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An API exposing a multitude of agent capacities

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Agents API

Agents API is a Bun-based application that provides agentic capabilities for personal use, allowing users to leverage various AI models for information retrieval and summarization. This project offers a flexible framework for processing and synthesizing information from multiple sources, including web searches.

Features

  • Implements agentic capabilities for personal use
  • Modular design allowing easy integration of different AI models
  • Web search summarization using Brave Search
  • Combines multiple search results into a coherent summary
  • Supports streaming responses for real-time interaction
  • Currently uses GPT-3.5, Llama 3.1, and Mistral AI models, with easy extensibility

Prerequisites

  • Bun runtime
  • API keys for OpenAI, Groq, and Brave Search

Installation

  1. Clone the repository:

    git clone git@github.com:GuiBibeau/agents-api.git
    cd agents-api
    
  2. Install dependencies:

    bun install
    
  3. Set up environment variables: Create a .env file in the root directory and add the following:

    OPENAI_API_KEY=your_openai_api_key
    GROQ_API_KEY=your_groq_api_key
    BRAVE_API_KEY=your_brave_api_key
    

Usage

  1. Start the server:

    bun run index.ts
    
  2. Access the API endpoints:

    • Health check: GET /
    • Search and summarize: GET /search?q=your_query&stream=true|false
  3. View API documentation:

    • Access Swagger UI: http://localhost:8080/api-docs

Project Structure

  • index.ts: Main application file
  • chat-models/: AI model configurations (easily extendable)
  • tools/: Search tool implementations
  • lib/: Utility functions and configurations

Dependencies

  • express: Web server framework
  • @langchain/openai: OpenAI language models
  • @langchain/groq: Groq AI models
  • langchain: LangChain library for building AI applications
  • swagger-jsdoc and swagger-ui-express: API documentation

Future Plans

  • Additional Tools: Integrate more tools for diverse data sources and functionalities.
  • Model Optimization: Fine-tune and optimize AI models for better performance.
  • Enhanced Agentic Capabilities: Develop more sophisticated agent behaviors and decision-making processes.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

Do as you wish my friend.

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