vision/USAGE.md

Skinbase Vision Stack — Usage Guide

This document explains how to run and use the Skinbase Vision Stack (Gateway + CLIP, BLIP, YOLO, Qdrant, Card Renderer, Maturity services).

Overview

• Services: gateway, clip, blip, yolo, qdrant, qdrant-svc, card-renderer, maturity (FastAPI each, except qdrant which is the official Qdrant DB).
• Gateway is the public API endpoint; the other services are internal.

Model overview

• CLIP: Contrastive Language–Image Pretraining — maps images and text into a shared embedding space. Used for zero-shot image tagging, similarity search, and returning ranked tags with confidence scores.

• BLIP: Bootstrapping Language-Image Pre-training — a vision–language model for image captioning and multimodal generation. BLIP produces human-readable captions (multiple variants supported) and can be tuned with max_length.

• YOLO: You Only Look Once — a family of real-time object-detection models. YOLO returns detected objects with class, confidence, and bbox (bounding box coordinates); use conf to filter low-confidence detections.

• Qdrant: High-performance vector similarity search engine. Stores CLIP image embeddings and enables reverse image search (find similar images). The qdrant-svc wrapper auto-embeds images via CLIP before upserting.

• Card Renderer: Generates branded social-card images (e.g. Open Graph previews) from artwork images. Applies smart center-weighted cropping, gradient overlays, title/username/tag text, and an optional logo. Returns binary image bytes (WebP by default). Template: nova-artwork-v1.

• Maturity: Dedicated NSFW/maturity classifier. Accepts an image and returns a normalized safety signal including maturity_label (safe/mature), confidence, raw score, optional sublabels (e.g. nsfw), and an action_hint (safe, review, flag_high) designed for Nova moderation workflows. Powered by Falconsai/nsfw_image_detection (ViT-based, HuggingFace). Thresholds are configurable via environment variables.

Prerequisites

• Docker Desktop (with docker compose) or a Docker environment.
• Recommended: at least 8GB RAM for CPU-only; more for model memory or GPU use.

Start the stack

Before starting the stack, create a .env file for runtime secrets and environment overrides.

Minimum example:

API_KEY=your_api_key_here
HUGGINGFACE_TOKEN=your_huggingface_token_here

Notes:

• API_KEY protects gateway endpoints.
• HUGGINGFACE_TOKEN is required if the configured BLIP model requires Hugging Face authentication.
• Startup uses container healthchecks, so initial boot can take longer while models download and warm up.

Optional maturity configuration (can be added to .env to override defaults):

MATURITY_MODEL=Falconsai/nsfw_image_detection
MATURITY_THRESHOLD_MATURE=0.80
MATURITY_THRESHOLD_REVIEW=0.60
MATURITY_ENABLED=true

• MATURITY_THRESHOLD_MATURE: score above this → mature + flag_high (default 0.80).
• MATURITY_THRESHOLD_REVIEW: score above this but below mature threshold → mature + review (default 0.60).
• MATURITY_ENABLED: set to false to disable maturity endpoints at the gateway without removing the service.

Run from repository root:

docker compose up -d --build

Stop:

docker compose down

View logs:

docker compose logs -f
docker compose logs -f gateway

Health

Check the gateway health endpoint:

curl https://vision.klevze.net/health

Universal analyze (ALL)

Analyze an image by URL (gateway aggregates CLIP, BLIP, YOLO):

curl -X POST https://vision.klevze.net/analyze/all \
  -H "X-API-Key: <your-api-key>" \
  -H "Content-Type: application/json" \
  -d '{"url":"https://files.skinbase.org/img/aa/bb/cc/md.webp","limit":5}'

File upload (multipart):

curl -X POST https://vision.klevze.net/analyze/all/file \
  -H "X-API-Key: <your-api-key>" \
  -F "file=@/path/to/image.webp" \
  -F "limit=5"

Parameters:

• limit: optional integer to limit returned tag/caption items.

Individual services (via gateway)

These endpoints call the specific service through the gateway.

CLIP — tags

URL request:

curl -X POST https://vision.klevze.net/analyze/clip \
  -H "X-API-Key: <your-api-key>" \
  -H "Content-Type: application/json" \
  -d '{"url":"https://files.skinbase.org/img/aa/bb/cc/md.webp","limit":5}'

File upload:

curl -X POST https://vision.klevze.net/analyze/clip/file \
  -H "X-API-Key: <your-api-key>" \
  -F "file=@/path/to/image.webp" \
  -F "limit=5"

Return: JSON list of tags with confidence scores.

BLIP — captioning

URL request:

curl -X POST https://vision.klevze.net/analyze/blip \
  -H "X-API-Key: <your-api-key>" \
  -H "Content-Type: application/json" \
  -d '{"url":"https://files.skinbase.org/img/aa/bb/cc/md.webp","variants":3}'

File upload:

curl -X POST https://vision.klevze.net/analyze/blip/file \
  -H "X-API-Key: <your-api-key>" \
  -F "file=@/path/to/image.webp" \
  -F "variants=3" \
  -F "max_length=60"

Parameters:

• variants: number of caption variants to return.
• max_length: optional maximum caption length.

Return: one or more caption strings (optionally with scores).

YOLO — object detection

URL request:

curl -X POST https://vision.klevze.net/analyze/yolo \
  -H "X-API-Key: <your-api-key>" \
  -H "Content-Type: application/json" \
  -d '{"url":"https://files.skinbase.org/img/aa/bb/cc/md.webp","conf":0.25}'

File upload:

curl -X POST https://vision.klevze.net/analyze/yolo/file \
  -H "X-API-Key: <your-api-key>" \
  -F "file=@/path/to/image.webp" \
  -F "conf=0.25"

Parameters:

• conf: confidence threshold (0.0–1.0).

Return: detected objects with class, confidence, and bbox (bounding box coordinates).

Maturity — NSFW / maturity analysis

Analyzes an image for mature or NSFW content and returns a structured signal intended for Nova moderation workflows.

URL request:

curl -X POST https://vision.klevze.net/analyze/maturity \
  -H "X-API-Key: <your-api-key>" \
  -H "Content-Type: application/json" \
  -d '{"url":"https://files.skinbase.org/img/aa/bb/cc/md.webp"}'

File upload:

curl -X POST https://vision.klevze.net/analyze/maturity/file \
  -H "X-API-Key: <your-api-key>" \
  -F "file=@/path/to/image.webp"

Example response:

{
  "maturity_label": "mature",
  "confidence": 0.94,
  "score": 0.94,
  "labels": ["nsfw"],
  "model": "Falconsai/nsfw_image_detection",
  "threshold_used": 0.80,
  "analysis_time_ms": 183.0,
  "source": "maturity-service",
  "action_hint": "flag_high",
  "advisory": "High-confidence mature content detected"
}

Response fields:

Field	Type	Description
maturity_label	string	safe or mature
confidence	float	Confidence in the label decision (0–1). For safe, this is 1 - score.
score	float	Raw NSFW probability from the model (0–1).
labels	array	Sublabels when mature: currently ["nsfw"]. Empty for safe results.
model	string	Model identifier / HuggingFace model ID.
threshold_used	float	The threshold value that determined the label.
analysis_time_ms	float	Inference time in milliseconds.
source	string	Always maturity-service.
action_hint	string	safe, review, or flag_high. Use this in Nova to drive blur/queue/flag decisions.
advisory	string	Short human-readable explanation.

action_hint decision logic:

• flag_high: score ≥ MATURITY_THRESHOLD_MATURE (default 0.80) — high-confidence mature, flag for moderation.
• review: score ≥ MATURITY_THRESHOLD_REVIEW (default 0.60) but below mature threshold — possible mature, queue for human review.
• safe: score below both thresholds — content appears safe.

If the maturity service is unavailable the gateway returns a 502 or 503 error. Nova must not treat a gateway failure as a safe result — retry or queue for later processing. store image embeddings and find visually similar images. Embeddings are generated automatically by the CLIP service.

Qdrant point IDs must be either an unsigned integer or a UUID string. If you send another string value, the wrapper may replace it with a generated UUID and store the original value in metadata as _original_id.

Upsert (store) an image by URL

curl -X POST https://vision.klevze.net/vectors/upsert \
  -H "X-API-Key: <your-api-key>" \
  -H "Content-Type: application/json" \
  -d '{"url":"https://files.skinbase.org/img/aa/bb/cc/md.webp","id":"550e8400-e29b-41d4-a716-446655440000","metadata":{"category":"wallpaper","source":"upload"}}'

Parameters:

• url (required): image URL to embed and store.
• id (optional): point ID. Use an unsigned integer or UUID string. If omitted, a UUID is auto-generated.
• metadata (optional): arbitrary key-value payload stored alongside the vector.
• collection (optional): target collection name (defaults to images).

Upsert by file upload

curl -X POST https://vision.klevze.net/vectors/upsert/file \
  -H "X-API-Key: <your-api-key>" \
  -F "file=@/path/to/image.webp" \
  -F 'id=550e8400-e29b-41d4-a716-446655440001' \
  -F 'metadata_json={"category":"photo"}'

Upsert a pre-computed vector

curl -X POST https://vision.klevze.net/vectors/upsert/vector \
  -H "X-API-Key: <your-api-key>" \
  -H "Content-Type: application/json" \
  -d '{"vector":[0.1,0.2,...],"id":"550e8400-e29b-41d4-a716-446655440002","metadata":{"custom":"data"}}'

Search similar images by URL

curl -X POST https://vision.klevze.net/vectors/search \
  -H "X-API-Key: <your-api-key>" \
  -H "Content-Type: application/json" \
  -d '{"url":"https://files.skinbase.org/img/aa/bb/cc/md.webp","limit":5}'

Parameters:

• url (required): query image URL.
• limit (optional, default 5): number of results.
• score_threshold (optional): minimum cosine similarity (0.0–1.0).
• filter_metadata (optional): filter results by payload fields, e.g. {"is_public":true,"category_id":3}.
• collection (optional): collection to search.
• hnsw_ef (optional, int): override the HNSW ef parameter at query time. Higher = better recall, slightly more latency.
• exact (optional, bool, default false): brute-force exact search. Avoid on large collections.
• indexed_only (optional, bool, default false): restrict search to fully indexed segments only. Useful during bulk ingest.

Return: list of {"id", "score", "metadata"} sorted by similarity.

Search by file upload

curl -X POST https://vision.klevze.net/vectors/search/file \
  -H "X-API-Key: <your-api-key>" \
  -F "file=@/path/to/image.webp" \
  -F "limit=5" \
  -F 'filter_metadata_json={"is_public":true}'

All URL search parameters are available as form fields; use filter_metadata_json (JSON string) for filters.

Search by pre-computed vector

curl -X POST https://vision.klevze.net/vectors/search/vector \
  -H "X-API-Key: <your-api-key>" \
  -H "Content-Type: application/json" \
  -d '{"vector":[0.1,0.2,...],"limit":5,"hnsw_ef":128}'

Collection management

List all collections:

curl -H "X-API-Key: <your-api-key>" https://vision.klevze.net/vectors/collections

Get collection info:

curl -H "X-API-Key: <your-api-key>" https://vision.klevze.net/vectors/collections/images

Create a custom collection:

curl -X POST https://vision.klevze.net/vectors/collections \
  -H "X-API-Key: <your-api-key>" \
  -H "Content-Type: application/json" \
  -d '{"name":"my_collection","vector_dim":512,"distance":"cosine"}'

Delete a collection:

curl -H "X-API-Key: <your-api-key>" -X DELETE https://vision.klevze.net/vectors/collections/my_collection

Full diagnostic inspect

Returns HNSW config, optimizer config, quantization, segment count, payload index coverage percentages, and RAM footprint estimate for every collection.

curl -H "X-API-Key: <your-api-key>" https://vision.klevze.net/vectors/inspect

Payload index management

Payload indexes are critical for fast filtered vector search. Always create indexes for fields used in filter_metadata filters.

# List existing indexes
curl -H "X-API-Key: <your-api-key>" https://vision.klevze.net/vectors/collections/images/indexes

# Create a single index
curl -X POST https://vision.klevze.net/vectors/collections/images/indexes \
  -H "X-API-Key: <your-api-key>" \
  -H "Content-Type: application/json" \
  -d '{"field":"is_public","type":"bool"}'

# Ensure multiple indexes exist (idempotent — safe to run multiple times)
curl -X POST https://vision.klevze.net/vectors/collections/images/ensure-indexes \
  -H "X-API-Key: <your-api-key>" \
  -H "Content-Type: application/json" \
  -d '{"fields":[{"field":"is_public","type":"bool"},{"field":"is_deleted","type":"bool"},{"field":"category_id","type":"integer"},{"field":"user_id","type":"keyword"}]}'

Supported index types: keyword, integer, float, bool, geo, datetime, text, uuid.

Collection configuration (HNSW / optimizer / quantization)

Updates HNSW, optimizer, or scalar quantization settings on an existing collection without data loss. HNSW graph and segment changes apply to newly created segments.

curl -X POST https://vision.klevze.net/vectors/collections/images/configure \
  -H "X-API-Key: <your-api-key>" \
  -H "Content-Type: application/json" \
  -d '{
    "hnsw_m": 16,
    "hnsw_ef_construct": 200,
    "hnsw_on_disk": false,
    "indexing_threshold": 20000,
    "default_segment_number": 4,
    "quantization_type": "int8",
    "quantization_quantile": 0.99,
    "quantization_always_ram": true
  }'

Parameters:

• hnsw_m (int, 4–64): edges per node in the HNSW graph.
• hnsw_ef_construct (int, 10–1000): ef during index construction.
• hnsw_on_disk (bool): store HNSW graph on disk (saves RAM, slightly slower queries).
• indexing_threshold (int): minimum vector changes before a segment is indexed.
• default_segment_number (int, 1–32): target segment count for parallelism.
• quantization_type (string, "int8" or null): enable scalar quantization (~4× RAM reduction).
• quantization_quantile (float, 0.5–1.0, default 0.99): calibration quantile.
• quantization_always_ram (bool, default true): keep quantized vectors in RAM.

Delete points

curl -X POST https://vision.klevze.net/vectors/delete \
  -H "X-API-Key: <your-api-key>" \
  -H "Content-Type: application/json" \
  -d '{"ids":["550e8400-e29b-41d4-a716-446655440000","550e8400-e29b-41d4-a716-446655440001"]}'

Get a point by ID

curl -H "X-API-Key: <your-api-key>" https://vision.klevze.net/vectors/points/550e8400-e29b-41d4-a716-446655440000

Get a point by original application ID

If the wrapper had to replace your string id with a generated UUID, the original value is preserved in metadata as _original_id.

curl -H "X-API-Key: <your-api-key>" https://vision.klevze.net/vectors/points/by-original-id/img-001

Card Renderer

The card renderer generates branded social-card images from artwork photos. It applies smart center-weighted cropping, a gradient overlay, title/subtitle/username/category text, optional tags, and an optional logo.

Default output: 1200×630 WebP (nova-artwork-v1 template).

List available templates

curl -H "X-API-Key: <your-api-key>" https://vision.klevze.net/cards/templates

Render a card from a URL

curl -X POST https://vision.klevze.net/cards/render \
  -H "X-API-Key: <your-api-key>" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://files.skinbase.org/img/aa/bb/cc/md.webp",
    "title": "Artwork Title",
    "subtitle": "Optional subtitle",
    "username": "@artist",
    "category": "Digital Art",
    "tags": ["surreal", "landscape"],
    "template": "nova-artwork-v1",
    "width": 1200,
    "height": 630,
    "output": "webp",
    "quality": 90,
    "show_logo": true
  }'

Returns binary image bytes with Content-Type: image/webp.

Render a card from a file upload

curl -X POST https://vision.klevze.net/cards/render/file \
  -H "X-API-Key: <your-api-key>" \
  -F "file=@/path/to/image.webp" \
  -F "title=Artwork Title" \
  -F "username=@artist" \
  -F "template=nova-artwork-v1" \
  -F "show_logo=true"

Returns binary image bytes.

Get card layout metadata (no image rendered)

curl -X POST https://vision.klevze.net/cards/render/meta \
  -H "X-API-Key: <your-api-key>" \
  -H "Content-Type: application/json" \
  -d '{"url":"https://files.skinbase.org/img/aa/bb/cc/md.webp","title":"Artwork Title"}'

Returns crop coordinates and layout data without producing an image.

Request/Response notes

• For URL requests use Content-Type: application/json.
• For uploads use multipart/form-data with a file field.
• Most gateway endpoints require the X-API-Key header.
• Remote image URLs must resolve to public hosts and return an image content type.
• The gateway aggregates and normalizes outputs for /analyze/all.

Running a single service

To run only one service via docker compose:

docker compose up -d --build clip

Or run locally (Python env) from the service folder:

# inside clip/ or blip/ or yolo/
uvicorn main:app --host 0.0.0.0 --port 8000

Production tips

• Add authentication (API keys or OAuth) at the gateway.
• Add rate-limiting and per-client quotas.
• Keep model services on an internal Docker network.
• For GPU: enable NVIDIA runtime and update service Dockerfiles / compose profiles.

Troubleshooting

• Service fails to start: check docker compose logs <service> for model load errors.
• BLIP startup error about Hugging Face auth: set HUGGINGFACE_TOKEN in .env and rebuild blip.
• Qdrant upsert error about invalid point ID: use a UUID or unsigned integer for id, or omit it and use the returned generated id.
• Image URL rejected before download: the URL may point to localhost, a private IP, a non-http/https scheme, or a non-image content type.
• High memory / OOM: increase host memory or reduce model footprint; consider GPUs.
• Slow startup: model weights load on service startup — expect extra time. The maturity service (start_period: 90s) may take longer on first boot as it downloads the classifier weights (~330 MB). Mount ~/.cache/huggingface as a volume to persist across rebuilds.
• Maturity endpoint returns 503: MATURITY_ENABLED is set to false in environment configuration.
• Maturity endpoint returns 502: the maturity container is unhealthy or still starting up; wait and retry.

Extending

• Swap or update models in each service by editing that service's main.py.
• Add request validation, timeouts, and retries in the gateway to improve robustness.

Files of interest

• docker-compose.yml — composition and service definitions.
• gateway/ — gateway FastAPI server.
• clip/, blip/, yolo/ — service implementations and Dockerfiles.
• maturity/ — NSFW/maturity classifier service (ViT-based, HuggingFace Falconsai/nsfw_image_detection).
• qdrant/ — Qdrant API wrapper service (FastAPI).
• card-renderer/ — card rendering service (FastAPI).
• common/ — shared helpers (e.g., image I/O).