Metadata-Version: 2.4
Name: r4u
Version: 0.1.7
Summary: Observability SDK for LLM applications
Author: R4U Team
License: Apache 2.0
Requires-Python: >=3.10
Requires-Dist: async-trace>=0.1.0
Requires-Dist: httpx>=0.28.1
Requires-Dist: pydantic>=2.12.2
Provides-Extra: aiohttp
Requires-Dist: aiohttp>=3.8.0; extra == 'aiohttp'
Provides-Extra: requests
Requires-Dist: requests>=2.25.0; extra == 'requests'
Description-Content-Type: text/markdown

# R4U Python SDK

An observability SDK that automatically traces HTTP requests from your applications, with special support for LLM API calls.

## Installation

```bash
pip install r4u
```

## Quick Start

### Automatic HTTP Tracing

The easiest way to get started is with automatic HTTP tracing. This will trace all HTTP requests made by any supported HTTP library:

```python
from r4u.tracing import trace_all

# Enable automatic tracing for all HTTP libraries with default AI provider patterns
trace_all()

# Or with custom patterns that extend the defaults
trace_all(
    allow_urls=["https://api.custom.com/*"],
    deny_urls=["https://api.openai.com/v1/models"]
)

# Now any HTTP requests will be automatically traced
import httpx
import requests
import aiohttp

# All of these will be automatically traced
httpx_client = httpx.Client()
requests_session = requests.Session()
aiohttp_session = aiohttp.ClientSession()
```

### URL Filtering

By default, the SDK only traces requests to common AI provider APIs. You can configure which URLs to trace using allow and deny patterns:

```python
from r4u.tracing.http.auto import configure_url_filter, trace_all

# Configure URL filtering
configure_url_filter(
    allow_patterns=[
        "https://api.openai.com/*",      # OpenAI API
        "https://api.anthropic.com/*",   # Anthropic API
        "https://api.groq.com/*",        # Groq API
    ],
    deny_patterns=[
        "https://api.openai.com/v1/models",  # Deny specific endpoints
    ]
)

# Enable tracing
trace_all()
```

**Default Allow Patterns:**
- OpenAI: `https://api.openai.com/*`
- Anthropic: `https://api.anthropic.com/*`, `https://docs.claude.com/*`
- Groq: `https://api.groq.com/*`, `https://console.groq.com/*`
- xAI (Grok): `https://api.x.ai/*`, `https://latenode.com/*`
- Mistral AI: `https://api.mistral.ai/*`, `https://apidog.com/*`
- Google: `https://generativelanguage.googleapis.com/*`, `https://aiplatform.googleapis.com/*`


### Pattern Matching

The filter supports wildcard patterns using `fnmatch` syntax:

- `*` matches any characters except `/`
- `**` matches any characters including `/`
- Patterns are case-insensitive
- Both full URLs and host-only patterns are supported

Examples:
- `https://api.openai.com/*` - matches all OpenAI API endpoints
- `*.openai.com/*` - matches all OpenAI subdomains
- `api.openai.com` - matches only the exact host



### OpenAI Integration

Since OpenAI uses httpx internally, you can trace OpenAI API calls by enabling HTTP tracing:

```python
from r4u.tracing import trace_all

# Enable tracing BEFORE importing OpenAI
trace_all()

# Now import and use OpenAI normally
from openai import OpenAI

client = OpenAI(api_key="your-api-key")
response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Hello, world!"}]
)
```

## Features

- **Automatic HTTP Tracing**: Automatically trace all HTTP requests from supported libraries (httpx, requests, aiohttp)
- **Multiple HTTP Library Support**: Works with httpx, requests, and aiohttp
- **OpenAI Integration**: Automatically trace OpenAI API calls since they use httpx internally
- **Streaming Support**: Full support for streaming HTTP requests and responses
- **Async Support**: Full async/await support for both sync and async HTTP clients
- **Background Processing**: Traces are sent asynchronously in batches to minimize performance impact
- **Error Tracking**: Automatic error capture and reporting
- **Minimal Overhead**: Lightweight wrapper with minimal performance impact
- **Custom Tracers**: Support for custom tracer implementations

### HTTP Trace Data

Each HTTP request generates a comprehensive trace with:

**Request Details**:
- HTTP method (GET, POST, etc.)
- Full URL
- Request headers (including Authorization)
- Request body (raw bytes)

**Response Details**:
- HTTP status code
- Response headers
- Response body (raw bytes, including streaming responses)

**Timing Information**:
- Request start time
- Request completion time
- Total duration

**Error Information** (if applicable):
- Error messages
- Exception details

**Custom Metadata**:
- Additional context you can provide
- Extracted fields for convenience


### Streaming Example

```python
from r4u.tracing import trace_all

# Enable tracing BEFORE importing OpenAI
trace_all()

from openai import OpenAI

client = OpenAI(api_key="your-api-key")

# Streaming requests are automatically traced
stream = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Tell me a story"}],
    stream=True
)

for chunk in stream:
    if chunk.choices[0].delta.content is not None:
        print(chunk.choices[0].delta.content, end="")
```

### Custom Tracer Example

```python
from r4u.client import AbstractTracer, HTTPTrace
from r4u.tracing import trace_all

class ConsoleTracer(AbstractTracer):
    def log(self, trace: HTTPTrace):
        print(f"HTTP {trace.method} {trace.url} -> {trace.status_code}")

# Use custom tracer
tracer = ConsoleTracer()
trace_all(tracer)

# All HTTP requests will now be printed to console
```

For more comprehensive examples, see the `examples/` directory.

## Configuration

### Environment Variables

- `R4U_API_URL`: Base URL for the R4U server (default: `http://localhost:8000`)
- `R4U_TIMEOUT`: HTTP request timeout in seconds (default: `30.0`)
- `R4U_TOKEN`: R4U Cloud server authorization token (optional, not needed for local Open R4U Server)


## Development

See the `examples/` directory for comprehensive usage examples and the `tests/` directory for test cases.
