GitHub

chatgpt-on-wechat (CoW)

What is the project about?

chatgpt-on-wechat (CoW) is an intelligent conversational AI robot based on large language models (LLMs). It allows users to interact with various LLMs through popular messaging platforms. It's essentially a bridge between LLMs and messaging apps.

What problem does it solve?

  • Accessibility: It makes powerful AI models easily accessible to users through familiar messaging interfaces, without requiring technical expertise or direct interaction with complex APIs.
  • Integration: It integrates AI capabilities into existing communication workflows, allowing users to leverage AI within their daily conversations.
  • Customization: It allows for customization through knowledge bases and plugins, enabling users to create specialized AI assistants for specific tasks or domains.
  • Multi-Platform Support: It removes the need to use different interfaces for different LLMs or messaging platforms, providing a unified experience.

What are the features of the project?

  • Multi-Platform Deployment: Supports deployment on WeChat Official Accounts, WeChat Work Applications, Feishu (Lark), and DingTalk.
  • Basic Conversation: Handles private and group chats, with support for multi-turn conversations and context memory. Works with a wide range of LLMs, including GPT-3.5, GPT-4o, GPT-4, Claude-3.5, Gemini, Wenxin Yiyan (ERNIE Bot), Xunfei Spark, Tongyi Qianwen, ChatGLM-4, Kimi, MiniMax, and GiteeAI.
  • Voice Capabilities: Recognizes voice messages and can reply with text or voice, using various voice models like Azure, Baidu, Google, and OpenAI (Whisper/TTS).
  • Image Capabilities: Supports image generation, image recognition, and image-to-image transformations (e.g., photo restoration). Integrates with models like Dall-E-3, Stable Diffusion, Replicate, Midjourney, CogView-3, and vision models.
  • Rich Plugins: Allows for custom plugin extensions. Existing plugins include role-switching, text adventures, sensitive word filtering, chat summarization, document summarization and Q&A, and web search.
  • Knowledge Base: Enables users to create custom robots by uploading knowledge base files. This allows for the creation of digital twins, intelligent customer service agents, and private domain assistants. This feature is powered by LinkAI.

What are the technologies used in the project?

  • Programming Language: Python (3.7.1 - 3.9.X recommended, 3.8 preferred).
  • Large Language Models (LLMs): GPT-3.5, GPT-4o-mini, GPT-4o, GPT-4, Claude-3.5, Gemini, Wenxin Yiyan, Xunfei Spark, Tongyi Qianwen, ChatGLM-4, Kimi, MiniMax, GiteeAI, and more.
  • Voice Models: Azure, Baidu, Google, OpenAI (Whisper/TTS).
  • Image Models: Dall-E-3, Stable Diffusion, Replicate, Midjourney, CogView-3, vision models.
  • Messaging Platforms: WeChat Official Accounts, WeChat Work, Feishu (Lark), DingTalk.
  • Dependencies: itchat (for WeChat interaction), various other Python libraries for LLM interaction, voice processing, image processing, and plugin support.
  • Deployment: Supports local execution, server deployment (using nohup), Docker, and Railway.
  • External Services: LinkAI (for knowledge base and other features).

What are the benefits of the project?

  • Easy Access to AI: Brings the power of LLMs to a wide audience through familiar messaging apps.
  • Enhanced Communication: Improves communication workflows by integrating AI assistance.
  • Customization and Specialization: Allows users to tailor AI assistants to specific needs.
  • Cost-Effective: Provides a cost-effective way to leverage various LLMs (especially with LinkAI integration).
  • Open Source: The MIT license allows for free use, modification, and distribution for research and learning purposes.
  • Community Support: Active community and support channels.
  • Enterprise Solutions: Offers enterprise services and product consultation through LinkAI.

What are the use cases of the project?

  • Personal Assistant: Answering questions, providing information, generating creative content.
  • Customer Service: Automating responses to customer inquiries, providing support.
  • Private Domain Assistant: Creating specialized assistants for specific industries or tasks.
  • Digital Twin: Creating a virtual representation of a person or entity.
  • Education and Training: Providing interactive learning experiences.
  • Content Creation: Generating text, images, and other content.
  • Workflow Automation: Automating tasks within messaging platforms.
  • Research and Development: Experimenting with LLMs and their applications.
  • Private Operations: Using AI to improve efficiency in private operations.
  • Enterprise Efficiency Assistant: Using AI to improve efficiency in enterprise operations.

In summary, chatgpt-on-wechat is a versatile project that bridges the gap between powerful LLMs and everyday messaging platforms, making AI more accessible and useful for a wide range of users and applications. It emphasizes ease of use, customization, and integration with existing workflows.

chatgpt-on-wechat screenshot