kindred-tracer 1.0.0

Kindred Tracer SDK for Python - Auto-instrumentation for AI agents

kindred-tracer

Kindred Tracer SDK for Python - Auto-instrumentation for AI agents.

This package automatically intercepts HTTP requests from your AI agent, categorizes them as LLM calls or tool executions, and exports logs to the Kindred log-search system.

Installation

pip install kindred-tracer

Or with optional dependencies:

pip install kindred-tracer[all]  # Includes requests support

Usage

Basic Usage

Just call kindred_tracer() once at startup, and all HTTP requests will be automatically intercepted and logged:

from kindred_tracer import kindred_tracer
import openai

# At startup - initialize the tracer
kindred_tracer()

# Your agent code here - no wrapping needed!
# All HTTP requests will be automatically logged
client = openai.OpenAI()
response = client.chat.completions.create(
    model="gpt-4",
    messages=[{"role": "user", "content": "Hello!"}]
)

Async Usage

Works the same way with async code:

import asyncio
from kindred_tracer import kindred_tracer
from openai import AsyncOpenAI

# Initialize once at startup
kindred_tracer()

async def main():
    # No wrapping needed - all requests are automatically logged
    client = AsyncOpenAI()
    response = await client.chat.completions.create(
        model="gpt-4",
        messages=[{"role": "user", "content": "Hello!"}]
    )

asyncio.run(main())

Configuration

Set the following environment variables:

• KINDRED_API_KEY (required) - Your Kindred API key for authentication
• KINDRED_API_URL (optional) - Base URL for Kindred API, defaults to https://api.usekindred.dev
• KINDRED_SESSION_ID (optional) - Session identifier. If not set, a UUID will be auto-generated
• KINDRED_AGENT_ID (optional) - Agent identifier
• KINDRED_RUN_ID (optional) - Run identifier

You can also pass these values directly to kindred_tracer():

from kindred_tracer import kindred_tracer

# Initialize with explicit values
kindred_tracer(session_id='session-123', agent_id='agent-456', run_id='run-789')

How It Works

1. Simple Initialization: Call kindred_tracer() once at startup to set up global context and enable interception.

2. Auto-instrumentation: The tracer automatically patches httpx.Client.request and httpx.AsyncClient.request when initialized. This is critical because OpenAI SDK v1+ uses httpx internally.

3. Global Context: Uses a global context that applies to all HTTP requests after initialization.

4. Request Detection:

   • LLM Calls: Detected by hostname (e.g., api.openai.com, api.anthropic.com) → logged as role: "agent"
   • Tool Calls: Any other hostname → logged as role: "tool"

5. Non-blocking Export: Logs are batched and exported in a background thread to avoid slowing down your agent.

Log Format

Logs are automatically formatted and sent to ${KINDRED_API_URL}/api/logs/ingest with the following structure:

{
    "session_id": str,
    "timestamp": str,  # ISO 8601
    "role": "user" | "agent" | "tool" | "system",
    "content": str,
    "agent_id": str | None,
    "run_id": str | None,
    "meta": {
        "type": "llm_generation" | "tool_execution",
        "request_id": str,
        "host": str,
        "method": str,
        "path": str,
        "request_headers": dict,
        "request_body": str | None,
        "response_status": int | None,
        "response_headers": dict,
        "response_body": str | None,
        "duration_ms": float,
        "tool_calls": list | None,  # Extracted from OpenAI responses
    }
}

Flushing Logs

Before shutting down your application, you can flush any pending logs:

from kindred_tracer import flush

# On shutdown
flush()

Security

The tracer automatically sanitizes sensitive headers before logging:

• Authorization
• x-api-key
• api-key
• x-auth-token
• cookie

Supported LLM Providers

The tracer automatically detects requests to:

• OpenAI (api.openai.com)
• Anthropic (api.anthropic.com)
• Google Gemini (generativelanguage.googleapis.com)
• Cohere (api.cohere.com)
• Mistral (api.mistral.ai)

Example

Here's a complete example:

from kindred_tracer import kindred_tracer, flush
import openai
import os

# Set your API key
os.environ['KINDRED_API_KEY'] = 'your-api-key-here'

# Initialize the tracer (reads session_id from KINDRED_SESSION_ID env var, or auto-generates)
kindred_tracer()

# Your agent code - all HTTP requests are automatically logged
client = openai.OpenAI()
response = client.chat.completions.create(
    model="gpt-4",
    messages=[{"role": "user", "content": "Hello!"}]
)

# Before shutdown, flush any pending logs
flush()

Requirements

• Python 3.10+
• wrapt>=1.14.0 (for safe monkey-patching)
• httpx>=0.24.0 (for HTTP client and patching)

License

MIT