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OpenAI Adapter for RAG Control

A high-performance OpenAI adapter for RAG (Retrieval-Augmented Generation) systems, providing seamless integration with rag-control framework for LLM and embedding operations.

Features​

🚀 High-Performance LLM Generation - Support for chat completions with streaming 🔍 Query Embeddings - Generate embeddings for text queries using OpenAI's embedding models 📊 Comprehensive Metadata - Track latency, token usage, and request IDs ⚙️ Flexible Configuration - Full OpenAI client configuration support 🛡️ Error Handling - Robust exception handling with custom adapter errors 📝 Type-Safe - Full type annotations for Python static analysis

Installation​

Install the package from PyPI:

pip install openai-adapter

Or with uv:

uv pip install openai-adapter

Version Compatibility​

  • Current Stable Version: v0.1.0
  • Compatible with: rag-control v0.1.3

Quick Start​

Integration with rag-control​

The OpenAI Adapter is designed to integrate seamlessly with the rag-control framework:

from rag_control import RAGControl
from openai_adapter import OpenAILLMAdapter, OpenAIQueryEmbeddingAdapter

# Initialize adapters
llm_adapter = OpenAILLMAdapter(api_key="sk-...")
embedding_adapter = OpenAIQueryEmbeddingAdapter(api_key="sk-...")

# Create RAG system with OpenAI adapters
rag = RAGControl(
    llm_adapter=llm_adapter,
    embedding_adapter=embedding_adapter
)

# Use for RAG operations
response = rag.query("What is machine learning?")
print(response.answer)

API Reference​

OpenAILLMAdapter​

__init__(api_key: str, model: str = "gpt-3.5-turbo", **kwargs)

Initialize the LLM adapter.

Parameters:

  • api_key (str): OpenAI API key for authentication
  • model (str): Language model to use (default: gpt-3.5-turbo)
  • **kwargs: Additional OpenAI client configuration
    • organization (str): Organization ID
    • project (str): Project ID
    • base_url (str): Custom API endpoint
    • timeout (float): Request timeout in seconds

Raises:

  • LLMAdapterError: If client initialization fails

OpenAIQueryEmbeddingAdapter​

__init__(api_key: str, model: str = "text-embedding-3-small", **kwargs)

Initialize the embedding adapter.

Parameters:

  • api_key (str): OpenAI API key
  • model (str): Embedding model (default: text-embedding-3-small)
  • **kwargs: Additional OpenAI client configuration

Raises:

  • QueryEmbeddingAdapterError: If client initialization fails

Open Source​

This project is open source and contributions are welcome!

You can contribute by reporting issues, suggesting features, or submitting pull requests on GitHub.