Documentation Index
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AgentBasis supports Pydantic AI with built-in OpenTelemetry instrumentation.
Setup
import agentbasis
from agentbasis.frameworks.pydanticai import instrument
# Initialize AgentBasis first
agentbasis.init(api_key="your-api-key", agent_id="your-agent-id")
# Enable global instrumentation for all Pydantic AI agents
instrument()
Basic Usage
Once instrumented, all Pydantic AI agents are automatically traced:
from pydantic_ai import Agent
agent = Agent("openai:gpt-4")
result = agent.run_sync("Hello!")
print(result.data)
Privacy Controls
Control what data is captured in traces:
from agentbasis.frameworks.pydanticai import instrument
# Don't log prompts and completions (for sensitive data)
instrument(include_content=False)
# Include binary content like images (increases trace size)
instrument(include_content=True, include_binary_content=True)
| Parameter | Default | Description |
|---|
include_content | True | Log prompts and completions |
include_binary_content | False | Include images and other binary data |
Per-Agent Instrumentation
If you need different settings for different agents, use get_instrumentation_settings():
from agentbasis.frameworks.pydanticai import get_instrumentation_settings
from pydantic_ai import Agent
# Agent with full tracing
agent_full = Agent(
"openai:gpt-4",
instrument=get_instrumentation_settings()
)
# Agent without content logging (privacy mode)
agent_private = Agent(
"openai:gpt-4",
instrument=get_instrumentation_settings(include_content=False)
)
User Context Integration
Using create_traced_agent
The easiest way to create an agent with context support:
from agentbasis.frameworks.pydanticai import create_traced_agent
import agentbasis
# Create an agent pre-configured with tracing and context
agent = create_traced_agent(
"openai:gpt-4",
system_prompt="You are a helpful assistant."
)
# Set user context - automatically included in traces
agentbasis.set_user("user-123")
agentbasis.set_session("session-456")
result = agent.run_sync("Hello!")
from agentbasis.frameworks.pydanticai import get_metadata_callback
from pydantic_ai import Agent
import agentbasis
agent = Agent(
"openai:gpt-4",
metadata=get_metadata_callback()
)
# Set context before running
agentbasis.set_user("user-123")
# This run will include user_id in the trace metadata
result = agent.run_sync("Hello!")
Async Usage
All methods work with async agents:
from pydantic_ai import Agent
import asyncio
agent = Agent("openai:gpt-4")
async def main():
result = await agent.run("Hello!")
print(result.data)
asyncio.run(main())
Captured Data
The integration automatically records:
| Field | Description |
|---|
gen_ai.system | LLM provider (e.g., openai) |
gen_ai.request.model | Model name |
gen_ai.prompt | Input messages (if include_content=True) |
gen_ai.completion | Response (if include_content=True) |
user_id | User ID from context |
session_id | Session ID from context |
duration | Request latency |
