent?.removeChild(el); + }); + }); +} + +export async function simpleCache(instruction: string, actionToCache: Action) { + try { + let cache: Record = {}; + try { + const existingCache = await fs.readFile("cache.json", "utf-8"); + cache = JSON.parse(existingCache); + } catch { + // no file yet + } + + cache[instruction] = actionToCache; + + await fs.writeFile("cache.json", JSON.stringify(cache, null, 2)); + } catch (error) { + console.error(chalk.red("Failed to save to cache:"), error); + } +} + +export async function readCache(instruction: string): Promise { + try { + const existingCache = await fs.readFile("cache.json", "utf-8"); + const cache: Record = JSON.parse(existingCache); + return cache[instruction] || null; + } catch { + return null; + } +} + +export async function actWithCache( + stagehand: Stagehand, + page: Page, + instruction: string, +): Promise { + const cachedAction = await readCache(instruction); + if (cachedAction) { + console.log(chalk.blue("Using cached action for:"), instruction); + await stagehand.act(cachedAction); + return; + } + + const results = await stagehand.observe(instruction); + console.log(chalk.blue("Got results:"), results); + + const actionToCache = results[0]; + console.log(chalk.blue("Taking cacheable action:"), actionToCache); + await simpleCache(instruction, actionToCache); + await drawObserveOverlay(page, results); + await page.waitForTimeout(1000); + await clearOverlays(page); + + await stagehand.act(actionToCache); +} diff --git a/examples/integrations/stripe/node/README.md b/examples/integrations/stripe/node/README.md new file mode 100644 index 0000000..c3b2b00 --- /dev/null +++ b/examples/integrations/stripe/node/README.md @@ -0,0 +1,108 @@ +# 🚀 Agentic Credit Card Automation - Node.js + +Effortlessly create virtual cards with **Stripe** and automate purchases using **Browserbase** in Node.js/TypeScript. + +## 📌 Overview + +This Node.js implementation enables you to: +- **Create virtual cards** with spending controls using Stripe Issuing +- **Retrieve virtual card details** securely +- **Automate online purchases** with Playwright and Browserbase + +## 🛠️ Setup + +### Prerequisites +- Node.js 18+ +- npm or yarn +- Stripe account with Issuing enabled +- Browserbase account + +### Installation + +1. **Install dependencies**: +```bash +npm install +``` + +2. **Configure environment variables**: +Create a `.env` file in this directory: +```env +STRIPE_API_KEY=sk_test_your_stripe_secret_key +BROWSERBASE_API_KEY=your_browserbase_api_key +BROWSERBASE_PROJECT_ID=your_browserbase_project_id +``` + +3. **Install Playwright browsers**: +```bash +npm run postinstall +``` + +## 🚀 Usage + +### Step 1: Create a Cardholder +```bash +npx tsx 1-create-cardholder.ts +``` + +### Step 2: Create a Virtual Card +```bash +npx tsx 2-create-card.ts +``` +⚠️ **Important**: Update the `cardholderId` variable with the ID from Step 1 + +### Step 3: Retrieve Card Details +```bash +npx tsx 3-get-card.ts +``` +⚠️ **Important**: Update the `cardId` variable with the ID from Step 2 + +### Step 4: Make an Automated Payment +```bash +npx tsx 4-make-payment.ts +``` +⚠️ **Important**: Update the `cardId` variable with the ID from Step 2 + +## 📁 Files + +| File | Description | +|------|-------------| +| `1-create-cardholder.ts` | Creates a Stripe cardholder with billing information | +| `2-create-card.ts` | Creates a virtual card with spending limits | +| `3-get-card.ts` | Retrieves card details including sensitive information | +| `4-make-payment.ts` | Automates a donation using Playwright and Browserbase | +| `package.json` | Node.js dependencies and scripts | +| `.env` | Environment variables (not tracked in git) | + +## 🔧 Configuration + +### Spending Controls +Edit `2-create-card.ts` to customize: +- **Allowed categories**: Restrict card usage to specific merchant categories +- **Spending limits**: Set daily/monthly/yearly limits +- **Blocked categories**: Prevent usage at certain merchant types + +### Payment Automation +Modify `4-make-payment.ts` to: +- Change the target website +- Customize form filling logic +- Add error handling and validation + +## 🔐 Security Notes + +- Never commit `.env` files to version control +- Use test API keys for development +- Implement proper error handling in production +- Consider using Stripe webhooks for real-time updates + +## 📖 Documentation + +For full API documentation and advanced usage: +📄 **[Stripe Issuing API](https://stripe.com/docs/issuing)** +📄 **[Browserbase Documentation](https://docs.browserbase.com)** + +## 🎯 Example Use Cases + +- **Expense management**: Create cards for specific projects or employees +- **Testing payments**: Automate payment flow testing +- **Subscription management**: Programmatically manage recurring payments +- **Budget enforcement**: Set spending limits per card or category \ No newline at end of file diff --git a/examples/integrations/stripe/node/package.json b/examples/integrations/stripe/node/package.json index 6e2eb57..b7b86d9 100644 --- a/examples/integrations/stripe/node/package.json +++ b/examples/integrations/stripe/node/package.json @@ -7,8 +7,8 @@ "postinstall": "playwright install" }, "dependencies": { - "@browserbasehq/sdk": "2.3.0", - "@browserbasehq/stagehand": "1.12.0", + "@browserbasehq/sdk": "^2.6.0", + "@browserbasehq/stagehand": "^2.4.4", "@playwright/test": "^1.49.1", "boxen": "^8.0.1", "chalk": "^5.3.0", diff --git a/examples/integrations/stripe/python/README.md b/examples/integrations/stripe/python/README.md new file mode 100644 index 0000000..2e66b48 --- /dev/null +++ b/examples/integrations/stripe/python/README.md @@ -0,0 +1,139 @@ +# 🚀 Agentic Credit Card Automation - Python + +Effortlessly create virtual cards with **Stripe** and automate purchases using **Browserbase** in Python. + +## 📌 Overview + +This Python implementation enables you to: +- **Create virtual cards** with spending controls using Stripe Issuing +- **Retrieve virtual card details** securely +- **Automate online purchases** with Playwright and Browserbase + +## 🛠️ Setup + +### Prerequisites +- Python 3.8+ +- pip or poetry +- Stripe account with Issuing enabled +- Browserbase account + +### Installation + +1. **Install dependencies**: +```bash +pip install -r requirements.txt +``` + +2. **Configure environment variables**: +Create a `.env` file in this directory: +```env +STRIPE_API_KEY=sk_test_your_stripe_secret_key +BROWSERBASE_API_KEY=your_browserbase_api_key +BROWSERBASE_PROJECT_ID=your_browserbase_project_id +``` + +3. **Install Playwright browsers**: +```bash +playwright install +``` + +## 🚀 Usage + +### Step 1: Create a Cardholder +```bash +python create_cardholder.py +``` + +### Step 2: Create a Virtual Card +```bash +python create_card.py +``` +⚠️ **Important**: Update the `cardholder_id` variable with the ID from Step 1 + +### Step 3: Retrieve Card Details +```bash +python get_card.py +``` +⚠️ **Important**: Uncomment and update the `card_id` variable with the ID from Step 2 + +### Step 4: Make an Automated Payment +```bash +python make-payment.py +``` +⚠️ **Important**: Update the `cardId` variable with the ID from Step 2 + +## 📁 Files + +| File | Description | +|------|-------------| +| `create_cardholder.py` | Creates a Stripe cardholder with billing information | +| `create_card.py` | Creates a virtual card with spending limits | +| `get_card.py` | Retrieves card details including sensitive information | +| `make-payment.py` | Automates a donation using Playwright and Browserbase | +| `requirements.txt` | Python dependencies | +| `.env` | Environment variables (not tracked in git) | + +## 🔧 Configuration + +### Spending Controls +Edit `create_card.py` to customize: +- **Allowed categories**: Restrict card usage to specific merchant categories +- **Spending limits**: Set daily/monthly/yearly limits +- **Blocked categories**: Prevent usage at certain merchant types + +### Payment Automation +Modify `make-payment.py` to: +- Change the target website +- Customize form filling logic +- Add error handling and validation + +## 🐍 Python-Specific Features + +### Virtual Environment (Recommended) +```bash +python -m venv venv +source venv/bin/activate # On Windows: venv\Scripts\activate +pip install -r requirements.txt +``` + +### Error Handling +The Python implementation includes: +- Environment variable validation +- Stripe API error handling +- Playwright timeout management + +### Dependencies +- **stripe**: Official Stripe Python library +- **browserbasehq**: Browserbase SDK for Python +- **playwright**: Browser automation framework +- **python-dotenv**: Environment variable management + +## 🔐 Security Notes + +- Never commit `.env` files to version control +- Use test API keys for development +- Implement proper exception handling in production +- Consider using Stripe webhooks for real-time updates +- Always validate sensitive card data before use + +## 📖 Documentation + +For full API documentation and advanced usage: +📄 **[Stripe Python SDK](https://stripe.com/docs/api/python)** +📄 **[Browserbase Python SDK](https://docs.browserbase.com/sdk/python)** +📄 **[Playwright Python](https://playwright.dev/python/)** + +## 🎯 Example Use Cases + +- **Financial automation**: Automate expense reporting and payment processing +- **E-commerce testing**: Test payment flows across multiple platforms +- **Budget management**: Create spending-limited cards for different departments +- **Subscription automation**: Programmatically manage recurring payments + +## 🚨 Troubleshooting + +### Common Issues +- **Import errors**: Ensure all dependencies are installed via `pip install -r requirements.txt` +- **Playwright errors**: Run `playwright install` to download browser binaries +- **Stripe API errors**: Verify your API keys and account permissions +- **Environment variables**: Double-check your `.env` file formatting \ No newline at end of file diff --git a/examples/integrations/stripe/stagehand/4-make-payment.ts b/examples/integrations/stripe/stagehand/4-make-payment.ts index ea14eff..629b753 100644 --- a/examples/integrations/stripe/stagehand/4-make-payment.ts +++ b/examples/integrations/stripe/stagehand/4-make-payment.ts @@ -10,7 +10,7 @@ * To edit config, see `stagehand.config.ts` * */ -import { Page, BrowserContext, Stagehand } from "@browserbasehq/stagehand"; +import { Stagehand } from "@browserbasehq/stagehand"; import { z } from "zod"; import chalk from "chalk"; import dotenv from "dotenv"; @@ -21,55 +21,42 @@ dotenv.config(); const cardId = "ic_1Qu1XJGhqv5yXZ43z9OdjbXs"; // replace with your card id from the previous step export async function main({ - page, - context, stagehand, }: { - page: Page; // Playwright Page with act, extract, and observe methods - context: BrowserContext; // Playwright BrowserContext - stagehand: Stagehand; // Stagehand instance + stagehand: Stagehand; }) { - // Learn more about Stagehand: https://www.stagehand.dev/ - + const page = stagehand.context.pages()[0]; const paymentInfo = await getCard(cardId); // Navigate to Red Cross donation page await page.goto('https://www.redcross.org/donate/donation.html/') - const donationAmount = await page.observe({ - instruction: "Find the donation amounts", - returnAction: true, - onlyVisible: false, - }); + const donationAmount = await stagehand.observe( + "Find the donation amounts" + ); // Click the first donation amount - await page.act(donationAmount[0]) + await stagehand.act(donationAmount[0]) // Find the continue button and click it - const continueButton = await page.observe({ - instruction: "Find the continue button and click it", - returnAction: true, - onlyVisible: false, - }); - await page.act(continueButton[0]) + const continueButton = await stagehand.observe( + "Find the continue button and click it" + ); + await stagehand.act(continueButton[0]) // Find the credit card button and click it - const creditCardButton = await page.observe({ - instruction: "Find the credit card button and click it", - returnAction: true, - onlyVisible: false, - }); - await page.act(creditCardButton[0]) + const creditCardButton = await stagehand.observe( + "Find the credit card button and click it" + ); + await stagehand.act(creditCardButton[0]) - await page.act({action: "click the continue button"}) + await stagehand.act("click the continue button") - const formValues = await page.observe({ - instruction: `Fill in the form with the following values: ${JSON.stringify(paymentInfo)}`, - returnAction: true, - onlyVisible: false, - }); + const formValues = await stagehand.observe( + `Fill in the form with the following values: ${JSON.stringify(paymentInfo)}` + ); console.log("formValues", formValues); // Fill in the form with the values for (const value of formValues) { - await page.act(value); + await stagehand.act(value); } } diff --git a/examples/integrations/stripe/stagehand/index.ts b/examples/integrations/stripe/stagehand/index.ts index ae5a06a..db5c36e 100644 --- a/examples/integrations/stripe/stagehand/index.ts +++ b/examples/integrations/stripe/stagehand/index.ts @@ -36,11 +36,7 @@ async function run() { ); } - const page = stagehand.page; - const context = stagehand.context; await main({ - page, - context, stagehand, }); await stagehand.close(); diff --git a/examples/integrations/stripe/stagehand/package.json b/examples/integrations/stripe/stagehand/package.json index 6e2eb57..0571e4b 100644 --- a/examples/integrations/stripe/stagehand/package.json +++ b/examples/integrations/stripe/stagehand/package.json @@ -7,8 +7,9 @@ "postinstall": "playwright install" }, "dependencies": { - "@browserbasehq/sdk": "2.3.0", - "@browserbasehq/stagehand": "1.12.0", + "@browserbasehq/sdk": "^2.6.0", + "@browserbasehq/stagehand": "^3.2.0", + "stripe": "^17.7.0", "@playwright/test": "^1.49.1", "boxen": "^8.0.1", "chalk": "^5.3.0", diff --git a/examples/integrations/stripe/stagehand/stagehand.config.ts b/examples/integrations/stripe/stagehand/stagehand.config.ts index 59a56e3..d56a294 100644 --- a/examples/integrations/stripe/stagehand/stagehand.config.ts +++ b/examples/integrations/stripe/stagehand/stagehand.config.ts @@ -1,65 +1,24 @@ -import type { ConstructorParams, LogLine } from "@browserbasehq/stagehand"; +import type { LogLine, V3Options } from "@browserbasehq/stagehand"; import dotenv from "dotenv"; -false -false dotenv.config(); -const StagehandConfig: ConstructorParams = { +const StagehandConfig: V3Options = { env: "BROWSERBASE", - apiKey: process.env.BROWSERBASE_API_KEY /* API key for authentication */, - projectId: process.env.BROWSERBASE_PROJECT_ID /* Project identifier */, - debugDom: undefined /* Enable DOM debugging features */, - headless: false /* Run browser in headless mode */, - logger: (message: LogLine) => - console.log(logLineToString(message)) /* Custom logging function */, - domSettleTimeoutMs: 30_000 /* Timeout for DOM to settle in milliseconds */, + apiKey: process.env.BROWSERBASE_API_KEY, + projectId: process.env.BROWSERBASE_PROJECT_ID, + domSettleTimeout: 30_000, + logger: (message: LogLine) => console.log(logLineToString(message)), + model: "openai/gpt-4o", browserbaseSessionCreateParams: { projectId: process.env.BROWSERBASE_PROJECT_ID!, }, - enableCaching: undefined /* Enable caching functionality */, - browserbaseSessionID: - undefined /* Session ID for resuming Browserbase sessions */, - modelName: "gpt-4o" /* Name of the model to use */, - modelClientOptions: { - apiKey: process.env.OPENAI_API_KEY, - } /* Configuration options for the model client */, - - + browserbaseSessionID: undefined, }; export default StagehandConfig; -/** - * Custom logging function that you can use to filter logs. - * - * General pattern here is that `message` will always be unique with no params - * Any param you would put in a log is in `auxiliary`. - * - * For example, an error log looks like this: - * - * ``` - * { - * category: "error", - * message: "Some specific error occurred", - * auxiliary: { - * message: { value: "Error message", type: "string" }, - * trace: { value: "Error trace", type: "string" } - * } - * } - * ``` - * - * You can then use `logLineToString` to filter for a specific log pattern like - * - * ``` - * if (logLine.message === "Some specific error occurred") { - * console.log(logLineToString(logLine)); - * } - * ``` - */ export function logLineToString(logLine: LogLine): string { - // If you want more detail, set this to false. However, this will make the logs - // more verbose and harder to read. const HIDE_AUXILIARY = true; try { @@ -68,7 +27,6 @@ export function logLineToString(logLine: LogLine): string { return `${timestamp}::[stagehand:${logLine.category}] ${logLine.message}\n ${logLine.auxiliary.error.value}\n ${logLine.auxiliary.trace.value}`; } - // If we want to hide auxiliary information, we don't add it to the log return `${timestamp}::[stagehand:${logLine.category}] ${logLine.message} ${ logLine.auxiliary && !HIDE_AUXILIARY ? JSON.stringify(logLine.auxiliary) @@ -78,4 +36,4 @@ export function logLineToString(logLine: LogLine): string { console.error(`Error logging line:`, error); return "error logging line"; } -} \ No newline at end of file +} diff --git a/examples/integrations/stripe/stagehand/utils.ts b/examples/integrations/stripe/stagehand/utils.ts index 2ef7c26..4708ce8 100644 --- a/examples/integrations/stripe/stagehand/utils.ts +++ b/examples/integrations/stripe/stagehand/utils.ts @@ -1,4 +1,9 @@ -import { ObserveResult, Page } from "@browserbasehq/stagehand"; +import type { + Action, + ObserveResult, + Page, + Stagehand, +} from "@browserbasehq/stagehand"; import boxen from "boxen"; import chalk from "chalk"; import fs from "fs/promises"; @@ -10,15 +15,10 @@ export function announce(message: string, title?: string) { padding: 1, margin: 3, title: title || "Stagehand", - }) + }), ); } -/** - * Get an environment variable and throw an error if it's not found - * @param name - The name of the environment variable - * @returns The value of the environment variable - */ export function getEnvVar(name: string, required = true): string | undefined { const value = process.env[name]; if (!value && required) { @@ -27,12 +27,6 @@ export function getEnvVar(name: string, required = true): string | undefined { return value; } -/** - * Validate a Zod schema against some data - * @param schema - The Zod schema to validate against - * @param data - The data to validate - * @returns Whether the data is valid against the schema - */ export function validateZodSchema(schema: z.ZodTypeAny, data: unknown) { try { schema.parse(data); @@ -42,11 +36,9 @@ export function validateZodSchema(schema: z.ZodTypeAny, data: unknown) { } } -export async function drawObserveOverlay(page: Page, results: ObserveResult[]) { - // Convert single xpath to array for consistent handling - const xpathList = results.map((result) => result.selector); +export async function drawObserveOverlay(page: Page, results: ObserveResult) { + const xpathList = results.map((result: Action) => result.selector); - // Filter out empty xpaths const validXpaths = xpathList.filter((xpath) => xpath !== "xpath="); await page.evaluate((selectors) => { @@ -59,7 +51,7 @@ export async function drawObserveOverlay(page: Page, results: ObserveResult[]) { document, null, XPathResult.FIRST_ORDERED_NODE_TYPE, - null + null, ).singleNodeValue; } else { element = document.querySelector(selector); @@ -84,7 +76,6 @@ export async function drawObserveOverlay(page: Page, results: ObserveResult[]) { } export async function clearOverlays(page: Page) { - // remove existing stagehandObserve attributes await page.evaluate(() => { const elements = document.querySelectorAll('[stagehandObserve="true"]'); elements.forEach((el) => { @@ -97,39 +88,55 @@ export async function clearOverlays(page: Page) { }); } -export async function simpleCache( - instruction: string, - actionToCache: ObserveResult -) { - // Save action to cache.json +export async function simpleCache(instruction: string, actionToCache: Action) { try { - // Read existing cache if it exists - let cache: Record = {}; + let cache: Record = {}; try { const existingCache = await fs.readFile("cache.json", "utf-8"); cache = JSON.parse(existingCache); - } catch (error) { - // File doesn't exist yet, use empty cache + } catch { + // no file yet } - // Add new action to cache cache[instruction] = actionToCache; - // Write updated cache to file await fs.writeFile("cache.json", JSON.stringify(cache, null, 2)); } catch (error) { console.error(chalk.red("Failed to save to cache:"), error); } } -export async function readCache( - instruction: string -): Promise { +export async function readCache(instruction: string): Promise { try { const existingCache = await fs.readFile("cache.json", "utf-8"); - const cache: Record = JSON.parse(existingCache); + const cache: Record = JSON.parse(existingCache); return cache[instruction] || null; - } catch (error) { + } catch { return null; } } + +export async function actWithCache( + stagehand: Stagehand, + page: Page, + instruction: string, +): Promise { + const cachedAction = await readCache(instruction); + if (cachedAction) { + console.log(chalk.blue("Using cached action for:"), instruction); + await stagehand.act(cachedAction); + return; + } + + const results = await stagehand.observe(instruction); + console.log(chalk.blue("Got results:"), results); + + const actionToCache = results[0]; + console.log(chalk.blue("Taking cacheable action:"), actionToCache); + await simpleCache(instruction, actionToCache); + await drawObserveOverlay(page, results); + await page.waitForTimeout(1000); + await clearOverlays(page); + + await stagehand.act(actionToCache); +} diff --git a/examples/integrations/temporal/.env.example b/examples/integrations/temporal/.env.example new file mode 100644 index 0000000..cbc48cf --- /dev/null +++ b/examples/integrations/temporal/.env.example @@ -0,0 +1,18 @@ +# Temporal Server Configuration +TEMPORAL_ADDRESS=localhost:7233 +TEMPORAL_NAMESPACE=default + +# Stagehand Configuration +# Get these from https://www.browserbase.com/ +BROWSERBASE_API_KEY=your_browserbase_api_key_here +BROWSERBASE_PROJECT_ID=your_browserbase_project_id_here + +# LLM Configuration (choose one) +# OpenAI (recommended) +OPENAI_API_KEY=your_openai_api_key_here + +# OR Anthropic +ANTHROPIC_API_KEY=your_anthropic_api_key_here + +# Research Output Directory +RESEARCH_OUTPUT_DIR=./research_outputs \ No newline at end of file diff --git a/examples/integrations/temporal/.eslintignore b/examples/integrations/temporal/.eslintignore new file mode 100644 index 0000000..7bd99a4 --- /dev/null +++ b/examples/integrations/temporal/.eslintignore @@ -0,0 +1,3 @@ +node_modules +lib +.eslintrc.js \ No newline at end of file diff --git a/examples/integrations/temporal/.eslintrc.js b/examples/integrations/temporal/.eslintrc.js new file mode 100644 index 0000000..ab1b239 --- /dev/null +++ b/examples/integrations/temporal/.eslintrc.js @@ -0,0 +1,50 @@ +const { builtinModules } = require('module'); + +const ALLOWED_NODE_BUILTINS = new Set(['assert']); + +module.exports = { + root: true, + parser: '@typescript-eslint/parser', + parserOptions: { + project: './tsconfig.json', + tsconfigRootDir: __dirname, + }, + plugins: ['@typescript-eslint', 'deprecation'], + extends: [ + 'eslint:recommended', + 'plugin:@typescript-eslint/eslint-recommended', + 'plugin:@typescript-eslint/recommended', + 'prettier', + ], + rules: { + // recommended for safety + '@typescript-eslint/no-floating-promises': 'error', // forgetting to await Activities and Workflow APIs is bad + 'deprecation/deprecation': 'warn', + + // code style preference + 'object-shorthand': ['error', 'always'], + + // relaxed rules, for convenience + '@typescript-eslint/no-unused-vars': [ + 'warn', + { + argsIgnorePattern: '^_', + varsIgnorePattern: '^_', + }, + ], + '@typescript-eslint/no-explicit-any': 'off', + }, + overrides: [ + { + files: ['src/workflows.ts', 'src/workflows-*.ts', 'src/workflows/*.ts'], + rules: { + 'no-restricted-imports': [ + 'error', + ...builtinModules + .filter((m) => !ALLOWED_NODE_BUILTINS.has(m)) + .flatMap((m) => [m, `node:${m}`]), + ], + }, + }, + ], +}; diff --git a/examples/integrations/temporal/.gitignore b/examples/integrations/temporal/.gitignore new file mode 100644 index 0000000..1b4957e --- /dev/null +++ b/examples/integrations/temporal/.gitignore @@ -0,0 +1,9 @@ +lib +node_modules +coverage + +.env + +tmp + +/research_outputs \ No newline at end of file diff --git a/examples/integrations/temporal/.nvmrc b/examples/integrations/temporal/.nvmrc new file mode 100644 index 0000000..25bf17f --- /dev/null +++ b/examples/integrations/temporal/.nvmrc @@ -0,0 +1 @@ +18 \ No newline at end of file diff --git a/examples/integrations/temporal/.prettierrc b/examples/integrations/temporal/.prettierrc new file mode 100644 index 0000000..0176969 --- /dev/null +++ b/examples/integrations/temporal/.prettierrc @@ -0,0 +1 @@ +singleQuote: true diff --git a/examples/integrations/temporal/README.md b/examples/integrations/temporal/README.md new file mode 100644 index 0000000..3efa328 --- /dev/null +++ b/examples/integrations/temporal/README.md @@ -0,0 +1,104 @@ +# Temporal + Stagehand Integration + +A best practices example showing how Temporal handles browser automation failures with automatic retries using atomic, idempotent activities. + +## What it does + +- Uses Stagehand to perform Google searches in a real browser +- Each individual task is encapsulated within a Temporal Activity following best practices for atomicity and idempotency +- If any individual task fails, Temporal will automatically retry it, resulting in reliable browser automation +- Clean, maintainable code following Temporal patterns + +## Temporal Best Practices Demonstrated + +### Atomic Activities +Each Temporal activity performs a single, well-defined task: +1. **initializeBrowser** - Creates and initializes browser session +2. **navigateToSearchPage** - Navigates to Google +3. **executeSearch** - Types query and submits search +4. **extractSearchResults** - Extracts and validates results +5. **cleanupBrowser** - Closes browser session +6. **formatResults** - Formats results for display + +### Why Atomic Activities? +- **Efficient retries**: If extraction fails after search succeeds, only extraction is retried +- **Better performance**: No need to repeat successful steps +- **Clearer debugging**: Each activity's purpose is obvious +- **Flexible retry policies**: Different activities can have different retry strategies + +### Idempotent Design +- Browser sessions are reused if already initialized +- Cleanup handles already-closed sessions gracefully +- Navigation always results in the same state +- Formatting produces consistent output + +## Setup + +1. Install dependencies: +```bash +npm install +``` + +2. Set up environment variables in `.env`: +``` +BROWSERBASE_API_KEY=your_api_key +BROWSERBASE_PROJECT_ID=your_project_id +OPENAI_API_KEY=your_openai_key # or ANTHROPIC_API_KEY depending on the model you choose +``` + +3. Start Temporal (if not already running): +```bash +temporal server start-dev +``` + +## Running the Example + +1. Start the worker in one terminal: +```bash +npm run worker +``` + +2. Run a search in another terminal: +```bash +npm run demo # Default search +npm run demo "your search term" # Custom search +``` + +## How it Works + +### Activities (`research-activities.ts`) +Each activity is designed to be: +- **Atomic**: Does one thing only +- **Idempotent**: Can be safely retried +- **Focused**: Clear single responsibility + +### Workflow (`workflows.ts`) +- Orchestrates the atomic activities in sequence +- Uses tailored retry policies for each activity type +- Handles cleanup in a finally block +- Provides clear progress logging + +### Worker (`research-worker.ts`) +- Processes workflow tasks +- Limits to 2 concurrent browser sessions +- Simple configuration focused on essentials + +## Retry Behavior + +Each activity has a custom retry policy based on its characteristics: + +- **Initialize Browser**: 5 attempts, 2-10 second intervals +- **Navigate**: 8 attempts, 1-5 second intervals (fast retries) +- **Execute Search**: 10 attempts, 2-15 second intervals +- **Extract Results**: 10 attempts, 3-20 second intervals (most likely to fail) +- **Cleanup**: 3 attempts, 1-3 second intervals +- **Format**: 2 attempts, minimal retry (deterministic) + +## Benefits + +- **Simplicity**: Clean code without complex error handling +- **Efficiency**: Only failed steps are retried +- **Reliability**: Temporal ensures tasks complete or fail definitively +- **Visibility**: Monitor progress in Temporal Web UI at http://localhost:8233 +- **Maintainability**: Each activity can be tested and updated independently +- **Flexibility**: Easy to add new steps or modify retry behavior diff --git a/examples/integrations/temporal/jest.config.js b/examples/integrations/temporal/jest.config.js new file mode 100644 index 0000000..bb4ba2f --- /dev/null +++ b/examples/integrations/temporal/jest.config.js @@ -0,0 +1,7 @@ +/** @type {import('ts-jest/dist/types').InitialOptionsTsJest} */ +module.exports = { + preset: 'ts-jest', + testEnvironment: 'node', + modulePathIgnorePatterns: ['lib'], + clearMocks: true, +}; diff --git a/examples/integrations/temporal/package-lock.json b/examples/integrations/temporal/package-lock.json new file mode 100644 index 0000000..3b5ae1f --- /dev/null +++ b/examples/integrations/temporal/package-lock.json @@ -0,0 +1,6061 @@ +{ + "name": "temporal-money-transfer", + "version": "0.1.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "temporal-money-transfer", + "version": "0.1.0", + "dependencies": { + "@anthropic-ai/sdk": "^0.52.0", + "@browserbasehq/stagehand": "^2.4.4", + "@temporalio/activity": "^1.11.8", + "@temporalio/client": "^1.11.8", + "@temporalio/common": "^1.11.8", + "@temporalio/worker": "^1.11.8", + "@temporalio/workflow": "^1.11.8", + "nanoid": "3.x", + "playwright": "^1.52.0", + "zod": "^3.25.28" + }, + "devDependencies": { + "@tsconfig/node18": "^1.0.0", + "@typescript-eslint/eslint-plugin": "^6.7.3", + "@typescript-eslint/parser": "^6.7.3", + "eslint": 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+ } + } + } +} diff --git a/examples/integrations/temporal/package.json b/examples/integrations/temporal/package.json new file mode 100644 index 0000000..0d03cbc --- /dev/null +++ b/examples/integrations/temporal/package.json @@ -0,0 +1,49 @@ +{ + "name": "temporal-money-transfer", + "version": "0.1.0", + "private": true, + "scripts": { + "build": "tsc --build", + "build.watch": "tsc --build --watch", + "format": "prettier --write .", + "lint": "eslint src", + "test": "echo \"No tests configured\"", + "worker": "ts-node src/research-worker.ts", + "worker.watch": "nodemon src/research-worker.ts", + "demo": "ts-node src/demo.ts", + "demo:custom": "ts-node src/demo.ts" + }, + "nodemonConfig": { + "execMap": { + "ts": "ts-node" + }, + "ext": "ts", + "watch": [ + "src" + ] + }, + "dependencies": { + "@anthropic-ai/sdk": "^0.52.0", + "@browserbasehq/stagehand": "^2.4.4", + "@temporalio/activity": "^1.11.8", + "@temporalio/client": "^1.11.8", + "@temporalio/common": "^1.11.8", + "@temporalio/worker": "^1.11.8", + "@temporalio/workflow": "^1.11.8", + "nanoid": "3.x", + "playwright": "^1.52.0", + "zod": "^3.25.28" + }, + "devDependencies": { + "@tsconfig/node18": "^1.0.0", + "@typescript-eslint/eslint-plugin": "^6.7.3", + "@typescript-eslint/parser": "^6.7.3", + "eslint": "^7.32.0", + "eslint-config-prettier": "^8.3.0", + "eslint-plugin-deprecation": "^1.2.1", + "nodemon": "^2.0.12", + "prettier": "2.8.8", + "ts-node": "^10.9.1", + "typescript": "^4.9.5" + } +} diff --git a/examples/integrations/temporal/src/demo.ts b/examples/integrations/temporal/src/demo.ts new file mode 100644 index 0000000..51528c3 --- /dev/null +++ b/examples/integrations/temporal/src/demo.ts @@ -0,0 +1,28 @@ +import { Client } from '@temporalio/client'; +import { searchWithRetry } from './workflows'; + +async function runDemo() { + const client = new Client(); + const query = process.argv[2] || 'TypeScript web scraping'; + + try { + const handle = await client.workflow.start(searchWithRetry, { + args: [query], + taskQueue: 'browser-automation', + workflowId: `resilience-test-${Date.now()}`, + }); + + console.log(`Started workflow: ${handle.workflowId}`); + console.log(`Monitor at: http://localhost:8233/namespaces/default/workflows/${handle.workflowId}`); + + const result = await handle.result(); + console.log(result); + + } catch (error: any) { + console.error('Error:', error.message); + } +} + +if (require.main === module) { + runDemo().catch(console.error); +} \ No newline at end of file diff --git a/examples/integrations/temporal/src/research-activities.ts b/examples/integrations/temporal/src/research-activities.ts new file mode 100644 index 0000000..4cf5090 --- /dev/null +++ b/examples/integrations/temporal/src/research-activities.ts @@ -0,0 +1,313 @@ +import { Stagehand, ConstructorParams } from '@browserbasehq/stagehand'; +import { z } from 'zod'; + +export interface SearchResult { + title: string; + snippet: string; +} + +export interface BrowserSession { + browserbaseSessionId: string; + attemptId: string; +} + +// Simulate network disconnection with lower failure rate for better success +function simulateNetworkDisconnect(stage: string): void { + // 15% chance of network failure - more realistic and allows eventual success + if (Math.random() < 0.15) { + const failures = [ + 'ECONNRESET: Connection reset by peer', + 'ETIMEDOUT: Connection timed out', + 'ENOTFOUND: DNS lookup failed', + 'ECONNREFUSED: Connection refused' + ]; + const failure = failures[Math.floor(Math.random() * failures.length)]; + console.error(`Network disconnection during ${stage}: ${failure}`); + throw new Error(`Network failure during ${stage}: ${failure}`); + } + console.log(`Network OK for ${stage}`); +} + +// Validate with fallback - more lenient to ensure we get data +function validateSearchResults(results: any[]): SearchResult[] { + if (!results || results.length === 0) { + throw new Error('No search results extracted - page structure may have changed'); + } + + console.log(`Validating ${results.length} raw results...`); + + // First try strict validation + let validResults = results.filter(r => + r.title && + r.snippet && + r.title.length > 5 && + r.snippet.length > 10 && + r.title !== 'null' && // Reject 'null' string values + r.snippet !== 'null' + ); + + // Fallback to more lenient validation if strict fails + if (validResults.length === 0) { + console.log('Strict validation failed, trying lenient validation...'); + validResults = results.filter(r => + r.title && + r.title.length > 2 && + r.snippet && + r.title !== 'null' && // Still reject 'null' string values + r.snippet !== 'null' + ).map(r => ({ + title: r.title, + snippet: r.snippet || r.description || 'Description not available' + })); + } + + if (validResults.length === 0) { + console.error('Raw extraction data:', JSON.stringify(results, null, 2)); + // Check if we hit a CAPTCHA or other blocking page + const hasNullValues = results.some(r => + r.title === 'null' || r.snippet === 'null' || + r.title === null || r.snippet === null + ); + if (hasNullValues) { + throw new Error('Extraction returned null values - likely hit CAPTCHA or blocking page. Retrying...'); + } + throw new Error('No valid search results found - extracted data was completely malformed'); + } + + console.log(`Validated ${validResults.length} search results`); + return validResults; +} + +/** + * Activity 1: Initialize browser session + * Atomic: Only responsible for creating and initializing a browser session + * Idempotent: Returns session data that can be used to reconnect + */ +export async function initializeBrowser(): Promise { + const attemptId = Math.random().toString(36).substring(2, 8); + console.log(`\n[${attemptId}] Initializing new browser session`); + + try { + // Network failure during initialization (15% chance) + simulateNetworkDisconnect('browser initialization'); + + const config: ConstructorParams = { + verbose: 0, + domSettleTimeoutMs: 8000, + env: "BROWSERBASE", + apiKey: process.env.BROWSERBASE_API_KEY, + modelName: "openai/gpt-4o", + modelClientOptions: { + apiKey: process.env.OPENAI_API_KEY, + }, + browserbaseSessionCreateParams: { + // Only available in paid plans + // proxies: true, + projectId: process.env.BROWSERBASE_PROJECT_ID!, + browserSettings: { + viewport: { + width: 1024, + height: 768 + }, + // Only available on Scale Plans + // advancedStealth: true + } + }, + }; + + console.log(`[${attemptId}] Creating new browser session...`); + const stagehand = new Stagehand(config); + await stagehand.init(); + + // Get the Browserbase session ID to reconnect later + const browserbaseSessionId = stagehand.browserbaseSessionID; + if (!browserbaseSessionId) { + throw new Error('Failed to get Browserbase session ID'); + } + + console.log(`[${attemptId}] Browser session initialized with ID: ${browserbaseSessionId}`); + + + return { browserbaseSessionId, attemptId }; + } catch (error: any) { + console.error(`[${attemptId}] Failed to initialize browser:`, error.message); + throw error; + } +} + +/** + * Helper function to reconnect to an existing Browserbase session + */ +async function reconnectToSession(session: BrowserSession): Promise { + console.log(`[${session.attemptId}] Reconnecting to session: ${session.browserbaseSessionId}`); + + const config: ConstructorParams = { + verbose: 1, + domSettleTimeoutMs: 8000, + env: "BROWSERBASE", + apiKey: process.env.BROWSERBASE_API_KEY, + browserbaseSessionID: session.browserbaseSessionId, + }; + + const stagehand = new Stagehand(config); + await stagehand.init(); + + // Browserbase requires at least one page in the session + // If reconnecting to a session with no pages, we need to create one + if (!stagehand.page) { + console.log(`[${session.attemptId}] No page found in session, creating new page...`); + throw new Error('Failed to create page in Browserbase session'); + } + + return stagehand; +} + +/** + * Activity 2: Navigate to search page + * Atomic: Only responsible for navigation + * Idempotent: Multiple calls result in same state (on Google homepage) + */ +export async function navigateToSearchPage(session: BrowserSession): Promise { + console.log(`\n[${session.attemptId}] Navigating to search page for session: ${session.browserbaseSessionId}`); + + let stagehand: Stagehand | null = null; + + try { + // Network failure during navigation (15% chance) + simulateNetworkDisconnect('page navigation'); + + stagehand = await reconnectToSession(session); + + console.log(`[${session.attemptId}] Navigating to Brave...`); + await stagehand.page.goto('https://search.brave.com/'); + console.log(`[${session.attemptId}] Successfully navigated to Brave`); + + } catch (error: any) { + console.error(`[${session.attemptId}] Navigation failed:`, error.message); + throw error; + } +} + +/** + * Activity 3: Execute search + * Atomic: Only responsible for performing the search + * Idempotent: Same query produces same search action + */ +export async function executeSearch(session: BrowserSession, query: string): Promise { + console.log(`\n[${session.attemptId}] Executing search for: "${query}"`); + + let stagehand: Stagehand | null = null; + + try { + // Network failure during search (15% chance) + simulateNetworkDisconnect('search execution'); + + stagehand = await reconnectToSession(session); + + console.log(`[${session.attemptId}] Typing search query...`); + await stagehand.page.act({ + action: `Type "${query}" in the search box` + }); + + await stagehand.page.act({ + action: "Click the enter button" + }); + + // Wait for search results to load + console.log(`[${session.attemptId}] Waiting for results to load...`); + await stagehand.page.waitForTimeout(4000); + + } catch (error: any) { + console.error(`[${session.attemptId}] Search execution failed:`, error.message); + throw error; + } +} + +/** + * Activity 4: Extract search results + * Atomic: Only responsible for extraction and validation + * Idempotent: Multiple extractions from same page state produce same results + */ +export async function extractSearchResults(session: BrowserSession): Promise { + console.log(`\n[${session.attemptId}] Extracting search results...`); + + let stagehand: Stagehand | null = null; + + try { + // Network failure during extraction (15% chance) + simulateNetworkDisconnect('data extraction'); + + stagehand = await reconnectToSession(session); + + // Check if we've been redirected to a CAPTCHA or blocking page + const currentUrl = stagehand.page.url(); + console.log(`[${session.attemptId}] Current URL: ${currentUrl}`); + + if (currentUrl.includes('/sorry/') || currentUrl.includes('captcha')) { + throw new Error('Detected CAPTCHA/blocking page - need to retry with new session'); + } + + console.log(`[${session.attemptId}] Performing extraction...`); + + const extraction = await stagehand.page.extract({ + instruction: `Extract the top 3 organic search results from Google. + For each result, get: + - title: The main headline/title text + - snippet: The description text below the title + Ignore ads, images, shopping results, and featured snippets.`, + schema: z.object({ + results: z.array(z.object({ + title: z.string().describe('The main headline of the search result'), + snippet: z.string().describe('The description text'), + })).min(1) + }) + }); + + console.log(`[${session.attemptId}] Raw extraction:`, JSON.stringify(extraction, null, 2)); + + // Validate the extracted data + const validResults = validateSearchResults(extraction.results); + + console.log(`[${session.attemptId}] Successfully extracted ${validResults.length} search results!`); + return validResults; + + } catch (error: any) { + console.error(`[${session.attemptId}] Extraction failed:`, error.message); + throw error; + } +} + +/** + * Activity 5: Cleanup browser session + * Atomic: Only responsible for cleanup + * Idempotent: Multiple calls safely handle already-closed sessions + */ +export async function cleanupBrowser(session: BrowserSession): Promise { + console.log(`\n[${session.attemptId}] Cleaning up browser session: ${session.browserbaseSessionId}`); + + try { + const stagehand = await reconnectToSession(session); + await stagehand.close(); + console.log(`[${session.attemptId}] Browser session ${session.browserbaseSessionId} cleaned up`); + } catch (e) { + console.warn(`[${session.attemptId}] Failed to close browser session:`, e); + // Session might already be closed or expired - that's ok + } +} + +/** + * Activity 6: Format results + * Atomic: Only responsible for formatting + * Idempotent: Same input produces same output + */ +export async function formatResults(results: SearchResult[]): Promise { + if (results.length === 0) { + throw new Error('Cannot format empty results - this indicates a data extraction issue'); + } + + const formatted = results.map((r, i) => + `${i + 1}. ${r.title}\n ${r.snippet}\n` + ).join('\n'); + + return `Successfully found ${results.length} search results:\n\n${formatted}`; +} \ No newline at end of file diff --git a/examples/integrations/temporal/src/research-worker.ts b/examples/integrations/temporal/src/research-worker.ts new file mode 100644 index 0000000..6e852e7 --- /dev/null +++ b/examples/integrations/temporal/src/research-worker.ts @@ -0,0 +1,24 @@ +import { Worker } from '@temporalio/worker'; +import * as activities from './research-activities'; + +async function run() { + const worker = await Worker.create({ + workflowsPath: require.resolve('./workflows'), + activities, + taskQueue: 'browser-automation', + maxConcurrentActivityTaskExecutions: 2, + }); + + // Handle worker shutdown gracefully + process.on('SIGINT', async () => { + worker.shutdown(); + process.exit(0); + }); + + await worker.run(); +} + +run().catch((err) => { + console.error('Worker failed to start:', err); + process.exit(1); +}); \ No newline at end of file diff --git a/examples/integrations/temporal/src/workflows.ts b/examples/integrations/temporal/src/workflows.ts new file mode 100644 index 0000000..338e61e --- /dev/null +++ b/examples/integrations/temporal/src/workflows.ts @@ -0,0 +1,132 @@ +import { proxyActivities, workflowInfo } from '@temporalio/workflow'; +import type * as activities from './research-activities'; + +export async function searchWithRetry(query: string): Promise { + // Get workflow info for logging + const info = workflowInfo(); + + // Quick retry for initialization - might fail due to network + const { initializeBrowser } = proxyActivities({ + retry: { + initialInterval: '2 seconds', + maximumInterval: '10 seconds', + backoffCoefficient: 1.5, + maximumAttempts: 5, + nonRetryableErrorTypes: [], + }, + startToCloseTimeout: '1 minute', + }); + + // Quick retry for navigation - usually fast + const { navigateToSearchPage } = proxyActivities({ + retry: { + initialInterval: '1 second', + maximumInterval: '5 seconds', + backoffCoefficient: 1.5, + maximumAttempts: 8, + nonRetryableErrorTypes: [], + }, + startToCloseTimeout: '30 seconds', + }); + + // Standard retry for search execution + const { executeSearch } = proxyActivities({ + retry: { + initialInterval: '2 seconds', + maximumInterval: '15 seconds', + backoffCoefficient: 1.8, + maximumAttempts: 10, + nonRetryableErrorTypes: [], + }, + startToCloseTimeout: '1 minute', + }); + + // More aggressive retry for extraction - most likely to fail + const { extractSearchResults } = proxyActivities({ + retry: { + initialInterval: '3 seconds', + maximumInterval: '20 seconds', + backoffCoefficient: 2, + maximumAttempts: 10, + nonRetryableErrorTypes: [], + }, + startToCloseTimeout: '2 minutes', + }); + + // Cleanup should always succeed quickly + const { cleanupBrowser } = proxyActivities({ + retry: { + initialInterval: '1 second', + maximumInterval: '3 seconds', + backoffCoefficient: 1.2, + maximumAttempts: 3, + nonRetryableErrorTypes: [], + }, + startToCloseTimeout: '10 seconds', + }); + + // Formatting is deterministic - minimal retry + const { formatResults } = proxyActivities({ + retry: { + initialInterval: '1 second', + maximumInterval: '2 seconds', + backoffCoefficient: 1, + maximumAttempts: 2, + nonRetryableErrorTypes: [], + }, + startToCloseTimeout: '5 seconds', + }); + + console.log(`Starting resilient search workflow for: "${query}"`); + console.log(`Workflow ID: ${info.workflowId}`); + console.log(`\nUsing atomic activities with tailored retry policies:`); + console.log(`- Initialize browser: up to 5 attempts`); + console.log(`- Navigate to page: up to 8 attempts (fast retries)`); + console.log(`- Execute search: up to 10 attempts`); + console.log(`- Extract results: up to 10 attempts (most likely to fail)`); + console.log(`- Cleanup: up to 3 attempts\n`); + + let browserSession; + let searchResults; + + try { + // Step 1: Initialize browser + console.log('Step 1: Initializing browser session...'); + browserSession = await initializeBrowser(); + + // Step 2: Navigate to search page + console.log('Step 2: Navigating to search page...'); + await navigateToSearchPage(browserSession); + + // Step 3: Execute search + console.log(`Step 3: Executing search for "${query}"...`); + await executeSearch(browserSession, query); + + // Step 4: Extract results + console.log('Step 4: Extracting search results...'); + searchResults = await extractSearchResults(browserSession); + + // Step 5: Format results + console.log('Step 5: Formatting results...'); + const formatted = await formatResults(searchResults); + + console.log('Workflow completed successfully!'); + return formatted; + + } catch (error: any) { + console.error(`Workflow failed:`, error.message); + throw error; + + } finally { + // Always try to cleanup the browser session + if (browserSession) { + try { + console.log('Cleaning up browser session...'); + await cleanupBrowser(browserSession); + } catch (cleanupError) { + console.warn('Failed to cleanup browser session:', cleanupError); + // Don't rethrow - cleanup failure shouldn't fail the workflow + } + } + } +} \ No newline at end of file diff --git a/examples/integrations/temporal/tsconfig.json b/examples/integrations/temporal/tsconfig.json new file mode 100644 index 0000000..adfc9a4 --- /dev/null +++ b/examples/integrations/temporal/tsconfig.json @@ -0,0 +1,12 @@ +{ + "extends": "@tsconfig/node18/tsconfig.json", + "version": "4.4.2", + "compilerOptions": { + "declaration": true, + "declarationMap": true, + "sourceMap": true, + "rootDir": "./src", + "outDir": "./lib" + }, + "include": ["src/**/*.ts"] +} diff --git a/examples/integrations/trigger/.env.example b/examples/integrations/trigger/.env.example new file mode 100644 index 0000000..e1b4869 --- /dev/null +++ b/examples/integrations/trigger/.env.example @@ -0,0 +1,18 @@ +# Trigger.dev Configuration +TRIGGER_SECRET_KEY=your-trigger-secret-key + +# Browserbase Configuration (for web scraping) +BROWSERBASE_API_KEY=your-browserbase-api-key +BROWSERBASE_PROJECT_ID=your-browserbase-project-id + +# Cloudflare R2 Storage Configuration (for file uploads) +S3_ENDPOINT=https://your-account-id.r2.cloudflarestorage.com +R2_ACCESS_KEY_ID=your-r2-access-key-id +R2_SECRET_ACCESS_KEY=your-r2-secret-access-key +S3_BUCKET=your-r2-bucket-name + +# OpenAI Configuration (for AI summarization) +OPENAI_API_KEY=your-openai-api-key + +# Resend Configuration (for email delivery) +RESEND_API_KEY=your-resend-api-key \ No newline at end of file diff --git a/examples/integrations/trigger/README.md b/examples/integrations/trigger/README.md new file mode 100644 index 0000000..0a199fc --- /dev/null +++ b/examples/integrations/trigger/README.md @@ -0,0 +1,208 @@ +# Browserbase + Trigger.dev Integration + +## Overview + +Trigger.dev is a background job framework that enables you to create, run, and monitor background tasks with built-in retry logic, scheduling, and observability. This integration showcases multiple use cases: + +- **PDF Processing**: Convert PDFs to images and upload to cloud storage +- **Web Scraping**: Extract data from websites using Puppeteer and Browserbase +- **Document Generation**: Create PDFs from React components +- **Email Automation**: Scheduled tasks with email notifications +- **Task Hierarchies**: Complex workflows with parent-child task relationships + +## Task Examples + +### 1. PDF to Image Conversion (`pdf-to-image.tsx`) +Converts PDF documents to PNG images using MuPDF and uploads them to Cloudflare R2 storage. + +**Features:** +- Downloads PDF from URL +- Converts each page to PNG using `mutool` +- Uploads images to R2 bucket +- Returns array of image URLs +- Automatic cleanup of temporary files + +### 2. Puppeteer Web Scraping (`puppeteer-*.tsx`) + +#### Basic Page Title Extraction +Simple example that launches Puppeteer, navigates to Google, and logs the page title. + +#### Scraping with Browserbase Proxy +Uses Browserbase's cloud browser infrastructure to scrape data through a proxy: +- Connects to Browserbase WebSocket endpoint +- Scrapes GitHub star count from trigger.dev website +- Handles errors gracefully + +#### Webpage to PDF Generation +Converts web pages to PDF documents: +- Navigates to target URL +- Generates PDF from webpage +- Uploads PDF to cloud storage + +### 3. React PDF Generation (`react-pdf.tsx`) +Creates PDF documents using React components and @react-pdf/renderer: +- Accepts text payload +- Renders PDF using React components +- Uploads generated PDF to cloud storage +- Returns PDF URL + +### 4. Hacker News Summarization (`summarize-hn.tsx`) +Scheduled task that runs weekdays at 9 AM (London time): + +**Workflow:** +1. **Scrapes Hacker News** - Gets top 3 articles +2. **Batch Processing** - Triggers child tasks for each article +3. **Content Extraction** - Scrapes full article content +4. **AI Summarization** - Uses OpenAI GPT-4 to create summaries +5. **Email Delivery** - Sends formatted email with summaries + +**Features:** +- Scheduled execution with cron syntax +- Batch task processing with `batchTriggerAndWait` +- Retry logic with exponential backoff +- Request interception to optimize scraping +- Email templates using React Email + +### 5. Task Hierarchy (`taskHierarchy.ts`) +Demonstrates complex task workflows with parent-child relationships: +- **Root Task** → **Child Task** → **Grandchild Task** → **Great-grandchild Task** +- Shows both synchronous (`triggerAndWait`) and asynchronous (`trigger`) patterns +- Batch processing capabilities +- Run hierarchy logging and visualization + +## Configuration + +### Trigger.dev Config (`trigger.config.ts`) +```typescript + +export default defineConfig({ + project: "proj_ljbidlufugyxuhjxzkyy", // your Trigger Project ID + logLevel: "log", + retries: { + enabledInDev: true, + default: { + maxAttempts: 3, + minTimeoutInMs: 1000, + maxTimeoutInMs: 10000, + factor: 2, + randomize: true, + }, + }, + build: { + extensions: [ + aptGet({ packages: ["mupdf-tools", "curl"] }), + puppeteer(), + ], + }, +}); +``` + +**Key Features:** +- **System Dependencies**: Installs MuPDF tools and curl via `aptGet` extension +- **Puppeteer Extension**: Automatically sets up Puppeteer with Chrome +- **Retry Configuration**: Global retry settings with exponential backoff +- **Development Mode**: Retries enabled in development environment + +## Dependencies + +Key packages used in this integration: + +```json +{ + "@trigger.dev/sdk": "3.0.13", + "@trigger.dev/build": "3.0.13", + "@aws-sdk/client-s3": "^3.651.0", + "@react-pdf/renderer": "^3.4.4", + "@react-email/components": "^0.1.0", + "puppeteer": "^23.4.0", + "puppeteer-core": "^23.5.3", + "openai": "^4.67.3", + "resend": "^4.0.0" +} +``` + +## Environment Variables + +Create a `.env.local` file in your project root with the following variables: + +```bash +# Trigger.dev Configuration +TRIGGER_SECRET_KEY=your-trigger-secret-key + +# Browserbase Configuration (for web scraping) +BROWSERBASE_API_KEY=your-browserbase-api-key +BROWSERBASE_PROJECT_ID=your-browserbase-project-id + +# Cloudflare R2 Storage Configuration (for file uploads) +S3_ENDPOINT=https://your-account-id.r2.cloudflarestorage.com +R2_ACCESS_KEY_ID=your-r2-access-key-id +R2_SECRET_ACCESS_KEY=your-r2-secret-access-key +S3_BUCKET=your-r2-bucket-name + +# OpenAI Configuration (for AI summarization) +OPENAI_API_KEY=your-openai-api-key + +# Resend Configuration (for email delivery) +RESEND_API_KEY=your-resend-api-key +``` + +## Getting Started + +1. **Install dependencies:** +```bash +npm install +``` + +2. **Set up environment variables:** +Copy the environment variables above into a `.env.local` file and fill in your actual values. + +3. **Start development server:** +```bash +npm run dev +``` + +4. **Deploy to Trigger.dev:** +```bash +npx trigger.dev@latest deploy +``` + +## Machine Presets + +Tasks can specify machine requirements: +```typescript +export const puppeteerBasicTask = task({ + id: "puppeteer-log-title", + machine: { + preset: "large-1x", + }, + // ... +}); +``` + +Available presets provide different CPU/memory configurations for resource-intensive tasks. + +## Error Handling & Retries + +All tasks include comprehensive error handling: +- **Automatic retries** with exponential backoff +- **Resource cleanup** (browser instances, temporary files) +- **Detailed logging** for debugging +- **Graceful failure** handling + +## Integration Services + +This example integrates with several external services: +- **Browserbase**: Cloud browser infrastructure for web scraping +- **Cloudflare R2**: Object storage for files +- **OpenAI**: AI-powered content summarization +- **Resend**: Email delivery service +- **React Email**: Email template rendering + +## Use Cases + +Perfect for: +- **Document processing workflows** +- **Web scraping and data extraction** +- **Automated content generation** +- **Scheduled reporting and notifications** +- **Complex multi-step background processes** diff --git a/examples/integrations/trigger/next-env.d.ts b/examples/integrations/trigger/next-env.d.ts new file mode 100644 index 0000000..1b3be08 --- /dev/null +++ b/examples/integrations/trigger/next-env.d.ts @@ -0,0 +1,5 @@ +/// +/// + +// NOTE: This file should not be edited +// see https://nextjs.org/docs/app/api-reference/config/typescript for more information. diff --git a/examples/integrations/trigger/next.config.mjs b/examples/integrations/trigger/next.config.mjs new file mode 100644 index 0000000..4678774 --- /dev/null +++ b/examples/integrations/trigger/next.config.mjs @@ -0,0 +1,4 @@ +/** @type {import('next').NextConfig} */ +const nextConfig = {}; + +export default nextConfig; diff --git a/examples/integrations/trigger/package-lock.json b/examples/integrations/trigger/package-lock.json new file mode 100644 index 0000000..cae7de7 --- /dev/null +++ b/examples/integrations/trigger/package-lock.json @@ -0,0 +1,12824 @@ +{ + "name": "react-pdf", + "version": "0.1.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "react-pdf", + "version": "0.1.0", + "dependencies": { + "@aws-sdk/client-s3": "^3.651.0", + "@react-email/components": "^0.1.0", + 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"^3.18.0" + } + } + } +} diff --git a/examples/integrations/trigger/package.json b/examples/integrations/trigger/package.json new file mode 100644 index 0000000..1f02d27 --- /dev/null +++ b/examples/integrations/trigger/package.json @@ -0,0 +1,36 @@ +{ + "name": "react-pdf", + "version": "0.1.0", + "private": true, + "scripts": { + "dev": "next dev", + "build": "next build", + "start": "next start", + "lint": "next lint" + }, + "dependencies": { + "@aws-sdk/client-s3": "^3.651.0", + "@react-email/components": "^0.1.0", + "@react-pdf/renderer": "^3.4.4", + "@trigger.dev/sdk": "3.0.13", + "next": "15.2.4", + "openai": "^4.67.3", + "puppeteer": "^23.4.0", + "puppeteer-core": "^23.5.3", + "react": "^18", + "react-dom": "^18", + "react-email": "^4.0.16", + "resend": "^4.0.0" + }, + "devDependencies": { + "@trigger.dev/build": "3.0.13", + "@types/node": "^20", + "@types/react": "^18", + "@types/react-dom": "^18", + "eslint": "^8", + "eslint-config-next": "14.2.10", + "postcss": "^8", + "tailwindcss": "^3.4.1", + "typescript": "^5" + } +} diff --git a/examples/integrations/trigger/postcss.config.mjs b/examples/integrations/trigger/postcss.config.mjs new file mode 100644 index 0000000..1a69fd2 --- /dev/null +++ b/examples/integrations/trigger/postcss.config.mjs @@ -0,0 +1,8 @@ +/** @type {import('postcss-load-config').Config} */ +const config = { + plugins: { + tailwindcss: {}, + }, +}; + +export default config; diff --git a/examples/integrations/trigger/screenshot.png b/examples/integrations/trigger/screenshot.png new file mode 100644 index 0000000..173e6dc Binary files /dev/null and b/examples/integrations/trigger/screenshot.png differ diff --git a/examples/integrations/trigger/src/app/api/route.ts b/examples/integrations/trigger/src/app/api/route.ts new file mode 100644 index 0000000..8ed940e --- /dev/null +++ b/examples/integrations/trigger/src/app/api/route.ts @@ -0,0 +1,50 @@ +import { NextResponse } from "next/server"; +import { exec } from "child_process"; +import util from "util"; +import fs from "fs"; +import path from "path"; + +const execPromise = util.promisify(exec); + +export async function GET() { + const pdfUrl = "https://pdfobject.com/pdf/sample.pdf"; + const documentId = "unique-document-id"; + + try { + // Create temp directory + const tempDir = path.join(process.cwd(), "temp"); + if (!fs.existsSync(tempDir)) { + fs.mkdirSync(tempDir); + } + + // Download PDF + const pdfPath = path.join(tempDir, `${documentId}.pdf`); + await execPromise(`curl -o ${pdfPath} ${pdfUrl}`); + + // Convert PDF to images + const outputDir = path.join(tempDir, documentId); + if (!fs.existsSync(outputDir)) { + fs.mkdirSync(outputDir); + } + await execPromise(`mutool convert -o ${outputDir}/page-%d.png ${pdfPath}`); + + // List generated images + const images = fs.readdirSync(outputDir); + + // Clean up + fs.unlinkSync(pdfPath); + images.forEach((img) => fs.unlinkSync(path.join(outputDir, img))); + fs.rmdirSync(outputDir); + + return NextResponse.json({ + message: "PDF converted to images successfully", + imageCount: images.length, + }); + } catch (error) { + console.error("Error:", error); + return NextResponse.json( + { error: "Failed to convert PDF" }, + { status: 500 } + ); + } +} diff --git a/examples/integrations/trigger/src/app/favicon.ico b/examples/integrations/trigger/src/app/favicon.ico new file mode 100644 index 0000000..718d6fe Binary files /dev/null and b/examples/integrations/trigger/src/app/favicon.ico differ diff --git a/examples/integrations/trigger/src/app/fonts/GeistMonoVF.woff b/examples/integrations/trigger/src/app/fonts/GeistMonoVF.woff new file mode 100644 index 0000000..f2ae185 Binary files /dev/null and b/examples/integrations/trigger/src/app/fonts/GeistMonoVF.woff differ diff --git a/examples/integrations/trigger/src/app/fonts/GeistVF.woff b/examples/integrations/trigger/src/app/fonts/GeistVF.woff new file mode 100644 index 0000000..1b62daa Binary files /dev/null and b/examples/integrations/trigger/src/app/fonts/GeistVF.woff differ diff --git a/examples/integrations/trigger/src/app/globals.css b/examples/integrations/trigger/src/app/globals.css new file mode 100644 index 0000000..13d40b8 --- /dev/null +++ b/examples/integrations/trigger/src/app/globals.css @@ -0,0 +1,27 @@ +@tailwind base; +@tailwind components; +@tailwind utilities; + +:root { + --background: #ffffff; + --foreground: #171717; +} + +@media (prefers-color-scheme: dark) { + :root { + --background: #0a0a0a; + --foreground: #ededed; + } +} + +body { + color: var(--foreground); + background: var(--background); + font-family: Arial, Helvetica, sans-serif; +} + +@layer utilities { + .text-balance { + text-wrap: balance; + } +} diff --git a/examples/integrations/trigger/src/app/layout.tsx b/examples/integrations/trigger/src/app/layout.tsx new file mode 100644 index 0000000..921179a --- /dev/null +++ b/examples/integrations/trigger/src/app/layout.tsx @@ -0,0 +1,35 @@ +import type { Metadata } from "next"; +import localFont from "next/font/local"; +import "./globals.css"; + +const geistSans = localFont({ + src: "./fonts/GeistVF.woff", + variable: "--font-geist-sans", + weight: "100 900", +}); +const geistMono = localFont({ + src: "./fonts/GeistMonoVF.woff", + variable: "--font-geist-mono", + weight: "100 900", +}); + +export const metadata: Metadata = { + title: "Browserbase + Trigger.dev Integration", + description: "Browserbase + Trigger.dev Integration", +}; + +export default function RootLayout({ + children, +}: Readonly<{ + children: React.ReactNode; +}>) { + return ( + + + {children} + + + ); +} diff --git a/examples/integrations/trigger/src/app/page.tsx b/examples/integrations/trigger/src/app/page.tsx new file mode 100644 index 0000000..2edc808 --- /dev/null +++ b/examples/integrations/trigger/src/app/page.tsx @@ -0,0 +1,61 @@ +"use client"; + +export default function Home() { + return ( +
+

Resume Builder

+
+
+ + +
+
+ + +
+
+ + +
+
+ + +
+ +
+
+ ); +} diff --git a/examples/integrations/trigger/src/trigger/pdf-to-image.tsx b/examples/integrations/trigger/src/trigger/pdf-to-image.tsx new file mode 100644 index 0000000..0b1f8cb --- /dev/null +++ b/examples/integrations/trigger/src/trigger/pdf-to-image.tsx @@ -0,0 +1,59 @@ +import { logger, task } from "@trigger.dev/sdk/v3"; +import { PutObjectCommand, S3Client } from "@aws-sdk/client-s3"; +import { execSync } from "child_process"; +import fs from "fs"; +import path from "path"; + +// Initialize S3 client +const s3Client = new S3Client({ + region: "auto", + endpoint: process.env.S3_ENDPOINT, + credentials: { + accessKeyId: process.env.R2_ACCESS_KEY_ID ?? "", + secretAccessKey: process.env.R2_SECRET_ACCESS_KEY ?? "", + }, +}); + +export const pdfToImage = task({ + id: "pdf-to-image", + run: async (payload: { pdfUrl: string; documentId: string }) => { + logger.log("Converting PDF to images", payload); + + const pdfPath = `/tmp/${payload.documentId}.pdf`; + const outputDir = `/tmp/${payload.documentId}`; + + // Download PDF and convert to images using MuPDF + execSync(`curl -s -o ${pdfPath} ${payload.pdfUrl}`); + fs.mkdirSync(outputDir, { recursive: true }); + execSync(`mutool convert -o ${outputDir}/page-%d.png ${pdfPath}`); + + // Upload images to R2 + const uploadedUrls = []; + for (const file of fs.readdirSync(outputDir)) { + const s3Key = `images/${payload.documentId}/${file}`; + const uploadParams = { + Bucket: process.env.S3_BUCKET, + Key: s3Key, + Body: fs.readFileSync(path.join(outputDir, file)), + ContentType: "image/png", + }; + + logger.log("Uploading to R2", uploadParams); + + await s3Client.send(new PutObjectCommand(uploadParams)); + const s3Url = `https://${process.env.S3_BUCKET}.r2.cloudflarestorage.com/${s3Key}`; + uploadedUrls.push(s3Url); + logger.log("Image uploaded to R2", { url: s3Url }); + } + + // Clean up + fs.rmSync(outputDir, { recursive: true, force: true }); + fs.unlinkSync(pdfPath); + + logger.log("All images uploaded to R2", { urls: uploadedUrls }); + + return { + imageUrls: uploadedUrls, + }; + }, +}); diff --git a/examples/integrations/trigger/src/trigger/puppeteer-log-page-title.tsx b/examples/integrations/trigger/src/trigger/puppeteer-log-page-title.tsx new file mode 100644 index 0000000..ae8cd01 --- /dev/null +++ b/examples/integrations/trigger/src/trigger/puppeteer-log-page-title.tsx @@ -0,0 +1,19 @@ +import { logger, task } from "@trigger.dev/sdk/v3"; +import puppeteer from "puppeteer"; + +export const puppeteerBasicTask = task({ + id: "puppeteer-log-title", + machine: { + preset: "large-1x", + }, + run: async () => { + const browser = await puppeteer.launch(); + const page = await browser.newPage(); + await page.goto("https://google.com"); + + const content = await page.title(); + + logger.info("Content", { content }); + await browser.close(); + }, +}); diff --git a/examples/integrations/trigger/src/trigger/puppeteer-scrape-with-proxy.tsx b/examples/integrations/trigger/src/trigger/puppeteer-scrape-with-proxy.tsx new file mode 100644 index 0000000..7114c5d --- /dev/null +++ b/examples/integrations/trigger/src/trigger/puppeteer-scrape-with-proxy.tsx @@ -0,0 +1,37 @@ +import { logger, task } from "@trigger.dev/sdk/v3"; +import puppeteer from "puppeteer-core"; + +export const puppeteerScrapeWithProxy = task({ + id: "puppeteer-scrape-with-proxy", + run: async () => { + const browser = await puppeteer.connect({ + browserWSEndpoint: `wss://connect.browserbase.com?apiKey=${process.env.BROWSERBASE_API_KEY}`, + }); + + const page = await browser.newPage(); + + try { + // Navigate to the target website + await page.goto("https://trigger.dev", { waitUntil: "networkidle0" }); + + // Scrape the GitHub stars count + const starCount = await page.evaluate(() => { + const starElement = document.querySelector(".github-star-count"); + const text = starElement?.textContent ?? "0"; + const numberText = text.replace(/[^0-9]/g, ""); + return parseInt(numberText); + }); + + logger.info("GitHub star count", { starCount }); + + return { starCount }; + } catch (error) { + logger.error("Error during scraping", { + error: error instanceof Error ? error.message : String(error), + }); + throw error; + } finally { + await browser.close(); + } + }, +}); diff --git a/examples/integrations/trigger/src/trigger/puppeteer-webpage-to-pdf.tsx b/examples/integrations/trigger/src/trigger/puppeteer-webpage-to-pdf.tsx new file mode 100644 index 0000000..8079bee --- /dev/null +++ b/examples/integrations/trigger/src/trigger/puppeteer-webpage-to-pdf.tsx @@ -0,0 +1,47 @@ +import { logger, task } from "@trigger.dev/sdk/v3"; +import puppeteer from "puppeteer"; +import { PutObjectCommand, S3Client } from "@aws-sdk/client-s3"; + +// Initialize S3 client +const s3Client = new S3Client({ + region: "auto", + endpoint: process.env.S3_ENDPOINT, + credentials: { + accessKeyId: process.env.R2_ACCESS_KEY_ID ?? "", + secretAccessKey: process.env.R2_SECRET_ACCESS_KEY ?? "", + }, +}); + +export const puppeteerWebpageToPDF = task({ + id: "puppeteer-webpage-to-pdf", + run: async () => { + const browser = await puppeteer.launch(); + const page = await browser.newPage(); + const response = await page.goto("https://google.com"); + const url = response?.url() ?? "No URL found"; + + // Generate PDF from the webpage + const generatePdf = await page.pdf(); + + logger.info("PDF generated from URL", { url }); + + await browser.close(); + + // Upload to R2 + const s3Key = `pdfs/test.pdf`; + const uploadParams = { + Bucket: process.env.S3_BUCKET, + Key: s3Key, + Body: generatePdf, + ContentType: "application/pdf", + }; + + logger.log("Uploading to R2 with params", uploadParams); + + // Upload the PDF to R2 and return the URL. + await s3Client.send(new PutObjectCommand(uploadParams)); + const s3Url = `https://${process.env.S3_BUCKET}.s3.amazonaws.com/${s3Key}`; + logger.log("PDF uploaded to R2", { url: s3Url }); + return { pdfUrl: s3Url }; + }, +}); diff --git a/examples/integrations/trigger/src/trigger/react-pdf.tsx b/examples/integrations/trigger/src/trigger/react-pdf.tsx new file mode 100644 index 0000000..f2c98ff --- /dev/null +++ b/examples/integrations/trigger/src/trigger/react-pdf.tsx @@ -0,0 +1,45 @@ +import { logger, task } from "@trigger.dev/sdk/v3"; +import { Document, Page, Text, View } from "@react-pdf/renderer"; +import { renderToBuffer } from "@react-pdf/renderer"; +import { PutObjectCommand, S3Client } from "@aws-sdk/client-s3"; + +const s3Client = new S3Client({ + region: "auto", + endpoint: process.env.S3_ENDPOINT, + credentials: { + accessKeyId: process.env.R2_ACCESS_KEY_ID ?? "", + secretAccessKey: process.env.R2_SECRET_ACCESS_KEY ?? "", + }, +}); + +export const generateResumePDF = task({ + id: "generate-resume-pdf", + run: async (payload: { text: string }) => { + logger.log("Generating PDF resume", payload); + + const pdfBuffer = await renderToBuffer( + + + + {payload.text} + + + + ); + + const s3Key = "resumes/my-resume.pdf"; + const uploadParams = { + Bucket: process.env.S3_BUCKET, + Key: s3Key, + Body: pdfBuffer, + ContentType: "application/pdf", + }; + + logger.log("Uploading to R2 with params", uploadParams); + + await s3Client.send(new PutObjectCommand(uploadParams)); + const s3Url = `https://${process.env.S3_BUCKET}.s3.amazonaws.com/${s3Key}`; + logger.log("PDF uploaded to R2", { url: s3Url }); + return { pdfUrl: s3Url }; + }, +}); diff --git a/examples/integrations/trigger/src/trigger/summarize-hn-email.tsx b/examples/integrations/trigger/src/trigger/summarize-hn-email.tsx new file mode 100644 index 0000000..00d87cf --- /dev/null +++ b/examples/integrations/trigger/src/trigger/summarize-hn-email.tsx @@ -0,0 +1,37 @@ +import { + Html, + Head, + Body, + Container, + Section, + Heading, + Text, + Link, +} from "@react-email/components"; + +interface Article { + title: string; + link: string; + summary: string | null; +} + +export const HNSummaryEmail: React.FC<{ articles: Article[] }> = ({ + articles, +}) => ( + + + + + Your Morning HN Summary + {articles.map((article, index) => ( +
+ + {article.title} + + {article.summary || "No summary available"} +
+ ))} + + + +); diff --git a/examples/integrations/trigger/src/trigger/summarize-hn.tsx b/examples/integrations/trigger/src/trigger/summarize-hn.tsx new file mode 100644 index 0000000..9f08bc6 --- /dev/null +++ b/examples/integrations/trigger/src/trigger/summarize-hn.tsx @@ -0,0 +1,136 @@ +import { render } from "@react-email/render"; +import { logger, schedules, task, wait } from "@trigger.dev/sdk/v3"; +import { OpenAI } from "openai"; +import puppeteer from "puppeteer-core"; +import { Resend } from "resend"; +import { HNSummaryEmail } from "./summarize-hn-email"; + +const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY }); +const resend = new Resend(process.env.RESEND_API_KEY); + +// Parent task (scheduled) +export const summarizeHackerNews = schedules.task({ + id: "summarize-hacker-news", + cron: { + pattern: "0 9 * * 1-5", + timezone: "Europe/London", + }, // Run at 9 AM, Monday to Friday + run: async () => { + const browser = await puppeteer.connect({ + browserWSEndpoint: `wss://connect.browserbase.com?apiKey=${process.env.BROWSERBASE_API_KEY}`, + }); + logger.info("Connected to Browserbase"); + + const page = await browser.newPage(); + + // Navigate to Hacker News and scrape top 3 articles + await page.goto("https://news.ycombinator.com/news", { + waitUntil: "networkidle0", + }); + logger.info("Navigated to Hacker News"); + + const articles = await page.evaluate(() => { + const items = document.querySelectorAll(".athing"); + return Array.from(items) + .slice(0, 3) + .map((item) => { + const titleElement = item.querySelector(".titleline > a"); + const link = titleElement?.getAttribute("href"); + const title = titleElement?.textContent; + return { title, link }; + }); + }); + logger.info("Scraped top 3 articles", { articles }); + + await browser.close(); + await wait.for({ seconds: 5 }); + + // Use batchTriggerAndWait to process articles + const summaries = await scrapeAndSummarizeArticle + .batchTriggerAndWait( + articles.map((article) => ({ + payload: { title: article.title!, link: article.link! }, + idempotencyKey: article.link, + })) + ) + .then((batch) => + batch.runs.filter((run) => run.ok).map((run) => run.output) + ); + + // Send email using Resend + await resend.emails.send({ + from: "Hacker News Summary ", + to: ["james@trigger.dev"], + subject: "Your morning HN summary", + html: await render(), + }); + + logger.info("Email sent successfully"); + }, +}); + +// Child task for scraping and summarizing individual articles +export const scrapeAndSummarizeArticle = task({ + id: "scrape-and-summarize-articles", + retry: { + maxAttempts: 3, + minTimeoutInMs: 5000, + maxTimeoutInMs: 10000, + factor: 2, + randomize: true, + }, + run: async ({ title, link }: { title: string; link: string }) => { + logger.info(`Summarizing ${title}`); + + const browser = await puppeteer.connect({ + browserWSEndpoint: `wss://connect.browserbase.com?apiKey=${process.env.BROWSERBASE_API_KEY}`, + }); + const page = await browser.newPage(); + + // Prevent all assets from loading, images, stylesheets etc + await page.setRequestInterception(true); + page.on("request", (request) => { + if ( + ["script", "stylesheet", "image", "media", "font"].includes( + request.resourceType() + ) + ) { + request.abort(); + } else { + request.continue(); + } + }); + + await page.goto(link, { waitUntil: "networkidle0" }); + logger.info(`Navigated to article: ${title}`); + + // Extract the main content of the article + const content = await page.evaluate(() => { + const articleElement = document.querySelector("article") || document.body; + return articleElement.innerText.trim().slice(0, 1500); // Limit to 1500 characters + }); + + await browser.close(); + + logger.info(`Extracted content for article: ${title}`, { content }); + + // Summarize the content using ChatGPT + const response = await openai.chat.completions.create({ + model: "gpt-4o", + messages: [ + { + role: "user", + content: `Summarize this article in 2-3 concise sentences:\n\n${content}`, + }, + ], + }); + + logger.info(`Generated summary for article: ${title}`); + + return { + title, + link, + summary: response.choices[0].message.content, + }; + }, +}); diff --git a/examples/integrations/trigger/src/trigger/taskHierarchy.ts b/examples/integrations/trigger/src/trigger/taskHierarchy.ts new file mode 100644 index 0000000..27dfe32 --- /dev/null +++ b/examples/integrations/trigger/src/trigger/taskHierarchy.ts @@ -0,0 +1,143 @@ +import { runs, task } from "@trigger.dev/sdk/v3"; +import { setTimeout } from "node:timers/promises"; + +export const rootTask = task({ + id: "task-hierarchy/root-task", + run: async ( + { + useWaits = true, + useBatch = false, + }: { useWaits: boolean; useBatch: boolean }, + { ctx } + ) => { + console.log("root-task"); + + if (useWaits) { + if (useBatch) { + await childTask.batchTriggerAndWait([ + { payload: { useWaits, useBatch } }, + ]); + } else { + await childTask.triggerAndWait({ useWaits, useBatch }); + } + } else { + if (useBatch) { + await childTask.batchTrigger([ + { payload: { useWaits, useBatch } }, + { payload: { useWaits, useBatch } }, + ]); + } else { + await childTask.trigger({ useWaits, useBatch }); + } + } + + if (!useWaits) { + await setTimeout(10_000); // Wait for 10 seconds, all the runs will be finished by then + } + + await logRunHierarchy(ctx.run.id); + }, +}); + +export const childTask = task({ + id: "task-hierarchy/child-task", + run: async ({ + useWaits = true, + useBatch = false, + }: { + useWaits: boolean; + useBatch: boolean; + }) => { + console.log("child-task"); + + if (useWaits) { + if (useBatch) { + await grandChildTask.batchTriggerAndWait([ + { payload: { useWaits, useBatch } }, + ]); + } else { + await grandChildTask.triggerAndWait({ useWaits, useBatch }); + } + } else { + if (useBatch) { + await grandChildTask.batchTrigger([ + { payload: { useWaits, useBatch } }, + ]); + } else { + await grandChildTask.trigger({ useWaits, useBatch }); + } + } + }, +}); + +export const grandChildTask = task({ + id: "task-hierarchy/grand-child-task", + run: async ({ + useWaits = true, + useBatch = false, + }: { + useWaits: boolean; + useBatch: boolean; + }) => { + console.log("grand-child-task"); + + if (useWaits) { + if (useBatch) { + await greatGrandChildTask.batchTriggerAndWait([ + { payload: { useWaits, useBatch } }, + ]); + } else { + await greatGrandChildTask.triggerAndWait({ useWaits, useBatch }); + } + } else { + if (useBatch) { + await greatGrandChildTask.batchTrigger([ + { payload: { useWaits, useBatch } }, + ]); + } else { + await greatGrandChildTask.trigger({ useWaits, useBatch }); + } + } + }, +}); + +export const greatGrandChildTask = task({ + id: "task-hierarchy/great-grand-child-task", + run: async ({ + useWaits = true, + useBatch = false, + }: { + useWaits: boolean; + useBatch: boolean; + }) => { + console.log("great-grand-child-task"); + }, +}); + +async function logRunHierarchy( + runId: string, + parentTaskIdentifier?: string, + triggerFunction?: string +) { + const runData = await runs.retrieve(runId); + + const indent = " ".repeat(runData.depth * 2); + const triggerInfo = triggerFunction + ? ` (triggered by ${triggerFunction})` + : ""; + const parentInfo = parentTaskIdentifier + ? ` (parent task: ${parentTaskIdentifier})` + : ""; + + console.log( + `${indent}Level ${runData.depth}: [${runData.taskIdentifier}] run ${runData.id}${triggerInfo}${parentInfo}` + ); + + for (const childRun of runData.relatedRuns.children ?? []) { + await logRunHierarchy( + childRun.id, + runData.taskIdentifier, + childRun.triggerFunction + ); + } +} diff --git a/examples/integrations/trigger/tailwind.config.ts b/examples/integrations/trigger/tailwind.config.ts new file mode 100644 index 0000000..021c393 --- /dev/null +++ b/examples/integrations/trigger/tailwind.config.ts @@ -0,0 +1,19 @@ +import type { Config } from "tailwindcss"; + +const config: Config = { + content: [ + "./src/pages/**/*.{js,ts,jsx,tsx,mdx}", + "./src/components/**/*.{js,ts,jsx,tsx,mdx}", + "./src/app/**/*.{js,ts,jsx,tsx,mdx}", + ], + theme: { + extend: { + colors: { + background: "var(--background)", + foreground: "var(--foreground)", + }, + }, + }, + plugins: [], +}; +export default config; diff --git a/examples/integrations/trigger/trigger.config.ts b/examples/integrations/trigger/trigger.config.ts new file mode 100644 index 0000000..269ca13 --- /dev/null +++ b/examples/integrations/trigger/trigger.config.ts @@ -0,0 +1,56 @@ +import { defineConfig } from "@trigger.dev/sdk/v3"; +import { aptGet } from "@trigger.dev/build/extensions/core"; +import { puppeteer } from "@trigger.dev/build/extensions/puppeteer"; + +export default defineConfig({ + project: "proj_ljbidlufugyxuhjxzkyy", + logLevel: "log", + retries: { + enabledInDev: true, + default: { + maxAttempts: 3, + minTimeoutInMs: 1000, + maxTimeoutInMs: 10000, + factor: 2, + randomize: true, + }, + }, + build: { + extensions: [ + aptGet({ packages: ["mupdf-tools", "curl"] }), + puppeteer(), + // { + // name: "puppeteer-2", + // onBuildComplete: async (context) => { + // if (context.target === "dev") { + // return; + // } + + // // context.logger.debug(`Adding ${this.name} to the build`); + + // const instructions = [ + // `RUN apt-get update && apt-get install curl gnupg -y \ + // && curl --location --silent https://dl-ssl.google.com/linux/linux_signing_key.pub | apt-key add - \ + // && sh -c 'echo "deb [arch=amd64] http://dl.google.com/linux/chrome/deb/ stable main" >> /etc/apt/sources.list.d/google.list' \ + // && apt-get update \ + // && apt-get install google-chrome-stable -y --no-install-recommends \ + // && rm -rf /var/lib/apt/lists/*`, + // ]; + + // context.addLayer({ + // id: "puppeteer", + // image: { + // instructions, + // }, + // deploy: { + // env: { + // PUPPETEER_EXECUTABLE_PATH: "/usr/bin/google-chrome-stable", + // }, + // override: true, + // }, + // }); + // }, + // }, + ], + }, +}); diff --git a/examples/integrations/trigger/tsconfig.json b/examples/integrations/trigger/tsconfig.json new file mode 100644 index 0000000..7a7787d --- /dev/null +++ b/examples/integrations/trigger/tsconfig.json @@ -0,0 +1,41 @@ +{ + "compilerOptions": { + "lib": [ + "dom", + "dom.iterable", + "esnext" + ], + "allowJs": true, + "skipLibCheck": true, + "strict": true, + "noEmit": true, + "esModuleInterop": true, + "module": "esnext", + "moduleResolution": "bundler", + "resolveJsonModule": true, + "isolatedModules": true, + "jsx": "preserve", + "incremental": true, + "plugins": [ + { + "name": "next" + } + ], + "paths": { + "@/*": [ + "./src/*" + ] + }, + "target": "ES2017" + }, + "include": [ + "next-env.d.ts", + "**/*.ts", + "**/*.tsx", + ".next/types/**/*.ts", + "trigger.config.ts" + ], + "exclude": [ + "node_modules" + ] +} diff --git a/examples/integrations/vercel/BrowseGPT/app/api/chat/route.ts b/examples/integrations/vercel/BrowseGPT/app/api/chat/route.ts index 31e5392..59c5b8c 100644 --- a/examples/integrations/vercel/BrowseGPT/app/api/chat/route.ts +++ b/examples/integrations/vercel/BrowseGPT/app/api/chat/route.ts @@ -1,5 +1,5 @@ import { openai } from '@ai-sdk/openai'; -import { streamText, convertToCoreMessages, tool, generateText } from 'ai'; +import { streamText, convertToModelMessages, tool, generateText } from 'ai'; import { z } from 'zod'; import { chromium } from 'playwright'; import {anthropic} from '@ai-sdk/anthropic' @@ -45,16 +45,13 @@ export const maxDuration = 300; // Set max duration to 300 seconds (5 minutes) export async function POST(req: Request) { const { messages } = await req.json(); - const result = await streamText({ - experimental_toolCallStreaming: true, - model: openai('gpt-4-turbo'), - // model: openai('gpt-4o'), - // model: anthropic('claude-3-5-sonnet-20240620'), - messages: convertToCoreMessages(messages), + const result = streamText({ + model: openai('gpt-4.1'), + messages: await convertToModelMessages(messages), tools: { createSession: tool({ description: 'Create a new session', - parameters: z.object({}), + inputSchema: z.object({}), execute: async () => { const session = await createSession(); const debugUrl = await getDebugUrl(session.id); @@ -63,13 +60,13 @@ export async function POST(req: Request) { }), askForConfirmation: tool({ description: 'Ask the user for confirmation.', - parameters: z.object({ + inputSchema: z.object({ message: z.string().describe('The message to ask for confirmation.'), }), }), googleSearch: tool({ description: 'Search Google for a query', - parameters: z.object({ + inputSchema: z.object({ toolName: z.string().describe('What the tool is doing'), query: z.string().describe('The exact and complete search query as provided by the user. Do not modify this in any way.'), sessionId: z.string().describe('The session ID to use for the search. If there is no session ID, create a new session with createSession Tool.'), @@ -104,7 +101,7 @@ export async function POST(req: Request) { const response = await generateText({ // model: openai('gpt-4-turbo'), - model: anthropic('claude-3-5-sonnet-20240620'), + model: anthropic('claude-sonnet-4-6'), prompt: `Evaluate the following web page content: ${text}`, }); @@ -125,7 +122,7 @@ export async function POST(req: Request) { }), getPageContent: tool({ description: 'Get the content of a page using Playwright', - parameters: z.object({ + inputSchema: z.object({ toolName: z.string().describe('What the tool is doing'), url: z.string().describe('The url to get the content of'), sessionId: z.string().describe('The session ID to use for the search. If there is no session ID, create a new session with createSession Tool.'), @@ -151,7 +148,7 @@ export async function POST(req: Request) { const response = await generateText({ // model: openai('gpt-4-turbo'), - model: anthropic('claude-3-5-sonnet-20240620'), + model: anthropic('claude-sonnet-4-6'), prompt: `Evaluate the following web page content: ${text}`, }); @@ -171,5 +168,5 @@ export async function POST(req: Request) { }, }); - return result.toDataStreamResponse(); + return result.toUIMessageStreamResponse(); } \ No newline at end of file diff --git a/examples/integrations/vercel/BrowseGPT/app/page.tsx b/examples/integrations/vercel/BrowseGPT/app/page.tsx index 6126770..a56df57 100644 --- a/examples/integrations/vercel/BrowseGPT/app/page.tsx +++ b/examples/integrations/vercel/BrowseGPT/app/page.tsx @@ -1,55 +1,78 @@ 'use client'; -import { useChat } from 'ai/react'; +import { useChat } from '@ai-sdk/react'; +import { DefaultChatTransport, type UIMessage } from 'ai'; import { useState, useEffect } from 'react'; import { Alert, AlertTitle, AlertDescription } from '@/components/ui/alert'; import Markdown from 'react-markdown'; import { MarkdownWrapper } from '@/components/ui/markdown'; import remarkGfm from 'remark-gfm'; import BlurFade from "@/components/ui/blur-fade"; -// import Spinner from "@/components/spinner"; import VercelLogo from "@/components/vercel"; import BrowserbaseLogo from "@/components/browserbase" import FlickeringGrid from '@/components/ui/flickering-grid'; import FlickeringLoad from '@/components/ui/flickering-load'; import { Prompts } from '@/components/prompts'; +function messageText(m: UIMessage): string { + return m.parts + .filter((p): p is { type: 'text'; text: string } => p.type === 'text') + .map((p) => p.text) + .join(''); +} + +function isToolUIPart(p: UIMessage['parts'][number]): boolean { + return typeof p.type === 'string' && p.type.startsWith('tool-'); +} + +type ToolPartLoose = { + type: string; + state?: string; + input?: Record; + output?: Record; +}; + export default function Chat() { - const { messages, input, handleInputChange, handleSubmit, isLoading } = useChat({ - maxSteps: 5, + const [input, setInput] = useState(''); + const { messages, sendMessage, status } = useChat({ + transport: new DefaultChatTransport({ api: '/api/chat' }), }); + const isLoading = status === 'streaming' || status === 'submitted'; + const [showAlert, setShowAlert] = useState(false); const [statusMessage, setStatusMessage] = useState(''); const [sessionId, setSessionId] = useState(null); const [hasInteracted, setHasInteracted] = useState(false); + const lastMessage = messages[messages.length - 1]; + const lastText = lastMessage ? messageText(lastMessage) : ''; + const isGenerating = isLoading && (!messages.length || - messages[messages.length - 1].role !== 'assistant' || - !messages[messages.length - 1].content); + lastMessage?.role !== 'assistant' || + !lastText); useEffect(() => { - const lastMessage = messages[messages.length - 1]; - if (isGenerating) { setShowAlert(true); - // Check if any tool invocation has dataCollected = true - const dataCollected = lastMessage?.toolInvocations?.some( - invocation => 'result' in invocation && - typeof invocation.result === 'object' && - invocation.result !== null && - 'dataCollected' in invocation.result && - invocation.result.dataCollected === true - ); - - if (dataCollected && !lastMessage.content) { - // The AI has collected data and is generating a response + const dataCollected = lastMessage?.parts.some((part) => { + if (!isToolUIPart(part)) return false; + const tp = part as ToolPartLoose; + const out = tp.state === 'output-available' ? tp.output : undefined; + return ( + out && + typeof out === 'object' && + 'dataCollected' in out && + (out as { dataCollected?: boolean }).dataCollected === true + ); + }); + + if (dataCollected && !lastText) { setStatusMessage('The AI has collected data and is generating a response. Please wait.'); } else { - // The AI is currently processing the request setStatusMessage('The AI is currently processing your request. Please wait.'); } @@ -57,37 +80,33 @@ export default function Chat() { } else { setShowAlert(false); } - }, [isGenerating, messages]); + }, [isGenerating, messages, lastMessage, lastText]); useEffect(() => { - const lastMessage = messages[messages.length - 1]; - if (lastMessage?.toolInvocations) { - for (const invocation of lastMessage.toolInvocations) { - if ('result' in invocation && invocation.result?.sessionId) { - setSessionId(invocation.result.sessionId); - break; - } + if (!lastMessage?.parts) return; + for (const part of lastMessage.parts) { + if (!isToolUIPart(part)) continue; + const tp = part as ToolPartLoose; + if (tp.state !== 'output-available') continue; + const out = tp.output as { sessionId?: string } | undefined; + if (out?.sessionId) { + setSessionId(out.sessionId); + break; } } - }, [messages]); + }, [messages, lastMessage]); const handleSubmitWrapper = (e: React.FormEvent) => { e.preventDefault(); - setHasInteracted(true); - handleSubmit(e, { data: { message: input } }); + if (!input.trim()) return; + setHasInteracted(true); + void sendMessage({ text: input }); + setInput(''); }; const handlePromptClick = (text: string) => { setHasInteracted(true); - // Set the input value - handleInputChange({ target: { value: text } } as React.ChangeEvent); - // Submit the form after a short delay - setTimeout(() => { - const submitButton = document.querySelector('button[type="submit"]') as HTMLButtonElement; - if (submitButton) { - submitButton.click(); - } - }, 100); // 100ms delay, adjust as needed + void sendMessage({ text }); }; return ( @@ -125,31 +144,42 @@ export default function Chat() { ) : ( - messages.map((m, index) => ( + messages.map((m, index) => { + const text = messageText(m); + const toolParts = m.parts.filter(isToolUIPart); + + return (
{m.role === 'user' ? ( <> User: -

{m.content}

+

{text}

- ) : m.toolInvocations ? ( + ) : toolParts.length > 0 ? ( - {m.toolInvocations?.map((invocation, index) => { + {toolParts.map((part, partIndex) => { + const tp = part as ToolPartLoose; + const input = tp.input; + const out = + tp.state === 'output-available' + ? tp.output + : undefined; + let content = ''; - if ('result' in invocation) { - if (invocation.result?.sessionId) { - content = `Session ID: ${invocation.result.sessionId}`; - } else if (invocation.result?.content) { - content = `Content: ${invocation.result.content}`; - } + if (out?.sessionId) { + content = `Session ID: ${String(out.sessionId)}`; + } else if (out?.content) { + content = `Content: ${String(out.content)}`; } - if (invocation.args?.debuggerFullscreenUrl) { + + const debuggerUrl = input?.debuggerFullscreenUrl; + if (typeof debuggerUrl === 'string') { return ( -
+