Thinh Lam
142 lines
3.8 KiB
Markdown
142 lines
3.8 KiB
Markdown
# Chat Assistant - Backend Integration
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## Overview
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The ChatAssistant component has been successfully integrated with the backend Ollama service to enable real-time policy question answering and content verification.
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## What Was Done
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### 1. Created Chat Feature Module
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Following the new frontend architecture, a complete chat feature module was created:
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- **Types** (`features/chat/types/chat.types.ts`): TypeScript types for messages and API requests
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- **Service** (`features/chat/services/chatService.ts`): API service for chat operations
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- **Hooks** (`features/chat/hooks/useChat.ts`): React hooks for chat functionality
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### 2. Updated ChatAssistant Component
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The `ChatAssistant` component now:
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- ✅ Connects to backend Ollama API (`/test_ollama_1` endpoint)
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- ✅ Sends real questions to the AI model
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- ✅ Displays AI responses in real-time
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- ✅ Handles verification requests from forms
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- ✅ Shows loading states during API calls
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- ✅ Displays error messages if API calls fail
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- ✅ Maintains conversation history
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## API Endpoint
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The chat uses the backend endpoint:
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- **URL**: `POST /test_ollama_1`
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- **Request Body**: `{ "prompt": "user question" }`
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- **Response**: `{ "oss_json": "AI response text" }`
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## Features
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### 1. Policy Question Answering
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Users can ask questions about:
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- IT governance policies
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- Compliance requirements
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- Regulatory standards
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- Workflow processes
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**Example questions:**
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- "What are the requirements for ISO 27001 compliance?"
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- "How do I submit a workflow approval?"
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- "What documents are needed for compliance verification?"
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### 2. Content Verification
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When users click "Verify" on form fields, the assistant:
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- Analyzes the content against compliance requirements
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- Provides feedback on whether it meets requirements
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- Suggests improvements
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- Identifies potential issues
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### 3. Real-time Responses
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- Loading indicators while waiting for AI response
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- Error handling with user-friendly messages
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- Conversation history maintained in the chat
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## Usage
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The ChatAssistant is already integrated in the Dashboard. Users can:
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1. **Ask Questions**: Type questions in the chat input and press Enter
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2. **Verify Content**: Click "Verify" buttons on form fields to get AI feedback
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3. **View History**: Scroll through previous messages
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## Configuration
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The API URL is configured in:
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- **File**: `src/shared/config/env.ts`
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- **Environment Variable**: `VITE_API_URL`
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- **Default**: `http://localhost:4402`
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To change the API URL, update the `.env` file:
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```env
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VITE_API_URL=http://your-backend-url:4402
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```
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## Backend Requirements
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Ensure the backend is running and accessible:
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1. Backend service should be running on port 4402
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2. Ollama service should be running and accessible
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3. The `/test_ollama_1` endpoint should be available
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## Testing
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To test the integration:
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1. Start the backend:
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```bash
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cd be0
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docker-compose up be0
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```
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2. Start the frontend:
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```bash
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cd fe0
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npm run dev
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```
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3. Open the Dashboard and try:
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- Asking a question about policies
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- Verifying form content
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## Troubleshooting
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### Issue: "Failed to get response from assistant"
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**Solutions:**
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- Check if backend is running: `curl http://localhost:4402/health`
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- Check browser console for detailed error messages
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- Verify `VITE_API_URL` in `.env` file
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### Issue: "Network error"
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**Solutions:**
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- Ensure backend is accessible at the configured URL
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- Check CORS settings in backend
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- Verify network connectivity
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### Issue: Slow responses
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**Solutions:**
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- Ollama model might be loading (first request)
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- Check backend logs for errors
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- Verify Ollama service is running
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## Next Steps
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Potential improvements:
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1. Add streaming responses for real-time text generation
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2. Add conversation context/memory
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3. Add support for document uploads
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4. Add voice input/output
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5. Add response rating/feedback
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