chatbot

A collection of simple transformer based chatbots.

Knowledge base Q&A program using LangChain for retrieval-augmented prompting and PGVector as vector store.

Llava, Ollama and Streamlit | Create POWERFUL Image Analyzer Chatbot for FREE - Windows & Mac

Multimodal AI Assistant is an advanced chatbot designed for local interactions with LLMs, files, and multimodal functionalities. Built on the Chainlit framework, it integrates Langchain and ChatOllama for hosting models locally, with cloud storage and monitoring via LiteralAI.

AI-powered RAG app to chat with any documentation - scrape, generate knowledge base, and query docs with source-backed answers.

Uncensored AI platform — chat, roleplay, image generation. Built on open-source models.

Perform RAG (Retrieval-Augmented Generation) from your PDFs using this Colab notebook! Powered by Llama 2

Query, ask and chat with a document-index via transformer models!

A PDF Question-Answering App built with RAG (Retrieval-Augmented Generation), allowing users to upload PDFs and ask context-based questions. Powered by Streamlit, LangChain, Ollama, and Chroma for efficient and accurate answers.

Zero-dependency Python SDK for WeChat Bot (iLink protocol) — text, image, video messaging & MCP server | 零依赖微信机器人 Python SDK，支持多媒体消息和 MCP 服务器

Open source voice bot for Humanoid Robots and virtual digital humans

It is a voice bot based on LLM.

AI-powered multimodal chat app with real-time responses, file support, token tracking, and dark mode. Built with Next.js. Open source under MIT.

A self-hosted omni-modal agentic retrieval platform that understands, searches, and explores documents, images, audio, and video through semantic routing, hybrid retrieval, adaptive agents, and traceable citations.

LLM-powered financial analyst using LoRA-tuned Llama-3 and RAG pipeline to answer complex queries over SEC 10-K filings with contextual accuracy.

Fine-tuning a quantized Llama 2 chat model on Q&A pairs from counselchat.com to provide empathetic and appropriate mental health advice

A LLaMA2-7b chatbot with memory running on CPU, and optimized using smooth quantization, 4-bit quantization or Intel® Extension For PyTorch with bfloat16.

Implements a framework to build Generative AI applications.

LangGraphRAG: A terminal-based Retrieval-Augmented Generation system using LangGraph. Features include message history caching, query transformation, and vector database retrieval. Ideal for NLP researchers and developers working on advanced conversational AI and information retrieval systems.

An advanced AI-powered conversational agent leveraging the Llama 3.2 model and Phidata framework. Features include reasoning, natural language interaction, and tool integration for web searches and calculations. Designed for interactivity with enhanced logging, support for custom tools, and structured outputs.