A curated collection of LLM Apps Experiments 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.
- 🌟 My LLM Apps Experiments
- 📑 Table of Contents
- 🤔 Why LLM-Apps-Experiments ?
- 📂 Featured Projects
- 💻 Local Lllama-3 with RAG
- 🎯 Generative AI Web Search Assistant
- 💬 Chat with GitHub Repo
- 📈 AI Investment Agent
- 🗞️ AI Journalist Agent
- 💰 AI Personal Finance Agent
- 🛫 AI Travel Agent
- 🎬 AI Movie Production Agent
- 📰 Multi-Agent AI Researcher
- 📚 AI Research Agent with Memory
- 📄 Chat with PDF
- 💻 Web Scraping AI Agent
- 📨 Chat with Gmail
- 📽️ Chat with YouTube Videos
- 🔎 Chat with Arxiv Research Papers
- 📝 Chat with Substack Newsletter
- 🚀 Getting Started
- 🤝 Contributing to Opensource
- 💡 Discover practical and creative ways LLMs can be applied across different domains, from code repositories to email inboxes and more.
- 🔥 Explore apps that combine LLMs from OpenAI, Anthropic, Gemini, and open-source alternatives with RAG and AI Agents.
- 🎓 Learn from well-documented projects and contribute to the growing open-source ecosystem of LLM-powered applications.
Chat with any webpage using local Llama-3 and Retrieval Augmented Generation (RAG) in a Streamlit app. Enjoy 100% free and offline functionality.
Get pinpointed answers to your queries by combining search engines and LLMs using OpenAI's GPT-4 and the DuckDuckGo search engine for accurate responses.
Engage in natural conversations with your GitHub repositories using GPT-4. Uncover valuable insights and documentation effortlessly.
AI investment agent that compares the performance of two stocks and generates detailed stock reports with company insights, news, and analyst recommendations to help you make smart investment choices.
AI-powered journalist agent that generates high-quality articles using OpenAI GPT-4o. It automates the process of researching, writing, and editing articles, allowing you to create compelling content on any topic with ease.
AI-powered personal finance planner that generates personalized financial plans using OpenAI GPT-4o. It automates the process of researching, planning, and creating tailored budgets, investment strategies, and savings goals.
AI-powered travel Agent that generates personalized travel itineraries using OpenAI GPT-4o. It automates the process of researching, planning, and organizing your dream vacation, allowing you to explore exciting destinations with ease.
AI-powered movie production assistant that helps bring your movie ideas to life using Claude 3.5 Sonnet model. It automates the process of script writing and casting, allowing you to create compelling movie concepts with ease.
Use a team of AI agents to research top HackerNews stories and users with GPT-4 to generate blog posts, reports, and social media content on autopilot.
AI Research Agent that helps user find research papers on Arxiv based on their interests and past interactions with LLMs. It maintains a memory of user interests and past interactions using Mem0 and Qdrant.
Engage in intelligent conversation and question-answering based on the content of your PDF documents. Simply upload and start asking questions.
Intelligently scrape websites using OpenAI API and the scrapegraphai library. Specify the URL and extraction requirements, and let the AI agent handle the rest.
Interact with your Gmail inbox using natural language. Get accurate answers to your questions based on the content of your emails with Retrieval Augmented Generation (RAG).
Dive into video content with interactive conversation and question-answering based on YouTube videos. Provide a URL and engage with the video's content through natural language.
Explore the vast knowledge in arXiv research papers through interactive conversations using GPT-4 and unlock insights from millions of research papers.
Chat with a Substack newsletter using OpenAI's API and the Embedchain library in a Streamlit app. Leverage GPT-4 for precise answers based on newsletter content.
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Clone the repository
git clone https://github.com/sachnaror/LLM-Apps-Experiments.git
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Navigate to the desired project directory
cd LLM-Apps-Experiments/chat_with_gmail
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Install the required dependencies
pip install -r requirements.txt
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Follow the project-specific instructions in each project's README.md file to set up and run the app.
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.