b73fe0cc3c
### What problem does this PR solve? This PR introduces the `ragflow_chat` plugin for the ChatGPT-on-WeChat project, extending its functionality by integrating Retrieval-Augmented Generation (RAG) capabilities. It allows users to have more contextually relevant conversations by retrieving information from external knowledge sources (via the RAGFlow API) and incorporating it into their chat interactions. The primary goal of this PR is to enable seamless communication between ChatGPT-on-WeChat and the RAGFlow server, improving response accuracy by embedding knowledge-based data into conversational flows. This is particularly useful for users who need more complex, data-driven responses. This PR adds a new plugin that enhances ChatGPT-on-WeChat with Ragflow capabilities, allowing for a more enriched conversational experience driven by external knowledge. ### Type of change - [x] New Feature (non-breaking change which adds functionality)
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RAGFlow Chat Plugin for ChatGPT-on-WeChat
This folder contains the source code for the ragflow_chat plugin, which extends the core functionality of the RAGFlow API to support conversational interactions using Retrieval-Augmented Generation (RAG). This plugin integrates seamlessly with the ChatGPT-on-WeChat project, enabling WeChat and other platforms to leverage the knowledge retrieval capabilities provided by RAGFlow in chat interactions.
Features
- Conversational Interactions: Combine WeChat's conversational interface with powerful RAG (Retrieval-Augmented Generation) capabilities.
- Knowledge-Based Responses: Enrich conversations by retrieving relevant data from external knowledge sources and incorporating them into chat responses.
- Multi-Platform Support: Works across WeChat, WeCom, and various other platforms supported by the ChatGPT-on-WeChat framework.
Plugin vs. ChatGPT-on-WeChat Configurations
Note: There are two distinct configuration files used in this setup—one for the ChatGPT-on-WeChat core project and another specific to the ragflow_chat plugin. It is important to configure both correctly to ensure smooth integration.
ChatGPT-on-WeChat Root Configuration (config.json)
This file is located in the root directory of the ChatGPT-on-WeChat project and is responsible for defining the communication channels and overall behavior. For example, it handles the configuration for WeChat, WeCom, and other services like Feishu and DingTalk.
Example config.json (for WeChat channel):
{
"channel_type": "wechatmp",
"wechatmp_app_id": "YOUR_APP_ID",
"wechatmp_app_secret": "YOUR_APP_SECRET",
"wechatmp_token": "YOUR_TOKEN",
"wechatmp_port": 80,
...
}
This file can also be modified to support other communication platforms, such as:
- Personal WeChat (
channel_type: wx) - WeChat Public Account (
wechatmporwechatmp_service) - WeChat Work (WeCom) (
wechatcom_app) - Feishu (
feishu) - DingTalk (
dingtalk)
For detailed configuration options, see the official LinkAI documentation.
RAGFlow Chat Plugin Configuration (plugins/ragflow_chat/config.json)
This configuration is specific to the ragflow_chat plugin and is used to set up communication with the RAGFlow server. Ensure that your RAGFlow server is running, and update the plugin's config.json file with your server details:
Example config.json (for ragflow_chat):
{
"ragflow_api_key": "YOUR_API_KEY",
"ragflow_host": "127.0.0.1:80"
}
This file must be configured to point to your RAGFlow instance, with the ragflow_api_key and ragflow_host fields set appropriately. The ragflow_host is typically your server's address and port number, and the ragflow_api_key is obtained from your RAGFlow API setup.
Requirements
Before you can use this plugin, ensure the following are in place:
- You have installed and configured ChatGPT-on-WeChat.
- You have deployed and are running the RAGFlow server.
Make sure both config.json files (ChatGPT-on-WeChat and RAGFlow Chat Plugin) are correctly set up as per the examples above.