From eff80b2abaa021777a51e36c2738449660d1b494 Mon Sep 17 00:00:00 2001 From: Brian Strauch Date: Wed, 2 Sep 2026 16:51:54 -0700 Subject: [PATCH 1/8] Add Pydantic AI plugin samples --- README.md | 1 + pydantic_ai_plugin/README.md | 35 + pydantic_ai_plugin/__init__.py | 1 + pydantic_ai_plugin/chat/README.md | 20 + pydantic_ai_plugin/chat/__init__.py | 1 + pydantic_ai_plugin/chat/run_worker.py | 24 + pydantic_ai_plugin/chat/workflow.py | 67 ++ .../human_in_the_loop/README.md | 22 + .../human_in_the_loop/__init__.py | 1 + .../human_in_the_loop/run_worker.py | 24 + .../human_in_the_loop/workflow.py | 92 ++ pydantic_ai_plugin/logfire/README.md | 16 + pydantic_ai_plugin/logfire/__init__.py | 1 + pydantic_ai_plugin/logfire/run_worker.py | 27 + pydantic_ai_plugin/logfire/workflow.py | 34 + pydantic_ai_plugin/mcp/README.md | 16 + pydantic_ai_plugin/mcp/__init__.py | 1 + pydantic_ai_plugin/mcp/run_worker.py | 24 + pydantic_ai_plugin/mcp/workflow.py | 46 + pydantic_ai_plugin/multi_agent/README.md | 16 + pydantic_ai_plugin/multi_agent/__init__.py | 1 + pydantic_ai_plugin/multi_agent/run_worker.py | 24 + pydantic_ai_plugin/multi_agent/workflow.py | 45 + pydantic_ai_plugin/streaming/README.md | 20 + pydantic_ai_plugin/streaming/__init__.py | 1 + pydantic_ai_plugin/streaming/run_worker.py | 24 + pydantic_ai_plugin/streaming/run_workflow.py | 32 + pydantic_ai_plugin/streaming/workflow.py | 51 + .../structured_output/README.md | 16 + .../structured_output/__init__.py | 1 + .../structured_output/run_worker.py | 24 + .../structured_output/workflow.py | 48 + pydantic_ai_plugin/tools/README.md | 21 + pydantic_ai_plugin/tools/__init__.py | 1 + pydantic_ai_plugin/tools/run_worker.py | 24 + pydantic_ai_plugin/tools/workflow.py | 47 + pyproject.toml | 8 + tests/pydantic_ai_plugin/__init__.py | 1 + tests/pydantic_ai_plugin/chat_test.py | 58 ++ tests/pydantic_ai_plugin/helpers.py | 9 + .../human_in_the_loop_test.py | 50 + tests/pydantic_ai_plugin/logfire_test.py | 44 + tests/pydantic_ai_plugin/mcp_test.py | 26 + tests/pydantic_ai_plugin/multi_agent_test.py | 37 + tests/pydantic_ai_plugin/streaming_test.py | 65 ++ .../structured_output_test.py | 34 + tests/pydantic_ai_plugin/tools_test.py | 34 + uv.lock | 892 ++++++++++++++++-- 48 files changed, 2005 insertions(+), 102 deletions(-) create mode 100644 pydantic_ai_plugin/README.md create mode 100644 pydantic_ai_plugin/__init__.py create mode 100644 pydantic_ai_plugin/chat/README.md create mode 100644 pydantic_ai_plugin/chat/__init__.py create mode 100644 pydantic_ai_plugin/chat/run_worker.py create mode 100644 pydantic_ai_plugin/chat/workflow.py create mode 100644 pydantic_ai_plugin/human_in_the_loop/README.md create mode 100644 pydantic_ai_plugin/human_in_the_loop/__init__.py create mode 100644 pydantic_ai_plugin/human_in_the_loop/run_worker.py create mode 100644 pydantic_ai_plugin/human_in_the_loop/workflow.py create mode 100644 pydantic_ai_plugin/logfire/README.md create mode 100644 pydantic_ai_plugin/logfire/__init__.py create mode 100644 pydantic_ai_plugin/logfire/run_worker.py create mode 100644 pydantic_ai_plugin/logfire/workflow.py create mode 100644 pydantic_ai_plugin/mcp/README.md create mode 100644 pydantic_ai_plugin/mcp/__init__.py create mode 100644 pydantic_ai_plugin/mcp/run_worker.py create mode 100644 pydantic_ai_plugin/mcp/workflow.py create mode 100644 pydantic_ai_plugin/multi_agent/README.md create mode 100644 pydantic_ai_plugin/multi_agent/__init__.py create mode 100644 pydantic_ai_plugin/multi_agent/run_worker.py create mode 100644 pydantic_ai_plugin/multi_agent/workflow.py create mode 100644 pydantic_ai_plugin/streaming/README.md create mode 100644 pydantic_ai_plugin/streaming/__init__.py create mode 100644 pydantic_ai_plugin/streaming/run_worker.py create mode 100644 pydantic_ai_plugin/streaming/run_workflow.py create mode 100644 pydantic_ai_plugin/streaming/workflow.py create mode 100644 pydantic_ai_plugin/structured_output/README.md create mode 100644 pydantic_ai_plugin/structured_output/__init__.py create mode 100644 pydantic_ai_plugin/structured_output/run_worker.py create mode 100644 pydantic_ai_plugin/structured_output/workflow.py create mode 100644 pydantic_ai_plugin/tools/README.md create mode 100644 pydantic_ai_plugin/tools/__init__.py create mode 100644 pydantic_ai_plugin/tools/run_worker.py create mode 100644 pydantic_ai_plugin/tools/workflow.py create mode 100644 tests/pydantic_ai_plugin/__init__.py create mode 100644 tests/pydantic_ai_plugin/chat_test.py create mode 100644 tests/pydantic_ai_plugin/helpers.py create mode 100644 tests/pydantic_ai_plugin/human_in_the_loop_test.py create mode 100644 tests/pydantic_ai_plugin/logfire_test.py create mode 100644 tests/pydantic_ai_plugin/mcp_test.py create mode 100644 tests/pydantic_ai_plugin/multi_agent_test.py create mode 100644 tests/pydantic_ai_plugin/streaming_test.py create mode 100644 tests/pydantic_ai_plugin/structured_output_test.py create mode 100644 tests/pydantic_ai_plugin/tools_test.py diff --git a/README.md b/README.md index 2954d242..c3165d35 100644 --- a/README.md +++ b/README.md @@ -101,6 +101,7 @@ without wrapping them in a workflow. * [patching](patching) - Alter workflows safely with `patch` and `deprecate_patch`. * [polling](polling) - Recommended implementation of an activity that needs to periodically poll an external resource waiting its successful completion. * [prometheus](prometheus) - Configure Prometheus metrics on clients/workers. +* [pydantic_ai_plugin](pydantic_ai_plugin) - Run Pydantic AI agents as durable Temporal workflows, including chat, tools, MCP, HITL, structured output, streaming, multi-agent orchestration, and Logfire. * [pydantic_converter](pydantic_converter) - Data converter for using Pydantic models. * [pydantic_converter_v1](pydantic_converter_v1) - Data converter for Pydantic v1 models (prefer pydantic_converter for v2). * [replay](replay) - Verify that workflow code changes are compatible with existing histories. diff --git a/pydantic_ai_plugin/README.md b/pydantic_ai_plugin/README.md new file mode 100644 index 00000000..52e53a2d --- /dev/null +++ b/pydantic_ai_plugin/README.md @@ -0,0 +1,35 @@ +# Pydantic AI Plugin Samples + +These samples run ordinary [Pydantic AI](https://ai.pydantic.dev/) agents inside Temporal Workflows with `TemporalDurability`. `PydanticAIPlugin` configures Pydantic payload conversion, the Workflow Sandbox, non-retryable failures, and automatic Activity registration for agents declared on `PydanticAIWorkflow` classes. + +The samples use Pydantic AI's credential-free `TestModel` by default. Pass an OpenAI model name in the Workflow input to use a live model instead. + +| Sample | What it demonstrates | +| --- | --- | +| [chat](chat) | Multi-turn Updates, durable message history, and Continue-As-New. | +| [tools](tools) | A deterministic in-Workflow tool beside an I/O-style Activity tool. | +| [mcp](mcp) | A stateless in-process FastMCP server whose operations run as Activities. | +| [streaming](streaming) | Pydantic AI events over Temporal Workflow Streams. | +| [human_in_the_loop](human_in_the_loop) | Approval, rejection, and cancellation decisions delivered by Signal. | +| [structured_output](structured_output) | A typed Pydantic model crossing Activity and Workflow boundaries. | +| [multi_agent](multi_agent) | Durable researcher and writer agents coordinated by one Workflow. | +| [logfire](logfire) | Pydantic AI and Temporal tracing wired together by `LogfirePlugin`. | + +## Install + +```bash +uv sync --group pydantic-ai +temporal server start-dev +``` + +The dependency group pins `pydantic-ai-slim` to commit `2b45faa97e76461c60500e9755a130b158a2418d`, the head of [pydantic-ai PR #6639](https://github.com/pydantic/pydantic-ai/pull/6639), because the Workflow Streams API used by the streaming sample is not yet released. + +## Run + +Start a category's Worker, then use the Temporal CLI command in that category's README. With no `model` value, the Workflow uses `TestModel` and needs no API key or network access. For a live run, set `model` to `gateway/openai:gpt-5.2` and export `PYDANTIC_AI_GATEWAY_API_KEY` in the Worker process. + +The examples use the declarative registration path: each Workflow subclasses `PydanticAIWorkflow`, lists its agents in `__pydantic_ai_agents__`, and the Client installs `PydanticAIPlugin`. `AgentPlugin(agent)` is the narrower Worker-only alternative when a Workflow class cannot declare its agents; it does not replace the Client-side `PydanticAIPlugin` configuration. + +## Unsupported + +**Sandboxes:** Pydantic AI does not provide an agent-facing isolation environment whose sessions and shell or filesystem operations are durably managed by this integration. Temporal's Workflow determinism sandbox is a different boundary and is not an AI-agent sandbox. diff --git a/pydantic_ai_plugin/__init__.py b/pydantic_ai_plugin/__init__.py new file mode 100644 index 00000000..9d3afea4 --- /dev/null +++ b/pydantic_ai_plugin/__init__.py @@ -0,0 +1 @@ +"""Pydantic AI integration samples.""" diff --git a/pydantic_ai_plugin/chat/README.md b/pydantic_ai_plugin/chat/README.md new file mode 100644 index 00000000..f641471f --- /dev/null +++ b/pydantic_ai_plugin/chat/README.md @@ -0,0 +1,20 @@ +# Agent chat + +`ChatWorkflow` accepts each user turn as an Update, returns the assistant response from that Update, and keeps Pydantic AI `ModelMessage` history in Workflow state. When Temporal recommends Continue-As-New, it waits for active handlers and carries the typed history into the next run. + +```bash +uv run pydantic_ai_plugin/chat/run_worker.py + +temporal workflow start --type ChatWorkflow --task-queue pydantic-ai-chat --workflow-id pydantic-ai-chat-1 --input '{"messages":[],"model":null}' +temporal workflow update --workflow-id pydantic-ai-chat-1 --name turn --input '"Hello"' +temporal workflow query --workflow-id pydantic-ai-chat-1 --type message_count +temporal workflow signal --workflow-id pydantic-ai-chat-1 --name end_chat +``` + +For a live model, start with `{"messages":[],"model":"gateway/openai:gpt-5.2"}`. + +Expected offline Update result: `Ready for the next turn.` + +```bash +uv run --group pydantic-ai pytest tests/pydantic_ai_plugin/chat_test.py +``` diff --git a/pydantic_ai_plugin/chat/__init__.py b/pydantic_ai_plugin/chat/__init__.py new file mode 100644 index 00000000..e83ab34b --- /dev/null +++ b/pydantic_ai_plugin/chat/__init__.py @@ -0,0 +1 @@ +"""Durable chat sample.""" diff --git a/pydantic_ai_plugin/chat/run_worker.py b/pydantic_ai_plugin/chat/run_worker.py new file mode 100644 index 00000000..72528006 --- /dev/null +++ b/pydantic_ai_plugin/chat/run_worker.py @@ -0,0 +1,24 @@ +import asyncio +import os + +from temporalio.client import Client +from temporalio.worker import Worker + +from pydantic_ai.durable_exec.temporal import PydanticAIPlugin +from pydantic_ai_plugin.chat.workflow import ChatWorkflow + + +async def main() -> None: + client = await Client.connect( + os.environ.get("TEMPORAL_ADDRESS", "localhost:7233"), + plugins=[PydanticAIPlugin()], + ) + await Worker( + client, + task_queue="pydantic-ai-chat", + workflows=[ChatWorkflow], + ).run() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/pydantic_ai_plugin/chat/workflow.py b/pydantic_ai_plugin/chat/workflow.py new file mode 100644 index 00000000..384665e2 --- /dev/null +++ b/pydantic_ai_plugin/chat/workflow.py @@ -0,0 +1,67 @@ +import asyncio +from dataclasses import dataclass, field + +from temporalio import workflow + +with workflow.unsafe.imports_passed_through(): + from pydantic_ai import Agent, ModelMessage + from pydantic_ai.durable_exec.temporal import ( + PydanticAIWorkflow, + TemporalDurability, + ) + from pydantic_ai.models.test import TestModel + + +@dataclass +class ChatInput: + messages: list[ModelMessage] = field(default_factory=list) + model: str | None = None + + +agent = Agent( + TestModel(custom_output_text="Ready for the next turn."), + name="durable_chat", + capabilities=[TemporalDurability()], +) + + +@workflow.defn +class ChatWorkflow(PydanticAIWorkflow): + __pydantic_ai_agents__ = [agent] + + @workflow.init + def __init__(self, input: ChatInput) -> None: + self._input = input + self._messages = list(input.messages) + self._done = False + self._lock = asyncio.Lock() + + @workflow.update + async def turn(self, prompt: str) -> str: + async with self._lock: + result = await agent.run( + prompt, + message_history=self._messages, + model=self._input.model, + ) + self._messages = result.all_messages() + return result.output + + @workflow.signal + def end_chat(self) -> None: + self._done = True + + @workflow.query + def message_count(self) -> int: + return len(self._messages) + + @workflow.run + async def run(self, input: ChatInput) -> None: + await workflow.wait_condition( + lambda: self._done or workflow.info().is_continue_as_new_suggested() + ) + await workflow.wait_condition(workflow.all_handlers_finished) + if not self._done: + workflow.continue_as_new( + ChatInput(messages=self._messages, model=input.model) + ) diff --git a/pydantic_ai_plugin/human_in_the_loop/README.md b/pydantic_ai_plugin/human_in_the_loop/README.md new file mode 100644 index 00000000..688bfea2 --- /dev/null +++ b/pydantic_ai_plugin/human_in_the_loop/README.md @@ -0,0 +1,22 @@ +# Human in the loop + +The `delete_record` tool requires approval. Pydantic AI ends the first run with `DeferredToolRequests`; the Workflow exposes the pending tool through a Query and waits durably for an `approve`, `reject`, or `cancel` Signal. + +Approval resumes the agent with `DeferredToolResults`. Rejection sends `ToolDenied` back to the model. Cancellation ends the business operation without executing the tool. + +```bash +uv run pydantic_ai_plugin/human_in_the_loop/run_worker.py + +temporal workflow start --type ApprovalWorkflow --task-queue pydantic-ai-approval --workflow-id pydantic-ai-approval-1 --input '{"prompt":"Delete record 42.","model":null}' +temporal workflow query --workflow-id pydantic-ai-approval-1 --type pending_approval +temporal workflow signal --workflow-id pydantic-ai-approval-1 --name decide --input '"approve"' +temporal workflow show --workflow-id pydantic-ai-approval-1 +``` + +Send `"reject"` or `"cancel"` to exercise the other paths. Use `"model":"gateway/openai:gpt-5.2"` for a live run. + +Expected offline result after approval or rejection: `The operator decision was applied.` Cancellation returns `Cancelled by the operator.` + +```bash +uv run --group pydantic-ai pytest tests/pydantic_ai_plugin/human_in_the_loop_test.py +``` diff --git a/pydantic_ai_plugin/human_in_the_loop/__init__.py b/pydantic_ai_plugin/human_in_the_loop/__init__.py new file mode 100644 index 00000000..cbdf3815 --- /dev/null +++ b/pydantic_ai_plugin/human_in_the_loop/__init__.py @@ -0,0 +1 @@ +"""Human-in-the-loop sample.""" diff --git a/pydantic_ai_plugin/human_in_the_loop/run_worker.py b/pydantic_ai_plugin/human_in_the_loop/run_worker.py new file mode 100644 index 00000000..75c76eb6 --- /dev/null +++ b/pydantic_ai_plugin/human_in_the_loop/run_worker.py @@ -0,0 +1,24 @@ +import asyncio +import os + +from temporalio.client import Client +from temporalio.worker import Worker + +from pydantic_ai.durable_exec.temporal import PydanticAIPlugin +from pydantic_ai_plugin.human_in_the_loop.workflow import ApprovalWorkflow + + +async def main() -> None: + client = await Client.connect( + os.environ.get("TEMPORAL_ADDRESS", "localhost:7233"), + plugins=[PydanticAIPlugin()], + ) + await Worker( + client, + task_queue="pydantic-ai-approval", + workflows=[ApprovalWorkflow], + ).run() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/pydantic_ai_plugin/human_in_the_loop/workflow.py b/pydantic_ai_plugin/human_in_the_loop/workflow.py new file mode 100644 index 00000000..0c4d87bc --- /dev/null +++ b/pydantic_ai_plugin/human_in_the_loop/workflow.py @@ -0,0 +1,92 @@ +from dataclasses import dataclass +from typing import Literal + +from temporalio import workflow + +with workflow.unsafe.imports_passed_through(): + from pydantic_ai import ( + Agent, + DeferredToolRequests, + ToolApproved, + ToolDenied, + ) + from pydantic_ai.durable_exec.temporal import ( + PydanticAIWorkflow, + TemporalDurability, + ) + from pydantic_ai.models.test import TestModel + + +Decision = Literal["approve", "reject", "cancel"] + + +@dataclass +class ApprovalInput: + prompt: str + model: str | None = None + + +agent = Agent( + TestModel( + call_tools=["delete_record"], + custom_output_text="The operator decision was applied.", + ), + name="approval_agent", + output_type=[str, DeferredToolRequests], + capabilities=[TemporalDurability()], +) + + +@agent.tool_plain(requires_approval=True) +async def delete_record(record_id: str) -> str: + return f"deleted {record_id}" + + +@workflow.defn +class ApprovalWorkflow(PydanticAIWorkflow): + __pydantic_ai_agents__ = [agent] + + def __init__(self) -> None: + self._decision: Decision | None = None + self._pending: str | None = None + + @workflow.signal + def decide(self, decision: Decision) -> None: + self._decision = decision + + @workflow.query + def pending_approval(self) -> str | None: + return self._pending + + @workflow.run + async def run(self, input: ApprovalInput) -> str: + first = await agent.run(input.prompt, model=input.model) + if not isinstance(first.output, DeferredToolRequests): + return first.output + + calls = first.output.approvals + self._pending = calls[0].tool_name if calls else None + await workflow.wait_condition(lambda: self._decision is not None) + decision = self._decision + self._pending = None + + if decision == "cancel": + return "Cancelled by the operator." + + approvals: dict[str, bool | ToolApproved | ToolDenied] = { + call.tool_call_id: ( + True + if decision == "approve" + else ToolDenied(message="Rejected by the operator.") + ) + for call in calls + } + deferred_results = first.output.build_results(approvals=approvals) + resumed = await agent.run( + "Continue after the operator decision.", + message_history=first.all_messages(), + deferred_tool_results=deferred_results, + model=input.model, + ) + assert isinstance(resumed.output, str) + return resumed.output diff --git a/pydantic_ai_plugin/logfire/README.md b/pydantic_ai_plugin/logfire/README.md new file mode 100644 index 00000000..920f9eaa --- /dev/null +++ b/pydantic_ai_plugin/logfire/README.md @@ -0,0 +1,16 @@ +# Observability with Logfire + +`LogfirePlugin` installs Temporal's OpenTelemetry tracing interceptor and Pydantic AI instrumentation, producing one connected trace across Workflow execution, model Activities, agent runs, and tools. The sample disables remote export when `LOGFIRE_TOKEN` is absent, so it also runs credential-free. + +```bash +uv run pydantic_ai_plugin/logfire/run_worker.py +temporal workflow execute --type ObservabilityWorkflow --task-queue pydantic-ai-logfire --workflow-id pydantic-ai-logfire-1 --input '{"prompt":"Run an observable agent.","model":null}' +``` + +To send traces to Logfire, authenticate with `logfire auth`, export `LOGFIRE_TOKEN`, and restart the Worker. Use `"model":"gateway/openai:gpt-5.2"` for a live model. + +Expected offline result: `This run is traced.` The test captures both the agent and Workflow spans in memory. + +```bash +uv run --group pydantic-ai pytest tests/pydantic_ai_plugin/logfire_test.py +``` diff --git a/pydantic_ai_plugin/logfire/__init__.py b/pydantic_ai_plugin/logfire/__init__.py new file mode 100644 index 00000000..d3707d81 --- /dev/null +++ b/pydantic_ai_plugin/logfire/__init__.py @@ -0,0 +1 @@ +"""Logfire observability sample.""" diff --git a/pydantic_ai_plugin/logfire/run_worker.py b/pydantic_ai_plugin/logfire/run_worker.py new file mode 100644 index 00000000..09ee4604 --- /dev/null +++ b/pydantic_ai_plugin/logfire/run_worker.py @@ -0,0 +1,27 @@ +import asyncio +import os + +import logfire +from temporalio.client import Client +from temporalio.worker import Worker + +from pydantic_ai.durable_exec.temporal import LogfirePlugin, PydanticAIPlugin +from pydantic_ai_plugin.logfire.workflow import ObservabilityWorkflow + + +async def main() -> None: + if os.environ.get("LOGFIRE_TOKEN") is None: + logfire.configure(send_to_logfire=False) + client = await Client.connect( + os.environ.get("TEMPORAL_ADDRESS", "localhost:7233"), + plugins=[PydanticAIPlugin(), LogfirePlugin(metrics=False)], + ) + await Worker( + client, + task_queue="pydantic-ai-logfire", + workflows=[ObservabilityWorkflow], + ).run() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/pydantic_ai_plugin/logfire/workflow.py b/pydantic_ai_plugin/logfire/workflow.py new file mode 100644 index 00000000..c8a360f1 --- /dev/null +++ b/pydantic_ai_plugin/logfire/workflow.py @@ -0,0 +1,34 @@ +from dataclasses import dataclass + +from temporalio import workflow + +with workflow.unsafe.imports_passed_through(): + from pydantic_ai import Agent + from pydantic_ai.durable_exec.temporal import ( + PydanticAIWorkflow, + TemporalDurability, + ) + from pydantic_ai.models.test import TestModel + + +@dataclass +class ObservabilityInput: + prompt: str + model: str | None = None + + +agent = Agent( + TestModel(custom_output_text="This run is traced."), + name="observable_agent", + capabilities=[TemporalDurability()], +) + + +@workflow.defn +class ObservabilityWorkflow(PydanticAIWorkflow): + __pydantic_ai_agents__ = [agent] + + @workflow.run + async def run(self, input: ObservabilityInput) -> str: + result = await agent.run(input.prompt, model=input.model) + return result.output diff --git a/pydantic_ai_plugin/mcp/README.md b/pydantic_ai_plugin/mcp/README.md new file mode 100644 index 00000000..80a0f54e --- /dev/null +++ b/pydantic_ai_plugin/mcp/README.md @@ -0,0 +1,16 @@ +# MCP + +The agent uses a stateless in-process FastMCP server. `MCPToolset` exposes its `support_hours` tool, while `TemporalDurability` moves MCP listing and tool calls into Temporal Activities. The server keeps no session state, so Activity retries are safe. + +```bash +uv run pydantic_ai_plugin/mcp/run_worker.py +temporal workflow execute --type MCPWorkflow --task-queue pydantic-ai-mcp --workflow-id pydantic-ai-mcp-1 --input '{"prompt":"When is support staffed?","model":null}' +``` + +Use `"model":"gateway/openai:gpt-5.2"` for a live run. + +Expected offline result: `Hours found.` + +```bash +uv run --group pydantic-ai pytest tests/pydantic_ai_plugin/mcp_test.py +``` diff --git a/pydantic_ai_plugin/mcp/__init__.py b/pydantic_ai_plugin/mcp/__init__.py new file mode 100644 index 00000000..199a32a5 --- /dev/null +++ b/pydantic_ai_plugin/mcp/__init__.py @@ -0,0 +1 @@ +"""Durable MCP sample.""" diff --git a/pydantic_ai_plugin/mcp/run_worker.py b/pydantic_ai_plugin/mcp/run_worker.py new file mode 100644 index 00000000..ec0341ac --- /dev/null +++ b/pydantic_ai_plugin/mcp/run_worker.py @@ -0,0 +1,24 @@ +import asyncio +import os + +from temporalio.client import Client +from temporalio.worker import Worker + +from pydantic_ai.durable_exec.temporal import PydanticAIPlugin +from pydantic_ai_plugin.mcp.workflow import MCPWorkflow + + +async def main() -> None: + client = await Client.connect( + os.environ.get("TEMPORAL_ADDRESS", "localhost:7233"), + plugins=[PydanticAIPlugin()], + ) + await Worker( + client, + task_queue="pydantic-ai-mcp", + workflows=[MCPWorkflow], + ).run() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/pydantic_ai_plugin/mcp/workflow.py b/pydantic_ai_plugin/mcp/workflow.py new file mode 100644 index 00000000..eac94a7a --- /dev/null +++ b/pydantic_ai_plugin/mcp/workflow.py @@ -0,0 +1,46 @@ +from dataclasses import dataclass + +from temporalio import workflow + +with workflow.unsafe.imports_passed_through(): + from fastmcp import FastMCP + from pydantic_ai import Agent + from pydantic_ai.durable_exec.temporal import ( + PydanticAIWorkflow, + TemporalDurability, + ) + from pydantic_ai.mcp import MCPToolset + from pydantic_ai.models.test import TestModel + + +@dataclass +class MCPInput: + prompt: str + model: str | None = None + + +server = FastMCP("support-directory") + + +@server.tool +def support_hours() -> str: + return "Support is staffed 09:00-17:00 UTC." + + +toolset = MCPToolset(server, id="support_directory") +agent = Agent( + TestModel(call_tools=["support_hours"], custom_output_text="Hours found."), + name="mcp_support", + toolsets=[toolset], + capabilities=[TemporalDurability()], +) + + +@workflow.defn +class MCPWorkflow(PydanticAIWorkflow): + __pydantic_ai_agents__ = [agent] + + @workflow.run + async def run(self, input: MCPInput) -> str: + result = await agent.run(input.prompt, model=input.model) + return result.output diff --git a/pydantic_ai_plugin/multi_agent/README.md b/pydantic_ai_plugin/multi_agent/README.md new file mode 100644 index 00000000..1b6465da --- /dev/null +++ b/pydantic_ai_plugin/multi_agent/README.md @@ -0,0 +1,16 @@ +# Multi-agent + +This sample uses Pydantic AI's programmatic handoff pattern. The researcher finishes first, then its durable result becomes input to the writer. Each model request is a separately recorded Temporal Activity, so a Worker restart resumes from completed work instead of repeating the whole pipeline. + +```bash +uv run pydantic_ai_plugin/multi_agent/run_worker.py +temporal workflow execute --type MultiAgentWorkflow --task-queue pydantic-ai-multi-agent --workflow-id pydantic-ai-multi-agent-1 --input '{"topic":"How Temporal recovers from failures","model":null}' +``` + +Use `"model":"gateway/openai:gpt-5.2"` for a live run. + +Expected offline result: `A concise explanation is ready.` + +```bash +uv run --group pydantic-ai pytest tests/pydantic_ai_plugin/multi_agent_test.py +``` diff --git a/pydantic_ai_plugin/multi_agent/__init__.py b/pydantic_ai_plugin/multi_agent/__init__.py new file mode 100644 index 00000000..76f6bf8f --- /dev/null +++ b/pydantic_ai_plugin/multi_agent/__init__.py @@ -0,0 +1 @@ +"""Durable multi-agent sample.""" diff --git a/pydantic_ai_plugin/multi_agent/run_worker.py b/pydantic_ai_plugin/multi_agent/run_worker.py new file mode 100644 index 00000000..a1125fab --- /dev/null +++ b/pydantic_ai_plugin/multi_agent/run_worker.py @@ -0,0 +1,24 @@ +import asyncio +import os + +from temporalio.client import Client +from temporalio.worker import Worker + +from pydantic_ai.durable_exec.temporal import PydanticAIPlugin +from pydantic_ai_plugin.multi_agent.workflow import MultiAgentWorkflow + + +async def main() -> None: + client = await Client.connect( + os.environ.get("TEMPORAL_ADDRESS", "localhost:7233"), + plugins=[PydanticAIPlugin()], + ) + await Worker( + client, + task_queue="pydantic-ai-multi-agent", + workflows=[MultiAgentWorkflow], + ).run() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/pydantic_ai_plugin/multi_agent/workflow.py b/pydantic_ai_plugin/multi_agent/workflow.py new file mode 100644 index 00000000..a7594277 --- /dev/null +++ b/pydantic_ai_plugin/multi_agent/workflow.py @@ -0,0 +1,45 @@ +from dataclasses import dataclass + +from temporalio import workflow + +with workflow.unsafe.imports_passed_through(): + from pydantic_ai import Agent + from pydantic_ai.durable_exec.temporal import ( + PydanticAIWorkflow, + TemporalDurability, + ) + from pydantic_ai.models.test import TestModel + + +@dataclass +class MultiAgentInput: + topic: str + model: str | None = None + + +researcher = Agent( + TestModel(custom_output_text="Temporal records each completed step."), + name="researcher", + instructions="Find one accurate fact about the requested topic.", + capabilities=[TemporalDurability()], +) +writer = Agent( + TestModel(custom_output_text="A concise explanation is ready."), + name="writer", + instructions="Turn the supplied research into one concise sentence.", + capabilities=[TemporalDurability()], +) + + +@workflow.defn +class MultiAgentWorkflow(PydanticAIWorkflow): + __pydantic_ai_agents__ = [researcher, writer] + + @workflow.run + async def run(self, input: MultiAgentInput) -> str: + research = await researcher.run(input.topic, model=input.model) + draft = await writer.run( + f"Topic: {input.topic}\nResearch: {research.output}", + model=input.model, + ) + return draft.output diff --git a/pydantic_ai_plugin/streaming/README.md b/pydantic_ai_plugin/streaming/README.md new file mode 100644 index 00000000..f0dd3005 --- /dev/null +++ b/pydantic_ai_plugin/streaming/README.md @@ -0,0 +1,20 @@ +# Streaming + +This sample uses the Workflow Streams support introduced by [pydantic-ai PR #6639](https://github.com/pydantic/pydantic-ai/pull/6639). + +`TemporalDurability(event_stream_topic=...)` publishes typed agent events. `AgentEventStream` hosts the stream in the Workflow and keeps the Workflow alive until the terminal `AgentRunResultEvent` is acknowledged, bounded by `drain_timeout`. The consumer uses `durability.stream_agent_events(...)`; its iterator ends when the terminal event arrives and exposes an offset for reconnecting. + +The topic filters token-level `PartDeltaEvent` objects to limit Workflow state. The terminal event is always retained. + +```bash +uv run pydantic_ai_plugin/streaming/run_worker.py +uv run pydantic_ai_plugin/streaming/run_workflow.py +``` + +The producer still completes if no subscriber connects after the drain timeout. Model events published from an Activity have at-least-once delivery, so production consumers should tolerate duplicates after Activity retries. + +The offline consumer prints typed event names, ending with `AgentRunResultEvent`, followed by `The durable response is complete.` + +```bash +uv run --group pydantic-ai pytest tests/pydantic_ai_plugin/streaming_test.py +``` diff --git a/pydantic_ai_plugin/streaming/__init__.py b/pydantic_ai_plugin/streaming/__init__.py new file mode 100644 index 00000000..20c08dc2 --- /dev/null +++ b/pydantic_ai_plugin/streaming/__init__.py @@ -0,0 +1 @@ +"""Workflow Streams sample.""" diff --git a/pydantic_ai_plugin/streaming/run_worker.py b/pydantic_ai_plugin/streaming/run_worker.py new file mode 100644 index 00000000..75faa949 --- /dev/null +++ b/pydantic_ai_plugin/streaming/run_worker.py @@ -0,0 +1,24 @@ +import asyncio +import os + +from temporalio.client import Client +from temporalio.worker import Worker + +from pydantic_ai.durable_exec.temporal import PydanticAIPlugin +from pydantic_ai_plugin.streaming.workflow import StreamingWorkflow + + +async def main() -> None: + client = await Client.connect( + os.environ.get("TEMPORAL_ADDRESS", "localhost:7233"), + plugins=[PydanticAIPlugin()], + ) + await Worker( + client, + task_queue="pydantic-ai-streaming", + workflows=[StreamingWorkflow], + ).run() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/pydantic_ai_plugin/streaming/run_workflow.py b/pydantic_ai_plugin/streaming/run_workflow.py new file mode 100644 index 00000000..f7641b7c --- /dev/null +++ b/pydantic_ai_plugin/streaming/run_workflow.py @@ -0,0 +1,32 @@ +import asyncio +import uuid + +from temporalio.client import Client + +from pydantic_ai.durable_exec.temporal import PydanticAIPlugin +from pydantic_ai_plugin.streaming.workflow import ( + StreamingInput, + StreamingWorkflow, + durability, +) + + +async def main() -> None: + client = await Client.connect( + "localhost:7233", + plugins=[PydanticAIPlugin()], + ) + handle = await client.start_workflow( + StreamingWorkflow.run, + StreamingInput(prompt="Explain durable execution in one sentence."), + id=f"pydantic-ai-streaming-{uuid.uuid4()}", + task_queue="pydantic-ai-streaming", + ) + events = durability.stream_agent_events(client, handle, output_type=str) + async for event in events: + print(type(event).__name__, event) + print(await handle.result()) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/pydantic_ai_plugin/streaming/workflow.py b/pydantic_ai_plugin/streaming/workflow.py new file mode 100644 index 00000000..45f658d0 --- /dev/null +++ b/pydantic_ai_plugin/streaming/workflow.py @@ -0,0 +1,51 @@ +from dataclasses import dataclass +from datetime import timedelta + +from temporalio import workflow + +with workflow.unsafe.imports_passed_through(): + from pydantic_ai import Agent + from pydantic_ai.durable_exec.temporal import ( + AgentEventStream, + PydanticAIWorkflow, + TemporalDurability, + WorkflowStreamTopic, + ) + from pydantic_ai.messages import PartDeltaEvent + from pydantic_ai.models.test import TestModel + + +@dataclass +class StreamingInput: + prompt: str + model: str | None = None + drain_timeout_seconds: float = 30 + + +topic = WorkflowStreamTopic( + "agent-events", + events=lambda event: not isinstance(event, PartDeltaEvent), +) +durability = TemporalDurability(event_stream_topic=topic) +agent = Agent( + TestModel(custom_output_text="The durable response is complete."), + name="workflow_streaming", + capabilities=[durability], +) + + +@workflow.defn +class StreamingWorkflow(PydanticAIWorkflow): + __pydantic_ai_agents__ = [agent] + + @workflow.init + def __init__(self, input: StreamingInput) -> None: + self.events = AgentEventStream( + drain_timeout=timedelta(seconds=input.drain_timeout_seconds) + ) + + @workflow.run + async def run(self, input: StreamingInput) -> str: + async with self.events: + result = await agent.run(input.prompt, model=input.model) + return result.output diff --git a/pydantic_ai_plugin/structured_output/README.md b/pydantic_ai_plugin/structured_output/README.md new file mode 100644 index 00000000..f0396ff5 --- /dev/null +++ b/pydantic_ai_plugin/structured_output/README.md @@ -0,0 +1,16 @@ +# Structured output + +The agent returns `IncidentSummary`, a validated Pydantic model. `PydanticAIPlugin` installs the payload converter that preserves this type across the model Activity, Workflow state, and Workflow result. + +```bash +uv run pydantic_ai_plugin/structured_output/run_worker.py +temporal workflow execute --type StructuredOutputWorkflow --task-queue pydantic-ai-structured-output --workflow-id pydantic-ai-structured-1 --input '{"prompt":"Summarize the payments incident with severity and next action.","model":null}' +``` + +Use `"model":"gateway/openai:gpt-5.2"` for a live run. + +The offline result is a validated `IncidentSummary` for the payments service. + +```bash +uv run --group pydantic-ai pytest tests/pydantic_ai_plugin/structured_output_test.py +``` diff --git a/pydantic_ai_plugin/structured_output/__init__.py b/pydantic_ai_plugin/structured_output/__init__.py new file mode 100644 index 00000000..250fb410 --- /dev/null +++ b/pydantic_ai_plugin/structured_output/__init__.py @@ -0,0 +1 @@ +"""Structured output sample.""" diff --git a/pydantic_ai_plugin/structured_output/run_worker.py b/pydantic_ai_plugin/structured_output/run_worker.py new file mode 100644 index 00000000..ef2180a3 --- /dev/null +++ b/pydantic_ai_plugin/structured_output/run_worker.py @@ -0,0 +1,24 @@ +import asyncio +import os + +from temporalio.client import Client +from temporalio.worker import Worker + +from pydantic_ai.durable_exec.temporal import PydanticAIPlugin +from pydantic_ai_plugin.structured_output.workflow import StructuredOutputWorkflow + + +async def main() -> None: + client = await Client.connect( + os.environ.get("TEMPORAL_ADDRESS", "localhost:7233"), + plugins=[PydanticAIPlugin()], + ) + await Worker( + client, + task_queue="pydantic-ai-structured-output", + workflows=[StructuredOutputWorkflow], + ).run() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/pydantic_ai_plugin/structured_output/workflow.py b/pydantic_ai_plugin/structured_output/workflow.py new file mode 100644 index 00000000..97398a3f --- /dev/null +++ b/pydantic_ai_plugin/structured_output/workflow.py @@ -0,0 +1,48 @@ +from dataclasses import dataclass + +from temporalio import workflow + +with workflow.unsafe.imports_passed_through(): + from pydantic import BaseModel, Field + from pydantic_ai import Agent + from pydantic_ai.durable_exec.temporal import ( + PydanticAIWorkflow, + TemporalDurability, + ) + from pydantic_ai.models.test import TestModel + + +class IncidentSummary(BaseModel): + service: str = Field(description="Affected service") + severity: int = Field(ge=1, le=5) + action: str + + +@dataclass +class StructuredInput: + prompt: str + model: str | None = None + + +agent = Agent( + TestModel( + custom_output_args={ + "service": "payments", + "severity": 2, + "action": "Restart the worker pool.", + } + ), + name="incident_structurer", + output_type=IncidentSummary, + capabilities=[TemporalDurability()], +) + + +@workflow.defn +class StructuredOutputWorkflow(PydanticAIWorkflow): + __pydantic_ai_agents__ = [agent] + + @workflow.run + async def run(self, input: StructuredInput) -> IncidentSummary: + result = await agent.run(input.prompt, model=input.model) + return result.output diff --git a/pydantic_ai_plugin/tools/README.md b/pydantic_ai_plugin/tools/README.md new file mode 100644 index 00000000..0cbd8c92 --- /dev/null +++ b/pydantic_ai_plugin/tools/README.md @@ -0,0 +1,21 @@ +# Tools + +This sample puts two tools behind one durable agent: + +- `read_policy` is async, deterministic, and marked with `metadata={"temporal": False}`, so it runs in Workflow code. +- `lookup_inventory` represents I/O and keeps the default behavior, so Pydantic AI dispatches it as a Temporal Activity. + +The model request is also an Activity. The test inspects Workflow history to verify the tool boundary. + +```bash +uv run pydantic_ai_plugin/tools/run_worker.py +temporal workflow execute --type ToolsWorkflow --task-queue pydantic-ai-tools --workflow-id pydantic-ai-tools-1 --input '{"prompt":"Check policy and inventory.","model":null}' +``` + +Use `"model":"gateway/openai:gpt-5.2"` for a live run. + +Expected offline result: `Both checks completed.` + +```bash +uv run --group pydantic-ai pytest tests/pydantic_ai_plugin/tools_test.py +``` diff --git a/pydantic_ai_plugin/tools/__init__.py b/pydantic_ai_plugin/tools/__init__.py new file mode 100644 index 00000000..9e6ff440 --- /dev/null +++ b/pydantic_ai_plugin/tools/__init__.py @@ -0,0 +1 @@ +"""Durable tools sample.""" diff --git a/pydantic_ai_plugin/tools/run_worker.py b/pydantic_ai_plugin/tools/run_worker.py new file mode 100644 index 00000000..aa308efb --- /dev/null +++ b/pydantic_ai_plugin/tools/run_worker.py @@ -0,0 +1,24 @@ +import asyncio +import os + +from temporalio.client import Client +from temporalio.worker import Worker + +from pydantic_ai.durable_exec.temporal import PydanticAIPlugin +from pydantic_ai_plugin.tools.workflow import ToolsWorkflow + + +async def main() -> None: + client = await Client.connect( + os.environ.get("TEMPORAL_ADDRESS", "localhost:7233"), + plugins=[PydanticAIPlugin()], + ) + await Worker( + client, + task_queue="pydantic-ai-tools", + workflows=[ToolsWorkflow], + ).run() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/pydantic_ai_plugin/tools/workflow.py b/pydantic_ai_plugin/tools/workflow.py new file mode 100644 index 00000000..01271d6d --- /dev/null +++ b/pydantic_ai_plugin/tools/workflow.py @@ -0,0 +1,47 @@ +from dataclasses import dataclass + +from temporalio import workflow + +with workflow.unsafe.imports_passed_through(): + from pydantic_ai import Agent + from pydantic_ai.durable_exec.temporal import ( + PydanticAIWorkflow, + TemporalDurability, + ) + from pydantic_ai.models.test import TestModel + + +@dataclass +class ToolsInput: + prompt: str + model: str | None = None + + +agent = Agent( + TestModel( + call_tools=["read_policy", "lookup_inventory"], + custom_output_text="Both checks completed.", + ), + name="tool_boundaries", + capabilities=[TemporalDurability()], +) + + +@agent.tool_plain(metadata={"temporal": False}) +async def read_policy() -> str: + return "policy: standard shipping" + + +@agent.tool_plain +async def lookup_inventory() -> str: + return "inventory: 12 units" + + +@workflow.defn +class ToolsWorkflow(PydanticAIWorkflow): + __pydantic_ai_agents__ = [agent] + + @workflow.run + async def run(self, input: ToolsInput) -> str: + result = await agent.run(input.prompt, model=input.model) + return result.output diff --git a/pyproject.toml b/pyproject.toml index 63bbed3d..f412afc4 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -81,6 +81,11 @@ openai-agents = [ "requests>=2.32.0,<3", ] pydantic-converter = ["pydantic>=2.10.6,<3"] +pydantic-ai = [ + "fastmcp>=3.3.0,<5", + "logfire>=4.39,<4.40", + "pydantic-ai-slim[mcp,temporal]", +] sentry = ["sentry-sdk>=2.13.0"] strands-agents = [ "strands-agents>=1.39.0", @@ -104,6 +109,9 @@ constraint-dependencies = [ "yarl!=1.24.0", ] +[tool.uv.sources] +pydantic-ai-slim = { git = "https://github.com/pydantic/pydantic-ai.git", rev = "2b45faa97e76461c60500e9755a130b158a2418d", subdirectory = "pydantic_ai_slim" } + [tool.setuptools.packages.find] exclude = ["lambda_worker*"] diff --git a/tests/pydantic_ai_plugin/__init__.py b/tests/pydantic_ai_plugin/__init__.py new file mode 100644 index 00000000..8b7fd81e --- /dev/null +++ b/tests/pydantic_ai_plugin/__init__.py @@ -0,0 +1 @@ +"""Tests for Pydantic AI integration samples.""" diff --git a/tests/pydantic_ai_plugin/chat_test.py b/tests/pydantic_ai_plugin/chat_test.py new file mode 100644 index 00000000..8c0a635e --- /dev/null +++ b/tests/pydantic_ai_plugin/chat_test.py @@ -0,0 +1,58 @@ +import asyncio +import uuid + +from temporalio.client import Client, WorkflowExecutionStatus +from temporalio.testing import WorkflowEnvironment +from temporalio.worker import Worker + +from pydantic_ai.durable_exec.temporal import PydanticAIPlugin +from pydantic_ai_plugin.chat.workflow import ChatInput, ChatWorkflow + + +async def test_chat_carries_messages_across_continue_as_new() -> None: + async with await WorkflowEnvironment.start_local( + dev_server_extra_args=[ + "--dynamic-config-value", + "limit.historyCount.suggestContinueAsNew=5", + ] + ) as env: + config = env.client.config() + config["plugins"] = [*config["plugins"], PydanticAIPlugin()] + client = Client(**config) + task_queue = f"pydantic-ai-chat-{uuid.uuid4()}" + workflow_id = f"pydantic-ai-chat-{uuid.uuid4()}" + + async with Worker( + client, + task_queue=task_queue, + workflows=[ChatWorkflow], + max_cached_workflows=0, + ): + handle = await client.start_workflow( + ChatWorkflow.run, + ChatInput(), + id=workflow_id, + task_queue=task_queue, + ) + first_run_id = handle.result_run_id + assert await handle.execute_update(ChatWorkflow.turn, "Hello") == ( + "Ready for the next turn." + ) + + first_run = client.get_workflow_handle(workflow_id, run_id=first_run_id) + for _ in range(100): + if ( + await first_run.describe() + ).status == WorkflowExecutionStatus.CONTINUED_AS_NEW: + break + await asyncio.sleep(0.1) + else: + raise AssertionError("workflow did not continue as new") + + latest = client.get_workflow_handle(workflow_id) + assert await latest.execute_update(ChatWorkflow.turn, "Again") == ( + "Ready for the next turn." + ) + assert await latest.query(ChatWorkflow.message_count) == 4 + await latest.signal(ChatWorkflow.end_chat) + await latest.result() diff --git a/tests/pydantic_ai_plugin/helpers.py b/tests/pydantic_ai_plugin/helpers.py new file mode 100644 index 00000000..3336feaf --- /dev/null +++ b/tests/pydantic_ai_plugin/helpers.py @@ -0,0 +1,9 @@ +from temporalio.client import Client + +from pydantic_ai.durable_exec.temporal import PydanticAIPlugin + + +def with_pydantic_ai(client: Client) -> Client: + config = client.config() + config["plugins"] = [*config["plugins"], PydanticAIPlugin()] + return Client(**config) diff --git a/tests/pydantic_ai_plugin/human_in_the_loop_test.py b/tests/pydantic_ai_plugin/human_in_the_loop_test.py new file mode 100644 index 00000000..d2a54b4c --- /dev/null +++ b/tests/pydantic_ai_plugin/human_in_the_loop_test.py @@ -0,0 +1,50 @@ +import asyncio +import uuid + +import pytest +from temporalio.client import Client +from temporalio.worker import Worker + +from pydantic_ai_plugin.human_in_the_loop.workflow import ( + ApprovalInput, + ApprovalWorkflow, + Decision, +) +from tests.pydantic_ai_plugin.helpers import with_pydantic_ai + + +@pytest.mark.parametrize( + ("decision", "expected"), + [ + ("approve", "The operator decision was applied."), + ("reject", "The operator decision was applied."), + ("cancel", "Cancelled by the operator."), + ], +) +async def test_operator_decision( + client: Client, decision: Decision, expected: str +) -> None: + client = with_pydantic_ai(client) + task_queue = f"pydantic-ai-approval-{uuid.uuid4()}" + async with Worker( + client, + task_queue=task_queue, + workflows=[ApprovalWorkflow], + max_cached_workflows=0, + ): + handle = await client.start_workflow( + ApprovalWorkflow.run, + ApprovalInput(prompt="Delete the record."), + id=f"pydantic-ai-approval-{uuid.uuid4()}", + task_queue=task_queue, + ) + for _ in range(100): + if await handle.query(ApprovalWorkflow.pending_approval): + break + await asyncio.sleep(0.05) + else: + raise AssertionError("approval was not requested") + await handle.signal(ApprovalWorkflow.decide, decision) + result = await handle.result() + + assert result == expected diff --git a/tests/pydantic_ai_plugin/logfire_test.py b/tests/pydantic_ai_plugin/logfire_test.py new file mode 100644 index 00000000..c867d77d --- /dev/null +++ b/tests/pydantic_ai_plugin/logfire_test.py @@ -0,0 +1,44 @@ +import uuid + +from logfire.testing import CaptureLogfire +from temporalio.client import Client +from temporalio.contrib.opentelemetry import TracingInterceptor +from temporalio.worker import Worker + +from pydantic_ai.durable_exec.temporal import LogfirePlugin, PydanticAIPlugin +from pydantic_ai_plugin.logfire.workflow import ( + ObservabilityInput, + ObservabilityWorkflow, +) + + +async def test_logfire_plugin_traces_durable_agent( + client: Client, capfire: CaptureLogfire +) -> None: + traced = await Client.connect( + client.service_client.config.target_host, + plugins=[PydanticAIPlugin(), LogfirePlugin(metrics=False)], + ) + assert any( + isinstance(interceptor, TracingInterceptor) + for interceptor in traced.config(active_config=True)["interceptors"] + ) + + task_queue = f"pydantic-ai-logfire-{uuid.uuid4()}" + async with Worker( + traced, + task_queue=task_queue, + workflows=[ObservabilityWorkflow], + max_cached_workflows=0, + ): + result = await traced.execute_workflow( + ObservabilityWorkflow.run, + ObservabilityInput(prompt="Trace this run."), + id=f"pydantic-ai-logfire-{uuid.uuid4()}", + task_queue=task_queue, + ) + + assert result == "This run is traced." + span_names = [span["name"] for span in capfire.exporter.exported_spans_as_dict()] + assert any("observable_agent" in name for name in span_names), span_names + assert any("Workflow" in name for name in span_names), span_names diff --git a/tests/pydantic_ai_plugin/mcp_test.py b/tests/pydantic_ai_plugin/mcp_test.py new file mode 100644 index 00000000..21d3020c --- /dev/null +++ b/tests/pydantic_ai_plugin/mcp_test.py @@ -0,0 +1,26 @@ +import uuid + +from temporalio.client import Client +from temporalio.worker import Worker + +from pydantic_ai_plugin.mcp.workflow import MCPInput, MCPWorkflow +from tests.pydantic_ai_plugin.helpers import with_pydantic_ai + + +async def test_stateless_mcp_tool(client: Client) -> None: + client = with_pydantic_ai(client) + task_queue = f"pydantic-ai-mcp-{uuid.uuid4()}" + async with Worker( + client, + task_queue=task_queue, + workflows=[MCPWorkflow], + max_cached_workflows=0, + ): + result = await client.execute_workflow( + MCPWorkflow.run, + MCPInput(prompt="Find support hours."), + id=f"pydantic-ai-mcp-{uuid.uuid4()}", + task_queue=task_queue, + ) + + assert result == "Hours found." diff --git a/tests/pydantic_ai_plugin/multi_agent_test.py b/tests/pydantic_ai_plugin/multi_agent_test.py new file mode 100644 index 00000000..698c751d --- /dev/null +++ b/tests/pydantic_ai_plugin/multi_agent_test.py @@ -0,0 +1,37 @@ +import uuid + +from temporalio.client import Client +from temporalio.worker import Worker + +from pydantic_ai_plugin.multi_agent.workflow import ( + MultiAgentInput, + MultiAgentWorkflow, +) +from tests.pydantic_ai_plugin.helpers import with_pydantic_ai + + +async def test_two_agents_run_durably(client: Client) -> None: + client = with_pydantic_ai(client) + task_queue = f"pydantic-ai-multi-agent-{uuid.uuid4()}" + async with Worker( + client, + task_queue=task_queue, + workflows=[MultiAgentWorkflow], + max_cached_workflows=0, + ): + handle = await client.start_workflow( + MultiAgentWorkflow.run, + MultiAgentInput(topic="Temporal recovery"), + id=f"pydantic-ai-multi-agent-{uuid.uuid4()}", + task_queue=task_queue, + ) + result = await handle.result() + + assert result == "A concise explanation is ready." + activity_names = [] + async for event in handle.fetch_history_events(): + if event.HasField("activity_task_scheduled_event_attributes"): + attributes = event.activity_task_scheduled_event_attributes + activity_names.append(attributes.activity_type.name) + assert any("agent__researcher__model_request" == name for name in activity_names) + assert any("agent__writer__model_request" == name for name in activity_names) diff --git a/tests/pydantic_ai_plugin/streaming_test.py b/tests/pydantic_ai_plugin/streaming_test.py new file mode 100644 index 00000000..d70d476b --- /dev/null +++ b/tests/pydantic_ai_plugin/streaming_test.py @@ -0,0 +1,65 @@ +import uuid +from datetime import timedelta + +from pydantic_ai.run import AgentRunResultEvent +from temporalio.client import Client +from temporalio.worker import Worker + +from pydantic_ai_plugin.streaming.workflow import ( + StreamingInput, + StreamingWorkflow, + durability, +) +from tests.pydantic_ai_plugin.helpers import with_pydantic_ai + + +async def test_stream_ends_with_agent_result(client: Client) -> None: + client = with_pydantic_ai(client) + task_queue = f"pydantic-ai-streaming-{uuid.uuid4()}" + async with Worker( + client, + task_queue=task_queue, + workflows=[StreamingWorkflow], + max_cached_workflows=0, + ): + handle = await client.start_workflow( + StreamingWorkflow.run, + StreamingInput(prompt="Stream a response."), + id=f"pydantic-ai-streaming-{uuid.uuid4()}", + task_queue=task_queue, + ) + stream = durability.stream_agent_events( + client, + handle, + output_type=str, + poll_cooldown=timedelta(milliseconds=10), + ) + events = [event async for event in stream] + result = await handle.result() + + assert result == "The durable response is complete." + assert isinstance(events[-1], AgentRunResultEvent) + assert stream.result is not None + assert stream.result.output == result + + +async def test_streaming_workflow_finishes_without_subscriber(client: Client) -> None: + client = with_pydantic_ai(client) + task_queue = f"pydantic-ai-streaming-unwatched-{uuid.uuid4()}" + async with Worker( + client, + task_queue=task_queue, + workflows=[StreamingWorkflow], + max_cached_workflows=0, + ): + result = await client.execute_workflow( + StreamingWorkflow.run, + StreamingInput( + prompt="Run unwatched.", + drain_timeout_seconds=0.01, + ), + id=f"pydantic-ai-streaming-unwatched-{uuid.uuid4()}", + task_queue=task_queue, + ) + + assert result == "The durable response is complete." diff --git a/tests/pydantic_ai_plugin/structured_output_test.py b/tests/pydantic_ai_plugin/structured_output_test.py new file mode 100644 index 00000000..c2788d9b --- /dev/null +++ b/tests/pydantic_ai_plugin/structured_output_test.py @@ -0,0 +1,34 @@ +import uuid + +from temporalio.client import Client +from temporalio.worker import Worker + +from pydantic_ai_plugin.structured_output.workflow import ( + IncidentSummary, + StructuredInput, + StructuredOutputWorkflow, +) +from tests.pydantic_ai_plugin.helpers import with_pydantic_ai + + +async def test_structured_output_crosses_workflow_boundary(client: Client) -> None: + client = with_pydantic_ai(client) + task_queue = f"pydantic-ai-structured-{uuid.uuid4()}" + async with Worker( + client, + task_queue=task_queue, + workflows=[StructuredOutputWorkflow], + max_cached_workflows=0, + ): + result = await client.execute_workflow( + StructuredOutputWorkflow.run, + StructuredInput(prompt="Summarize the incident."), + id=f"pydantic-ai-structured-{uuid.uuid4()}", + task_queue=task_queue, + ) + + assert result == IncidentSummary( + service="payments", + severity=2, + action="Restart the worker pool.", + ) diff --git a/tests/pydantic_ai_plugin/tools_test.py b/tests/pydantic_ai_plugin/tools_test.py new file mode 100644 index 00000000..523d2711 --- /dev/null +++ b/tests/pydantic_ai_plugin/tools_test.py @@ -0,0 +1,34 @@ +import uuid + +from temporalio.client import Client +from temporalio.worker import Worker + +from pydantic_ai_plugin.tools.workflow import ToolsInput, ToolsWorkflow +from tests.pydantic_ai_plugin.helpers import with_pydantic_ai + + +async def test_tool_execution_boundaries(client: Client) -> None: + client = with_pydantic_ai(client) + task_queue = f"pydantic-ai-tools-{uuid.uuid4()}" + async with Worker( + client, + task_queue=task_queue, + workflows=[ToolsWorkflow], + max_cached_workflows=0, + ): + handle = await client.start_workflow( + ToolsWorkflow.run, + ToolsInput(prompt="Use both tools."), + id=f"pydantic-ai-tools-{uuid.uuid4()}", + task_queue=task_queue, + ) + assert await handle.result() == "Both checks completed." + + activity_names = [] + async for event in handle.fetch_history_events(): + if event.HasField("activity_task_scheduled_event_attributes"): + attributes = event.activity_task_scheduled_event_attributes + activity_names.append(attributes.activity_type.name) + + tool_activities = [name for name in activity_names if name.endswith("__call_tool")] + assert len(tool_activities) == 1 diff --git a/uv.lock b/uv.lock index 537beabd..8599dfb6 100644 --- a/uv.lock +++ b/uv.lock @@ -49,6 +49,40 @@ boto3 = [ { name = "boto3" }, ] +[[package]] +name = "aiofile" +version = "3.9.0" +source = { registry = "https://pypi.org/simple" } +resolution-markers = [ + "python_full_version < '3.11'", +] +dependencies = [ + { name = "caio", version = "0.9.25", source = { registry = "https://pypi.org/simple" } }, +] +sdist = { url = "https://files.pythonhosted.org/packages/67/e2/d7cb819de8df6b5c1968a2756c3cb4122d4fa2b8fc768b53b7c9e5edb646/aiofile-3.9.0.tar.gz", hash = "sha256:e5ad718bb148b265b6df1b3752c4d1d83024b93da9bd599df74b9d9ffcf7919b", size = 17943, 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integration. Temporal's Workflow determinism sandbox is a different boundary and is not an AI-agent sandbox. +**Sandboxes:** Pydantic AI does not provide an agent-facing isolation environment whose sessions and shell or filesystem operations are durably managed by this integration. From 9752e3649ced1722b0e16c74065a50e33aaf8dbb Mon Sep 17 00:00:00 2001 From: Brian Strauch Date: Wed, 2 Sep 2026 16:56:41 -0700 Subject: [PATCH 3/8] Fix Pydantic AI sample import ordering --- pydantic_ai_plugin/chat/run_worker.py | 2 +- pydantic_ai_plugin/human_in_the_loop/run_worker.py | 2 +- pydantic_ai_plugin/logfire/run_worker.py | 2 +- pydantic_ai_plugin/mcp/run_worker.py | 2 +- pydantic_ai_plugin/multi_agent/run_worker.py | 2 +- pydantic_ai_plugin/streaming/run_worker.py | 2 +- pydantic_ai_plugin/streaming/run_workflow.py | 2 +- pydantic_ai_plugin/structured_output/run_worker.py | 2 +- pydantic_ai_plugin/tools/run_worker.py | 2 +- tests/pydantic_ai_plugin/chat_test.py | 2 +- tests/pydantic_ai_plugin/helpers.py | 3 +-- tests/pydantic_ai_plugin/logfire_test.py | 2 +- 12 files changed, 12 insertions(+), 13 deletions(-) diff --git a/pydantic_ai_plugin/chat/run_worker.py b/pydantic_ai_plugin/chat/run_worker.py index 72528006..a5d85086 100644 --- a/pydantic_ai_plugin/chat/run_worker.py +++ b/pydantic_ai_plugin/chat/run_worker.py @@ -1,10 +1,10 @@ import asyncio import os +from pydantic_ai.durable_exec.temporal import PydanticAIPlugin from temporalio.client import Client from temporalio.worker import Worker -from pydantic_ai.durable_exec.temporal import PydanticAIPlugin from pydantic_ai_plugin.chat.workflow import ChatWorkflow diff --git a/pydantic_ai_plugin/human_in_the_loop/run_worker.py b/pydantic_ai_plugin/human_in_the_loop/run_worker.py index 75c76eb6..17011462 100644 --- a/pydantic_ai_plugin/human_in_the_loop/run_worker.py +++ b/pydantic_ai_plugin/human_in_the_loop/run_worker.py @@ -1,10 +1,10 @@ import asyncio import os +from pydantic_ai.durable_exec.temporal import PydanticAIPlugin from temporalio.client import Client from temporalio.worker import Worker -from pydantic_ai.durable_exec.temporal import PydanticAIPlugin from pydantic_ai_plugin.human_in_the_loop.workflow import ApprovalWorkflow diff --git a/pydantic_ai_plugin/logfire/run_worker.py b/pydantic_ai_plugin/logfire/run_worker.py index 09ee4604..4f55ffbe 100644 --- a/pydantic_ai_plugin/logfire/run_worker.py +++ b/pydantic_ai_plugin/logfire/run_worker.py @@ -2,10 +2,10 @@ import os import logfire +from pydantic_ai.durable_exec.temporal import LogfirePlugin, PydanticAIPlugin from temporalio.client import Client from temporalio.worker import Worker -from pydantic_ai.durable_exec.temporal import LogfirePlugin, PydanticAIPlugin from pydantic_ai_plugin.logfire.workflow import ObservabilityWorkflow diff --git a/pydantic_ai_plugin/mcp/run_worker.py b/pydantic_ai_plugin/mcp/run_worker.py index ec0341ac..578e48ba 100644 --- a/pydantic_ai_plugin/mcp/run_worker.py +++ b/pydantic_ai_plugin/mcp/run_worker.py @@ -1,10 +1,10 @@ import asyncio import os +from pydantic_ai.durable_exec.temporal import PydanticAIPlugin from temporalio.client import Client from temporalio.worker import Worker -from pydantic_ai.durable_exec.temporal import PydanticAIPlugin from pydantic_ai_plugin.mcp.workflow import MCPWorkflow diff --git a/pydantic_ai_plugin/multi_agent/run_worker.py b/pydantic_ai_plugin/multi_agent/run_worker.py index a1125fab..580ce3f4 100644 --- a/pydantic_ai_plugin/multi_agent/run_worker.py +++ b/pydantic_ai_plugin/multi_agent/run_worker.py @@ -1,10 +1,10 @@ import asyncio import os +from pydantic_ai.durable_exec.temporal import PydanticAIPlugin from temporalio.client import Client from temporalio.worker import Worker -from pydantic_ai.durable_exec.temporal import PydanticAIPlugin from pydantic_ai_plugin.multi_agent.workflow import MultiAgentWorkflow diff --git a/pydantic_ai_plugin/streaming/run_worker.py b/pydantic_ai_plugin/streaming/run_worker.py index 75faa949..ac1f464a 100644 --- a/pydantic_ai_plugin/streaming/run_worker.py +++ b/pydantic_ai_plugin/streaming/run_worker.py @@ -1,10 +1,10 @@ import asyncio import os +from pydantic_ai.durable_exec.temporal import PydanticAIPlugin from temporalio.client import Client from temporalio.worker import Worker -from pydantic_ai.durable_exec.temporal import PydanticAIPlugin from pydantic_ai_plugin.streaming.workflow import StreamingWorkflow diff --git a/pydantic_ai_plugin/streaming/run_workflow.py b/pydantic_ai_plugin/streaming/run_workflow.py index f7641b7c..45436b4d 100644 --- a/pydantic_ai_plugin/streaming/run_workflow.py +++ b/pydantic_ai_plugin/streaming/run_workflow.py @@ -1,9 +1,9 @@ import asyncio import uuid +from pydantic_ai.durable_exec.temporal import PydanticAIPlugin from temporalio.client import Client -from pydantic_ai.durable_exec.temporal import PydanticAIPlugin from pydantic_ai_plugin.streaming.workflow import ( StreamingInput, StreamingWorkflow, diff --git a/pydantic_ai_plugin/structured_output/run_worker.py b/pydantic_ai_plugin/structured_output/run_worker.py index ef2180a3..b5758734 100644 --- a/pydantic_ai_plugin/structured_output/run_worker.py +++ b/pydantic_ai_plugin/structured_output/run_worker.py @@ -1,10 +1,10 @@ import asyncio import os +from pydantic_ai.durable_exec.temporal import PydanticAIPlugin from temporalio.client import Client from temporalio.worker import Worker -from pydantic_ai.durable_exec.temporal import PydanticAIPlugin from pydantic_ai_plugin.structured_output.workflow import StructuredOutputWorkflow diff --git a/pydantic_ai_plugin/tools/run_worker.py b/pydantic_ai_plugin/tools/run_worker.py index aa308efb..7833ca44 100644 --- a/pydantic_ai_plugin/tools/run_worker.py +++ b/pydantic_ai_plugin/tools/run_worker.py @@ -1,10 +1,10 @@ import asyncio import os +from pydantic_ai.durable_exec.temporal import PydanticAIPlugin from temporalio.client import Client from temporalio.worker import Worker -from pydantic_ai.durable_exec.temporal import PydanticAIPlugin from pydantic_ai_plugin.tools.workflow import ToolsWorkflow diff --git a/tests/pydantic_ai_plugin/chat_test.py b/tests/pydantic_ai_plugin/chat_test.py index 8c0a635e..3dbf5acb 100644 --- a/tests/pydantic_ai_plugin/chat_test.py +++ b/tests/pydantic_ai_plugin/chat_test.py @@ -1,11 +1,11 @@ import asyncio import uuid +from pydantic_ai.durable_exec.temporal import PydanticAIPlugin from temporalio.client import Client, WorkflowExecutionStatus from temporalio.testing import WorkflowEnvironment from temporalio.worker import Worker -from pydantic_ai.durable_exec.temporal import PydanticAIPlugin from pydantic_ai_plugin.chat.workflow import ChatInput, ChatWorkflow diff --git a/tests/pydantic_ai_plugin/helpers.py b/tests/pydantic_ai_plugin/helpers.py index 3336feaf..a02f4605 100644 --- a/tests/pydantic_ai_plugin/helpers.py +++ b/tests/pydantic_ai_plugin/helpers.py @@ -1,6 +1,5 @@ -from temporalio.client import Client - from pydantic_ai.durable_exec.temporal import PydanticAIPlugin +from temporalio.client import Client def with_pydantic_ai(client: Client) -> Client: diff --git a/tests/pydantic_ai_plugin/logfire_test.py b/tests/pydantic_ai_plugin/logfire_test.py index c867d77d..b71771ce 100644 --- a/tests/pydantic_ai_plugin/logfire_test.py +++ b/tests/pydantic_ai_plugin/logfire_test.py @@ -1,11 +1,11 @@ import uuid from logfire.testing import CaptureLogfire +from pydantic_ai.durable_exec.temporal import LogfirePlugin, PydanticAIPlugin from temporalio.client import Client from temporalio.contrib.opentelemetry import TracingInterceptor from temporalio.worker import Worker -from pydantic_ai.durable_exec.temporal import LogfirePlugin, PydanticAIPlugin from pydantic_ai_plugin.logfire.workflow import ( ObservabilityInput, ObservabilityWorkflow, From 61b0426121afb4b6f963634b1365c5e7e4147492 Mon Sep 17 00:00:00 2001 From: Brian Strauch Date: Thu, 3 Sep 2026 09:09:26 -0700 Subject: [PATCH 4/8] Use stdio MCP server and update Beartype pin --- pydantic_ai_plugin/README.md | 2 +- pydantic_ai_plugin/mcp/README.md | 2 +- pydantic_ai_plugin/mcp/server.py | 12 ++ pydantic_ai_plugin/mcp/workflow.py | 19 ++- pyproject.toml | 6 +- uv.lock | 235 +---------------------------- 6 files changed, 34 insertions(+), 242 deletions(-) create mode 100644 pydantic_ai_plugin/mcp/server.py diff --git a/pydantic_ai_plugin/README.md b/pydantic_ai_plugin/README.md index 5d6c2edb..aebcbc03 100644 --- a/pydantic_ai_plugin/README.md +++ b/pydantic_ai_plugin/README.md @@ -8,7 +8,7 @@ The samples use Pydantic AI's credential-free `TestModel` by default. Pass an Op | --- | --- | | [chat](chat) | Multi-turn Updates, durable message history, and Continue-As-New. | | [tools](tools) | A deterministic in-Workflow tool beside an I/O-style Activity tool. | -| [mcp](mcp) | A stateless in-process FastMCP server whose operations run as Activities. | +| [mcp](mcp) | A stateless stdio MCP server whose operations run as Activities. | | [streaming](streaming) | Pydantic AI events over Temporal Workflow Streams. | | [human_in_the_loop](human_in_the_loop) | Approval, rejection, and cancellation decisions delivered by Signal. | | [structured_output](structured_output) | A typed Pydantic model crossing Activity and Workflow boundaries. | diff --git a/pydantic_ai_plugin/mcp/README.md b/pydantic_ai_plugin/mcp/README.md index 80a0f54e..7ffb4bf0 100644 --- a/pydantic_ai_plugin/mcp/README.md +++ b/pydantic_ai_plugin/mcp/README.md @@ -1,6 +1,6 @@ # MCP -The agent uses a stateless in-process FastMCP server. `MCPToolset` exposes its `support_hours` tool, while `TemporalDurability` moves MCP listing and tool calls into Temporal Activities. The server keeps no session state, so Activity retries are safe. +The agent starts a stateless MCP server in a separate stdio process. `MCPToolset` exposes its `support_hours` tool, while `TemporalDurability` moves MCP listing and tool calls into Temporal Activities. The server keeps no session state, so Activity retries are safe. ```bash uv run pydantic_ai_plugin/mcp/run_worker.py diff --git a/pydantic_ai_plugin/mcp/server.py b/pydantic_ai_plugin/mcp/server.py new file mode 100644 index 00000000..3431fe61 --- /dev/null +++ b/pydantic_ai_plugin/mcp/server.py @@ -0,0 +1,12 @@ +from mcp.server.fastmcp import FastMCP + +server = FastMCP("support-directory") + + +@server.tool() +def support_hours() -> str: + return "Support is staffed 09:00-17:00 UTC." + + +if __name__ == "__main__": + server.run() diff --git a/pydantic_ai_plugin/mcp/workflow.py b/pydantic_ai_plugin/mcp/workflow.py index eac94a7a..e5699144 100644 --- a/pydantic_ai_plugin/mcp/workflow.py +++ b/pydantic_ai_plugin/mcp/workflow.py @@ -3,7 +3,7 @@ from temporalio import workflow with workflow.unsafe.imports_passed_through(): - from fastmcp import FastMCP + from fastmcp.client.transports import StdioTransport from pydantic_ai import Agent from pydantic_ai.durable_exec.temporal import ( PydanticAIWorkflow, @@ -19,15 +19,14 @@ class MCPInput: model: str | None = None -server = FastMCP("support-directory") - - -@server.tool -def support_hours() -> str: - return "Support is staffed 09:00-17:00 UTC." - - -toolset = MCPToolset(server, id="support_directory") +toolset = MCPToolset( + StdioTransport( + command="python", + args=["-m", "pydantic_ai_plugin.mcp.server"], + ), + id="support_directory", + init_timeout=20, +) agent = Agent( TestModel(call_tools=["support_hours"], custom_output_text="Hours found."), name="mcp_support", diff --git a/pyproject.toml b/pyproject.toml index f412afc4..af112dc8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -82,8 +82,9 @@ openai-agents = [ ] pydantic-converter = ["pydantic>=2.10.6,<3"] pydantic-ai = [ - "fastmcp>=3.3.0,<5", + "beartype", "logfire>=4.39,<4.40", + "mcp>=1.24,<2", "pydantic-ai-slim[mcp,temporal]", ] sentry = ["sentry-sdk>=2.13.0"] @@ -110,6 +111,9 @@ constraint-dependencies = [ ] [tool.uv.sources] +# Temporal sandbox import-cycle fix: +# https://github.com/beartype/beartype/commit/f593cd6f4dad12028c65d7792291cdd228c2d91c +beartype = { git = "https://github.com/beartype/beartype.git", rev = "f593cd6f4dad12028c65d7792291cdd228c2d91c" } pydantic-ai-slim = { git = "https://github.com/pydantic/pydantic-ai.git", rev = "2b45faa97e76461c60500e9755a130b158a2418d", subdirectory = "pydantic_ai_slim" } [tool.setuptools.packages.find] diff --git a/uv.lock b/uv.lock index 8599dfb6..805db1d5 100644 --- a/uv.lock +++ b/uv.lock @@ -422,12 +422,8 @@ wheels = [ [[package]] name = "beartype" -version = "0.22.9" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/c7/94/1009e248bbfbab11397abca7193bea6626806be9a327d399810d523a07cb/beartype-0.22.9.tar.gz", hash = "sha256:8f82b54aa723a2848a56008d18875f91c1db02c32ef6a62319a002e3e25a975f", size = 1608866, upload-time = "2025-12-13T06:50:30.72Z" } -wheels = [ - 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[[package]] name = "wcmatch" version = "11.0" From 83498f3496740844f63532acb1c8d534d9fd6403 Mon Sep 17 00:00:00 2001 From: Brian Strauch Date: Thu, 3 Sep 2026 10:42:42 -0700 Subject: [PATCH 5/8] Recommend unique workflow IDs for chat --- pydantic_ai_plugin/chat/README.md | 11 +++++++---- 1 file changed, 7 insertions(+), 4 deletions(-) diff --git a/pydantic_ai_plugin/chat/README.md b/pydantic_ai_plugin/chat/README.md index f641471f..aa6313f7 100644 --- a/pydantic_ai_plugin/chat/README.md +++ b/pydantic_ai_plugin/chat/README.md @@ -2,13 +2,16 @@ `ChatWorkflow` accepts each user turn as an Update, returns the assistant response from that Update, and keeps Pydantic AI `ModelMessage` history in Workflow state. When Temporal recommends Continue-As-New, it waits for active handlers and carries the typed history into the next run. +Assign each independent chat a unique Workflow ID. Continue-As-New keeps that ID across the whole chain automatically, so do not reuse it for an unrelated workflow. + ```bash uv run pydantic_ai_plugin/chat/run_worker.py -temporal workflow start --type ChatWorkflow --task-queue pydantic-ai-chat --workflow-id pydantic-ai-chat-1 --input '{"messages":[],"model":null}' -temporal workflow update --workflow-id pydantic-ai-chat-1 --name turn --input '"Hello"' -temporal workflow query --workflow-id pydantic-ai-chat-1 --type message_count -temporal workflow signal --workflow-id pydantic-ai-chat-1 --name end_chat +WORKFLOW_ID="pydantic-ai-chat-$(uv run python -c 'import uuid; print(uuid.uuid4())')" +temporal workflow start --type ChatWorkflow --task-queue pydantic-ai-chat --workflow-id "$WORKFLOW_ID" --input '{"messages":[],"model":null}' +temporal workflow update --workflow-id "$WORKFLOW_ID" --name turn --input '"Hello"' +temporal workflow query --workflow-id "$WORKFLOW_ID" --type message_count +temporal workflow signal --workflow-id "$WORKFLOW_ID" --name end_chat ``` For a live model, start with `{"messages":[],"model":"gateway/openai:gpt-5.2"}`. From 7b46e00ac22b39a3093758b7d6323b961ed0c9a0 Mon Sep 17 00:00:00 2001 From: Brian Strauch Date: Sat, 10 Oct 2026 13:15:16 -0700 Subject: [PATCH 6/8] Use released Pydantic AI and Beartype dependencies --- pydantic_ai_plugin/README.md | 2 +- pydantic_ai_plugin/streaming/README.md | 2 +- pyproject.toml | 12 +-- uv.lock | 109 +++++++++++++++++++++---- 4 files changed, 97 insertions(+), 28 deletions(-) diff --git a/pydantic_ai_plugin/README.md b/pydantic_ai_plugin/README.md index aebcbc03..8627c79c 100644 --- a/pydantic_ai_plugin/README.md +++ b/pydantic_ai_plugin/README.md @@ -22,7 +22,7 @@ uv sync --group pydantic-ai temporal server start-dev ``` -The dependency group pins `pydantic-ai-slim` to commit `2b45faa97e76461c60500e9755a130b158a2418d`, the head of [pydantic-ai PR #6639](https://github.com/pydantic/pydantic-ai/pull/6639), because the Workflow Streams API used by the streaming sample is not yet released. +The dependency group uses released packages: Pydantic AI 2.46.0 or newer includes Workflow Streams support, and Beartype 0.23.0 or newer includes the Temporal Sandbox import-cycle fix. ## Run diff --git a/pydantic_ai_plugin/streaming/README.md b/pydantic_ai_plugin/streaming/README.md index f0dd3005..53dfdb3a 100644 --- a/pydantic_ai_plugin/streaming/README.md +++ b/pydantic_ai_plugin/streaming/README.md @@ -1,6 +1,6 @@ # Streaming -This sample uses the Workflow Streams support introduced by [pydantic-ai PR #6639](https://github.com/pydantic/pydantic-ai/pull/6639). +This sample uses the Workflow Streams support released in [Pydantic AI 2.46.0](https://github.com/pydantic/pydantic-ai/releases/tag/v2.46.0). `TemporalDurability(event_stream_topic=...)` publishes typed agent events. `AgentEventStream` hosts the stream in the Workflow and keeps the Workflow alive until the terminal `AgentRunResultEvent` is acknowledged, bounded by `drain_timeout`. The consumer uses `durability.stream_agent_events(...)`; its iterator ends when the terminal event arrives and exposes an offset for reconnecting. diff --git a/pyproject.toml b/pyproject.toml index 1dbfaf9c..1834f4ad 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -85,10 +85,10 @@ openai-agents = [ openrouter = ["openai>=1.4.0,<3"] pydantic-converter = ["pydantic>=2.10.6,<3"] pydantic-ai = [ - "beartype", - "logfire>=4.39,<4.40", + "beartype>=0.23.0,<0.24", + "logfire>=4.39,<5", "mcp>=1.24,<2", - "pydantic-ai-slim[mcp,temporal]", + "pydantic-ai-slim[mcp,temporal]>=2.46.0,<3", ] sentry = ["sentry-sdk>=2.13.0"] strands-agents = [ @@ -113,12 +113,6 @@ constraint-dependencies = [ "yarl!=1.24.0", ] -[tool.uv.sources] -# Temporal sandbox import-cycle fix: -# https://github.com/beartype/beartype/commit/f593cd6f4dad12028c65d7792291cdd228c2d91c -beartype = { git = "https://github.com/beartype/beartype.git", rev = "f593cd6f4dad12028c65d7792291cdd228c2d91c" } -pydantic-ai-slim = { git = "https://github.com/pydantic/pydantic-ai.git", rev = "2b45faa97e76461c60500e9755a130b158a2418d", subdirectory = "pydantic_ai_slim" } - 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{ name = "pydantic-ai-slim", extra = ["mcp", "temporal"] }, + { name = "pydantic-ai-slim", version = "2.54.0", source = { registry = "https://pypi.org/simple" }, extra = ["mcp", "temporal"], marker = "python_full_version < '3.11'" }, + { name = "pydantic-ai-slim", version = "2.55.0", source = { registry = "https://pypi.org/simple" }, extra = ["mcp", "temporal"], marker = "python_full_version >= '3.11'" }, ] pydantic-converter = [ { name = "pydantic" }, @@ -5217,10 +5292,10 @@ openai-agents = [ ] openrouter = [{ name = "openai", specifier = ">=1.4.0,<3" }] pydantic-ai = [ - { name = "beartype", git = "https://github.com/beartype/beartype.git?rev=f593cd6f4dad12028c65d7792291cdd228c2d91c" }, - { name = "logfire", specifier = ">=4.39,<4.40" }, + { name = "beartype", specifier = ">=0.23.0,<0.24" }, + { name = "logfire", specifier = ">=4.39,<5" }, { name = "mcp", specifier = ">=1.24,<2" }, - { name = "pydantic-ai-slim", extras = ["mcp", "temporal"], git = "https://github.com/pydantic/pydantic-ai.git?subdirectory=pydantic_ai_slim&rev=2b45faa97e76461c60500e9755a130b158a2418d" }, + { name = "pydantic-ai-slim", extras = ["mcp", "temporal"], specifier = ">=2.46.0,<3" }, ] pydantic-converter = [{ name = "pydantic", specifier = ">=2.10.6,<3" }] sentry = [{ name = "sentry-sdk", specifier = ">=2.13.0" }] From 9034f10e0efd2cb7e0876b5b4b768e1c5ffe0290 Mon Sep 17 00:00:00 2001 From: Brian Strauch Date: Mon, 12 Oct 2026 09:41:06 -0700 Subject: [PATCH 7/8] Fix Pydantic AI live setup and successive approval rounds --- .github/workflows/ci.yml | 3 +- pydantic_ai_plugin/README.md | 6 +- pydantic_ai_plugin/chat/README.md | 6 +- .../human_in_the_loop/README.md | 6 +- .../human_in_the_loop/workflow.py | 56 +- pydantic_ai_plugin/logfire/README.md | 4 +- pydantic_ai_plugin/mcp/README.md | 4 +- pydantic_ai_plugin/multi_agent/README.md | 4 +- pydantic_ai_plugin/pyproject.toml | 54 + pydantic_ai_plugin/streaming/README.md | 6 +- .../structured_output/README.md | 4 +- .../tests}/__init__.py | 0 .../tests}/chat_test.py | 0 pydantic_ai_plugin/tests/conftest.py | 1 + .../tests}/helpers.py | 0 .../tests/human_in_the_loop_test.py | 140 + .../tests}/logfire_test.py | 0 .../tests}/mcp_test.py | 2 +- pydantic_ai_plugin/tests/models_test.py | 20 + .../tests}/multi_agent_test.py | 2 +- .../tests}/streaming_test.py | 2 +- .../tests}/structured_output_test.py | 2 +- .../tests}/tools_test.py | 2 +- pydantic_ai_plugin/tools/README.md | 4 +- pydantic_ai_plugin/uv.lock | 2467 +++++++++++++++++ pyproject.toml | 6 - .../human_in_the_loop_test.py | 50 - uv.lock | 550 +--- 28 files changed, 2745 insertions(+), 656 deletions(-) create mode 100644 pydantic_ai_plugin/pyproject.toml rename {tests/pydantic_ai_plugin => pydantic_ai_plugin/tests}/__init__.py (100%) rename {tests/pydantic_ai_plugin => pydantic_ai_plugin/tests}/chat_test.py (100%) create mode 100644 pydantic_ai_plugin/tests/conftest.py rename {tests/pydantic_ai_plugin => pydantic_ai_plugin/tests}/helpers.py (100%) create mode 100644 pydantic_ai_plugin/tests/human_in_the_loop_test.py rename {tests/pydantic_ai_plugin => pydantic_ai_plugin/tests}/logfire_test.py (100%) rename {tests/pydantic_ai_plugin => pydantic_ai_plugin/tests}/mcp_test.py (91%) create mode 100644 pydantic_ai_plugin/tests/models_test.py rename {tests/pydantic_ai_plugin => pydantic_ai_plugin/tests}/multi_agent_test.py (95%) rename {tests/pydantic_ai_plugin => pydantic_ai_plugin/tests}/streaming_test.py (97%) rename {tests/pydantic_ai_plugin => pydantic_ai_plugin/tests}/structured_output_test.py (93%) rename {tests/pydantic_ai_plugin => pydantic_ai_plugin/tests}/tools_test.py (94%) create mode 100644 pydantic_ai_plugin/uv.lock delete mode 100644 tests/pydantic_ai_plugin/human_in_the_loop_test.py diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 0344824a..8e75184b 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -35,7 +35,8 @@ jobs: for project in \ bedrock_agentcore/strands_agent \ lambda_worker \ - openai_agents/mcp_v2 + openai_agents/mcp_v2 \ + pydantic_ai_plugin do if grep -q "^${project}/" <<< "$changed_files"; then printf '%s\n' "$project" diff --git a/pydantic_ai_plugin/README.md b/pydantic_ai_plugin/README.md index 8627c79c..62857003 100644 --- a/pydantic_ai_plugin/README.md +++ b/pydantic_ai_plugin/README.md @@ -17,12 +17,14 @@ The samples use Pydantic AI's credential-free `TestModel` by default. Pass an Op ## Install +Run these commands from the repository root. These samples use a standalone environment because their OpenAI SDK dependency differs from the shared samples. The `openai` extra installs the provider needed by the live model commands. + ```bash -uv sync --group pydantic-ai +uv sync --project pydantic_ai_plugin temporal server start-dev ``` -The dependency group uses released packages: Pydantic AI 2.46.0 or newer includes Workflow Streams support, and Beartype 0.23.0 or newer includes the Temporal Sandbox import-cycle fix. +The standalone project uses released packages: Pydantic AI 2.46.0 or newer includes Workflow Streams support, and Beartype 0.23.0 or newer includes the Temporal Sandbox import-cycle fix. ## Run diff --git a/pydantic_ai_plugin/chat/README.md b/pydantic_ai_plugin/chat/README.md index aa6313f7..22df70c9 100644 --- a/pydantic_ai_plugin/chat/README.md +++ b/pydantic_ai_plugin/chat/README.md @@ -5,9 +5,9 @@ Assign each independent chat a unique Workflow ID. Continue-As-New keeps that ID across the whole chain automatically, so do not reuse it for an unrelated workflow. ```bash -uv run pydantic_ai_plugin/chat/run_worker.py +uv run --project pydantic_ai_plugin pydantic_ai_plugin/chat/run_worker.py -WORKFLOW_ID="pydantic-ai-chat-$(uv run python -c 'import uuid; print(uuid.uuid4())')" +WORKFLOW_ID="pydantic-ai-chat-$(uv run --project pydantic_ai_plugin python -c 'import uuid; print(uuid.uuid4())')" temporal workflow start --type ChatWorkflow --task-queue pydantic-ai-chat --workflow-id "$WORKFLOW_ID" --input '{"messages":[],"model":null}' temporal workflow update --workflow-id "$WORKFLOW_ID" --name turn --input '"Hello"' temporal workflow query --workflow-id "$WORKFLOW_ID" --type message_count @@ -19,5 +19,5 @@ For a live model, start with `{"messages":[],"model":"gateway/openai:gpt-5.2"}`. Expected offline Update result: `Ready for the next turn.` ```bash -uv run --group pydantic-ai pytest tests/pydantic_ai_plugin/chat_test.py +uv run --project pydantic_ai_plugin pytest pydantic_ai_plugin/tests/chat_test.py ``` diff --git a/pydantic_ai_plugin/human_in_the_loop/README.md b/pydantic_ai_plugin/human_in_the_loop/README.md index 688bfea2..66baff8f 100644 --- a/pydantic_ai_plugin/human_in_the_loop/README.md +++ b/pydantic_ai_plugin/human_in_the_loop/README.md @@ -4,8 +4,10 @@ The `delete_record` tool requires approval. Pydantic AI ends the first run with Approval resumes the agent with `DeferredToolResults`. Rejection sends `ToolDenied` back to the model. Cancellation ends the business operation without executing the tool. +If the resumed agent requests more approvals, the Workflow exposes the next pending tool and waits for a fresh decision. Query and signal again for each round until the agent finishes. + ```bash -uv run pydantic_ai_plugin/human_in_the_loop/run_worker.py +uv run --project pydantic_ai_plugin pydantic_ai_plugin/human_in_the_loop/run_worker.py temporal workflow start --type ApprovalWorkflow --task-queue pydantic-ai-approval --workflow-id pydantic-ai-approval-1 --input '{"prompt":"Delete record 42.","model":null}' temporal workflow query --workflow-id pydantic-ai-approval-1 --type pending_approval @@ -18,5 +20,5 @@ Send `"reject"` or `"cancel"` to exercise the other paths. Use `"model":"gateway Expected offline result after approval or rejection: `The operator decision was applied.` Cancellation returns `Cancelled by the operator.` ```bash -uv run --group pydantic-ai pytest tests/pydantic_ai_plugin/human_in_the_loop_test.py +uv run --project pydantic_ai_plugin pytest pydantic_ai_plugin/tests/human_in_the_loop_test.py ``` diff --git a/pydantic_ai_plugin/human_in_the_loop/workflow.py b/pydantic_ai_plugin/human_in_the_loop/workflow.py index 0c4d87bc..dd6b5e67 100644 --- a/pydantic_ai_plugin/human_in_the_loop/workflow.py +++ b/pydantic_ai_plugin/human_in_the_loop/workflow.py @@ -60,33 +60,31 @@ def pending_approval(self) -> str | None: @workflow.run async def run(self, input: ApprovalInput) -> str: - first = await agent.run(input.prompt, model=input.model) - if not isinstance(first.output, DeferredToolRequests): - return first.output - - calls = first.output.approvals - self._pending = calls[0].tool_name if calls else None - await workflow.wait_condition(lambda: self._decision is not None) - decision = self._decision - self._pending = None - - if decision == "cancel": - return "Cancelled by the operator." - - approvals: dict[str, bool | ToolApproved | ToolDenied] = { - call.tool_call_id: ( - True - if decision == "approve" - else ToolDenied(message="Rejected by the operator.") + result = await agent.run(input.prompt, model=input.model) + while isinstance(result.output, DeferredToolRequests): + calls = result.output.approvals + self._pending = calls[0].tool_name if calls else None + await workflow.wait_condition(lambda: self._decision is not None) + decision = self._decision + self._decision = None + self._pending = None + + if decision == "cancel": + return "Cancelled by the operator." + + approvals: dict[str, bool | ToolApproved | ToolDenied] = { + call.tool_call_id: ( + True + if decision == "approve" + else ToolDenied(message="Rejected by the operator.") + ) + for call in calls + } + deferred_results = result.output.build_results(approvals=approvals) + result = await agent.run( + "Continue after the operator decision.", + message_history=result.all_messages(), + deferred_tool_results=deferred_results, + model=input.model, ) - for call in calls - } - deferred_results = first.output.build_results(approvals=approvals) - resumed = await agent.run( - "Continue after the operator decision.", - message_history=first.all_messages(), - deferred_tool_results=deferred_results, - model=input.model, - ) - assert isinstance(resumed.output, str) - return resumed.output + return result.output diff --git a/pydantic_ai_plugin/logfire/README.md b/pydantic_ai_plugin/logfire/README.md index 920f9eaa..ea2591af 100644 --- a/pydantic_ai_plugin/logfire/README.md +++ b/pydantic_ai_plugin/logfire/README.md @@ -3,7 +3,7 @@ `LogfirePlugin` installs Temporal's OpenTelemetry tracing interceptor and Pydantic AI instrumentation, producing one connected trace across Workflow execution, model Activities, agent runs, and tools. The sample disables remote export when `LOGFIRE_TOKEN` is absent, so it also runs credential-free. ```bash -uv run pydantic_ai_plugin/logfire/run_worker.py +uv run --project pydantic_ai_plugin pydantic_ai_plugin/logfire/run_worker.py temporal workflow execute --type ObservabilityWorkflow --task-queue pydantic-ai-logfire --workflow-id pydantic-ai-logfire-1 --input '{"prompt":"Run an observable agent.","model":null}' ``` @@ -12,5 +12,5 @@ To send traces to Logfire, authenticate with `logfire auth`, export `LOGFIRE_TOK Expected offline result: `This run is traced.` The test captures both the agent and Workflow spans in memory. ```bash -uv run --group pydantic-ai pytest tests/pydantic_ai_plugin/logfire_test.py +uv run --project pydantic_ai_plugin pytest pydantic_ai_plugin/tests/logfire_test.py ``` diff --git a/pydantic_ai_plugin/mcp/README.md b/pydantic_ai_plugin/mcp/README.md index 7ffb4bf0..308b5c46 100644 --- a/pydantic_ai_plugin/mcp/README.md +++ b/pydantic_ai_plugin/mcp/README.md @@ -3,7 +3,7 @@ The agent starts a stateless MCP server in a separate stdio process. `MCPToolset` exposes its `support_hours` tool, while `TemporalDurability` moves MCP listing and tool calls into Temporal Activities. The server keeps no session state, so Activity retries are safe. ```bash -uv run pydantic_ai_plugin/mcp/run_worker.py +uv run --project pydantic_ai_plugin pydantic_ai_plugin/mcp/run_worker.py temporal workflow execute --type MCPWorkflow --task-queue pydantic-ai-mcp --workflow-id pydantic-ai-mcp-1 --input '{"prompt":"When is support staffed?","model":null}' ``` @@ -12,5 +12,5 @@ Use `"model":"gateway/openai:gpt-5.2"` for a live run. Expected offline result: `Hours found.` ```bash -uv run --group pydantic-ai pytest tests/pydantic_ai_plugin/mcp_test.py +uv run --project pydantic_ai_plugin pytest pydantic_ai_plugin/tests/mcp_test.py ``` diff --git a/pydantic_ai_plugin/multi_agent/README.md b/pydantic_ai_plugin/multi_agent/README.md index 1b6465da..4a3401ca 100644 --- a/pydantic_ai_plugin/multi_agent/README.md +++ b/pydantic_ai_plugin/multi_agent/README.md @@ -3,7 +3,7 @@ This sample uses Pydantic AI's programmatic handoff pattern. The researcher finishes first, then its durable result becomes input to the writer. Each model request is a separately recorded Temporal Activity, so a Worker restart resumes from completed work instead of repeating the whole pipeline. ```bash -uv run pydantic_ai_plugin/multi_agent/run_worker.py +uv run --project pydantic_ai_plugin pydantic_ai_plugin/multi_agent/run_worker.py temporal workflow execute --type MultiAgentWorkflow --task-queue pydantic-ai-multi-agent --workflow-id pydantic-ai-multi-agent-1 --input '{"topic":"How Temporal recovers from failures","model":null}' ``` @@ -12,5 +12,5 @@ Use `"model":"gateway/openai:gpt-5.2"` for a live run. Expected offline result: `A concise explanation is ready.` ```bash -uv run --group pydantic-ai pytest tests/pydantic_ai_plugin/multi_agent_test.py +uv run --project pydantic_ai_plugin pytest pydantic_ai_plugin/tests/multi_agent_test.py ``` diff --git a/pydantic_ai_plugin/pyproject.toml b/pydantic_ai_plugin/pyproject.toml new file mode 100644 index 00000000..dc6036fc --- /dev/null +++ b/pydantic_ai_plugin/pyproject.toml @@ -0,0 +1,54 @@ +[project] +name = "temporalio-samples-pydantic-ai" +version = "0.1.0" +requires-python = ">=3.10" +dependencies = [ + "beartype>=0.23.0,<0.24", + "logfire>=4.39,<5", + "mcp>=1.24,<2", + "pydantic-ai-slim[mcp,openai,temporal]>=2.46.0,<3", + "temporalio>=1.32.0,<2", +] + +[dependency-groups] +dev = [ + "ruff>=0.5.0,<0.6", + "mypy>=1.4.1,<2", + "poethepoet>=0.36.0", + "pytest>=7.1.2,<8", + "pytest-asyncio>=0.18.3,<0.19", +] + +[build-system] +requires = ["setuptools>=77"] +build-backend = "setuptools.build_meta" + +[tool.setuptools.packages.find] +where = [".."] +include = ["pydantic_ai_plugin*"] + +[tool.poe.tasks] +format = [ + { cmd = "uv run ruff check --select I --fix" }, + { cmd = "uv run ruff format" }, +] +lint = [ + { cmd = "uv run ruff check --select I" }, + { cmd = "uv run ruff format --check" }, + { ref = "lint-types" }, +] +lint-types = "uv run --directory .. --project pydantic_ai_plugin mypy --config-file pydantic_ai_plugin/pyproject.toml --check-untyped-defs --namespace-packages pydantic_ai_plugin" +test = "uv run --directory .. --project pydantic_ai_plugin pytest pydantic_ai_plugin/tests" + +[tool.pytest.ini_options] +asyncio_mode = "auto" +pythonpath = [".."] +testpaths = ["tests"] + +[tool.ruff] +target-version = "py310" +src = [".."] + +[tool.mypy] +ignore_missing_imports = true +namespace_packages = true diff --git a/pydantic_ai_plugin/streaming/README.md b/pydantic_ai_plugin/streaming/README.md index 53dfdb3a..5097344f 100644 --- a/pydantic_ai_plugin/streaming/README.md +++ b/pydantic_ai_plugin/streaming/README.md @@ -7,8 +7,8 @@ This sample uses the Workflow Streams support released in [Pydantic AI 2.46.0](h The topic filters token-level `PartDeltaEvent` objects to limit Workflow state. The terminal event is always retained. ```bash -uv run pydantic_ai_plugin/streaming/run_worker.py -uv run pydantic_ai_plugin/streaming/run_workflow.py +uv run --project pydantic_ai_plugin pydantic_ai_plugin/streaming/run_worker.py +uv run --project pydantic_ai_plugin pydantic_ai_plugin/streaming/run_workflow.py ``` The producer still completes if no subscriber connects after the drain timeout. Model events published from an Activity have at-least-once delivery, so production consumers should tolerate duplicates after Activity retries. @@ -16,5 +16,5 @@ The producer still completes if no subscriber connects after the drain timeout. The offline consumer prints typed event names, ending with `AgentRunResultEvent`, followed by `The durable response is complete.` ```bash -uv run --group pydantic-ai pytest tests/pydantic_ai_plugin/streaming_test.py +uv run --project pydantic_ai_plugin pytest pydantic_ai_plugin/tests/streaming_test.py ``` diff --git a/pydantic_ai_plugin/structured_output/README.md b/pydantic_ai_plugin/structured_output/README.md index f0396ff5..776b54c4 100644 --- a/pydantic_ai_plugin/structured_output/README.md +++ b/pydantic_ai_plugin/structured_output/README.md @@ -3,7 +3,7 @@ The agent returns `IncidentSummary`, a validated Pydantic model. `PydanticAIPlugin` installs the payload converter that preserves this type across the model Activity, Workflow state, and Workflow result. ```bash -uv run pydantic_ai_plugin/structured_output/run_worker.py +uv run --project pydantic_ai_plugin pydantic_ai_plugin/structured_output/run_worker.py temporal workflow execute --type StructuredOutputWorkflow --task-queue pydantic-ai-structured-output --workflow-id pydantic-ai-structured-1 --input '{"prompt":"Summarize the payments incident with severity and next action.","model":null}' ``` @@ -12,5 +12,5 @@ Use `"model":"gateway/openai:gpt-5.2"` for a live run. The offline result is a validated `IncidentSummary` for the payments service. ```bash -uv run --group pydantic-ai pytest tests/pydantic_ai_plugin/structured_output_test.py +uv run --project pydantic_ai_plugin pytest pydantic_ai_plugin/tests/structured_output_test.py ``` diff --git a/tests/pydantic_ai_plugin/__init__.py b/pydantic_ai_plugin/tests/__init__.py similarity index 100% rename from tests/pydantic_ai_plugin/__init__.py rename to pydantic_ai_plugin/tests/__init__.py diff --git a/tests/pydantic_ai_plugin/chat_test.py b/pydantic_ai_plugin/tests/chat_test.py similarity index 100% rename from tests/pydantic_ai_plugin/chat_test.py rename to pydantic_ai_plugin/tests/chat_test.py diff --git a/pydantic_ai_plugin/tests/conftest.py b/pydantic_ai_plugin/tests/conftest.py new file mode 100644 index 00000000..5891ddd9 --- /dev/null +++ b/pydantic_ai_plugin/tests/conftest.py @@ -0,0 +1 @@ +pytest_plugins = ["tests.conftest"] diff --git a/tests/pydantic_ai_plugin/helpers.py b/pydantic_ai_plugin/tests/helpers.py similarity index 100% rename from tests/pydantic_ai_plugin/helpers.py rename to pydantic_ai_plugin/tests/helpers.py diff --git a/pydantic_ai_plugin/tests/human_in_the_loop_test.py b/pydantic_ai_plugin/tests/human_in_the_loop_test.py new file mode 100644 index 00000000..91bc0177 --- /dev/null +++ b/pydantic_ai_plugin/tests/human_in_the_loop_test.py @@ -0,0 +1,140 @@ +import asyncio +import uuid +from datetime import timedelta + +import pytest +from pydantic_ai.messages import ( + ModelMessage, + ModelResponse, + TextPart, + ToolCallPart, + ToolReturnPart, +) +from pydantic_ai.models import ModelRequestParameters +from pydantic_ai.models.test import TestModel +from pydantic_ai.settings import ModelSettings +from temporalio.client import Client +from temporalio.worker import Worker + +from pydantic_ai_plugin.human_in_the_loop.workflow import ( + ApprovalInput, + ApprovalWorkflow, + Decision, +) +from pydantic_ai_plugin.tests.helpers import with_pydantic_ai + + +@pytest.mark.parametrize( + ("decision", "expected"), + [ + ("approve", "The operator decision was applied."), + ("reject", "The operator decision was applied."), + ("cancel", "Cancelled by the operator."), + ], +) +async def test_operator_decision( + client: Client, decision: Decision, expected: str +) -> None: + client = with_pydantic_ai(client) + task_queue = f"pydantic-ai-approval-{uuid.uuid4()}" + async with Worker( + client, + task_queue=task_queue, + workflows=[ApprovalWorkflow], + max_cached_workflows=0, + ): + handle = await client.start_workflow( + ApprovalWorkflow.run, + ApprovalInput(prompt="Delete the record."), + id=f"pydantic-ai-approval-{uuid.uuid4()}", + task_queue=task_queue, + ) + for _ in range(100): + if await handle.query(ApprovalWorkflow.pending_approval): + break + await asyncio.sleep(0.05) + else: + raise AssertionError("approval was not requested") + await handle.signal(ApprovalWorkflow.decide, decision) + result = await handle.result() + + assert result == expected + + +@pytest.mark.parametrize("decision", ["approve", "reject", "cancel"]) +async def test_additional_approval_round( + client: Client, monkeypatch: pytest.MonkeyPatch, decision: Decision +) -> None: + second_round_requested = asyncio.Event() + observed_returns: list[list[str]] = [] + + async def request( + self: TestModel, + messages: list[ModelMessage], + model_settings: ModelSettings | None, + model_request_parameters: ModelRequestParameters, + ) -> ModelResponse: + returns = [ + str(part.content) + for message in messages + for part in message.parts + if isinstance(part, ToolReturnPart) + ] + observed_returns.append(returns) + if len(returns) < 2: + record_id = str(42 + len(returns)) + if returns: + second_round_requested.set() + return ModelResponse( + parts=[ + ToolCallPart( + "delete_record", + {"record_id": record_id}, + tool_call_id=f"delete-{record_id}", + ) + ] + ) + return ModelResponse(parts=[TextPart("Both decisions were applied.")]) + + monkeypatch.setattr(TestModel, "request", request) + client = with_pydantic_ai(client) + task_queue = f"pydantic-ai-approval-rounds-{uuid.uuid4()}" + async with Worker( + client, + task_queue=task_queue, + workflows=[ApprovalWorkflow], + max_cached_workflows=0, + ): + handle = await client.start_workflow( + ApprovalWorkflow.run, + ApprovalInput(prompt="Delete records 42 and 43."), + id=f"pydantic-ai-approval-rounds-{uuid.uuid4()}", + task_queue=task_queue, + execution_timeout=timedelta(seconds=20), + ) + for round_index in range(2): + if round_index: + await asyncio.wait_for(second_round_requested.wait(), timeout=5) + for _ in range(100): + if await handle.query(ApprovalWorkflow.pending_approval): + break + await asyncio.sleep(0.05) + else: + raise AssertionError( + f"approval round {round_index + 1} was not requested" + ) + await handle.signal( + ApprovalWorkflow.decide, "approve" if round_index == 0 else decision + ) + result = await asyncio.wait_for(handle.result(), timeout=5) + + assert observed_returns[:2] == [[], ["deleted 42"]] + if decision == "cancel": + assert result == "Cancelled by the operator." + assert len(observed_returns) == 2 + else: + assert result == "Both decisions were applied." + assert observed_returns[2] == [ + "deleted 42", + "deleted 43" if decision == "approve" else "Rejected by the operator.", + ] diff --git a/tests/pydantic_ai_plugin/logfire_test.py b/pydantic_ai_plugin/tests/logfire_test.py similarity index 100% rename from tests/pydantic_ai_plugin/logfire_test.py rename to pydantic_ai_plugin/tests/logfire_test.py diff --git a/tests/pydantic_ai_plugin/mcp_test.py b/pydantic_ai_plugin/tests/mcp_test.py similarity index 91% rename from tests/pydantic_ai_plugin/mcp_test.py rename to pydantic_ai_plugin/tests/mcp_test.py index 21d3020c..a06bdb6c 100644 --- a/tests/pydantic_ai_plugin/mcp_test.py +++ b/pydantic_ai_plugin/tests/mcp_test.py @@ -4,7 +4,7 @@ from temporalio.worker import Worker from pydantic_ai_plugin.mcp.workflow import MCPInput, MCPWorkflow -from tests.pydantic_ai_plugin.helpers import with_pydantic_ai +from pydantic_ai_plugin.tests.helpers import with_pydantic_ai async def test_stateless_mcp_tool(client: Client) -> None: diff --git a/pydantic_ai_plugin/tests/models_test.py b/pydantic_ai_plugin/tests/models_test.py new file mode 100644 index 00000000..2c1b41fc --- /dev/null +++ b/pydantic_ai_plugin/tests/models_test.py @@ -0,0 +1,20 @@ +import pytest +from pydantic_ai.models import infer_model + + +def test_documented_live_model_is_available(monkeypatch: pytest.MonkeyPatch) -> None: + for variable in ( + "HTTP_PROXY", + "HTTPS_PROXY", + "ALL_PROXY", + "http_proxy", + "https_proxy", + "all_proxy", + ): + monkeypatch.delenv(variable, raising=False) + monkeypatch.setenv("PYDANTIC_AI_GATEWAY_API_KEY", "test-key") + monkeypatch.setenv( + "PYDANTIC_AI_GATEWAY_BASE_URL", "https://gateway.example.invalid" + ) + model = infer_model("gateway/openai:gpt-5.2") + assert model.model_name == "gpt-5.2" diff --git a/tests/pydantic_ai_plugin/multi_agent_test.py b/pydantic_ai_plugin/tests/multi_agent_test.py similarity index 95% rename from tests/pydantic_ai_plugin/multi_agent_test.py rename to pydantic_ai_plugin/tests/multi_agent_test.py index 698c751d..1314d16b 100644 --- a/tests/pydantic_ai_plugin/multi_agent_test.py +++ b/pydantic_ai_plugin/tests/multi_agent_test.py @@ -7,7 +7,7 @@ MultiAgentInput, MultiAgentWorkflow, ) -from tests.pydantic_ai_plugin.helpers import with_pydantic_ai +from pydantic_ai_plugin.tests.helpers import with_pydantic_ai async def test_two_agents_run_durably(client: Client) -> None: diff --git a/tests/pydantic_ai_plugin/streaming_test.py b/pydantic_ai_plugin/tests/streaming_test.py similarity index 97% rename from tests/pydantic_ai_plugin/streaming_test.py rename to pydantic_ai_plugin/tests/streaming_test.py index d70d476b..58ec91aa 100644 --- a/tests/pydantic_ai_plugin/streaming_test.py +++ b/pydantic_ai_plugin/tests/streaming_test.py @@ -10,7 +10,7 @@ StreamingWorkflow, durability, ) -from tests.pydantic_ai_plugin.helpers import with_pydantic_ai +from pydantic_ai_plugin.tests.helpers import with_pydantic_ai async def test_stream_ends_with_agent_result(client: Client) -> None: diff --git a/tests/pydantic_ai_plugin/structured_output_test.py b/pydantic_ai_plugin/tests/structured_output_test.py similarity index 93% rename from tests/pydantic_ai_plugin/structured_output_test.py rename to pydantic_ai_plugin/tests/structured_output_test.py index c2788d9b..5a2a0177 100644 --- a/tests/pydantic_ai_plugin/structured_output_test.py +++ b/pydantic_ai_plugin/tests/structured_output_test.py @@ -8,7 +8,7 @@ StructuredInput, StructuredOutputWorkflow, ) -from tests.pydantic_ai_plugin.helpers import with_pydantic_ai +from pydantic_ai_plugin.tests.helpers import with_pydantic_ai async def test_structured_output_crosses_workflow_boundary(client: Client) -> None: diff --git a/tests/pydantic_ai_plugin/tools_test.py b/pydantic_ai_plugin/tests/tools_test.py similarity index 94% rename from tests/pydantic_ai_plugin/tools_test.py rename to pydantic_ai_plugin/tests/tools_test.py index 523d2711..c98ba316 100644 --- a/tests/pydantic_ai_plugin/tools_test.py +++ b/pydantic_ai_plugin/tests/tools_test.py @@ -3,8 +3,8 @@ from temporalio.client import Client from temporalio.worker import Worker +from pydantic_ai_plugin.tests.helpers import with_pydantic_ai from pydantic_ai_plugin.tools.workflow import ToolsInput, ToolsWorkflow -from tests.pydantic_ai_plugin.helpers import with_pydantic_ai async def test_tool_execution_boundaries(client: Client) -> None: diff --git a/pydantic_ai_plugin/tools/README.md b/pydantic_ai_plugin/tools/README.md index 0cbd8c92..9ec9b6d1 100644 --- a/pydantic_ai_plugin/tools/README.md +++ b/pydantic_ai_plugin/tools/README.md @@ -8,7 +8,7 @@ This sample puts two tools behind one durable agent: The model request is also an Activity. The test inspects Workflow history to verify the tool boundary. ```bash -uv run pydantic_ai_plugin/tools/run_worker.py +uv run --project pydantic_ai_plugin pydantic_ai_plugin/tools/run_worker.py temporal workflow execute --type ToolsWorkflow --task-queue pydantic-ai-tools --workflow-id pydantic-ai-tools-1 --input '{"prompt":"Check policy and inventory.","model":null}' ``` @@ -17,5 +17,5 @@ Use `"model":"gateway/openai:gpt-5.2"` for a live run. 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Pydantic AI 2.46.0 or newer includes Workflow Streams support, and Beartype 0.23.0 or newer includes the Temporal Sandbox import-cycle fix. - ## Run Start a category's Worker, then use the Temporal CLI command in that category's README. With no `model` value, the Workflow uses `TestModel` and needs no API key or network access. For a live run, set `model` to `gateway/openai:gpt-5.2` and export `PYDANTIC_AI_GATEWAY_API_KEY` in the Worker process.