awesome-llm-apps

awesome-llm-apps

Collection of awesome LLM apps with RAG using OpenAI, Anthropic, Gemini and opensource models.

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Awesome LLM Apps is a curated collection of applications that leverage RAG with OpenAI, Anthropic, Gemini, and open-source models. The repository contains projects such as Local Llama-3 with RAG for chatting with webpages locally, Chat with Gmail for interacting with Gmail using natural language, Chat with Substack Newsletter for conversing with Substack newsletters using GPT-4, Chat with PDF for intelligent conversation based on PDF documents, and Chat with YouTube Videos for engaging with YouTube video content through natural language. Users can clone the repository, navigate to specific project directories, install dependencies, and follow project-specific instructions to set up and run the apps. Contributions are encouraged, and new app ideas or improvements can be submitted via pull requests.

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🌟 Awesome LLM Apps

A curated collection of awesome LLM apps built with RAG and AI agents. This repository features LLM apps that use models from OpenAI, Anthropic, Google, and even open-source models like LLaMA that you can run locally on your computer.

Shubhamsaboo%2Fawesome-llm-apps | Trendshift

πŸ€” Why Awesome LLM Apps?

  • πŸ’‘ Discover practical and creative ways LLMs can be applied across different domains, from code repositories to email inboxes and more.
  • πŸ”₯ Explore apps that combine LLMs from OpenAI, Anthropic, Gemini, and open-source alternatives with RAG and AI Agents.
  • πŸŽ“ Learn from well-documented projects and contribute to the growing open-source ecosystem of LLM-powered applications.

πŸ“‚ Featured AI Projects

AI Agents

RAG (Retrieval Augmented Generation)

LLM Apps with Memory

Chat with X

LLM Finetuning

Advanced Tools and Frameworks

πŸš€ Getting Started

  1. Clone the repository

    git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git 
  2. Navigate to the desired project directory

    cd awesome-llm-apps/chat_with_X_tutorials/chat_with_gmail
  3. Install the required dependencies

    pip install -r requirements.txt
  4. Follow the project-specific instructions in each project's README.md file to set up and run the app.

🀝 Contributing to Open Source

Contributions are welcome! If you have any ideas, improvements, or new apps to add, please create a new GitHub Issue or submit a pull request. Make sure to follow the existing project structure and include a detailed README.md for each new app.

Thank You, Community, for the Support! πŸ™

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🌟 Don’t miss out on future updates! Star the repo now and be the first to know about new and exciting LLM apps with RAG and AI Agents.

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