feat(maturity): add dedicated NSFW/maturity analysis service

- Add maturity/ service (FastAPI + Falconsai/nsfw_image_detection ViT classifier)
  - /analyze (URL) and /analyze/file (multipart upload) endpoints
  - Normalized response: maturity_label, confidence, score, labels,
    action_hint (safe/review/flag_high), advisory, threshold_used,
    analysis_time_ms, model, source
  - Configurable thresholds via MATURITY_THRESHOLD_MATURE / MATURITY_THRESHOLD_REVIEW
  - Reuses common/image_io for URL validation and file-size enforcement
  - Explicit 502/503 errors on failure — no silent safe fallback
  - Per-request structured logging (score, label, threshold path, elapsed ms)

- Update gateway/main.py
  - MATURITY_URL + MATURITY_ENABLED env vars
  - POST /analyze/maturity and POST /analyze/maturity/file endpoints
  - /health includes maturity service status
  - _assert_maturity_enabled() guard for clean 503 when disabled
  - All existing endpoints untouched (additive change)

- Update docker-compose.yml
  - Add maturity service with healthcheck (start_period: 90s)
  - Gateway environment: MATURITY_URL, MATURITY_ENABLED
  - Gateway depends_on: maturity (service_healthy)

- Update README.md and USAGE.md
  - Document maturity service, env vars, curl examples,
    full response schema table, action_hint logic, failure guidance

README.md

@@ -1,6 +1,6 @@
-# Skinbase Vision Stack (CLIP + BLIP + YOLO + Qdrant + Card Renderer) – Dockerized FastAPI
+# Skinbase Vision Stack (CLIP + BLIP + YOLO + Qdrant + Card Renderer + Maturity) – Dockerized FastAPI
 
-This repository provides **five standalone vision services** (CLIP / BLIP / YOLO / Qdrant / Card Renderer)
+This repository provides **six standalone vision services** (CLIP / BLIP / YOLO / Qdrant / Card Renderer / Maturity)
 and a **Gateway API** that can call them individually or together.
 
 ## Services & Ports
@@ -12,6 +12,7 @@ and a **Gateway API** that can call them individually or together.
 - `qdrant`: vector DB (port `6333` exposed for direct access)
 - `qdrant-svc`: internal Qdrant API wrapper
 - `card-renderer`: internal card rendering service
+- `maturity`: internal NSFW/maturity classifier service
 
 ## Run
 
@@ -30,6 +31,15 @@ HUGGINGFACE_TOKEN=your_huggingface_token_here
 
 `HUGGINGFACE_TOKEN` is required when the configured BLIP model is private, gated, or otherwise requires Hugging Face authentication.
 
+Optional maturity configuration (override in `.env` if needed):
+
+```bash
+MATURITY_MODEL=Falconsai/nsfw_image_detection
+MATURITY_THRESHOLD_MATURE=0.80
+MATURITY_THRESHOLD_REVIEW=0.60
+MATURITY_ENABLED=true
+```
+
 Service startup now waits on container healthchecks, so first boot may take longer while models finish loading.
 
 ## Health
@@ -96,6 +106,41 @@ curl -H "X-API-Key: <your-api-key>" -X POST https://vision.klevze.net/analyze/yo
   -F "conf=0.25"
 ```
 
+## Maturity / NSFW analysis
+
+Analyzes an image and returns a normalized maturity signal for Nova moderation workflows.
+
+### Analyze by URL
+```bash
+curl -H "X-API-Key: <your-api-key>" -X POST https://vision.klevze.net/analyze/maturity \
+  -H "Content-Type: application/json" \
+  -d '{"url":"https://files.skinbase.org/img/aa/bb/cc/md.webp"}'
+```
+
+### Analyze from file upload
+```bash
+curl -H "X-API-Key: <your-api-key>" -X POST https://vision.klevze.net/analyze/maturity/file \
+  -F "file=@/path/to/image.webp"
+```
+
+Example response:
+```json
+{
+  "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"
+}
+```
+
+`action_hint` values: `safe`, `review`, `flag_high`. Nova should use these to decide blur/queue/flag behaviour.
+
 ## Vector DB (Qdrant) via gateway
 
 Qdrant point IDs must be either:
@@ -228,8 +273,9 @@ curl -H "X-API-Key: <your-api-key>" -X POST https://vision.klevze.net/cards/rend
 
 ## Notes
 
-- This is a **starter scaffold**. Models are loaded at service startup.
+- Models are loaded at service startup; initial container start can take 1–2 minutes as model weights are downloaded.
 - Qdrant data is persisted in the project folder at `./data/qdrant`, so it survives container restarts and recreates.
 - Remote image URLs are restricted to public `http`/`https` hosts. Localhost, private IP ranges, and non-image content types are rejected.
+- The maturity service uses `Falconsai/nsfw_image_detection` (ViT-based). Thresholds are configurable via `.env`. The model handles photos and stylized digital art but should be calibrated against real Skinbase content before production use.
 - For production: add auth, rate limits, and restrict gateway exposure (private network).
 - GPU: you can add NVIDIA runtime later (compose profiles) if needed.

USAGE.md

@@ -1,10 +1,10 @@
 # Skinbase Vision Stack — Usage Guide
 
-This document explains how to run and use the Skinbase Vision Stack (Gateway + CLIP, BLIP, YOLO, Qdrant services).
+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` (FastAPI each, except `qdrant` which is the official Qdrant DB).
+- 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
@@ -19,6 +19,8 @@ This document explains how to run and use the Skinbase Vision Stack (Gateway + C
 
 - **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.
@@ -40,6 +42,19 @@ Notes:
 - `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):
+
+```bash
+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:
 
 ```bash
@@ -168,9 +183,65 @@ Parameters:
 
 Return: detected objects with `class`, `confidence`, and `bbox` (bounding box coordinates).
 
-### Qdrant — vector storage & similarity search
+### Maturity — NSFW / maturity analysis
 
-The Qdrant integration lets you store image embeddings and find visually similar images. Embeddings are generated automatically by the CLIP service.
+Analyzes an image for mature or NSFW content and returns a structured signal intended for Nova moderation workflows.
+
+URL request:
+
+```bash
+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:
+
+```bash
+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:
+
+```json
+{
+  "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`.
 
@@ -457,7 +528,9 @@ uvicorn main:app --host 0.0.0.0 --port 8000
 - 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.
+- 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
 
@@ -469,6 +542,7 @@ uvicorn main:app --host 0.0.0.0 --port 8000
 - `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).

docker-compose.yml

@@ -13,6 +13,8 @@ services:
       - YOLO_URL=http://yolo:8000
       - QDRANT_SVC_URL=http://qdrant-svc:8000
       - CARD_RENDERER_URL=http://card-renderer:8000
+      - MATURITY_URL=http://maturity:8000
+      - MATURITY_ENABLED=true
       - API_KEY=${API_KEY}
       - VISION_TIMEOUT=300
       - MAX_IMAGE_BYTES=52428800
@@ -27,6 +29,8 @@ services:
         condition: service_healthy
       card-renderer:
         condition: service_healthy
+      maturity:
+        condition: service_healthy
     healthcheck:
       test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://127.0.0.1:8000/health', timeout=5).read()"]
       interval: 30s
@@ -131,3 +135,19 @@ services:
       retries: 5
       start_period: 60s
 
+  maturity:
+    build:
+      context: .
+      dockerfile: maturity/Dockerfile
+    environment:
+      - MATURITY_MODEL=${MATURITY_MODEL:-Falconsai/nsfw_image_detection}
+      - MATURITY_THRESHOLD_MATURE=${MATURITY_THRESHOLD_MATURE:-0.80}
+      - MATURITY_THRESHOLD_REVIEW=${MATURITY_THRESHOLD_REVIEW:-0.60}
+      - MAX_IMAGE_BYTES=52428800
+    healthcheck:
+      test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://127.0.0.1:8000/health', timeout=5).read()"]
+      interval: 30s
+      timeout: 10s
+      retries: 5
+      start_period: 90s
+

gateway/main.py

@@ -1,7 +1,10 @@
 from __future__ import annotations
 
-import os
 import asyncio
+import logging
+import os
+import time
+from contextlib import asynccontextmanager
 from typing import Any, Dict, Optional
 
 import httpx
@@ -10,16 +13,76 @@ from fastapi.responses import JSONResponse, Response
 from starlette.middleware.base import BaseHTTPMiddleware
 from pydantic import BaseModel, Field
 
+logger = logging.getLogger("gateway")
+logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(name)s %(message)s")
+
 CLIP_URL = os.getenv("CLIP_URL", "http://clip:8000")
 BLIP_URL = os.getenv("BLIP_URL", "http://blip:8000")
 YOLO_URL = os.getenv("YOLO_URL", "http://yolo:8000")
 QDRANT_SVC_URL = os.getenv("QDRANT_SVC_URL", "http://qdrant-svc:8000")
 CARD_RENDERER_URL = os.getenv("CARD_RENDERER_URL", "http://card-renderer:8000")
+MATURITY_URL = os.getenv("MATURITY_URL", "http://maturity:8000")
+MATURITY_ENABLED = os.getenv("MATURITY_ENABLED", "true").lower() not in ("0", "false", "no")
 VISION_TIMEOUT = float(os.getenv("VISION_TIMEOUT", "20"))
 
 # API key (set via env var `API_KEY`). If not set, gateway will reject requests.
 API_KEY = os.getenv("API_KEY")
 
+# ---------------------------------------------------------------------------
+# Shared persistent HTTP client — created once at startup, reused across all
+# requests.  This eliminates per-request TCP connect + DNS latency (the main
+# cause of 20 s first-request latency observed on /vectors/inspect).
+# ---------------------------------------------------------------------------
+_http_client: httpx.AsyncClient | None = None
+
+
+def get_http_client() -> httpx.AsyncClient:
+    """Return the shared httpx client. Raises if called before lifespan starts."""
+    if _http_client is None:
+        raise RuntimeError("HTTP client not initialised — lifespan not running")
+    return _http_client
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    """Application lifespan: create shared HTTP client and warm upstream connections."""
+    global _http_client
+
+    t0 = time.perf_counter()
+    logger.info("gateway startup: creating shared HTTP client")
+
+    limits = httpx.Limits(
+        max_connections=100,
+        max_keepalive_connections=20,
+        keepalive_expiry=30,
+    )
+    _http_client = httpx.AsyncClient(
+        timeout=httpx.Timeout(VISION_TIMEOUT, connect=10),
+        limits=limits,
+    )
+
+    # Warm the qdrant-svc connection so the first real request does not pay
+    # the TCP handshake + DNS cost.  Failure is non-fatal — the service may
+    # still be starting when the gateway starts.
+    try:
+        t_warm = time.perf_counter()
+        r = await _http_client.get(f"{QDRANT_SVC_URL}/health", timeout=8)
+        logger.info(
+            "gateway startup: qdrant-svc warm ping done status=%s elapsed_ms=%.1f",
+            r.status_code, (time.perf_counter() - t_warm) * 1000,
+        )
+    except Exception as exc:
+        logger.warning("gateway startup: qdrant-svc warm ping failed (non-fatal): %s", exc)
+
+    logger.info("gateway startup complete elapsed_ms=%.1f", (time.perf_counter() - t0) * 1000)
+
+    yield  # application runs
+
+    logger.info("gateway shutdown: closing shared HTTP client")
+    await _http_client.aclose()
+    _http_client = None
+
+
 class APIKeyMiddleware(BaseHTTPMiddleware):
     async def dispatch(self, request: Request, call_next):
         # allow health and docs endpoints without API key
@@ -30,7 +93,7 @@ class APIKeyMiddleware(BaseHTTPMiddleware):
             return JSONResponse(status_code=401, content={"detail": "Unauthorized"})
         return await call_next(request)
 
-app = FastAPI(title="Skinbase Vision Gateway", version="1.0.0")
+app = FastAPI(title="Skinbase Vision Gateway", version="1.0.0", lifespan=lifespan)
 app.add_middleware(APIKeyMiddleware)
 
 
@@ -51,19 +114,26 @@ class YoloRequest(BaseModel):
     conf: float = Field(default=0.25, ge=0.0, le=1.0)
 
 
-async def _get_health(client: httpx.AsyncClient, base: str) -> Dict[str, Any]:
+class MaturityRequest(BaseModel):
+    url: Optional[str] = None
+
+
+async def _get_health(base: str) -> Dict[str, Any]:
     try:
-        r = await client.get(f"{base}/health")
+        r = await get_http_client().get(f"{base}/health", timeout=5)
         return r.json() if r.status_code == 200 else {"status": "bad", "code": r.status_code}
     except Exception:
         return {"status": "unreachable"}
 
 
-async def _post_json(client: httpx.AsyncClient, url: str, payload: Dict[str, Any]) -> Dict[str, Any]:
+async def _post_json(url: str, payload: Dict[str, Any]) -> Dict[str, Any]:
+    t0 = time.perf_counter()
     try:
-        r = await client.post(url, json=payload)
+        r = await get_http_client().post(url, json=payload)
     except httpx.RequestError as e:
         raise HTTPException(status_code=502, detail=f"Upstream request failed {url}: {str(e)}")
+    elapsed = (time.perf_counter() - t0) * 1000
+    logger.debug("POST %s status=%s elapsed_ms=%.1f", url, r.status_code, elapsed)
     if r.status_code >= 400:
         raise HTTPException(status_code=502, detail=f"Upstream error {url}: {r.status_code} {r.text[:1000]}")
     try:
@@ -73,12 +143,15 @@ async def _post_json(client: httpx.AsyncClient, url: str, payload: Dict[str, Any
         raise HTTPException(status_code=502, detail=f"Upstream returned non-JSON at {url}: {r.status_code} {r.text[:1000]}")
 
 
-async def _post_file(client: httpx.AsyncClient, url: str, data: bytes, fields: Dict[str, Any]) -> Dict[str, Any]:
+async def _post_file(url: str, data: bytes, fields: Dict[str, Any]) -> Dict[str, Any]:
     files = {"file": ("image", data, "application/octet-stream")}
+    t0 = time.perf_counter()
     try:
-        r = await client.post(url, data={k: str(v) for k, v in fields.items()}, files=files)
+        r = await get_http_client().post(url, data={k: str(v) for k, v in fields.items()}, files=files)
     except httpx.RequestError as e:
         raise HTTPException(status_code=502, detail=f"Upstream request failed {url}: {str(e)}")
+    elapsed = (time.perf_counter() - t0) * 1000
+    logger.debug("POST(file) %s status=%s elapsed_ms=%.1f", url, r.status_code, elapsed)
     if r.status_code >= 400:
         raise HTTPException(status_code=502, detail=f"Upstream error {url}: {r.status_code} {r.text[:1000]}")
     try:
@@ -87,11 +160,14 @@ async def _post_file(client: httpx.AsyncClient, url: str, data: bytes, fields: D
         raise HTTPException(status_code=502, detail=f"Upstream returned non-JSON at {url}: {r.status_code} {r.text[:1000]}")
 
 
-async def _get_json(client: httpx.AsyncClient, url: str, params: Optional[Dict[str, Any]] = None) -> Dict[str, Any]:
+async def _get_json(url: str, params: Optional[Dict[str, Any]] = None) -> Dict[str, Any]:
+    t0 = time.perf_counter()
     try:
-        r = await client.get(url, params=params)
+        r = await get_http_client().get(url, params=params)
     except httpx.RequestError as e:
         raise HTTPException(status_code=502, detail=f"Upstream request failed {url}: {str(e)}")
+    elapsed = (time.perf_counter() - t0) * 1000
+    logger.debug("GET %s status=%s elapsed_ms=%.1f", url, r.status_code, elapsed)
     if r.status_code >= 400:
         raise HTTPException(status_code=502, detail=f"Upstream error {url}: {r.status_code} {r.text[:1000]}")
     try:
@@ -102,14 +178,25 @@ async def _get_json(client: httpx.AsyncClient, url: str, params: Optional[Dict[s
 
 @app.get("/health")
 async def health():
-    async with httpx.AsyncClient(timeout=5) as client:
+    health_checks = [
-        clip_h, blip_h, yolo_h, qdrant_h = await asyncio.gather(
+        _get_health(CLIP_URL),
-            _get_health(client, CLIP_URL),
+        _get_health(BLIP_URL),
-            _get_health(client, BLIP_URL),
+        _get_health(YOLO_URL),
-            _get_health(client, YOLO_URL),
+        _get_health(QDRANT_SVC_URL),
-            _get_health(client, QDRANT_SVC_URL),
+    ]
-        )
+    if MATURITY_ENABLED:
-        return {"status": "ok", "services": {"clip": clip_h, "blip": blip_h, "yolo": yolo_h, "qdrant": qdrant_h}}
+        health_checks.append(_get_health(MATURITY_URL))
+
+    results = await asyncio.gather(*health_checks)
+    services: Dict[str, Any] = {
+        "clip": results[0],
+        "blip": results[1],
+        "yolo": results[2],
+        "qdrant": results[3],
+    }
+    if MATURITY_ENABLED:
+        services["maturity"] = results[4]
+    return {"status": "ok", "services": services}
 
 
 # ---- Individual analyze endpoints (URL) ----
@@ -118,24 +205,21 @@ async def health():
 async def analyze_clip(req: ClipRequest):
     if not req.url:
         raise HTTPException(400, "url is required")
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _post_json(f"{CLIP_URL}/analyze", req.model_dump())
-        return await _post_json(client, f"{CLIP_URL}/analyze", req.model_dump())
 
 
 @app.post("/analyze/blip")
 async def analyze_blip(req: BlipRequest):
     if not req.url:
         raise HTTPException(400, "url is required")
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _post_json(f"{BLIP_URL}/caption", req.model_dump())
-        return await _post_json(client, f"{BLIP_URL}/caption", req.model_dump())
 
 
 @app.post("/analyze/yolo")
 async def analyze_yolo(req: YoloRequest):
     if not req.url:
         raise HTTPException(400, "url is required")
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _post_json(f"{YOLO_URL}/detect", req.model_dump())
-        return await _post_json(client, f"{YOLO_URL}/detect", req.model_dump())
 
 
 # ---- Individual analyze endpoints (file upload) ----
@@ -151,8 +235,7 @@ async def analyze_clip_file(
     fields: Dict[str, Any] = {"limit": int(limit)}
     if threshold is not None:
         fields["threshold"] = float(threshold)
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _post_file(f"{CLIP_URL}/analyze/file", data, fields)
-        return await _post_file(client, f"{CLIP_URL}/analyze/file", data, fields)
 
 
 @app.post("/analyze/blip/file")
@@ -163,8 +246,7 @@ async def analyze_blip_file(
 ):
     data = await file.read()
     fields = {"variants": int(variants), "max_length": int(max_length)}
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _post_file(f"{BLIP_URL}/caption/file", data, fields)
-        return await _post_file(client, f"{BLIP_URL}/caption/file", data, fields)
 
 
 @app.post("/analyze/yolo/file")
@@ -174,8 +256,7 @@ async def analyze_yolo_file(
 ):
     data = await file.read()
     fields = {"conf": float(conf)}
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _post_file(f"{YOLO_URL}/detect/file", data, fields)
-        return await _post_file(client, f"{YOLO_URL}/detect/file", data, fields)
 
 
 @app.post("/analyze/all")
@@ -188,13 +269,11 @@ async def analyze_all(payload: Dict[str, Any]):
     blip_req = {"url": url, "variants": int(payload.get("variants", 3)), "max_length": int(payload.get("max_length", 60))}
     yolo_req = {"url": url, "conf": float(payload.get("conf", 0.25))}
 
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    clip_res, blip_res, yolo_res = await asyncio.gather(
-        clip_task = _post_json(client, f"{CLIP_URL}/analyze", clip_req)
+        _post_json(f"{CLIP_URL}/analyze", clip_req),
-        blip_task = _post_json(client, f"{BLIP_URL}/caption", blip_req)
+        _post_json(f"{BLIP_URL}/caption", blip_req),
-        yolo_task = _post_json(client, f"{YOLO_URL}/detect", yolo_req)
+        _post_json(f"{YOLO_URL}/detect", yolo_req),
-
+    )
-        clip_res, blip_res, yolo_res = await asyncio.gather(clip_task, blip_task, yolo_task)
-
     return {"clip": clip_res, "blip": blip_res, "yolo": yolo_res}
 
 
@@ -202,8 +281,7 @@ async def analyze_all(payload: Dict[str, Any]):
 
 @app.post("/vectors/upsert")
 async def vectors_upsert(payload: Dict[str, Any]):
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _post_json(f"{QDRANT_SVC_URL}/upsert", payload)
-        return await _post_json(client, f"{QDRANT_SVC_URL}/upsert", payload)
 
 
 @app.post("/vectors/upsert/file")
@@ -221,20 +299,17 @@ async def vectors_upsert_file(
         fields["collection"] = collection
     if metadata_json is not None:
         fields["metadata_json"] = metadata_json
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _post_file(f"{QDRANT_SVC_URL}/upsert/file", data, fields)
-        return await _post_file(client, f"{QDRANT_SVC_URL}/upsert/file", data, fields)
 
 
 @app.post("/vectors/upsert/vector")
 async def vectors_upsert_vector(payload: Dict[str, Any]):
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _post_json(f"{QDRANT_SVC_URL}/upsert/vector", payload)
-        return await _post_json(client, f"{QDRANT_SVC_URL}/upsert/vector", payload)
 
 
 @app.post("/vectors/search")
 async def vectors_search(payload: Dict[str, Any]):
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _post_json(f"{QDRANT_SVC_URL}/search", payload)
-        return await _post_json(client, f"{QDRANT_SVC_URL}/search", payload)
 
 
 @app.post("/vectors/search/file")
@@ -258,51 +333,50 @@ async def vectors_search_file(
         fields["hnsw_ef"] = int(hnsw_ef)
     if filter_metadata_json is not None:
         fields["filter_metadata_json"] = filter_metadata_json
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _post_file(f"{QDRANT_SVC_URL}/search/file", data, fields)
-        return await _post_file(client, f"{QDRANT_SVC_URL}/search/file", data, fields)
 
 
 @app.post("/vectors/search/vector")
 async def vectors_search_vector(payload: Dict[str, Any]):
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _post_json(f"{QDRANT_SVC_URL}/search/vector", payload)
-        return await _post_json(client, f"{QDRANT_SVC_URL}/search/vector", payload)
 
 
 @app.post("/vectors/delete")
 async def vectors_delete(payload: Dict[str, Any]):
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _post_json(f"{QDRANT_SVC_URL}/delete", payload)
-        return await _post_json(client, f"{QDRANT_SVC_URL}/delete", payload)
 
 
 @app.get("/vectors/collections")
 async def vectors_collections():
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _get_json(f"{QDRANT_SVC_URL}/collections")
-        return await _get_json(client, f"{QDRANT_SVC_URL}/collections")
 
 
 @app.post("/vectors/collections")
 async def vectors_create_collection(payload: Dict[str, Any]):
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _post_json(f"{QDRANT_SVC_URL}/collections", payload)
-        return await _post_json(client, f"{QDRANT_SVC_URL}/collections", payload)
 
 
 @app.get("/vectors/collections/{name}")
 async def vectors_collection_info(name: str):
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _get_json(f"{QDRANT_SVC_URL}/collections/{name}")
-        return await _get_json(client, f"{QDRANT_SVC_URL}/collections/{name}")
 
 
 @app.get("/vectors/inspect")
 async def vectors_inspect():
     """Full diagnostic summary for all Qdrant collections (HNSW, optimizer, payload indexes, RAM estimate)."""
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    t0 = time.perf_counter()
-        return await _get_json(client, f"{QDRANT_SVC_URL}/inspect")
+    logger.info("vectors_inspect: start")
+    result = await _get_json(f"{QDRANT_SVC_URL}/inspect")
+    logger.info("vectors_inspect: done elapsed_ms=%.1f", (time.perf_counter() - t0) * 1000)
+    return result
 
 
 @app.delete("/vectors/collections/{name}")
 async def vectors_delete_collection(name: str):
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    try:
-        r = await client.delete(f"{QDRANT_SVC_URL}/collections/{name}")
+        r = await get_http_client().delete(f"{QDRANT_SVC_URL}/collections/{name}")
+    except httpx.RequestError as exc:
+        raise HTTPException(status_code=502, detail=f"Upstream request failed: {exc}")
     if r.status_code >= 400:
         raise HTTPException(status_code=502, detail=f"Upstream error: {r.status_code}")
     return r.json()
@@ -310,20 +384,18 @@ async def vectors_delete_collection(name: str):
 
 @app.get("/vectors/points/{point_id}")
 async def vectors_get_point(point_id: str, collection: Optional[str] = None):
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
     params = {}
     if collection:
         params["collection"] = collection
-        return await _get_json(client, f"{QDRANT_SVC_URL}/points/{point_id}", params=params)
+    return await _get_json(f"{QDRANT_SVC_URL}/points/{point_id}", params=params)
 
 
 @app.get("/vectors/points/by-original-id/{original_id}")
 async def vectors_get_point_by_original_id(original_id: str, collection: Optional[str] = None):
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
     params = {}
     if collection:
         params["collection"] = collection
-        return await _get_json(client, f"{QDRANT_SVC_URL}/points/by-original-id/{original_id}", params=params)
+    return await _get_json(f"{QDRANT_SVC_URL}/points/by-original-id/{original_id}", params=params)
 
 
 # ---- File-based universal analyze ----
@@ -337,31 +409,61 @@ async def analyze_all_file(
     max_length: int = Form(60),
 ):
     data = await file.read()
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    clip_res, blip_res, yolo_res = await asyncio.gather(
-        clip_task = _post_file(client, f"{CLIP_URL}/analyze/file", data, {"limit": limit})
+        _post_file(f"{CLIP_URL}/analyze/file", data, {"limit": limit}),
-        blip_task = _post_file(client, f"{BLIP_URL}/caption/file", data, {"variants": variants, "max_length": max_length})
+        _post_file(f"{BLIP_URL}/caption/file", data, {"variants": variants, "max_length": max_length}),
-        yolo_task = _post_file(client, f"{YOLO_URL}/detect/file", data, {"conf": conf})
+        _post_file(f"{YOLO_URL}/detect/file", data, {"conf": conf}),
-
+    )
-        clip_res, blip_res, yolo_res = await asyncio.gather(clip_task, blip_task, yolo_task)
-
     return {"clip": clip_res, "blip": blip_res, "yolo": yolo_res}
 
 
+# ---- Maturity / NSFW analysis endpoints ----
+
+
+def _assert_maturity_enabled() -> None:
+    if not MATURITY_ENABLED:
+        raise HTTPException(status_code=503, detail="Maturity service is disabled")
+
+
+@app.post("/analyze/maturity")
+async def analyze_maturity(req: MaturityRequest):
+    """Analyze an image URL for maturity / NSFW content.
+
+    Returns a normalized maturity signal including maturity_label (safe/mature),
+    confidence, score, optional sublabels, and an action_hint for Nova moderation.
+    """
+    _assert_maturity_enabled()
+    if not req.url:
+        raise HTTPException(status_code=400, detail="url is required")
+    logger.info("analyze_maturity: url=%s", req.url)
+    return await _post_json(f"{MATURITY_URL}/analyze", req.model_dump())
+
+
+@app.post("/analyze/maturity/file")
+async def analyze_maturity_file(file: UploadFile = File(...)):
+    """Analyze an uploaded image file for maturity / NSFW content.
+
+    Returns the same normalized maturity signal as /analyze/maturity.
+    """
+    _assert_maturity_enabled()
+    data = await file.read()
+    logger.info("analyze_maturity_file: filename=%s size=%d", file.filename, len(data))
+    return await _post_file(f"{MATURITY_URL}/analyze/file", data, {})
+
+
 # ---- Card renderer endpoints ----
 
 @app.get("/cards/templates")
 async def cards_templates():
     """List available card templates."""
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _get_json(f"{CARD_RENDERER_URL}/templates")
-        return await _get_json(client, f"{CARD_RENDERER_URL}/templates")
 
 
 @app.post("/cards/render")
 async def cards_render(payload: Dict[str, Any]):
     """Render a Nova card from a remote image URL. Returns binary image bytes."""
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
     try:
-            resp = await client.post(f"{CARD_RENDERER_URL}/render", json=payload)
+        resp = await get_http_client().post(f"{CARD_RENDERER_URL}/render", json=payload)
     except httpx.RequestError as exc:
         raise HTTPException(status_code=502, detail=f"card-renderer unreachable: {exc}")
     if resp.status_code >= 400:
@@ -409,9 +511,8 @@ async def cards_render_file(
         fields["tags_json"] = tags_json
 
     upload_files = {"file": (file.filename or "image", data, file.content_type or "application/octet-stream")}
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
     try:
-            resp = await client.post(
+        resp = await get_http_client().post(
             f"{CARD_RENDERER_URL}/render/file",
             data={k: str(v) for k, v in fields.items()},
             files=upload_files,
@@ -429,8 +530,7 @@ async def cards_render_file(
 @app.post("/cards/render/meta")
 async def cards_render_meta(payload: Dict[str, Any]):
     """Return crop and layout metadata for a card render (no image produced)."""
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _post_json(f"{CARD_RENDERER_URL}/render/meta", payload)
-        return await _post_json(client, f"{CARD_RENDERER_URL}/render/meta", payload)
 
 
 # ---- Qdrant administration endpoints (index management + collection config) ----
@@ -438,26 +538,22 @@ async def cards_render_meta(payload: Dict[str, Any]):
 @app.get("/vectors/collections/{name}/indexes")
 async def vectors_collection_indexes(name: str):
     """List payload indexes for a collection."""
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _get_json(f"{QDRANT_SVC_URL}/collections/{name}/indexes")
-        return await _get_json(client, f"{QDRANT_SVC_URL}/collections/{name}/indexes")
 
 
 @app.post("/vectors/collections/{name}/indexes")
 async def vectors_create_payload_index(name: str, payload: Dict[str, Any]):
     """Create a payload index on a field in a collection."""
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _post_json(f"{QDRANT_SVC_URL}/collections/{name}/indexes", payload)
-        return await _post_json(client, f"{QDRANT_SVC_URL}/collections/{name}/indexes", payload)
 
 
 @app.post("/vectors/collections/{name}/ensure-indexes")
 async def vectors_ensure_indexes(name: str, payload: Dict[str, Any]):
     """Idempotently ensure payload indexes exist for a list of fields."""
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _post_json(f"{QDRANT_SVC_URL}/collections/{name}/ensure-indexes", payload)
-        return await _post_json(client, f"{QDRANT_SVC_URL}/collections/{name}/ensure-indexes", payload)
 
 
 @app.post("/vectors/collections/{name}/configure")
 async def vectors_configure_collection(name: str, payload: Dict[str, Any]):
     """Update HNSW and optimizer configuration for a collection."""
-    async with httpx.AsyncClient(timeout=VISION_TIMEOUT) as client:
+    return await _post_json(f"{QDRANT_SVC_URL}/collections/{name}/configure", payload)
-        return await _post_json(client, f"{QDRANT_SVC_URL}/collections/{name}/configure", payload)

maturity/Dockerfile

@@ -0,0 +1,17 @@
+FROM python:3.11-slim
+
+WORKDIR /app
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    ca-certificates \
+  && rm -rf /var/lib/apt/lists/*
+
+COPY maturity/requirements.txt /app/requirements.txt
+RUN pip install --no-cache-dir -r /app/requirements.txt
+
+COPY maturity /app
+COPY common /app/common
+
+ENV PYTHONUNBUFFERED=1
+
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]

maturity/main.py

@@ -0,0 +1,221 @@
+"""Skinbase Maturity Analysis Service.
+
+Uses a dedicated NSFW/maturity ViT classifier (Falconsai/nsfw_image_detection)
+to produce a structured, normalized maturity signal consumable by Nova moderation
+workflows.
+
+Endpoints
+---------
+GET  /health           — liveness + model info
+POST /analyze          — URL-based maturity analysis
+POST /analyze/file     — multipart file-upload maturity analysis
+
+Response contract
+-----------------
+{
+    "maturity_label": "safe" | "mature",
+    "confidence": float,          # confidence in the maturity_label decision
+    "score": float,               # raw NSFW probability from model (0.0 – 1.0)
+    "labels": list[str],          # sublabels when mature, e.g. ["nsfw"]
+    "model": str,                 # model identifier
+    "threshold_used": float,      # threshold that produced the label
+    "analysis_time_ms": float,
+    "source": "maturity-service",
+    "action_hint": "safe" | "review" | "flag_high",
+    "advisory": str               # short human-readable reason
+}
+"""
+
+from __future__ import annotations
+
+import logging
+import os
+import time
+from typing import List, Optional
+
+import torch
+from fastapi import FastAPI, HTTPException, UploadFile, File, Form
+from pydantic import BaseModel, Field
+from transformers import AutoImageProcessor, AutoModelForImageClassification
+
+from common.image_io import fetch_url_bytes, bytes_to_pil, ImageLoadError
+
+logger = logging.getLogger("maturity")
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s %(levelname)s %(name)s %(message)s",
+)
+
+# ---------------------------------------------------------------------------
+# Configuration — all tunable via environment variables
+# ---------------------------------------------------------------------------
+MATURITY_MODEL = os.getenv("MATURITY_MODEL", "Falconsai/nsfw_image_detection")
+DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
+
+# Main threshold: score >= this → "mature" + "flag_high"
+THRESHOLD_MATURE = float(os.getenv("MATURITY_THRESHOLD_MATURE", "0.80"))
+# Review band: score >= this (but below MATURE) → "mature" + "review"
+THRESHOLD_REVIEW = float(os.getenv("MATURITY_THRESHOLD_REVIEW", "0.60"))
+
+# Max image bytes — same default as the rest of the stack (50 MB)
+MAX_IMAGE_BYTES = int(os.getenv("MAX_IMAGE_BYTES", str(50 * 1024 * 1024)))
+
+# ---------------------------------------------------------------------------
+# Model loading — done once at import time so Docker start captures it
+# ---------------------------------------------------------------------------
+logger.info("maturity service: loading model %s on %s", MATURITY_MODEL, DEVICE)
+_t_load = time.perf_counter()
+
+_processor = AutoImageProcessor.from_pretrained(MATURITY_MODEL)
+_model = AutoModelForImageClassification.from_pretrained(MATURITY_MODEL).to(DEVICE).eval()
+
+# Build a label→index map from the model config so we are not fragile to label
+# ordering changes.
+_ID2LABEL: dict[int, str] = _model.config.id2label  # e.g. {0: "normal", 1: "nsfw"}
+_NSFW_IDX: int = next(
+    (i for i, lbl in _ID2LABEL.items() if "nsfw" in lbl.lower() or "explicit" in lbl.lower()),
+    1,  # fallback: assume index 1 is the NSFW class
+)
+
+logger.info(
+    "maturity service: model loaded elapsed_ms=%.1f device=%s id2label=%s nsfw_idx=%s",
+    (time.perf_counter() - _t_load) * 1000,
+    DEVICE,
+    _ID2LABEL,
+    _NSFW_IDX,
+)
+
+app = FastAPI(title="Skinbase Maturity Service", version="1.0.0")
+
+# ---------------------------------------------------------------------------
+# Schemas
+# ---------------------------------------------------------------------------
+
+class MaturityRequest(BaseModel):
+    url: Optional[str] = Field(default=None, description="Public image URL to analyse")
+
+
+class MaturityResponse(BaseModel):
+    maturity_label: str = Field(description='"safe" or "mature"')
+    confidence: float = Field(description="Confidence in the maturity_label decision (0–1)")
+    score: float = Field(description="Raw NSFW probability from the model (0–1)")
+    labels: List[str] = Field(description="Sublabels when mature content is detected")
+    model: str = Field(description="Model identifier / version")
+    threshold_used: float = Field(description="Threshold applied to produce the label")
+    analysis_time_ms: float
+    source: str = "maturity-service"
+    action_hint: str = Field(description='"safe", "review", or "flag_high"')
+    advisory: str = Field(description="Short human-readable reason for the decision")
+
+# ---------------------------------------------------------------------------
+# Inference helper
+# ---------------------------------------------------------------------------
+
+def _run_inference(data: bytes) -> MaturityResponse:
+    """Run maturity inference on raw image bytes and return a structured response."""
+    t0 = time.perf_counter()
+
+    try:
+        img = bytes_to_pil(data)
+    except Exception as exc:
+        raise HTTPException(status_code=400, detail=f"Cannot decode image: {exc}") from exc
+
+    inputs = _processor(images=img, return_tensors="pt").to(DEVICE)
+
+    with torch.no_grad():
+        logits = _model(**inputs).logits
+
+    probs = torch.softmax(logits, dim=-1)[0]
+    nsfw_score = float(probs[_NSFW_IDX])
+
+    elapsed_ms = (time.perf_counter() - t0) * 1000
+
+    # Derive label, action_hint, advisory, sublabels
+    if nsfw_score >= THRESHOLD_MATURE:
+        maturity_label = "mature"
+        action_hint = "flag_high"
+        advisory = "High-confidence mature content detected"
+        labels = ["nsfw"]
+        threshold_used = THRESHOLD_MATURE
+        confidence = nsfw_score
+    elif nsfw_score >= THRESHOLD_REVIEW:
+        maturity_label = "mature"
+        action_hint = "review"
+        advisory = "Possible mature content — review recommended"
+        labels = ["nsfw"]
+        threshold_used = THRESHOLD_REVIEW
+        confidence = nsfw_score
+    else:
+        maturity_label = "safe"
+        action_hint = "safe"
+        advisory = "Content appears safe"
+        labels = []
+        threshold_used = THRESHOLD_REVIEW
+        confidence = 1.0 - nsfw_score  # confidence in the "safe" verdict
+
+    logger.info(
+        "maturity inference: maturity_label=%s action_hint=%s score=%.4f "
+        "confidence=%.4f threshold_mature=%.2f threshold_review=%.2f elapsed_ms=%.1f",
+        maturity_label,
+        action_hint,
+        nsfw_score,
+        confidence,
+        THRESHOLD_MATURE,
+        THRESHOLD_REVIEW,
+        elapsed_ms,
+    )
+
+    return MaturityResponse(
+        maturity_label=maturity_label,
+        confidence=round(confidence, 4),
+        score=round(nsfw_score, 4),
+        labels=labels,
+        model=MATURITY_MODEL,
+        threshold_used=threshold_used,
+        analysis_time_ms=round(elapsed_ms, 1),
+        source="maturity-service",
+        action_hint=action_hint,
+        advisory=advisory,
+    )
+
+
+# ---------------------------------------------------------------------------
+# Endpoints
+# ---------------------------------------------------------------------------
+
+@app.get("/health")
+def health():
+    return {
+        "status": "ok",
+        "device": DEVICE,
+        "model": MATURITY_MODEL,
+        "threshold_mature": THRESHOLD_MATURE,
+        "threshold_review": THRESHOLD_REVIEW,
+    }
+
+
+@app.post("/analyze", response_model=MaturityResponse)
+def analyze(req: MaturityRequest):
+    """URL-based maturity analysis."""
+    if not req.url:
+        raise HTTPException(status_code=400, detail="url is required")
+    try:
+        data = fetch_url_bytes(req.url, max_bytes=MAX_IMAGE_BYTES)
+    except ImageLoadError as exc:
+        logger.warning("maturity analyze: image load failed url=%s error=%s", req.url, exc)
+        raise HTTPException(status_code=400, detail=str(exc)) from exc
+    return _run_inference(data)
+
+
+@app.post("/analyze/file", response_model=MaturityResponse)
+async def analyze_file(file: UploadFile = File(...)):
+    """Multipart file-upload maturity analysis."""
+    data = await file.read()
+    if len(data) > MAX_IMAGE_BYTES:
+        raise HTTPException(
+            status_code=413,
+            detail=f"File exceeds maximum allowed size of {MAX_IMAGE_BYTES} bytes",
+        )
+    if not data:
+        raise HTTPException(status_code=400, detail="Empty file upload")
+    return _run_inference(data)

maturity/requirements.txt

@@ -0,0 +1,8 @@
+fastapi==0.115.5
+uvicorn[standard]==0.30.6
+python-multipart==0.0.9
+requests==2.32.3
+pillow==10.4.0
+torch==2.4.1
+torchvision==0.19.1
+transformers==4.44.2