Grafana Agent Observability Python Framework Module: Pydantic AI

agento11y-pydantic-ai provides an AbstractCapability implementation that maps Pydantic AI lifecycle hooks into agento11y generation recorder lifecycles.

Installation

pip install agento11y agento11y-pydantic-ai
pip install pydantic-ai

Quickstart

from pydantic_ai import Agent
from agento11y import Client
from agento11y_pydantic_ai import create_agento11y_pydantic_ai_capability

client = Client()
capability = create_agento11y_pydantic_ai_capability(client=client, provider_resolver="auto")

agent = Agent("openai:gpt-4o", capabilities=[capability])
result = agent.run_sync("What is the weather?")
print(result.output)

client.shutdown()

End-to-end example (run + run_stream)

from pydantic_ai import Agent
from agento11y import Client
from agento11y_pydantic_ai import with_agento11y_pydantic_ai_capability

client = Client()
capabilities = with_agento11y_pydantic_ai_capability(
    None,
    client=client,
    provider_resolver="auto",
    agent_name="pydantic-ai-example",
    agent_version="1.0.0",
)

agent = Agent("openai:gpt-4o-mini", capabilities=capabilities)

# Non-stream call -> SYNC generation mode.
result = agent.run_sync("Summarize why retry budgets matter.")
print(result.output)

# Stream call -> STREAM generation mode + TTFT tracking.
async def stream_example() -> None:
    async with agent.run_stream("Give me three short reliability tips.") as stream:
        async for chunk in stream.stream_text():
            print(chunk, end="", flush=True)
        print()

import asyncio
asyncio.run(stream_example())

client.shutdown()

Conversation mapping

Primary mapping is Pydantic AI run identity:

  1. conversation_id / session_id from ctx.deps or ctx.metadata
  2. thread_id from ctx.deps or ctx.metadata
  3. fallback agento11y:framework:pydantic-ai:<run_id>

Metadata and lineage

  • Required: agento11y.framework.run_type
  • Optional: agento11y.framework.run_id, agento11y.framework.parent_run_id, agento11y.framework.thread_id, agento11y.framework.event_id, agento11y.framework.component_name, agento11y.framework.retry_attempt

Provider resolver

Resolver order: explicit provider option -> callback payload -> model prefix inference -> custom.

Troubleshooting

  • Provide stable conversation_id via ctx.deps or ctx.metadata to avoid fragmented conversations.
  • If model aliases are custom, set explicit provider on the handler.
  • Always call client.shutdown() during teardown to flush buffered telemetry.

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (0.16.0)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for grafana-machine-learning from gravatar.com grafana-machine-learning

License

SPDX-License-Identifier: Apache-2.0

Requires

Python >=3.10

Provides Extra

dev

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