Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly

Appearance settings

https-deeplearning-ai/starting-ragchatbot-codebase

Open more actions menu

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
2 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Course Materials RAG System

A Retrieval-Augmented Generation (RAG) system designed to answer questions about course materials using semantic search and AI-powered responses.

Overview

This application is a full-stack web application that enables users to query course materials and receive intelligent, context-aware responses. It uses ChromaDB for vector storage, Anthropic's Claude for AI generation, and provides a web interface for interaction.

Prerequisites

  • Python 3.13 or higher
  • uv (Python package manager)
  • An Anthropic API key (for Claude AI)
  • For Windows: Use Git Bash to run the application commands - Download Git for Windows

Installation

  1. Install uv (if not already installed)

    curl -LsSf https://astral.sh/uv/install.sh | sh
  2. Install Python dependencies

    uv sync
  3. Set up environment variables

    Create a .env file in the root directory:

    ANTHROPIC_API_KEY=your_anthropic_api_key_here

Running the Application

Quick Start

Use the provided shell script:

chmod +x run.sh
./run.sh

Manual Start

cd backend
uv run uvicorn app:app --reload --port 8000

The application will be available at:

  • Web Interface: http://localhost:8000
  • API Documentation: http://localhost:8000/docs

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published
Morty Proxy This is a proxified and sanitized view of the page, visit original site.