langchian

BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation, SFT, Dataset Management, Enterprise-level System Management, Observability and more.

ChatGPT Web Nuxt 3 Vue 3 Version

Q&A based on elasticsearch+langchain+chatglm2 ｜ 基于elasticsearch，langchain，chatglm2的自有知识库问答

Syzygy-of-thoughts

Reddit_Poster_AIHawk is a Python script demonstrating AI's capabilities in social media interaction. It uses GPT models to analyze trending subreddits and automatically generate contextually relevant Reddit posts, showcasing AI's potential in understanding and engaging with online discussions.

Probably one of the lightest native RAG + Agent apps out there，experience the power of Agent-powered models and Agent-driven knowledge bases in one click, without complex configuration.

Mojuan: Write your own AI application.

A minimal, lightweight client designed to simplify SDK adoption into MCP

Use the open-source large model to train your own LLM model chatGPT

Personal assistant using Agent modulation with dialog, drawing, video and music playback.

Your Gateway to Tailored Career Messages: LLM-Powered Message Generator Application

The MCQ Generator uses OpenAI and LangChain to create multiple-choice questions from a provided PDF, allowing users to specify the subject and difficulty level.

GitSense is a developer tool that simplifies repository analysis with AI-powered commit summaries and a smart Q&A system. Built with Next.js, LangChain, and Google Gemini API, it helps you understand your codebase faster and smarter.

ATS Resume, Analaysis the resume of the user and generates questions based on resume.

LangGraph Agentic automation of SRE best practices in DevOps

Ứng dụng "Hỗ trợ nhân đạo thông minh" (Smart Aid).

Streamlit-based AI assistant powered by OpenAI with Langchain integration for SQL capabilities via CSV uploads.

A bot to generate query for Your database.

Chat with your PDF data using using LangChain Framework