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open-source-ai

Here are 18 public repositories matching this topic...

Your SDK solves all of this. One interface. Unified logic. Local + hosted models. Fine-tuning. Agent tools. Enterprise-ready. Hybrid RAG.Star 🌟 if you like it!

  • Updated Oct 17, 2025
  • Python

Experimental interface environment for open source LLM, designed to democratize the use of AI. Powered by llama-cpp, llama-cpp-python and Gradio.

  • Updated Oct 11, 2025
  • Python

An interactive AI chatbot built with Streamlit and Groq API using the powerful llama-3.3-70b-versatile model. Features include a modern UI, memory toggle, and downloadable chat history. Ideal for testing LLMs or deploying a smart assistant in real-time.

  • Updated Sep 27, 2025
  • Python

Made with Python, crafted by Vishnu 💻✨ Nexora AI – A smart Python voice agent with GUI, reminders, WhatsApp messaging, app control, jokes, and more! Built with 💻 + 🧠 + ❤️.

  • Updated May 12, 2025
  • Python

This project implements an AI agent that verifies if automated Hercules test runs were executed as intended by comparing planning logs, video evidence, and final outputs. It uses open-source LLMs and computer vision tools to flag deviations, providing detailed reports with technical insights.

  • Updated Jun 30, 2025
  • Python

⚡💾 Vectro — Compress LLM embeddings 🧠🚀 Save memory, speed up retrieval, and keep semantic accuracy 🎯✨ Lightning-fast quantization for Python + Mojo, vector DB friendly 🗄️, and perfect for RAG pipelines, AI research, and devs who want smaller, faster embeddings 📊💡

  • Updated Oct 21, 2025
  • Python

A lightweight Explainable AI CNN for PathMNIST medical imaging, achieving 91%+ accuracy with Integrated Gradients and SQLite-based attribution storage. Built in PyTorch, this scalable model delivers high performance, transparency, and real-world readiness, making it ideal for medical AI, edge deployment, and explainable deep learning research.

  • Updated Sep 13, 2025
  • Python

🔍 Enhance medical imaging with a lightweight CNN model that offers over 91% accuracy and integrated explainability for better clinical trust.

  • Updated Oct 21, 2025
  • Python

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