- Backend: add stop_after_decompose flag to QueryRequest, early-return
after decomposition in SSE stream with half_question:true event
- Frontend: add decomposeOnly method to useQueryDocumentStream hook
- QueryInput: remove grey italic from ASR partial text, rename Submit
to Final Submit, add gray Half Question button that decomposes
without clearing querybox text
- LTTPage: wire handleHalfQuestion to decomposeOnly
Reverts commits 284028b through b4096d6. Phase 4 (System Audio Capture)
will replace the YouTube use case with a more versatile getDisplayMedia approach.
Removed: YouTube router, HLS proxy, YouTubeService, YouTubeInput,
YouTubeVideoPlayer, useYouTubeASR hook, all Phase 3 tests, hls.js dep,
YouTube config fields, YouTube README/plan sections.
Modified files restored to pre-Phase-3 state: LTTPage (no source toggle),
api.ts (no YouTube extract), types (no YouTube types), config.py (no
youtube fields), main.py (no YouTube router), requirements.txt (no yt-dlp),
.env.example (no YouTube vars), package.json (no hls.js).
Relevant Phase 2 code preserved: ws_asr.py (unchanged), useVideoASR,
VideoPlayer, VideoUpload, QueryInput, Full Transcript.
Replace full_text responses with character-level deltas computed from
DashScope's monotonically-growing 'text' field. Stash-only events (empty
text) are skipped; trailing stash chars sent alongside deltas and
appended on pause to complete final sentences.
Backend:
- Delta = text[len(prev_text):] — simple suffix diff, no merge logic
- Track item_id for utterance boundaries, prepend space separator
- Send stash alongside delta for frontend pause handler
Frontend:
- Accumulate deltas locally (transcriptRef += msg.delta)
- Store lastStashRef from each message
- On pause: append stash to text, fire onFinalTranscript
Plan: .plans/phase2_enhancement_delta_sse.md updated to Complete
DashScope stashes are ~7-char rolling windows, not cumulative. Each partial
event replaces the previous. Completed events rarely sent. This caused text to
jump/replace during streaming and disappear on pause.
Backend:
- Add _merge_stash() — finds overlapping suffix between successive stashes
and appends only new characters, reconstructing full utterance from partials
- format_transcription_event returns raw stash for read_events to merge
- read_events maintains partial_buffer via _merge_stash, clears on completed
- Guard against empty/whitespace-only stashes
Frontend:
- transcriptRef + onFinalTranscriptRef avoid stale closures in pause handler
- stopStreaming fires onFinalTranscript(currentText) before clearing partial
- Removed blind setPartialTranscript('') that erased text on pause
Tests: 16/16 ws_protocol tests pass, frontend tests unchanged
Plan: Updated phase2_implementation_plan.md to Complete with 11-bug log
- Add DashScope ASR and video upload config fields to Settings
- Create Pydantic models (video.py, asr.py)
- Create VideoService with validation, save, serve, delete
- Create ASR client stub with float32_to_s16le utility
- Implement POST /api/v1/video/upload with streaming validation
- Implement GET /api/v1/video/{video_id} with FileResponse
- Create WebSocket ASR endpoint stub
- Register new routers in main.py
- Update .env.example and requirements.txt
- Add reference examples for DashScope integration
- 8 tests passing (3 config + 5 video upload)
QueryDecomposer now uses LLMClientDP (Deepseek) while RelevanceFilter and RAGService continue using LLMClient (OpenRouter/vLLM).
Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-openagent)
Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai>
- POST /api/v1/v2/highlights/batch: compute and cache highlights for cited chunks
- GET /api/v1/v2/highlights: serve cached highlighted HTML pages
- chunks.py router registered in main.py
- Dynamic DB path computation (prompts.db -> highlights.db), no Settings changes
- 7 endpoint tests: POST 200/422, GET 200/404, mock service verification
DOCX and TXT ingestion now produces chunk_file_path + per-chunk PDF files matching the PDF ingestion flow. Uses reportlab to render chunk text as simple PDFs with automatic text wrapping.
- Add reportlab==4.2.5 to requirements.txt
- New utils/text_to_pdf.py: generate_text_pdf() renders chunk text as PDF
- Ingest router DOCX/TXT branches: generate chunk_N.pdf per chunk, store in chunk_file_paths
- Graceful degradation: chunk_file_path stays None if PDF generation fails
- Update test_phase1_ingest_page_aware.py assertions: DOCX chunks now HAVE chunk_file_path
- New test_phase5_docx_pdf_generation.py: 5 tests (DOCX PDF gen, TXT PDF gen, PDF regression, file count, graceful degradation)
- 361 backend tests pass (4 pre-existing embedding failures unrelated)
Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai>
Break the hardcoded per-sub-q filter prompt into 3 editable PromptService templates (filter_intro, filter_section, filter_outro) with placeholders for the for-loop iteration pattern. Refactor RelevanceFilter._build_per_subq_prompt() to compose them at runtime, falling back to built-in defaults when PromptService is unavailable.
Fix two latent bugs from Package 4:
- generate_per_subq was called by rag.py but never added to _VALID_STEPS or DB seed (would ValueError at runtime)
- _SEED_GENERATE placeholder mismatch: flat generate_response() expects {question}/{context} but Package 4 changed it to {context_sections}. Restored flat template; generate_per_subq now holds {context_sections}.
Add database backfill migration in seed_default_profiles() to INSERT OR IGNORE missing steps into existing profile rows, ensuring all 7 steps exist on restart.
Restructure System Prompts UI: remove unused flat filter/generate steps, replace with Step 2.1-2.3 (filter_intro/section/outro) and Step 3 (generate_per_subq). Update PlaceholderDocs with {context_sections}, {subq_idx}, {subq_question}.
Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-openagent)
Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai>
Restructure _query_stream() to use per-sub-question retrieval, filtering, and generation. Add generative_subquestion SSE events for progressive frontend rendering. Add format_chunks_retrieved_per_subq() and format_chunks_filtered_per_subq() with <sub_q> XML wrappers. Add empty decomposition fallback using original question as single sub-q. Update history recording for grouped sources JSON (list-of-lists format).
Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-openagent)
Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai>
Convert /query endpoint from synchronous JSON to Server-Sent Events (SSE)
streaming. The frontend now receives extracted_questions as soon as the
first LLM call completes, without waiting for retrieval, filtering, and
answer generation.
Backend:
- Add StreamingQueryEvent union type (Decomposed, Retrieving, Filtering,
Generating, Completed, Error)
- Convert /query to return StreamingResponse with SSE format
- Yield events after each pipeline phase
Frontend:
- Add queryDocumentStream() using fetch + ReadableStream
- Add useQueryDocumentStream() hook with phase-aware state
- Update LTTPage to use streaming instead of mutation
- Update ResponsePanel to show phase messages (Searching documents...,
Filtering passages..., Generating answer...)
- Update ExtractedQuestionsDisplay to accept null
Tests:
- Update query_flow e2e test to mock queryDocumentStream
- 84/85 tests pass (1 pre-existing failure from removed file-input)
Change QueryDecomposer prompt to generate 2-5 sub-questions instead of keywords. Rename API field from keywords to extracted_questions across models, service, and router.
Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-openagent)
Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai>
- Add page_number and chunk_file_path to SourceMetadata model and query router
- Add GET /chunks/{file_path}/pdf endpoint with path traversal protection
- Add View PDF links in ResponsePanel source cards and ChunkList component
- Update TypeScript types and API helper for chunk PDF URLs
- Add backend tests (5) and frontend ChunkList tests (7)
- Update enhancement plan: all 3 features complete
Delete document endpoint now removes associated chunk PDF files from document_chunk/ before ChromaDB deletion. Delete chunk endpoint removes individual chunk PDF. Missing files logged as warnings, not errors.
Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-openagent)
Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai>
PDF uploads now use parse_pdf_by_page() -> chunk_pages() -> extract page PDFs -> enhanced metadata with page_number, chunk_file_path, and document_id. Same-filename replacement deletes old chunks and PDFs before re-ingest. DOCX/TXT keep original flat flow with document_id added. RAGService.ingest_document() accepts optional document_id parameter.
Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-openagent)
Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai>
When uploading files, the backend passes them through NamedTemporaryFile, causing os.path.basename to return temp names like 'tmp90i7xqa8.pdf'. Added original_filename parameter to extract_metadata() so the actual upload filename is stored.
Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-openagent)
Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai>
Add 4 REST endpoints for RAG database management: GET /documents, GET /documents/{id}/chunks, DELETE /documents/{id}, DELETE /chunks/{id}. Register documents router in main.py. 8 unit tests covering all CRUD operations.
Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-openagent)
Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai>
Woody