momentry_core/note.md

Chat History - 2026-03-18

User Request

User asked to:

1. Review files in ./docs directory related to API documentation
2. Save chat history to note.md

Files Reviewed

1. API_REFERENCE.md

• Base URL: http://localhost:3002/api/v1
• Port 3000 is used by Gitea, API runs on 3002

Endpoints:

Method	Endpoint	Description
POST	/api/v1/register	Register a video file
GET	/api/v1/progress/:uuid	Get real-time processing progress via Redis
POST	/api/v1/search	Natural language search using RAG
GET	/api/v1/lookup	Lookup video UUID by path or get video details
GET	/api/v1/videos	List all registered videos

Processor Status Values:

• pending - Not started
• info - Starting/info message
• progress - In progress
• complete - Finished
• error - Failed

2. CHUNK_DESIGN.md

Design Principles:

• Dual UUID system (external_uuid + internal id)
• Internal tables use videos.id (4 bytes) instead of uuid (32 bytes) for space efficiency

Database Tables:

• videos - File mapping table with internal ID
• pre_chunks - Pre-processed chunks from ASR, CUT, TIME, YOLO trace
• frames - Single image recognition results (YOLO, OCR, Face per frame)
• chunks - Final chunks after combination rules
• chunk_vectors - Vector embeddings

Combination Rules:

• Rule 1 (Direct): pre_chunk → chunk
• Rule 2 (Enrich): pre_chunk + frames → enriched chunk

3. CHUNK_SPEC.md

Chunk Types:

Type	Description	Can Overlap
Sentence	Speech recognition segments	Yes
Cut	Scene detection segments	Yes
TimeBased	Fixed duration segments (default 10s)	Yes

Time Coordinate System:

• All times in seconds (float with microsecond precision)
• Frame calculation: frame_number = floor(time_in_seconds * fps)

Chunk ID Format: {chunk_type}_{chunk_index:04}

• Examples: sentence_0001, cut_0002, time_based_0015

Processors:

Processor	Model	Description
ASR	WhisperX (faster-whisper)	Speech recognition
CUT	PySceneDetect	Scene detection
YOLO	YOLOv8n	Object detection
OCR	EasyOCR	Text recognition
Face	OpenCV Haar Cascade	Face detection
Pose	YOLOv8n-Pose	Pose estimation

4. SERVICES.md

Core Services:

Service	Port	Purpose
PostgreSQL	5432	Video metadata storage
Redis	6379	Cache and job queue
Ollama	11434	Local LLM inference
n8n	5678/5690	Workflow automation
Qdrant	6333	Vector database
Gitea	3000	Git service
Momentry API	3002	Rust API server

Notes

• Chat history saved to note.md
• User may want to continue with API implementation, code review, or new features