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Support Vercel AI Data Stream Protocol (#2923)
Co-authored-by: Douwe Maan <[email protected]>
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‎.gitignore‎

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/TODO.md
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.DS_Store
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examples/pydantic_ai_examples/.chat_app_messages.sqlite
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.chat_app_messages.sqlite
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/question_graph_history.json

‎README.md‎

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@@ -50,8 +50,8 @@ Designed to give your IDE or AI coding agent as much context as possible for aut
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5. **Powerful Evals**:
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Enables you to systematically test and [evaluate](https://ai.pydantic.dev/evals) the performance and accuracy of the agentic systems you build, and monitor the performance over time in Pydantic Logfire.
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6. **MCP, A2A, and AG-UI**:
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Integrates the [Model Context Protocol](https://ai.pydantic.dev/mcp/client), [Agent2Agent](https://ai.pydantic.dev/a2a), and [AG-UI](https://ai.pydantic.dev/ag-ui) standards to give your agent access to external tools and data, let it interoperate with other agents, and build interactive applications with streaming event-based communication.
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6. **MCP, A2A, and UI**:
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Integrates the [Model Context Protocol](https://ai.pydantic.dev/mcp/overview), [Agent2Agent](https://ai.pydantic.dev/a2a), and various [UI event stream](https://ai.pydantic.dev/ui/overview) standards to give your agent access to external tools and data, let it interoperate with other agents, and build interactive applications with streaming event-based communication.
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7. **Human-in-the-Loop Tool Approval**:
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Easily lets you flag that certain tool calls [require approval](https://ai.pydantic.dev/deferred-tools#human-in-the-loop-tool-approval) before they can proceed, possibly depending on tool call arguments, conversation history, or user preferences.

‎docs-site/src/index.ts‎

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'/examples': 'examples/setup/',
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'/mcp': '/mcp/overview/',
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'/models': '/models/overview/',
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'/ag-ui': '/ui/ag-ui/'
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}
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function redirect(pathname: string): string | null {

‎docs/agents.md‎

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FinalResultEvent(tool_name=None, tool_call_id=None),
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PartDeltaEvent(index=0, delta=TextPartDelta(content_delta='Mexico is Mexico ')),
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PartDeltaEvent(index=0, delta=TextPartDelta(content_delta='City.')),
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PartEndEvent(
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index=0, part=TextPart(content='The capital of Mexico is Mexico City.')
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),
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AgentRunResultEvent(
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),

‎docs/api/ui/ag_ui.md‎

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# `pydantic_ai.ui.ag_ui`
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::: pydantic_ai.ui.ag_ui
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::: pydantic_ai.ui.ag_ui.app

‎docs/api/ui/base.md‎

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# `pydantic_ai.ui`
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::: pydantic_ai.ui

‎docs/api/ui/vercel_ai.md‎

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# `pydantic_ai.ui.vercel_ai`
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::: pydantic_ai.ui.vercel_ai
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::: pydantic_ai.ui.vercel_ai.request_types
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::: pydantic_ai.ui.vercel_ai.response_types

‎docs/examples/ag-ui.md‎

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Example of using Pydantic AI agents with the [AG-UI Dojo](https://github.com/ag-ui-protocol/ag-ui/tree/main/typescript-sdk/apps/dojo) example app.
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See the [AG-UI docs](../ag-ui.md) for more information about the AG-UI integration.
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See the [AG-UI docs](../ui/ag-ui.md) for more information about the AG-UI integration.
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Demonstrates:
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- [AG-UI](../ag-ui.md)
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- [AG-UI](../ui/ag-ui.md)
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- [Tools](../tools.md)
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## Prerequisites

‎docs/index.md‎

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5. **Powerful Evals**:
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Enables you to systematically test and [evaluate](evals.md) the performance and accuracy of the agentic systems you build, and monitor the performance over time in Pydantic Logfire.
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6. **MCP, A2A, and AG-UI**:
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Integrates the [Model Context Protocol](mcp/client.md), [Agent2Agent](a2a.md), and [AG-UI](ag-ui.md) standards to give your agent access to external tools and data, let it interoperate with other agents, and build interactive applications with streaming event-based communication.
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6. **MCP, A2A, and UI**:
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Integrates the [Model Context Protocol](mcp/overview.md), [Agent2Agent](a2a.md), and various [UI event stream](ui/overview.md) standards to give your agent access to external tools and data, let it interoperate with other agents, and build interactive applications with streaming event-based communication.
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7. **Human-in-the-Loop Tool Approval**:
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Easily lets you flag that certain tool calls [require approval](deferred-tools.md#human-in-the-loop-tool-approval) before they can proceed, possibly depending on tool call arguments, conversation history, or user preferences.

‎docs/install.md‎

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`pydantic-ai-slim` has the following optional groups:
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* `logfire` — installs [`logfire`](logfire.md) [PyPI ↗](https://pypi.org/project/logfire){:target="_blank"}
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* `evals` — installs [`pydantic-evals`](evals.md) [PyPI ↗](https://pypi.org/project/pydantic-evals){:target="_blank"}
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* `openai` — installs `openai` [PyPI ↗](https://pypi.org/project/openai){:target="_blank"}
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* `vertexai` — installs `google-auth` [PyPI ↗](https://pypi.org/project/google-auth){:target="_blank"} and `requests` [PyPI ↗](https://pypi.org/project/requests){:target="_blank"}
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* `google` — installs `google-genai` [PyPI ↗](https://pypi.org/project/google-genai){:target="_blank"}
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* `anthropic` — installs `anthropic` [PyPI ↗](https://pypi.org/project/anthropic){:target="_blank"}
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* `groq` — installs `groq` [PyPI ↗](https://pypi.org/project/groq){:target="_blank"}
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* `mistral` — installs `mistralai` [PyPI ↗](https://pypi.org/project/mistralai){:target="_blank"}
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* `cohere` - installs `cohere` [PyPI ↗](https://pypi.org/project/cohere){:target="_blank"}
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* `bedrock` - installs `boto3` [PyPI ↗](https://pypi.org/project/boto3){:target="_blank"}
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* `huggingface` - installs `huggingface-hub[inference]` [PyPI ↗](https://pypi.org/project/huggingface-hub){:target="_blank"}
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* `outlines-transformers` - installs `outlines[transformers]` [PyPI ↗](https://pypi.org/project/outlines){:target="_blank"}
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* `outlines-llamacpp` - installs `outlines[llamacpp]` [PyPI ↗](https://pypi.org/project/outlines){:target="_blank"}
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* `outlines-mlxlm` - installs `outlines[mlxlm]` [PyPI ↗](https://pypi.org/project/outlines){:target="_blank"}
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* `outlines-sglang` - installs `outlines[sglang]` [PyPI ↗](https://pypi.org/project/outlines){:target="_blank"}
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* `outlines-vllm-offline` - installs `outlines[vllm-offline]` [PyPI ↗](https://pypi.org/project/outlines){:target="_blank"}
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* `duckduckgo` - installs `ddgs` [PyPI ↗](https://pypi.org/project/ddgs){:target="_blank"}
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* `tavily` - installs `tavily-python` [PyPI ↗](https://pypi.org/project/tavily-python){:target="_blank"}
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* `cli` - installs `rich` [PyPI ↗](https://pypi.org/project/rich){:target="_blank"}, `prompt-toolkit` [PyPI ↗](https://pypi.org/project/prompt-toolkit){:target="_blank"}, and `argcomplete` [PyPI ↗](https://pypi.org/project/argcomplete){:target="_blank"}
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* `mcp` - installs `mcp` [PyPI ↗](https://pypi.org/project/mcp){:target="_blank"}
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* `fastmcp` - installs `fastmcp` [PyPI ↗](https://pypi.org/project/fastmcp){:target="_blank"}
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* `a2a` - installs `fasta2a` [PyPI ↗](https://pypi.org/project/fasta2a){:target="_blank"}
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* `ag-ui` - installs `ag-ui-protocol` [PyPI ↗](https://pypi.org/project/ag-ui-protocol){:target="_blank"} and `starlette` [PyPI ↗](https://pypi.org/project/starlette){:target="_blank"}
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* `dbos` - installs [`dbos`](durable_execution/dbos.md) [PyPI ↗](https://pypi.org/project/dbos){:target="_blank"}
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* `prefect` - installs [`prefect`](durable_execution/prefect.md) [PyPI ↗](https://pypi.org/project/prefect){:target="_blank"}
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See the [models](models/overview.md) documentation for information on which optional dependencies are required for each model.
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* `logfire` — installs [Pydantic Logfire](logfire.md) dependency `logfire` [PyPI ↗](https://pypi.org/project/logfire){:target="_blank"}
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* `evals` — installs [Pydantic Evals](evals.md) dependency `pydantic-evals` [PyPI ↗](https://pypi.org/project/pydantic-evals){:target="_blank"}
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* `openai` — installs [OpenAI Model](models/openai.md) dependency `openai` [PyPI ↗](https://pypi.org/project/openai){:target="_blank"}
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* `vertexai` — installs `GoogleVertexProvider` dependencies `google-auth` [PyPI ↗](https://pypi.org/project/google-auth){:target="_blank"} and `requests` [PyPI ↗](https://pypi.org/project/requests){:target="_blank"}
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* `google` — installs [Google Model](models/google.md) dependency `google-genai` [PyPI ↗](https://pypi.org/project/google-genai){:target="_blank"}
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* `anthropic` — installs [Anthropic Model](models/anthropic.md) dependency `anthropic` [PyPI ↗](https://pypi.org/project/anthropic){:target="_blank"}
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* `groq` — installs [Groq Model](models/groq.md) dependency `groq` [PyPI ↗](https://pypi.org/project/groq){:target="_blank"}
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* `mistral` — installs [Mistral Model](models/mistral.md) dependency `mistralai` [PyPI ↗](https://pypi.org/project/mistralai){:target="_blank"}
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* `cohere` - installs [Cohere Model](models/cohere.md) dependency `cohere` [PyPI ↗](https://pypi.org/project/cohere){:target="_blank"}
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* `bedrock` - installs [Bedrock Model](models/bedrock.md) dependency `boto3` [PyPI ↗](https://pypi.org/project/boto3){:target="_blank"}
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* `huggingface` - installs [Hugging Face Model](models/huggingface.md) dependency `huggingface-hub[inference]` [PyPI ↗](https://pypi.org/project/huggingface-hub){:target="_blank"}
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* `outlines-transformers` - installs [Outlines Model](models/outlines.md) dependency `outlines[transformers]` [PyPI ↗](https://pypi.org/project/outlines){:target="_blank"}
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* `outlines-llamacpp` - installs [Outlines Model](models/outlines.md) dependency `outlines[llamacpp]` [PyPI ↗](https://pypi.org/project/outlines){:target="_blank"}
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* `outlines-mlxlm` - installs [Outlines Model](models/outlines.md) dependency `outlines[mlxlm]` [PyPI ↗](https://pypi.org/project/outlines){:target="_blank"}
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* `outlines-sglang` - installs [Outlines Model](models/outlines.md) dependency `outlines[sglang]` [PyPI ↗](https://pypi.org/project/outlines){:target="_blank"}
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* `outlines-vllm-offline` - installs [Outlines Model](models/outlines.md) dependencies `outlines` [PyPI ↗](https://pypi.org/project/outlines){:target="_blank"} and `vllm` [PyPI ↗](https://pypi.org/project/vllm){:target="_blank"}
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* `duckduckgo` - installs [DuckDuckGo Search Tool](common-tools.md#duckduckgo-search-tool) dependency `ddgs` [PyPI ↗](https://pypi.org/project/ddgs){:target="_blank"}
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* `tavily` - installs [Tavily Search Tool](common-tools.md#tavily-search-tool) dependency `tavily-python` [PyPI ↗](https://pypi.org/project/tavily-python){:target="_blank"}
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* `cli` - installs [CLI](cli.md) dependencies `rich` [PyPI ↗](https://pypi.org/project/rich){:target="_blank"}, `prompt-toolkit` [PyPI ↗](https://pypi.org/project/prompt-toolkit){:target="_blank"}, and `argcomplete` [PyPI ↗](https://pypi.org/project/argcomplete){:target="_blank"}
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* `mcp` - installs [MCP](mcp/client.md) dependency `mcp` [PyPI ↗](https://pypi.org/project/mcp){:target="_blank"}
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* `fastmcp` - installs [FastMCP](mcp/fastmcp-client.md) dependency `fastmcp` [PyPI ↗](https://pypi.org/project/fastmcp){:target="_blank"}
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* `a2a` - installs [A2A](a2a.md) dependency `fasta2a` [PyPI ↗](https://pypi.org/project/fasta2a){:target="_blank"}
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* `ui` - installs [UI Event Streams](ui/overview.md) dependency `starlette` [PyPI ↗](https://pypi.org/project/starlette){:target="_blank"}
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* `ag-ui` - installs [AG-UI Event Stream Protocol](ui/ag-ui.md) dependencies `ag-ui-protocol` [PyPI ↗](https://pypi.org/project/ag-ui-protocol){:target="_blank"} and `starlette` [PyPI ↗](https://pypi.org/project/starlette){:target="_blank"}
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* `dbos` - installs [DBOS Durable Execution](durable_execution/dbos.md) dependency `dbos` [PyPI ↗](https://pypi.org/project/dbos){:target="_blank"}
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* `prefect` - installs [Prefect Durable Execution](durable_execution/prefect.md) dependency `prefect` [PyPI ↗](https://pypi.org/project/prefect){:target="_blank"}
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You can also install dependencies for multiple models and use cases, for example:
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```bash
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pip/uv-add "pydantic-ai-slim[openai,google,logfire]"
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```

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