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Merge pull request #191 from UiPath/feat/structured-output-support
feat: structured output support for schema inference and runtime extraction
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‎packages/uipath-agent-framework/pyproject.toml‎

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[project]
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name = "uipath-agent-framework"
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version = "0.0.7"
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version = "0.0.8"
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description = "Python SDK that enables developers to build and deploy Microsoft Agent Framework agents to the UiPath Cloud Platform"
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readme = "README.md"
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requires-python = ">=3.11"

‎packages/uipath-agent-framework/samples/README.md‎

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| Sample | Description |
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|--------|-------------|
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| [quickstart-workflow](./quickstart-workflow/) | Single workflow agent with tool calling: fetches live weather data for any location |
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| [group-chat](./group-chat/) | Group chat orchestration: researcher, critic, and writer discuss a topic with an orchestrator picking speakers |
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| [structured-output](./structured-output/) | Structured output workflow: extracts city information and returns it as a typed Pydantic model |
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| [sequential-structured-output](./sequential-structured-output/) | Sequential pipeline with structured output: researcher and editor agents produce a typed Pydantic city profile |
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| [hitl-workflow](./hitl-workflow/) | Human-in-the-loop workflow: customer support with approval-gated billing and refund operations |
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| [sequential](./sequential/) | Sequential pipeline: writer, reviewer, and editor agents process a task one after another |
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| [concurrent](./concurrent/) | Concurrent orchestration: sentiment, topic extraction, and summarization agents analyze text in parallel |
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| [handoff](./handoff/) | Handoff orchestration: customer support agents transfer control to specialists with explicit routing rules |
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| [hitl-workflow](./hitl-workflow/) | Human-in-the-loop workflow: customer support with approval-gated billing and refund operations |
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| [group-chat](./group-chat/) | Group chat orchestration: researcher, critic, and writer discuss a topic with an orchestrator picking speakers |
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| [magentic](./magentic/) | Magentic-One orchestration: a manager dynamically coordinates researcher and analyst agents based on task progress |

‎packages/uipath-agent-framework/samples/hitl-workflow/README.md‎

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```
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uipath dev web
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```
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‎packages/uipath-agent-framework/samples/magentic/agent_framework.json‎

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{
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"agents": {
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"agent": "main.py:agent"
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}
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}

‎packages/uipath-agent-framework/samples/sequential-structured-output/README.md‎

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# Sequential + Structured Output
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A sequential pipeline that combines multi-agent processing with structured output. A researcher gathers facts about a city, then an editor organizes them into a well-defined Pydantic model (`CityInfo`). The final output is a typed JSON object — not free-form text.
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## Agent Graph
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```mermaid
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flowchart TB
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__start__(__start__)
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__end__(__end__)
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input-conversation(input-conversation)
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researcher(researcher)
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editor(editor)
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end_(end)
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__start__ --> |input|input-conversation
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input-conversation --> researcher
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researcher --> editor
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editor --> end_
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end_ --> |output|__end__
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```
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Internally, the sequential orchestration chains:
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- **researcher** — gathers key facts about the city (country, population, landmarks, cultural significance)
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- **editor** — organizes the research into a structured `CityInfo` schema with `response_format`
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Each agent sees the full conversation history from previous agents. The last agent's `response_format` determines the output schema.
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## Prerequisites
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Authenticate with UiPath to configure your `.env` file:
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```bash
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uipath auth
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```
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## Run
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```
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uipath run agent '{"messages": [{"contentParts": [{"data": {"inline": "Tell me about Tokyo"}}], "role": "user"}]}'
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```
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## Debug
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```
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uipath dev web
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```

‎packages/uipath-agent-framework/samples/sequential-structured-output/agent.mermaid‎

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flowchart TB
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__start__(__start__)
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__end__(__end__)
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input-conversation(input-conversation)
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researcher(researcher)
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editor(editor)
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end(end)
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__start__ --> |input|input-conversation
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input-conversation --> researcher
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researcher --> editor
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editor --> end
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end --> |output|__end__

‎packages/uipath-agent-framework/samples/sequential-structured-output/agent_framework.json‎

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{
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"agents": {
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"agent": "main.py:agent"
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}
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}

‎packages/uipath-agent-framework/samples/sequential-structured-output/main.py‎

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from agent_framework.orchestrations import SequentialBuilder
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from pydantic import BaseModel
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from uipath_agent_framework.chat import UiPathOpenAIChatClient
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class CityInfo(BaseModel):
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"""Structured output for city information."""
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city: str
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country: str
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description: str
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population_estimate: str
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famous_for: list[str]
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client = UiPathOpenAIChatClient(model="gpt-5-mini-2025-08-07")
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researcher = client.as_agent(
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name="researcher",
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description="Researches factual information about a city.",
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instructions=(
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"You are a thorough researcher. Given a city name, gather key facts "
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"including its country, population, notable landmarks, cultural "
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"significance, and what it is famous for. Present your findings clearly."
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),
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)
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editor = client.as_agent(
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name="editor",
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description="Edits research into a structured city profile.",
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instructions=(
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"You are a precise editor. Take the researcher's findings and organize "
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"them into a well-structured city profile. Ensure all facts are accurate "
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"and the description is concise and informative."
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),
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default_options={"response_format": CityInfo},
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)
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workflow = SequentialBuilder(
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participants=[researcher, editor],
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).build()
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agent = workflow.as_agent(name="sequential_structured_output_workflow")

‎packages/uipath-agent-framework/samples/sequential-structured-output/pyproject.toml‎

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[project]
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name = "sequential-structured-output"
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version = "0.0.1"
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description = "Sequential + structured output: agents process a task in a pipeline, the last agent returns data in a well-defined Pydantic schema"
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authors = [{ name = "John Doe" }]
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readme = "README.md"
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requires-python = ">=3.11"
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dependencies = [
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"uipath",
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"uipath-agent-framework",
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"agent-framework-core>=1.0.0rc1",
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"agent-framework-orchestrations>=1.0.0b260219",
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]
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[dependency-groups]
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dev = [
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"uipath-dev",
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]
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[tool.uv]
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prerelease = "allow"
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[tool.uv.sources]
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uipath-dev = { path = "../../../../../uipath-dev-python", editable = true }
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uipath-agent-framework = { path = "../../", editable = true }

‎packages/uipath-agent-framework/samples/sequential-structured-output/uipath.json‎

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{
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"$schema": "https://cloud.uipath.com/draft/2024-12/uipath",
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"runtimeOptions": {
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"isConversational": false
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},
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"packOptions": {
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"fileExtensionsIncluded": [],
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"filesIncluded": [],
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"filesExcluded": [],
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"directoriesExcluded": [],
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"includeUvLock": true
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},
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"functions": {}
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}

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