Chatbot UI powered by local LLaMA3 using Ollama + Streamlit. 100% offline, no API keys needed.
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Updated
May 10, 2025 - Python
Chatbot UI powered by local LLaMA3 using Ollama + Streamlit. 100% offline, no API keys needed.
An AI chatbot built with DeepScaleR and deployed locally using Ollama, FastAPI, and Gradio.
Video Summarizer using Local LLM (facebook/bart-large-cnn). Submit a YouTube URL and get an AI-generated summary of the video.
PHP Frontend for Hosting local LLM's (run via VSCode or basic php execution methods/ add to project)
AI-powered Bash terminal built with Python, Tkinter, tkterm, using local LLM through LMStudio for natural language command generation; features whitelist/blacklist management, intuitive interface.
python SDK for CZero Engine (API endpoints usage examples)
ResumeRefine AI is a state-of-the-art tool that enhances your resume to align perfectly with job descriptions. It analyzes and refines your resume content, ensuring it matches the key requirements of your target job. This application streamlines the process of resume customization, giving you a competitive edge in your job search.
☕ AI-powered assistant that answers Starbucks-related questions using real reviews, used LLaMA3:Instruct, LangChain, and Ollama , RAG & also Includes real-time Starbucks location lookup, runs fully offline (except for Maps), and styled with a cozy, coffee-themed UI.
Project demonstrates an agentic Retrieval-Augmented Generation (RAG) application built using CrewAI and Streamlit.
An Experimental Cognitive Architecture with Persistent Memory for stateful LLM-agents
A Chrome extension with Python backend that uses Ollama LLM to provide contextually enhanced responses about web content through a chat interface.
A local AI chatbot built with PyQt5 and LLaMA 3 (via Ollama). Fully offline, fast responses, smart character modes, and a polished UI.
Python application that uses local Ollama LLM models to give advice on results found from HIBP (Have I Been Pwned) API
Multi-agent AI system using CrewAI and Ollama to automatically research, write, and review beginner-friendly Python tutorials
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