opea/productivity-suite-react-ui-server repository overview

⁠Productivity Suite React UI

⁠📸 Project Screenshots

⁠🧐 Features

Here're some of the project's features:

⁠CHAT QNA

• Start a Text Chat：Initiate a text chat with the ability to input written conversations, where the dialogue content can also be customized based on uploaded files.
• Context Awareness: The AI assistant maintains the context of the conversation, understanding references to previous statements or questions. This allows for more natural and coherent exchanges.

⁠DATA SOURCE

• The choice between uploading locally or copying a remote link. Chat according to uploaded knowledge base.
• Uploaded File would get listed and user would be able add or remove file/links

⁠Screen Shot

• Clear: Clear the record of the current dialog box without retaining the contents of the dialog box.
• Chat history: Historical chat records can still be retained after refreshing, making it easier for users to view the context.
• Conversational Chat : The application maintains a history of the conversation, allowing users to review previous messages and the AI to refer back to earlier points in the dialogue when necessary.

⁠Screen Shots

⁠CODEGEN

• Generate code: generate the corresponding code based on the current user's input.

  Screen Shot

⁠DOC SUMMARY

• Summarizing Uploaded Files: Upload files from their local device, then click up arrow button to summarize the content of the uploaded file.
• Summarizing Text via Pasting: Paste the text to be summarized into the text box, then click up arrow button to produce a condensed summary of the content, which will be displayed in the new page
• Scroll to Bottom: The summarized content will automatically scroll to the bottom.

⁠Screen Shot

⁠🛠️ Get it Running

1. Clone the repo.

2. cd command to the current folder.

3. create a .env file and add the following variables and values.

    VITE_BACKEND_SERVICE_ENDPOINT_CHATQNA=""
    VITE_DATAPREP_DELETE_FILE_ENDPOINT=""
    VITE_BACKEND_SERVICE_ENDPOINT_CODEGEN=""
    VITE_BACKEND_SERVICE_ENDPOINT_DOCSUM=""
    VITE_DATAPREP_SERVICE_ENDPOINT=""
    VITE_DATAPREP_GET_FILE_ENDPOINT=""
    VITE_CHAT_HISTORY_CREATE_ENDPOINT=""
    VITE_CHAT_HISTORY_DELETE_ENDPOINT=""
    VITE_CHAT_HISTORY_GET_ENDPOINT=""
    VITE_PROMPT_SERVICE_GET_ENDPOINT=""
    VITE_PROMPT_SERVICE_CREATE_ENDPOINT=""
    VITE_PROMPT_SERVICE_DELETE_ENDPOINT=""
    VITE_KEYCLOAK_SERVICE_ENDPOINT=""
    VITE_PROMPT_COLLECTION_NAME="prompt"
   

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4. There is models_config.json file under public folder. It is in the below format. The types key in the below json array shows that the model is used for following types.

     [
   
         {
             "model_name": "Intel/neural-chat-7b-v3-3",
             "displayName": "Intel Neural Chat",
             "minToken": 100,
             "maxToken": 2000,
             "types": [
                 "chat",
                 "summary",
                 "code"
             ]
         }
   
     ]
   

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5. Execute npm install to install the corresponding dependencies.

6. Execute npm run dev

7. open http://localhost:5174⁠ in browser to the see the UI