aasherkamal216_axiom

aasherkamal216_axiom

by aasherkamal216
An AI agent built with LangGraph, MCP Docs, and Chainlit to assist in creating projects using natural language.

Axiom AI Documentation Assistant

Overview

Axiom is an AI-powered documentation assistant designed to help users create various projects using natural language instructions. Built with LangGraph, MCP Docs, and Chainlit, it specializes in modern AI frameworks, libraries, and tools. Axiom can assist in creating AI agents, RAG systems, chatbots, authentication mechanisms, and full-stack development.

AxiomAgent

Features

  • 🤖 Interactive chat interface
  • 📚 Access to multiple documentation sources
  • 🦾 Support for multiple Gemini models
  • 🎨 Support for image processing and analysis
  • 📈 Use images and graphs to create production-ready code
  • 🛠️ Customizable model settings (temperature, model version)
  • 🌐 Docker support for containerized deployment

Documentation Sources

Axiom uses llms.txt to fetch content from the following documentation sources:
- LangGraph Python
- CrewAI
- Model Context Protocol (MCP)
- Chainlit
- FastHTML
- Supabase
- Pinecone
- Composio
- Mem0
- Zep
- Stripe
- Resend
- Upstash
- Netlify
- Clerk Auth
- Stack Auth

Prerequisites

  • UV package manager
  • Python 3.11+
  • Google Gemini API Key
  • Docker (optional)

Installation

  1. Clone the repository:
    shell git clone https://github.com/aasherkamal216/Axiom.git cd Axiom
  2. Create and activate a virtual environment:
    shell uv venv .venv\Scripts\activate # For Windows source .venv/bin/activate # for Mac
  3. Install dependencies:
    shell uv sync
  4. Set up environment variables:
    shell cp .env.example .env
    Add your API keys and other credentials in the .env file.

Usage

Run the Application

  1. Start the MCP Doc server:
    shell uv run mcpdoc --yaml docs_config.yaml --transport sse --port 8082 --host localhost
  2. Run the Chainlit interface:
    shell uv run chainlit run app.py -w
    The application will be available at http://localhost:8000.

Building the Docker Image (Optional)

Alternatively, you can use Docker to run the application:

docker build -t axiom .
docker run -p 7860:7860 -p 8082:8082 axiom

Adding More Docs

You can add more documentations in the docs_config.yaml file. Any documentation with a llms.txt file can be added to the list.

About

Axiom is a documentation AI Agent built with LangGraph, MCP Docs, and Chainlit, designed to help users create different projects using natural language.

aasher-axiom.hf.space

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MIT license

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mcp_server model_context_protocol python docker langgraph chainlit gemini ai_agent api_integration

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