一个《原神》AI驱动视频项目，利用LLM API生成角色互动文案，VITS技术进行语音合成，并结合先进的文生图和视频合成技术，创造出游戏角色之间有趣的场景。最终产出为短视频。

搜索引擎API python版

A minimal example for in-memory RAG using ChromaDB and Ollama LLM

Chat With Documents is a Streamlit application designed to facilitate interactive, context-aware conversations with large language models (LLMs) by leveraging Retrieval-Augmented Generation (RAG). Users can upload documents or provide URLs, and the app indexes the content using a vector store called Chroma to supply relevant context during chats.

🚀 Transform Any PDF into an AI-Powered Q&A Chatbot!

FileChat-RAG is a simple Retrieval-Augmented Generation (RAG) system that allows users to ask questions about the contents of various file formats. It extracts text from PDFs, JSON, text files(.txt, .docx, .odt, .md), and code files, then enables interactive conversations using an LLM powered by Ollama.

Playing around with Retrieval Augmented Generation.

CSE572-DataMining

LLM Experimentation

Evaluation script for automatic evaluation of JCrRAG benchmark

LLM RAG