#python #ai #chatglm_4 #chatgpt #claude3 #dingtalk #feishu_bot #gemini #glm #gpt_4 #kimi #linkai #llm #openai #python3 #qwen #rag #wechat #wechat_bot #wenxinyiyan #xunfei_spark

This project, called "chatgpt-on-wechat" (CoW), is an intelligent chatbot based on large language models that can be integrated with various platforms like WeChat public accounts, enterprise WeChat apps, Feishu, and DingTalk. It supports multiple models such as GPT-3.5, GPT-4, Claude, Gemini, and more. The bot can handle text, voice, and image inputs and access external resources through plugins.

### Key Benefits Supports deployment on multiple platforms including WeChat public accounts, enterprise WeChat apps, Feishu, and DingTalk.
- **Advanced Conversations** Recognizes voice messages and generates images using various models.
- **Customizable Plugins** Enables custom AI applications using uploaded knowledge base files.

### How It Helps You:
This project helps you create a highly customizable AI chatbot that can be integrated into your existing communication platforms. It enhances customer service, personal assistance, and team efficiency by providing intelligent responses to text, voice, and image queries. The ability to customize knowledge bases and plugins makes it versatile for different business needs.

https://github.com/zhayujie/chatgpt-on-wechat

#jupyter_notebook #chatglm #chatglm3 #gemma_2b_it #glm_4 #internlm2 #llama3 #llm #lora #minicpm #q_wen #qwen #qwen1_5 #qwen2

This guide helps beginners set up and use open-source large language models (LLMs) on Linux or cloud platforms like AutoDL, with step-by-step instructions for environment setup, model deployment, and fine-tuning for models such as LLaMA, ChatGLM, and InternLM[2][4][5]. It covers everything from basic installation to advanced techniques like LoRA and distributed fine-tuning, and supports integration with tools like LangChain and online demo deployment. The main benefit is making powerful AI models accessible and easy to use for students, researchers, and anyone interested in experimenting with or customizing LLMs for their own projects[2][4][5].

https://github.com/datawhalechina/self-llm