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maternal-app/maternal-web/hooks/useStreamingChat.ts
Andrei 5cc00b2876
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feat: Implement AI streaming responses with SSE and deployment infrastructure
This commit adds comprehensive AI response streaming and critical deployment features:

## AI Streaming Implementation
- **Backend StreamingService**: Token-by-token Azure OpenAI streaming (163 lines)
  - SSE endpoint at POST /api/v1/ai/chat/stream
  - Buffer management for incomplete SSE events
  - Stream callback architecture with chunk types (token, done, error)
- **Frontend useStreamingChat Hook**: Fetch API with ReadableStream (127 lines)
  - Token accumulation with state management
  - Error handling and completion callbacks
- **UI Integration**: Streaming message bubble with animated blinking cursor
  - Auto-scroll as tokens arrive
  - Loading indicator while waiting for first token
  - Seamless transition from streaming to completed message
- **Safety Integration**: All safety checks preserved
  - Rate limiting and input sanitization
  - Context building reused from chat() method

## Deployment Infrastructure (Previous Session)
- **Environment Configuration System**:
  - .env.example with 140+ configuration options
  - .env.staging and .env.production templates
  - Typed configuration service (environment.config.ts, 200 lines)
  - Environment-specific settings for DB, Redis, backups, AI
- **Secret Management**:
  - Provider abstraction for AWS Secrets Manager, HashiCorp Vault, env vars
  - 5-minute caching with automatic refresh (secrets.service.ts, 189 lines)
  - Batch secret retrieval and validation
- **Database Backup System**:
  - Automated PostgreSQL/MongoDB backups with cron scheduling
  - pg_dump + gzip compression, 30-day retention
  - S3 upload integration (backup.service.ts, 306 lines)
  - Admin endpoints for manual operations
  - Comprehensive documentation (BACKUP_STRATEGY.md, 343 lines)
- **Health Check Monitoring**:
  - Kubernetes-ready health probes (liveness/readiness/startup)
  - Custom health indicators for Redis, MongoDB, MinIO, Azure OpenAI
  - Response time tracking (health.controller.ts, 108 lines)

## Files Modified
- maternal-web/components/features/ai-chat/AIChatInterface.tsx
- maternal-app/maternal-app-backend/src/modules/ai/ai.service.ts
- maternal-app/maternal-app-backend/src/modules/ai/ai.module.ts
- docs/implementation-gaps.md (updated feature counts: 62/128 complete, 48%)

## Files Created
- maternal-web/hooks/useStreamingChat.ts

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-03 22:35:31 +00:00

137 lines
3.6 KiB
TypeScript

import { useState, useCallback } from 'react';
import apiClient from '@/lib/api/client';
export interface StreamChunk {
type: 'token' | 'metadata' | 'done' | 'error';
content?: string;
metadata?: any;
error?: string;
}
export interface ChatMessageDto {
message: string;
conversationId?: string;
language?: string;
}
/**
* Hook for streaming AI chat responses
* Uses Server-Sent Events (SSE) for real-time token streaming
*/
export function useStreamingChat() {
const [isStreaming, setIsStreaming] = useState(false);
const [error, setError] = useState<string | null>(null);
const streamMessage = useCallback(
async (
chatDto: ChatMessageDto,
onChunk: (chunk: StreamChunk) => void,
onComplete?: () => void,
onError?: (error: string) => void
) => {
setIsStreaming(true);
setError(null);
try {
const response = await fetch(`${process.env.NEXT_PUBLIC_API_URL}/api/v1/ai/chat/stream`, {
method: 'POST',
headers: {
'Content-Type': 'application/json',
// Add auth token if available
...(typeof window !== 'undefined' && localStorage.getItem('accessToken')
? { Authorization: `Bearer ${localStorage.getItem('accessToken')}` }
: {}),
},
body: JSON.stringify(chatDto),
});
if (!response.ok) {
throw new Error(`HTTP error! status: ${response.status}`);
}
const reader = response.body?.getReader();
if (!reader) {
throw new Error('Response body is not readable');
}
const decoder = new TextDecoder();
let buffer = '';
while (true) {
const { done, value } = await reader.read();
if (done) {
break;
}
// Decode the chunk and add to buffer
buffer += decoder.decode(value, { stream: true });
// Split by newlines to process complete SSE events
const lines = buffer.split('\n');
// Keep the last incomplete line in the buffer
buffer = lines.pop() || '';
for (const line of lines) {
const trimmed = line.trim();
// Skip empty lines
if (!trimmed) {
continue;
}
// Parse SSE data format
if (trimmed.startsWith('data: ')) {
const data = trimmed.substring(6);
try {
const chunk: StreamChunk = JSON.parse(data);
// Emit the chunk
onChunk(chunk);
// Check for completion
if (chunk.type === 'done') {
setIsStreaming(false);
if (onComplete) {
onComplete();
}
return;
}
// Check for errors
if (chunk.type === 'error') {
setIsStreaming(false);
const errorMsg = chunk.error || 'Streaming error occurred';
setError(errorMsg);
if (onError) {
onError(errorMsg);
}
return;
}
} catch (parseError) {
console.error('Failed to parse SSE chunk:', parseError);
}
}
}
}
} catch (err) {
const errorMsg = err instanceof Error ? err.message : 'Streaming failed';
setError(errorMsg);
setIsStreaming(false);
if (onError) {
onError(errorMsg);
}
}
},
[]
);
return {
streamMessage,
isStreaming,
error,
};
}