From 43de2e9f1ddffe7ee89a3158bb1b71d734c39873 Mon Sep 17 00:00:00 2001 From: David Sanchez <64162682+dsfaccini@users.noreply.github.com> Date: Thu, 14 May 2026 14:28:16 -0500 Subject: [PATCH 1/2] Add pydantic-ai bridge submodule (v0.6 backport) Targets the pre-A2A-v1-spec schema (commit a6d6cf0, last commit before #46). Imports + accesses the discriminated TextPart/FilePart/DataPart shape that the released v0.6.0 ships. Goal: ship a 0.6.1 maintenance release with this bridge so Pydantic AI 1.x users have a migration target while v0.7 (with the v1-spec rewrite) is still pre-release. Includes the same fixes as the main-targeting bridge PR: - ruff format pass + import sort (I001) - pydantic-ai optional dep gated to python_version >= '3.10' - README 'Using Pydantic AI' section rewritten for the new bridge - pydantic-ai private-import fixes (AgentDepsT from _run_context, OutputDataT from output) - @asynccontextmanager AsyncIterator -> AsyncGenerator (reportDeprecated) Companion PR on Pydantic AI side: https://github.com/pydantic/pydantic-ai/pull/5426 --- README.md | 23 ++- fasta2a/pydantic_ai/__init__.py | 23 +++ fasta2a/pydantic_ai/_bridge.py | 242 ++++++++++++++++++++++++++++ pyproject.toml | 1 + uv.lock | 270 ++++++++++++++++++++++++++++++-- 5 files changed, 543 insertions(+), 16 deletions(-) create mode 100644 fasta2a/pydantic_ai/__init__.py create mode 100644 fasta2a/pydantic_ai/_bridge.py diff --git a/README.md b/README.md index 8fc7dd9..19f1181 100644 --- a/README.md +++ b/README.md @@ -7,7 +7,7 @@ [![license](https://img.shields.io/github/license/pydantic/pydantic-ai.svg)](https://github.com/pydantic/pydantic-ai/blob/main/LICENSE) **FastA2A** is an agentic framework agnostic implementation of the A2A protocol in Python. -The library is designed to be used with any agentic framework, and is not exclusive to PydanticAI. +The library is designed to be used with any agentic framework, and is not exclusive to Pydantic AI. ![Interactive Chat](./assets/docs.png) @@ -99,29 +99,38 @@ app = FastA2A(storage=storage, broker=broker, lifespan=lifespan) _You can run this example as is with `uvicorn main:app --reload`._ -### Using PydanticAI +### Using Pydantic AI -Initially, this **FastA2A** lived under **PydanticAI** repository, but since we received community feedback, +Initially, this **FastA2A** lived under **Pydantic AI** repository, but since we received community feedback, we've decided to move it to a separate repository. > [!NOTE] > Other agentic frameworks are welcome to implement the `Worker` component, and we'll be happy add the reference here. -For reference, you can [check the PydanticAI implementation of the `Worker`](https://github.com/pydantic/pydantic-ai/blob/3ef42ed9a1a2c799bb94a5a69c80aa9e8968ca72/pydantic_ai_slim/pydantic_ai/_a2a.py#L115-L304). +Install the integration with the `pydantic-ai` extra: -Let's see how to use it in practice: +```bash +pip install 'fasta2a[pydantic-ai]' # or `uv add 'fasta2a[pydantic-ai]'` +``` + +Then turn any `pydantic_ai.Agent` into an A2A-compatible ASGI app: ```python from pydantic_ai import Agent +from fasta2a.pydantic_ai import agent_to_a2a -agent = Agent('openai:gpt-4.1') -app = agent.to_a2a() +agent = Agent('openai:gpt-5.5') +app = agent_to_a2a(agent) ``` _You can run this example as is with `uvicorn main:app --reload`._ As you see, it's pretty easy from the point of view of the developer using your agentic framework. +> [!NOTE] +> In Pydantic AI 1.x, `Agent.to_a2a()` continues to work but emits a deprecation +> warning pointing here. It will be removed in Pydantic AI v2. + ## Design **FastA2A** is built on top of [Starlette](https://www.starlette.io/), which means it's fully compatible diff --git a/fasta2a/pydantic_ai/__init__.py b/fasta2a/pydantic_ai/__init__.py new file mode 100644 index 0000000..072da09 --- /dev/null +++ b/fasta2a/pydantic_ai/__init__.py @@ -0,0 +1,23 @@ +"""Pydantic AI bridge for FastA2A. + +Port of `pydantic_ai._a2a` into the FastA2A package, so users can keep using +`Agent.to_a2a()` after the corresponding wrapper is removed from pydantic-ai +in v2. See https://github.com/pydantic/pydantic-ai for the upstream +deprecation context. + +Usage: + + from pydantic_ai import Agent + from fasta2a.pydantic_ai import agent_to_a2a + + agent = Agent('openai:gpt-5.5') + app = agent_to_a2a(agent, name='my-agent', url='http://localhost:8000') + +Install the integration with the `pydantic-ai` extra: + + pip install 'fasta2a[pydantic-ai]' +""" + +from ._bridge import AgentWorker, agent_to_a2a, worker_lifespan + +__all__ = ['AgentWorker', 'agent_to_a2a', 'worker_lifespan'] diff --git a/fasta2a/pydantic_ai/_bridge.py b/fasta2a/pydantic_ai/_bridge.py new file mode 100644 index 0000000..ff5b115 --- /dev/null +++ b/fasta2a/pydantic_ai/_bridge.py @@ -0,0 +1,242 @@ +from __future__ import annotations + +import base64 +import uuid +from collections.abc import AsyncGenerator, Sequence +from contextlib import asynccontextmanager +from dataclasses import dataclass +from functools import partial +from typing import Any, Generic, TypeVar + +from pydantic import TypeAdapter +from typing_extensions import assert_never + +try: + from pydantic_ai import ( + AudioUrl, + BinaryContent, + DocumentUrl, + ImageUrl, + ModelMessage, + ModelRequest, + ModelRequestPart, + ModelResponse, + ModelResponsePart, + TextPart, + ThinkingPart, + ToolCallPart, + UserPromptPart, + VideoUrl, + ) + from pydantic_ai._run_context import AgentDepsT + from pydantic_ai.agent import AbstractAgent + from pydantic_ai.output import OutputDataT +except ImportError as _e: + raise ImportError( + 'Please install the `pydantic-ai` package to use `fasta2a.pydantic_ai`, ' + "e.g. `pip install 'fasta2a[pydantic-ai]'`" + ) from _e + +from starlette.middleware import Middleware +from starlette.routing import Route +from starlette.types import ExceptionHandler, Lifespan + +from fasta2a.applications import FastA2A +from fasta2a.broker import Broker, InMemoryBroker +from fasta2a.schema import ( + AgentProvider, + Artifact, + DataPart, + Message, + Part, + Skill, + TaskIdParams, + TaskSendParams, + TextPart as A2ATextPart, +) +from fasta2a.storage import InMemoryStorage, Storage +from fasta2a.worker import Worker + +WorkerOutputT = TypeVar('WorkerOutputT') + + +@asynccontextmanager +async def worker_lifespan( + app: FastA2A, worker: Worker, agent: AbstractAgent[AgentDepsT, OutputDataT] +) -> AsyncGenerator[None]: + """Lifespan that runs the worker during application startup.""" + async with app.task_manager, agent: + async with worker.run(): + yield + + +def agent_to_a2a( + agent: AbstractAgent[AgentDepsT, OutputDataT], + *, + storage: Storage | None = None, + broker: Broker | None = None, + name: str | None = None, + url: str = 'http://localhost:8000', + version: str = '1.0.0', + description: str | None = None, + provider: AgentProvider | None = None, + skills: list[Skill] | None = None, + debug: bool = False, + routes: Sequence[Route] | None = None, + middleware: Sequence[Middleware] | None = None, + exception_handlers: dict[Any, ExceptionHandler] | None = None, + lifespan: Lifespan[FastA2A] | None = None, +) -> FastA2A: + """Create a FastA2A server from a pydantic-ai agent.""" + storage = storage or InMemoryStorage() + broker = broker or InMemoryBroker() + worker = AgentWorker(agent=agent, broker=broker, storage=storage) + + lifespan = lifespan or partial(worker_lifespan, worker=worker, agent=agent) + + return FastA2A( + storage=storage, + broker=broker, + name=name or agent.name, + url=url, + version=version, + description=description, + provider=provider, + skills=skills, + debug=debug, + routes=routes, + middleware=middleware, + exception_handlers=exception_handlers, + lifespan=lifespan, + ) + + +@dataclass +class AgentWorker(Worker[list[ModelMessage]], Generic[WorkerOutputT, AgentDepsT]): + """A worker that uses a pydantic-ai agent to execute tasks.""" + + agent: AbstractAgent[AgentDepsT, WorkerOutputT] + + async def run_task(self, params: TaskSendParams) -> None: + task = await self.storage.load_task(params['id']) + if task is None: + raise ValueError(f'Task {params["id"]} not found') + + if task['status']['state'] != 'submitted': + raise ValueError(f'Task {params["id"]} has already been processed (state: {task["status"]["state"]})') + + await self.storage.update_task(task['id'], state='working') + + message_history = await self.storage.load_context(task['context_id']) or [] + message_history.extend(self.build_message_history(task.get('history', []))) + + try: + result = await self.agent.run(message_history=message_history) # type: ignore + + await self.storage.update_context(task['context_id'], result.all_messages()) + + a2a_messages: list[Message] = [] + for message in result.new_messages(): + if isinstance(message, ModelRequest): + continue + a2a_parts = self._response_parts_to_a2a(message.parts) + if a2a_parts: + a2a_messages.append( + Message(role='agent', parts=a2a_parts, kind='message', message_id=str(uuid.uuid4())) + ) + + artifacts = self.build_artifacts(result.output) + except Exception: + await self.storage.update_task(task['id'], state='failed') + raise + else: + await self.storage.update_task( + task['id'], state='completed', new_artifacts=artifacts, new_messages=a2a_messages + ) + + async def cancel_task(self, params: TaskIdParams) -> None: + pass + + def build_artifacts(self, result: WorkerOutputT) -> list[Artifact]: + artifact_id = str(uuid.uuid4()) + part = self._convert_result_to_part(result) + return [Artifact(artifact_id=artifact_id, name='result', parts=[part])] + + def _convert_result_to_part(self, result: WorkerOutputT) -> Part: + if isinstance(result, str): + return A2ATextPart(kind='text', text=result) + output_type = type(result) + type_adapter = TypeAdapter(output_type) + data = type_adapter.dump_python(result, mode='json') + json_schema = type_adapter.json_schema(mode='serialization') + return DataPart(kind='data', data={'result': data}, metadata={'json_schema': json_schema}) + + def build_message_history(self, history: list[Message]) -> list[ModelMessage]: + model_messages: list[ModelMessage] = [] + for message in history: + if message['role'] == 'user': + model_messages.append(ModelRequest(parts=self._request_parts_from_a2a(message['parts']))) + else: + model_messages.append(ModelResponse(parts=self._response_parts_from_a2a(message['parts']))) + return model_messages + + def _request_parts_from_a2a(self, parts: list[Part]) -> list[ModelRequestPart]: + model_parts: list[ModelRequestPart] = [] + for part in parts: + if part['kind'] == 'text': + model_parts.append(UserPromptPart(content=part['text'])) + elif part['kind'] == 'file': + file_content = part['file'] + if 'bytes' in file_content: + data = base64.b64decode(file_content['bytes']) + mime_type = file_content.get('mime_type', 'application/octet-stream') + content = BinaryContent(data=data, media_type=mime_type) + model_parts.append(UserPromptPart(content=[content])) + else: + url = file_content['uri'] + for url_cls in (DocumentUrl, AudioUrl, ImageUrl, VideoUrl): + content = url_cls(url=url) + try: + content.media_type + except ValueError: + continue + else: + break + else: + raise ValueError(f'Unsupported file type: {url}') + model_parts.append(UserPromptPart(content=[content])) + elif part['kind'] == 'data': + raise NotImplementedError('Data parts are not supported yet.') + else: + assert_never(part) + return model_parts + + def _response_parts_from_a2a(self, parts: list[Part]) -> list[ModelResponsePart]: + model_parts: list[ModelResponsePart] = [] + for part in parts: + if part['kind'] == 'text': + model_parts.append(TextPart(content=part['text'])) + elif part['kind'] == 'file': + raise NotImplementedError('File parts are not supported yet.') + elif part['kind'] == 'data': + raise NotImplementedError('Data parts are not supported yet.') + else: + assert_never(part) + return model_parts + + def _response_parts_to_a2a(self, parts: Sequence[ModelResponsePart]) -> list[Part]: + a2a_parts: list[Part] = [] + for part in parts: + if isinstance(part, TextPart): + a2a_parts.append(A2ATextPart(kind='text', text=part.content)) + elif isinstance(part, ThinkingPart): + a2a_parts.append( + A2ATextPart( + kind='text', + text=part.content, + metadata={'type': 'thinking', 'thinking_id': part.id, 'signature': part.signature}, + ) + ) + elif isinstance(part, ToolCallPart): + pass + return a2a_parts diff --git a/pyproject.toml b/pyproject.toml index 2af3b7d..19ce3c8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -52,6 +52,7 @@ dependencies = [ [project.optional-dependencies] logfire = ["logfire>=2.3"] +pydantic-ai = ["pydantic-ai-slim>=1.92; python_version >= '3.10'"] [dependency-groups] dev = [ diff --git a/uv.lock b/uv.lock index a77fc88..4512caf 100644 --- a/uv.lock +++ b/uv.lock @@ -1,11 +1,18 @@ version = 1 -revision = 2 +revision = 3 requires-python = ">=3.9" resolution-markers = [ "python_full_version >= '3.10'", "python_full_version < '3.10'", ] +[options] +exclude-newer = "2026-05-11T19:26:34.534129Z" +exclude-newer-span = "P3D" + 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~/.config/uv/uv.toml sets a supply-chain cooldown via `exclude-newer`, which gets baked into every uv.lock as an `[options]` block on regeneration. Doesn't belong in an upstream lockfile — strip it here. --- uv.lock | 7 ------- 1 file changed, 7 deletions(-) diff --git a/uv.lock b/uv.lock index 4512caf..0557720 100644 --- a/uv.lock +++ b/uv.lock @@ -6,13 +6,6 @@ resolution-markers = [ "python_full_version < '3.10'", ] -[options] -exclude-newer = "2026-05-11T19:26:34.534129Z" -exclude-newer-span = "P3D" - -[options.exclude-newer-package] -plaine = "2099-01-01T00:00:00Z" - [[package]] name = "annotated-types" version = "0.7.0"