# 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:
```env
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:
   ```bash
   cd be0
   docker-compose up be0
   ```

2. Start the frontend:
   ```bash
   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