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:
conversation_id/session_idfromctx.depsorctx.metadatathread_idfromctx.depsorctx.metadata- 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_idviactx.depsorctx.metadatato avoid fragmented conversations. - If model aliases are custom, set explicit
provideron the handler. - Always call
client.shutdown()during teardown to flush buffered telemetry.
Metadata
Release files for agento11y-pydantic-ai 0.18.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| agento11y_pydantic_ai-0.18.0.tar.gz | 13.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| agento11y_pydantic_ai-0.18.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 22.0 kB
Release files / agento11y_pydantic_ai-0.18.0.tar.gz
| Download URL | agento11y_pydantic_ai-0.18.0.tar.gz |
|---|---|
| Size | 13.0 kB |
| Tags | Source |
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| Size | 9.0 kB |
| Tags | Python 3 |
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Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.13
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PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 30, 2026.
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