sciagent/fe0/CHAT_INTEGRATION.md

Chat Assistant - Backend Integration

Overview

The ChatAssistant component has been successfully integrated with the backend Ollama service to enable real-time policy question answering and content verification.

What Was Done

1. Created Chat Feature Module

Following the new frontend architecture, a complete chat feature module was created:

• Types (features/chat/types/chat.types.ts): TypeScript types for messages and API requests
• Service (features/chat/services/chatService.ts): API service for chat operations
• Hooks (features/chat/hooks/useChat.ts): React hooks for chat functionality

2. Updated ChatAssistant Component

The ChatAssistant component now:

• ✅ Connects to backend Ollama API (/test_ollama_1 endpoint)
• ✅ Sends real questions to the AI model
• ✅ Displays AI responses in real-time
• ✅ Handles verification requests from forms
• ✅ Shows loading states during API calls
• ✅ Displays error messages if API calls fail
• ✅ Maintains conversation history

API Endpoint

The chat uses the backend endpoint:

• URL: POST /test_ollama_1
• Request Body: { "prompt": "user question" }
• Response: { "oss_json": "AI response text" }

Features

1. Policy Question Answering

Users can ask questions about:

• IT governance policies
• Compliance requirements
• Regulatory standards
• Workflow processes

Example questions:

• "What are the requirements for ISO 27001 compliance?"
• "How do I submit a workflow approval?"
• "What documents are needed for compliance verification?"

2. Content Verification

When users click "Verify" on form fields, the assistant:

• Analyzes the content against compliance requirements
• Provides feedback on whether it meets requirements
• Suggests improvements
• Identifies potential issues

3. Real-time Responses

• Loading indicators while waiting for AI response
• Error handling with user-friendly messages
• Conversation history maintained in the chat

Usage

The ChatAssistant is already integrated in the Dashboard. Users can:

1. Ask Questions: Type questions in the chat input and press Enter
2. Verify Content: Click "Verify" buttons on form fields to get AI feedback
3. View History: Scroll through previous messages

Configuration

The API URL is configured in:

• File: src/shared/config/env.ts
• Environment Variable: VITE_API_URL
• Default: http://localhost:4402

To change the API URL, update the .env file:

VITE_API_URL=http://your-backend-url:4402

Backend Requirements

Ensure the backend is running and accessible:

1. Backend service should be running on port 4402
2. Ollama service should be running and accessible
3. The /test_ollama_1 endpoint should be available

Testing

To test the integration:

1. Start the backend:

   cd be0
   docker-compose up be0
   

2. Start the frontend:

   cd fe0
   npm run dev
   

3. Open the Dashboard and try:

   • Asking a question about policies
   • Verifying form content

Troubleshooting

Issue: "Failed to get response from assistant"

Solutions:

• Check if backend is running: curl http://localhost:4402/health
• Check browser console for detailed error messages
• Verify VITE_API_URL in .env file

Issue: "Network error"

Solutions:

• Ensure backend is accessible at the configured URL
• Check CORS settings in backend
• Verify network connectivity

Issue: Slow responses

Solutions:

• Ollama model might be loading (first request)
• Check backend logs for errors
• Verify Ollama service is running

Next Steps

Potential improvements:

1. Add streaming responses for real-time text generation
2. Add conversation context/memory
3. Add support for document uploads
4. Add voice input/output
5. Add response rating/feedback