sciagent code + Gitea Actions CI/CD

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

be0/CHAT_ASSISTANT_README.md

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+# Chat Assistant Module
+
+## Overview
+
+The Chat Assistant module provides a conversational AI interface for answering policy and compliance questions using Ollama.
+
+## Architecture
+
+### Backend (`be0/src/chat_assistant.py`)
+
+The `ChatAssistant` class provides:
+- **Chat functionality**: Conversational AI for policy questions
+- **Content verification**: Verify content against compliance requirements
+- **Policy Q&A**: Answer questions about policies and compliance
+
+### Frontend (`fe0/src/features/chat/`)
+
+The frontend chat feature includes:
+- **Service layer**: API communication with backend
+- **React hooks**: Easy-to-use hooks for chat functionality
+- **Type definitions**: TypeScript types for type safety
+
+## API Endpoints
+
+### 1. Chat Endpoint
+```
+POST /api/v1/chat
+```
+
+**Request Body:**
+```json
+{
+  "message": "What are ISO 27001 requirements?",
+  "conversation_history": [
+    {
+      "role": "user",
+      "content": "Previous message"
+    },
+    {
+      "role": "assistant",
+      "content": "Previous response"
+    }
+  ],
+  "context": "Optional context about policies"
+}
+```
+
+**Response:**
+```json
+{
+  "message": "ISO 27001 is an information security management system...",
+  "model": "gemma3:27b",
+  "tokens_used": 150
+}
+```
+
+### 2. Verify Content Endpoint
+```
+POST /api/v1/chat/verify
+```
+
+**Form Data:**
+- `field_name`: Name of the field being verified
+- `content`: Content to verify
+- `verification_criteria`: (Optional) Specific criteria to check
+
+**Response:**
+```json
+{
+  "message": "The content meets compliance requirements...",
+  "model": "gemma3:27b",
+  "tokens_used": 200
+}
+```
+
+### 3. Policy Question Endpoint
+```
+POST /api/v1/chat/question
+```
+
+**Form Data:**
+- `question`: The user's question
+- `policy_context`: (Optional) Context about specific policies
+
+**Response:**
+```json
+{
+  "message": "Answer to the policy question...",
+  "model": "gemma3:27b",
+  "tokens_used": 180
+}
+```
+
+## Features
+
+### 1. Conversational Context
+- Maintains conversation history for context-aware responses
+- Keeps last 10 messages for context
+- System prompt guides the assistant's behavior
+
+### 2. Policy Expertise
+- Specialized in IT governance and compliance
+- Knowledgeable about ISO 27001, NIST, GDPR, etc.
+- Provides accurate, actionable advice
+
+### 3. Content Verification
+- Analyzes content against compliance requirements
+- Provides detailed feedback
+- Suggests improvements
+
+## Usage
+
+### Backend
+
+```python
+from src.chat_assistant import get_chat_assistant
+
+# Get chat assistant instance
+assistant = get_chat_assistant()
+
+# Chat
+request = ChatRequest(
+    message="What is ISO 27001?",
+    context="IT governance"
+)
+response = await assistant.chat(request)
+
+# Verify content
+response = await assistant.verify_content(
+    field_name="Project Description",
+    content="Our project implements security controls..."
+)
+```
+
+### Frontend
+
+```typescript
+import { useChat } from '@/features/chat/hooks/useChat';
+
+const { sendMessage, verifyContent, isLoading } = useChat();
+
+// Send a message
+const response = await sendMessage(
+  "What are compliance requirements?",
+  conversationHistory, // Optional
+  "ISO 27001 context"   // Optional
+);
+
+// Verify content
+const verification = await verifyContent(
+  "Project Name",
+  "Project content to verify"
+);
+```
+
+## Configuration
+
+### Model Selection
+
+The default model is `gemma3:27b`. To change it:
+
+```python
+# In chat_assistant.py
+assistant = ChatAssistant(model_name="your-model-name")
+```
+
+### System Prompt
+
+The system prompt can be customized in the `ChatAssistant.__init__` method to change the assistant's behavior and expertise.
+
+## Logging
+
+All chat interactions are logged to:
+- `be0/logs/ChatAssistant.log`
+
+This helps with debugging and monitoring.
+
+## Error Handling
+
+The module includes comprehensive error handling:
+- Catches and logs all exceptions
+- Returns user-friendly error messages
+- Raises HTTPException for API errors
+
+## Testing
+
+To test the chat assistant:
+
+1. **Start the backend:**
+   ```bash
+   cd be0
+   docker-compose up be0
+   ```
+
+2. **Test via API:**
+   ```bash
+   curl -X POST http://localhost:4402/api/v1/chat \
+     -H "Content-Type: application/json" \
+     -d '{"message": "What is ISO 27001?"}'
+   ```
+
+3. **Test via Frontend:**
+   - Open the Dashboard
+   - Use the ChatAssistant component
+   - Ask questions or verify content
+
+## Integration
+
+The ChatAssistant is integrated with:
+- **ChatAssistant.tsx**: React component in the Dashboard
+- **useChat hook**: React hook for chat functionality
+- **chatService**: API service layer
+
+## Future Enhancements
+
+Potential improvements:
+1. Streaming responses for real-time text generation
+2. Multi-turn conversation management
+3. Document context injection
+4. Voice input/output
+5. Response rating and feedback
+6. Conversation export
+7. Custom model fine-tuning