vblagoje/openapi-rag-service

vblagoje/openapi-rag-service demonstrates the seamless integration of OpenAPI-defined services with Large Language Models (LLMs) in the Haystack RAG (Retriever-Augmented Generation) pipeline. This project offers an easy way to explore the enhanced capabilities of Haystack's 2.x RAG architecture, enriching LLMs with structured data from various OpenAPI services. The vblagoje/openapi-rag-service Docker image facilitates quick experimentation, opening new possibilities for enriching LLM outputs in the RAG framework.

Key Features

Seamless OpenAPI Integration: Incorporates any OpenAPI-specified service into the RAG pipeline, expanding the potential sources of information beyond unstructured text.
Enhanced RAG Functionality: Enhances traditional RAG capabilities with structured, service-driven data, offering more contextually rich and accurate outputs.
Flexible LLM Compatibility: Supports various Large Language Models (LLMs) that adhere to OpenAI Python client standards, ensuring broad applicability and flexibility.

Getting Started

Prerequisites

Docker installed on your machine.
Access to LLM providers compatible with the OpenAI Python client.

Running the Service

To run the vblagoje/openapi-rag-service, pull the Docker image and execute it with the necessary parameters:

docker pull vblagoje/openapi-rag-service:latest
docker run <additional-parameters> vblagoje/openapi-rag-service

Configuration

Configure the service using the following environment variables:

OPENAI_API_KEY: Your API key for OpenAI.
OPENAI_BASE_URL: The base URL for the OpenAI API.
TEXT_GENERATION_MODEL: Name of the model used for text generation (e.g., gpt-4-1106-preview).
FUNCTION_CALLING_MODEL: Model name for handling function calls (e.g., gpt-3.5-turbo-0613).
SYSTEM_PROMPT: System message or prompt URL to assist the model in generating content.
FUNCTION_CALLING_PROMPT: Prompt for the function calling model.
USER_PROMPT: Additional user-defined prompt for guided output text generation.
FUNCTION_CALLING_VALIDATION_SCHEMA: Schema URL or json text for validating OpenAPI function calls (adds correction loop)
BOT_NAME: Bot name used in guiding the generation process.
OPENAPI_SERVICE_SPEC: URL or path to the OpenAPI service specification.
OPENAPI_SERVICE_TOKEN: Token for authenticating with the specified OpenAPI service.
SERVICE_RESPONSE_SUBTREE: Specific subtree to parse in the service response.
OUTPUT_KEY: Json key for the output of the text generation (if not the output is not a json)
OUTPUT_SCHEMA: Schema URL or json text defining the output format.
QUIET: Set to true to disable output to standard output (STDOUT).

Usage Example

TODO

License

Licensed under (LICENCE)[LICENCSE]

TuanaCelik / openapi-rag-service