# Plan: Show Extracted Questions Immediately (Streaming Query Response)

## Problem

On the LTT page, when a user submits a question like "what is power of project manager", the "Extracted Questions" section only appears after **all three LLM calls** complete:

1. **QueryDecomposer** (LLM #1) → `extracted_questions` — **available here**
2. **RelevanceFilter** (LLM #2) → filtered chunks
3. **ResponseGeneration** (LLM #3) → final answer

The user must wait 10-30+ seconds (depending on LLM latency) before seeing the extracted sub-questions, even though they are produced in the first ~3-5 seconds.

## Root Cause

The backend `/query` endpoint is a single synchronous HTTP call that awaits all pipeline steps before returning the complete `QueryResponse`. The frontend's `useMutation` receives the entire response at once.

## Objective

Show `extracted_questions` to the user **as soon as the first LLM call completes**, while the remaining pipeline steps continue in the background. The user sees:
1. Extracted questions immediately (after LLM #1)
2. A loading indicator for the answer (while LLM #2 and #3 run)
3. The final answer and sources when complete

## Recommended Approach: SSE Streaming

Convert the `/query` endpoint to use **Server-Sent Events (SSE)** — the industry-standard pattern for streaming LLM responses. This requires changes to both backend and frontend.

### Why SSE (not WebSocket or separate endpoint)

| Approach | Pros | Cons | Verdict |
|----------|------|------|---------|
| **SSE Streaming** | Single connection, automatic reconnect, HTTP-based, simple JSON lines | One-directional (server→client only) | ✅ **Best fit** — we only need server→client |
| **WebSocket** | Bidirectional, lower overhead | Overkill for this use case, more complex | ❌ Unnecessary complexity |
| **Separate `/decompose` endpoint** | Minimal backend change | Two HTTP round-trips, awkward UX (submit twice), harder to maintain state | ❌ Poor UX, more frontend complexity |

## Backend Changes

### 1. New Streaming Response Models

**File**: `backend/app/models/query.py`

Add a `StreamingQueryEvent` union type for SSE events:

```python
from pydantic import BaseModel
from typing import Literal, Union

class DecomposedEvent(BaseModel):
    phase: Literal["decomposed"]
    extracted_questions: list[str]

class RetrievingEvent(BaseModel):
    phase: Literal["retrieving"]

class FilteringEvent(BaseModel):
    phase: Literal["filtering"]

class CompletedEvent(BaseModel):
    phase: Literal["completed"]
    answer: str
    sources: list[SourceMetadata]

class ErrorEvent(BaseModel):
    phase: Literal["error"]
    message: str

StreamingQueryEvent = Union[
    DecomposedEvent, RetrievingEvent, FilteringEvent, 
    CompletedEvent, ErrorEvent
]
```

### 2. Streaming Query Endpoint

**File**: `backend/app/routers/query.py`

Convert `/query` to return `StreamingResponse` with `text/event-stream`:

```python
from fastapi.responses import StreamingResponse
import json

async def _query_stream(request: QueryRequest):
    """Generator that yields SSE events for the query pipeline."""
    settings = get_settings()
    
    try:
        llm_client = LLMClient(settings)
        rag = RAGService(llm_client=llm_client, settings=settings)
        
        # Step 1: Decompose (LLM #1)
        decomposer = QueryDecomposer(llm_client)
        extracted_questions = await decomposer.decompose(request.question)
        yield f"data: {json.dumps({'phase': 'decomposed', 'extracted_questions': extracted_questions})}\n\n"
        
        # Step 2: Retrieve (ChromaDB)
        yield f"data: {json.dumps({'phase': 'retrieving'})}\n\n"
        chunks = rag.retrieve(extracted_questions, n_results=settings.retrieval_n_results)
        
        if not chunks:
            yield f"data: {json.dumps({'phase': 'completed', 'answer': NO_RESULTS_ANSWER, 'sources': []})}\n\n"
            return
        
        # Step 3: Filter (LLM #2)
        yield f"data: {json.dumps({'phase': 'filtering'})}\n\n"
        chunks_for_filter = [(text, meta) for text, meta, _dist in chunks]
        relevance_filter = RelevanceFilter(llm_client)
        filtered = await relevance_filter.filter(
            request.question, chunks_for_filter, threshold=settings.relevance_threshold
        )
        
        if not filtered:
            yield f"data: {json.dumps({'phase': 'completed', 'answer': NO_RESULTS_ANSWER, 'sources': []})}\n\n"
            return
        
        # Step 4: Generate (LLM #3)
        chunk_texts = [chunk for chunk, _meta in filtered]
        chunk_metadata = [meta for _chunk, meta in filtered]
        answer = await rag.generate_response(request.question, chunk_texts, chunk_metadata)
        
        sources = [
            SourceMetadata(
                filename=meta.get("filename", "unknown"),
                upload_date=meta.get("upload_date", ""),
                content_summary=meta.get("content_summary", ""),
                chunk_index=meta.get("chunk_index", 0),
                page_number=meta.get("page_number"),
                chunk_file_path=meta.get("chunk_file_path"),
            )
            for meta in chunk_metadata
        ]
        
        yield f"data: {json.dumps({'phase': 'completed', 'answer': answer, 'sources': [s.model_dump() for s in sources]})}\n\n"
        
    except Exception as e:
        logger.error("Query stream failed: %s", str(e))
        yield f"data: {json.dumps({'phase': 'error', 'message': str(e)})}\n\n"

@router.post("/query")
async def query(request: QueryRequest):
    if not request.question or not request.question.strip():
        raise HTTPException(status_code=400, detail="Question is required")
    
    return StreamingResponse(
        _query_stream(request),
        media_type="text/event-stream",
    )
```

### 3. Keep Old Endpoint (Backward Compatibility)

Add a new `/query/stream` endpoint and keep the existing `/query` for backward compatibility, or version the API. For simplicity in this plan, we'll replace `/query` but the implementation could support both.

**Decision**: Replace `/query` with streaming. The frontend is the only consumer and will be updated together.

## Frontend Changes

### 1. New Streaming API Client

**File**: `frontend/src/lib/api.ts`

Add a streaming query function:

```typescript
export interface QueryStreamEvent {
  phase: 'decomposed' | 'retrieving' | 'filtering' | 'completed' | 'error'
  extracted_questions?: string[]
  answer?: string
  sources?: SourceMetadata[]
  message?: string
}

export const queryDocumentStream = (
  request: QueryRequest,
  onEvent: (event: QueryStreamEvent) => void,
  onError: (error: Error) => void,
  onComplete: () => void
): (() => void) => {
  const baseUrl = import.meta.env.VITE_API_BASE_URL ?? 'http://localhost:8000/api/v1'
  const url = `${baseUrl}/query`
  
  const eventSource = new EventSource(url, {
    // EventSource doesn't support POST with body natively
    // We need to use fetch + ReadableStream or a polyfill
  })
  
  // ... implementation using fetch + ReadableStream
  
  return () => eventSource.close() // cleanup function
}
```

**Important**: Standard `EventSource` only supports GET, not POST. We need to use `fetch()` with `ReadableStream` to POST the question and read SSE events.

```typescript
export const queryDocumentStream = async (
  request: QueryRequest,
  onEvent: (event: QueryStreamEvent) => void
): Promise<void> => {
  const baseUrl = import.meta.env.VITE_API_BASE_URL ?? 'http://localhost:8000/api/v1'
  const response = await fetch(`${baseUrl}/query`, {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify(request),
  })
  
  if (!response.ok) {
    throw new Error(`HTTP ${response.status}: ${await response.text()}`)
  }
  
  const reader = response.body!.getReader()
  const decoder = new TextDecoder()
  let buffer = ''
  
  while (true) {
    const { done, value } = await reader.read()
    if (done) break
    
    buffer += decoder.decode(value, { stream: true })
    const lines = buffer.split('\n')
    buffer = lines.pop() || ''
    
    for (const line of lines) {
      if (line.startsWith('data: ')) {
        const data = line.slice(6)
        if (data === '[DONE]') return
        onEvent(JSON.parse(data))
      }
    }
  }
}
```

### 2. New React Hook for Streaming

**File**: `frontend/src/lib/queries.tsx`

Add a custom hook that manages streaming state:

```typescript
import { useState, useCallback, useRef } from 'react'

interface QueryStreamState {
  extractedQuestions: string[] | null
  answer: string | null
  sources: SourceMetadata[] | null
  phase: 'idle' | 'decomposing' | 'retrieving' | 'filtering' | 'generating' | 'completed' | 'error'
  error: Error | null
}

export const useQueryDocumentStream = () => {
  const [state, setState] = useState<QueryStreamState>({
    extractedQuestions: null,
    answer: null,
    sources: null,
    phase: 'idle',
    error: null,
  })
  const abortRef = useRef<AbortController | null>(null)
  
  const mutate = useCallback(async (request: QueryRequest) => {
    setState({
      extractedQuestions: null,
      answer: null,
      sources: null,
      phase: 'decomposing',
      error: null,
    })
    
    abortRef.current = new AbortController()
    
    try {
      await queryDocumentStream(request, (event) => {
        switch (event.phase) {
          case 'decomposed':
            setState(prev => ({
              ...prev,
              extractedQuestions: event.extracted_questions!,
              phase: 'retrieving',
            }))
            break
          case 'retrieving':
            setState(prev => ({ ...prev, phase: 'retrieving' }))
            break
          case 'filtering':
            setState(prev => ({ ...prev, phase: 'filtering' }))
            break
          case 'completed':
            setState(prev => ({
              ...prev,
              answer: event.answer!,
              sources: event.sources!,
              phase: 'completed',
            }))
            break
          case 'error':
            setState(prev => ({
              ...prev,
              phase: 'error',
              error: new Error(event.message!),
            }))
            break
        }
      })
    } catch (err) {
      setState(prev => ({
        ...prev,
        phase: 'error',
        error: err instanceof Error ? err : new Error(String(err)),
      }))
    }
  }, [])
  
  const reset = useCallback(() => {
    abortRef.current?.abort()
    setState({
      extractedQuestions: null,
      answer: null,
      sources: null,
      phase: 'idle',
      error: null,
    })
  }, [])
  
  return { ...state, mutate, reset }
}
```

### 3. Update LTTPage to Use Streaming

**File**: `frontend/src/pages/LTTPage.tsx`

Replace `useQueryDocument` with `useQueryDocumentStream`:

```typescript
const queryStream = useQueryDocumentStream()

const handleQuerySubmit = (question: string) => {
  queryStream.mutate({ question })
}

// In JSX:
<ExtractedQuestionsDisplay
  extractedQuestions={queryStream.extractedQuestions}
  isLoading={queryStream.phase === 'decomposing'}
/>

<ResponsePanel
  answer={queryStream.answer}
  sources={queryStream.sources}
  isLoading={queryStream.phase === 'retrieving' || queryStream.phase === 'filtering' || queryStream.phase === 'generating'}
  extractedQuestions={queryStream.extractedQuestions}
/>
```

### 4. Update ExtractedQuestionsDisplay

**File**: `frontend/src/components/ExtractedQuestionsDisplay.tsx`

The component should already work with the new state shape. Ensure it handles the case where `extractedQuestions` is available but `answer` is still loading:

```typescript
// Show questions as soon as they arrive, even if answer is still loading
if (extractedQuestions && extractedQuestions.length > 0) {
  return (
    <div>
      <h3>Extracted Questions:</h3>
      <ol>
        {extractedQuestions.map((q, i) => <li key={i}>{q}</li>)}
      </ol>
    </div>
  )
}
```

### 5. Update ResponsePanel Loading States

**File**: `frontend/src/components/ResponsePanel.tsx`

Show different loading states based on phase:
- `phase === 'retrieving'`: "Searching documents..."
- `phase === 'filtering'`: "Filtering relevant passages..."
- `phase === 'generating'`: "Generating answer..."

## Implementation Order

1. **Backend streaming endpoint** (`backend/app/routers/query.py`)
   - Add `_query_stream()` generator
   - Update `/query` to return `StreamingResponse`
   - Test with `curl` to verify SSE format

2. **Frontend streaming API** (`frontend/src/lib/api.ts`)
   - Add `queryDocumentStream()` function
   - Add `QueryStreamEvent` type

3. **Frontend streaming hook** (`frontend/src/lib/queries.tsx`)
   - Add `useQueryDocumentStream()` hook

4. **Update LTTPage** (`frontend/src/pages/LTTPage.tsx`)
   - Replace `useQueryDocument` with `useQueryDocumentStream`
   - Wire up new state to components

5. **Update ResponsePanel** (`frontend/src/components/ResponsePanel.tsx`)
   - Add phase-aware loading messages

6. **Tests**
   - Mock `fetch` with `ReadableStream` for testing
   - Test each phase transition
   - Test error handling

## Testing Strategy

### Backend Tests
- Test SSE event format matches expected JSON structure
- Test each phase event is emitted in correct order
- Test error events on failures
- Test early exit (no chunks) still emits `decomposed` then `completed`

### Frontend Tests
- Mock `fetch` to return a `ReadableStream` with SSE data
- Test `useQueryDocumentStream` state transitions:
  - idle → decomposing → decomposed (extractedQuestions set) → retrieving → filtering → completed (answer set)
- Test error handling: stream emits error event → state.error set
- Test abort: calling reset() aborts in-flight request

## Risks & Mitigations

| Risk | Mitigation |
|------|-----------|
| SSE not supported by older browsers | Use fetch + ReadableStream (works in all modern browsers) |
| Proxy/CDN buffering SSE | Set `X-Accel-Buffering: no` header, use `Cache-Control: no-cache` |
| CORS with streaming | Ensure `Access-Control-Allow-Origin` includes frontend origin |
| Connection drops mid-stream | Add retry logic or show "Connection lost" message |
| TanStack Query cache invalidation | Not needed — streaming bypasses cache, keep old `useQueryDocument` for non-streaming use |

## Files to Modify

| File | Change |
|------|--------|
| `backend/app/models/query.py` | Add streaming event models |
| `backend/app/routers/query.py` | Convert to StreamingResponse |
| `frontend/src/lib/api.ts` | Add `queryDocumentStream()` |
| `frontend/src/lib/queries.tsx` | Add `useQueryDocumentStream()` hook |
| `frontend/src/pages/LTTPage.tsx` | Use streaming hook |
| `frontend/src/components/ResponsePanel.tsx` | Phase-aware loading states |

## Success Criteria

- [ ] Extracted questions appear within 5 seconds of submitting a query
- [ ] Answer appears when generation completes (no UI blocking)
- [ ] Loading states clearly indicate which pipeline step is running
- [ ] Error handling works (shows error message if any step fails)
- [ ] All existing tests pass (or are updated for new behavior)
- [ ] New tests cover streaming state transitions