--- title: "Pydantic AI" description: "Pydantic AI defines a typed agent with tools, dependencies, and output types. The Dex adapter runs a Pydantic AI agent inside a durable session. It is available for Python." canonical_url: "https://docs.superdurable.io/agent-frameworks/pydantic-ai/" source: "docs/content/agent-frameworks/pydantic-ai.mdx" locale: "en" --- # Pydantic AI Pydantic AI defines a typed agent with tools, dependencies, and output types. The Dex adapter runs a Pydantic AI agent inside a durable session. It is available for Python. ## When to use it Use it when your agent already uses Pydantic AI. Keep the agent, its tools, and its capabilities, and let Dex own the session. The adapter replaces Pydantic AI's own durable execution integrations. ## How a session runs Each **RunModel** Step runs the agent with a capability that marks every function tool as an external tool. Pydantic AI never runs an external tool, so the run ends right after the model asks for tools. Each tool call runs in its own Step, in parallel: **CallTool** for a read or an idempotent write, **CallSingleAttemptTool** for any other write. A call that needs approval waits in **AwaitToolApproval** first. The tool Step runs the tool once, through the agent, so the agent's tool hooks run there. The next **RunModel** resumes the run with the recorded results. A turn that looks up an order runs **RunModel**, **CallTool**, **ResumeTurn**, and **RunModel**. ## Install Install the adapter with its framework. Each adapter brings in the Dex Agents core. **Python** ```bash pip install dex-agents-pydantic-ai "pydantic-ai-slim[openai]" ``` Example: [agents/python/pydantic-ai/README.md](https://github.com/superdurable/dex/tree/main/agents/python/pydantic-ai/README.md) ## The example The example is the [order support agent](https://docs.superdurable.io/agent-frameworks.md#the-examples) that every framework page uses. The Flow type is **PydanticAIOrderSupport**. The full example is under [examples/python/agent-harnesses](https://github.com/superdurable/dex/tree/main/examples/python/agent-harnesses). ### Agent and tools The tools are plain Pydantic AI tools on the agent. The tool policies name each tool. The agent defers its model check, so a Client process needs no provider key. **Python** ```python def build_pydantic_ai_order_support_flow( order_desk: OrderDesk, model: str | Model, slack_connection: slack.Connection | None ) -> AgentSessionFlow: """Builds the session Flow; ``model`` is a Pydantic AI model name, such as "openai:gpt-5.2".""" # The model is resolved at the first run, so a Client process needs no provider key. agent = Agent(model, instructions=ORDER_SUPPORT_INSTRUCTIONS, defer_model_check=True) # The tools are closures, so they call the OrderDesk passed in here. @agent.tool_plain def look_up_order(order_id: str) -> str: """Look up one order by its order ID and return its items and status.""" return order_desk.describe_order(order_id) @agent.tool_plain def cancel_order(order_id: str, reason: str) -> str: """Cancel one order that has not shipped yet.""" return order_desk.cancel_order(order_id, reason) return pydantic_ai_session_flow( agent, flow_type=PYDANTIC_AI_ORDER_SUPPORT_FLOW_TYPE, tool_sources=build_slack_tool_sources(slack_connection), tool_policies={ "look_up_order": ToolPolicy(ToolEffect.READ), "cancel_order": ToolPolicy(ToolEffect.NON_IDEMPOTENT_WRITE), }, ) ``` Example: [examples/python/agent-harnesses/agent_harness_examples/pydantic_ai_order_support.py](https://github.com/superdurable/dex/tree/main/examples/python/agent-harnesses/agent_harness_examples/pydantic_ai_order_support.py) ### Worker One Worker serves the session Flows of every harness in the example. Agent session Steps are async, so the Python Registry allows async handlers. Build the same session Flow in every process that starts sessions or calls their RPCs. **Python** ```python # Agent session Steps are async, so the Registry allows async handlers. self.registry = Registry( tuple(example.session_flow for example in self.examples), allow_async_handlers=True ) config.blob_cache_dir.mkdir(parents=True, exist_ok=True) self.blob_cache = open_blob_cache(BlobCacheConfig(str(config.blob_cache_dir), 1 << 30)) self.worker = AsyncWorker( self.registry, self.blob_cache, WorkerOptions( server_address=config.server_address, pull=PullWorkerOptions(max_concurrent_tasks=MAX_CONCURRENT_TASKS), ), ) self.client = AsyncClient( self.registry, self.blob_cache, ClientOptions(server_address=config.server_address) ) # ... def _new_pydantic_ai_example( config: AgentHarnessExamplesConfig, slack_connection: slack.Connection | None ) -> AgentHarnessExample: order_desk = OrderDesk() model = _pydantic_ai_model(config.pydantic_ai_model) flow = build_pydantic_ai_order_support_flow(order_desk, model, slack_connection) return AgentHarnessExample("pydantic-ai", flow, order_desk) # ... def _pydantic_ai_model(model: str) -> str | PydanticAIModel: return build_pydantic_ai_demo_model() if is_demo_model(model) else model ``` Example: [examples/python/agent-harnesses/agent_harness_examples/app.py](https://github.com/superdurable/dex/tree/main/examples/python/agent-harnesses/agent_harness_examples/app.py) ### Session routes Every harness serves these same routes. [Session routes](https://docs.superdurable.io/agent-frameworks.md#session-routes) explains them and the session token. **Python** ```python @blueprint.post("/sessions") async def start_session() -> Response: # The server picks the session ID, so a caller cannot claim an existing session. session_id = f"{harness_name}-order-support-{uuid.uuid4()}" await sessions.start_session(session_id) session_token = sign_session_id(app_state.config.session_key, session_id) return jsonify(session_id=session_id, session_token=session_token) @blueprint.post("/messages") async def send_user_message() -> Response: body, session_id = await session_request() accepted = await sessions.send_user_message(session_id, _required_string(body, "text")) return jsonify(accepted=accepted) @blueprint.post("/interrupts/resolve") async def resolve_interrupt() -> Response: body, session_id = await session_request() interrupt_id = _required_string(body, "interrupt_id") if not isinstance(approved := body.get("approved"), bool): raise BadRequest("approved must be a boolean") rejection_message = body.get("rejection_message") if rejection_message is not None and not isinstance(rejection_message, str): raise BadRequest("rejection_message must be a string") accepted = await sessions.resolve_interrupt( session_id, interrupt_id, approved=approved, rejection_message=rejection_message ) return jsonify(accepted=accepted) @blueprint.get("/snapshot") async def get_agent_snapshot() -> Response: session_id = request.args.get("session_id", "") if not session_id: raise BadRequest("session_id is required") authorize_session(session_id) try: snapshot = await read_agent_event_stream_snapshot( app_state.client, example.session_flow, session_id ) except FlowNotActiveOrNotFoundError as error: raise NotFound("the agent session is missing or no longer retained") from error return jsonify(snapshot.to_json()) ``` Example: [examples/python/agent-harnesses/agent_harness_examples/http_routes.py](https://github.com/superdurable/dex/tree/main/examples/python/agent-harnesses/agent_harness_examples/http_routes.py) ## Run it locally ### Start Dex and the example In a first terminal, render the session graph, then start Dex. Dex Web reads the graph when it starts, to show the session and its approval controls. **Python** ```bash cd examples/python/agent-harnesses uv sync --locked mkdir -p definitions uv run --frozen dex-agents-session-graph --flow-type PydanticAIOrderSupport \ --permission order-support.operate --out definitions/pydantic-ai.json dexcli dev --flow-rendering-dir ./definitions ``` Example: [examples/python/agent-harnesses/README.md](https://github.com/superdurable/dex/tree/main/examples/python/agent-harnesses/README.md) **dexcli dev** stays in the foreground. In a second terminal, start the example: **Python** ```bash cd examples/python/agent-harnesses uv run --frozen python -m agent_harness_examples ``` Example: [examples/python/agent-harnesses/README.md](https://github.com/superdurable/dex/tree/main/examples/python/agent-harnesses/README.md) The app serves on **127.0.0.1:8081**. Dex Web is at ****. Without **DEX_PYDANTIC_AI_MODEL**, the agent uses **mock/order-support**, a local demo model that needs no key. It calls **look_up_order** for "look up order 1001" and **cancel_order** for "cancel order 1002". | Variable | Default | Meaning | | ------------------------- | ---------------------- | ----------------------------------------------------- | | **DEX_PYDANTIC_AI_MODEL** | **mock/order-support** | A Pydantic AI model name, such as **openai:gpt-5.2**. | | **OPENAI_API_KEY** | none | The provider key, for an OpenAI model. | | **DEX_AGENT_SESSION_KEY** | a random key | The key that signs session tokens. | ### Call the session Start a session, ask the agent to cancel order 1002, and approve the call: **Python** ```bash base=http://127.0.0.1:8081/products/agent-harnesses/pydantic-ai session=$(curl -s -X POST "$base/sessions" -H 'Content-Type: application/json' -d '{}') id=$(echo "$session" | jq -r .session_id) token=$(echo "$session" | jq -r .session_token) curl -s -X POST "$base/messages" -H 'Content-Type: application/json' \ -H "X-Agent-Session-Token: $token" -d "{\"session_id\": \"$id\", \"text\": \"Cancel order 1002\"}" until interrupt=$(curl -s "$base/snapshot?session_id=$id" -H "X-Agent-Session-Token: $token" \ | jq -re '.snapshot.pending_interrupts[0].interrupt_id'); do sleep 1; done curl -s -X POST "$base/interrupts/resolve" -H 'Content-Type: application/json' \ -H "X-Agent-Session-Token: $token" \ -d "{\"session_id\": \"$id\", \"interrupt_id\": \"$interrupt\", \"approved\": true}" ``` Example: [examples/python/agent-harnesses/README.md](https://github.com/superdurable/dex/tree/main/examples/python/agent-harnesses/README.md) The loop reads the snapshot until the agent asks to run **cancel_order**. That call waits for approval, then runs once. Read the snapshot again to see the agent's answer. ### Approve in Dex Web Instead of the last command, you can approve the call in Dex Web. Follow the steps in [Approve in Dex Web](https://docs.superdurable.io/agent-frameworks.md#approve-in-dex-web). ## Connect Connectors The agent can call [Connector](https://docs.superdurable.io/concepts/connector.md) operations as tools, as [Connectors as tools](https://docs.superdurable.io/agent-frameworks.md#connectors-as-tools) describes. The example adds the Slack tool **slack_post_thread_reply**, which replies in a Slack thread. ### Offer the tool Install the **connectors** extra of **dex-agents** and the Connector package, such as **dex-connector-slack**. The install commands are in [Connector tools](https://docs.superdurable.io/reference/agents/connector-tools.md#install). The Worker opens the Slack connection **support-slack** from the project configuration. **connector_tool** turns the operation into a tool, and **ConnectorToolSource** holds it. Without the connection, the agent gets no Slack tool. **Python** ```python def build_slack_tool_sources(connection: slack.Connection | None) -> list[ToolSource]: """Returns the Slack tool source, or no source when Slack is not configured.""" if connection is None: return [] return [ ConnectorToolSource([ # The manifest does not ask for approval; this agent asks before every post. connector_tool( connection.post_thread_reply(), connection.reference, requires_approval=True ), ]), ] # ... async def open_slack_project_connection( environment: Mapping[str, str] = os.environ, ) -> SlackProjectConnection | None: # ... # An incomplete or invalid configuration raises here, so the Worker fails at startup. try: project = await load_from_environment(environment) except FileNotFoundError: _log_slack_not_set_up("the connector configuration file does not exist") return None # ... try: connection = slack.new_project_connection(project, SLACK_CONNECTION_NAME) except BaseException: await project.close() raise return SlackProjectConnection(project, connection) ``` Example: [examples/python/agent-harnesses/agent_harness_examples/slack_connector_tools.py](https://github.com/superdurable/dex/tree/main/examples/python/agent-harnesses/agent_harness_examples/slack_connector_tools.py) The Worker opens the connection once, at startup, and every agent uses it: **Python** ```python async def main() -> None: config = AgentHarnessExamplesConfig.from_env() slack_setup = await open_slack_project_connection() try: app_state = AgentHarnessExamplesApp(config, slack_setup.connection if slack_setup else None) # ... finally: if slack_setup is not None: await slack_setup.aclose() ``` Example: [examples/python/agent-harnesses/agent_harness_examples/\_\_main\_\_.py](https://github.com/superdurable/dex/tree/main/examples/python/agent-harnesses/agent_harness_examples/__main__.py) The agent passes the tool source next to its own tools: **Python** ```python return pydantic_ai_session_flow( agent, flow_type=PYDANTIC_AI_ORDER_SUPPORT_FLOW_TYPE, tool_sources=build_slack_tool_sources(slack_connection), # ... ) ``` Example: [examples/python/agent-harnesses/agent_harness_examples/pydantic_ai_order_support.py](https://github.com/superdurable/dex/tree/main/examples/python/agent-harnesses/agent_harness_examples/pydantic_ai_order_support.py) ### How a call runs Each call of **slack_post_thread_reply** runs once, in its own **CallSingleAttemptTool** Step, after a person approves it. [The Slack Connector tool](https://docs.superdurable.io/agent-frameworks.md#slack-connector-tool) explains why. The adapter passes the Connector tools to each run as an **ExternalToolset**. Pydantic AI never runs an external tool, so a Connector tool call ends the run, and the call runs in its tool Step. ### Configure the connection [Connections](https://docs.superdurable.io/reference/agents/connector-tools.md#connector-tools-connection) explains where the Worker finds the **support-slack** connection and what the Slack app needs. To try it, start the example with **DEX_CONNECTOR_CONFIG_FILE** set. Then ask the agent to reply in a Slack thread, with the channel ID and the thread timestamp: ```text Reply in Slack thread C0123456789 1710000000.000100: Order 1002 ships on Thursday. ``` The post waits for approval, like **cancel_order**. ## Limits - Retries that Pydantic AI sends to the model itself make another model call in the same **RunModel** Step. Examples are invalid tool arguments and output that fails validation. - Output functions run inside **RunModel** and are at least once. Put a write in a tool instead. - Provider-run tools, such as **WebSearchTool**, repeat when **RunModel** reruns. - A deferred tool returns text to the model. Images and files are lost. - A tool that asks for approval only while it runs needs a **ToolPolicy** with **requires_approval=True**. - **UsageLimits** and tool retry budgets apply per Step, not per turn. The adapter README lists every limit. See [Limits for long sessions](https://docs.superdurable.io/reference/agents/session-limits.md) for the server limits. ## Related - [Agent Frameworks](https://docs.superdurable.io/agent-frameworks.md) - [Agents reference](https://docs.superdurable.io/reference/agents.md) - [Python adapter README](https://github.com/superdurable/dex/tree/main/agents/python/pydantic-ai)