Welcome to the Lang-x-Index Learning Repository! This repository is dedicated to teaching developers how to effectively use LangChain and LlamaIndex to build advanced AI applications. It covers everything from basic concepts to real-world implementations.
The goal of this repository is to provide structured and practical tutorials on leveraging LangChain and LlamaIndex for building AI-powered applications. You'll find hands-on examples, best practices, and comprehensive guides to help you master these frameworks.
- LangChain enables developers to integrate large language models (LLMs) with external data sources, memory, and agents.
- LlamaIndex provides an optimized indexing and retrieval system, making it easier to work with large document datasets efficiently.
- Together, they power context-aware, intelligent applications such as AI chatbots, retrieval-augmented generation (RAG) systems, and automated data analysis.
This repository utilizes the following technologies:
- Programming Language: Python
- Frameworks: LangChain, LlamaIndex
- LLM Providers: OpenAI, Hugging Face, Anthropic
- Data Handling: Pandas, NumPy
- Databases & Vector Stores: Pinecone, ChromaDB, FAISS
- Deployment Tools: FastAPI, Streamlit, Gradio
- Overview of LangChain and LlamaIndex
- Installation and setup
- First steps with LangChain pipelines
- Using OpenAI’s API for language tasks
- Implementing memory and conversation history
- Customizing prompts for better results
- Understanding vector databases
- Implementing document indexing with LlamaIndex
- Optimizing query responses
- Introduction to Retrieval-Augmented Generation
- Combining LangChain & LlamaIndex for intelligent search
- Enhancing response accuracy with embeddings
- Creating a chatbot using Gradio
- Building a web API with FastAPI
- Deploying on cloud services
- Python 3.8+
- Install required dependencies:
pip install langchain llama-index openai chromadb pandas gradio
- Set up API keys for OpenAI and vector databases.
We welcome contributions! To contribute:
- Fork the repository.
- Create a new branch (
feature/your-feature-name). - Commit your changes and push to your fork.
- Open a pull request.
Please read our CONTRIBUTING.md for more details.
This project is licensed under the MIT License - see the LICENSE file for details.
For questions or collaborations, reach out via:
- GitHub: saadsalmanakram
- LinkedIn: Saad Salman Akram
- Email: saadsalman1@gmail.com
If you find this project useful, consider giving it a star ⭐ to support its development!