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Project exploring RAG LLM agents

Minimal AI agent kernel for a distributed future. <10MB binary, <50ms boot, Rust sandbox, dual-mode runtime. Pico Mode or full mesh — same binary.

🎶 Enhance audio quality with ComfyUI-AudioSR, a versatile tool for upscaling sounds to 48kHz for better clarity and listening experience.

This is the Deno 2 implementation of all tasks I did during AI Devs 3 course. It's integrated with Anthropic and OpenAI APIs here. Many different tools regarding LLMs are used here.

Self-hosted AI assistant with web interface, integrated autonomous agents and sandboxed execution

OpenClaw Bootstrapping Benchmark is an automated test suite that evaluates how well local LLM models (served via Ollama or compatible OpenAI-API endpoints) can complete OpenClaw's first-run "bootstrapping ritual".

AI-Powered Appointment Scheduling Assistant (LangGraph v1+)

A simple local python AI chatbot using HuggingFace inference API and streaming/history with Redis

A pure Python implementation of ReAct agent without using any frameworks like LangChain. It follows the standard ReAct loop of Thought, Action, PAUSE, and Observation. The agent utilizes multiple tools, including Calculator, Wikipedia, Web Search, and Weather. A web UI is also provided using Streamlit.

A project demonstrating the ability to utilize Agentic AI workflows to perform analysis and discovery on aspects of US Healthcare Taxation Laws. Utilizes an underlying RAG framework for Response Generation. Also includes a comparison of LlamaIndex vs a custom framework that makes use of retrieval strategies like Hyde and Multi-Query Transformations

A starter template for building powerful, local, tool-calling LLM agents using LangGraph and llama-cpp-python

AskGPT is a real-time AI assistant that enhances your calls, interviews, meetings, and lectures by providing instant AI-generated insights. It captures live audio, transcribes speech into text, and generates context-aware responses—all in real-time!

[Hitachi Digital Services] Demo on LangGraph-based Lightweight Multi-Agent System