Deploy Detect-X API with Docker and models

Co-authored-by: Cursor <cursoragent@cursor.com>

Dockerfile

@@ -0,0 +1,22 @@
+FROM python:3.10-slim
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    ffmpeg \
+    libgl1 \
+    libglib2.0-0 \
+    && rm -rf /var/lib/apt/lists/*
+
+WORKDIR /app
+
+COPY backend/requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY backend/app ./app
+COPY models ./models
+
+ENV MODELS_DIR=/app/models
+ENV PORT=7860
+
+EXPOSE 7860
+
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860"]

README.md

@@ -1,10 +1,23 @@
 ---
-title: DetectX
-emoji: 🐠
-colorFrom: green
-colorTo: red
+title: Detect-X
+emoji: 🔬
+colorFrom: gray
+colorTo: blue
 sdk: docker
+app_port: 7860
 pinned: false
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Detect-X
+
+Digital forensics platform — photo, video, and audio integrity analysis.
+
+| Layer | Host |
+|-------|------|
+| UI | Vercel (`frontend/`) |
+| API | Hugging Face Space (Docker, root `Dockerfile`) |
+| Code | GitHub `solvion-iq/DetectX` |
+
+See [DEPLOY.md](./DEPLOY.md) for setup steps.
+
+**Alpha** — analytical observations only, not a legal verdict.

backend/app/config.py

@@ -0,0 +1,19 @@
+from pydantic_settings import BaseSettings
+
+
+class Settings(BaseSettings):
+    app_name: str = "Detect-X API"
+    app_version: str = "0.1.0-alpha"
+    cors_origins: str = "*"
+    max_upload_mb: int = 100
+    max_video_seconds: int = 90
+    job_retention_hours: int = 2
+    models_dir: str = "/app/models"
+    visual_model_file: str = "IDF_Solid_Final.pth"
+    audio_model_file: str = "IDF_Audio_Scientific_Solid.pth"
+
+    class Config:
+        env_file = ".env"
+
+
+settings = Settings()

backend/app/jobs.py

@@ -0,0 +1,68 @@
+from __future__ import annotations
+
+import uuid
+from dataclasses import dataclass, field
+from datetime import datetime, timezone
+from enum import Enum
+from typing import Any
+
+
+class JobStatus(str, Enum):
+    QUEUED = "queued"
+    RUNNING = "running"
+    COMPLETED = "completed"
+    FAILED = "failed"
+
+
+STAGES = [
+    "ingest",
+    "metadata",
+    "audio_extract",
+    "frame_extract",
+    "visual_model",
+    "audio_model",
+    "ela_analysis",
+    "face_sync",
+    "dna_extract",
+    "findings",
+    "report",
+]
+
+
+@dataclass
+class Job:
+    id: str
+    filename: str
+    status: JobStatus = JobStatus.QUEUED
+    progress: int = 0
+    current_stage: str = STAGES[0]
+    created_at: str = field(default_factory=lambda: datetime.now(timezone.utc).isoformat())
+    error: str | None = None
+    result: dict[str, Any] = field(default_factory=dict)
+
+
+_jobs: dict[str, Job] = {}
+
+
+def create_job(filename: str) -> Job:
+    job = Job(id=str(uuid.uuid4()), filename=filename)
+    _jobs[job.id] = job
+    return job
+
+
+def get_job(job_id: str) -> Job | None:
+    return _jobs.get(job_id)
+
+
+def job_to_dict(job: Job) -> dict[str, Any]:
+    return {
+        "id": job.id,
+        "filename": job.filename,
+        "status": job.status.value,
+        "progress": job.progress,
+        "current_stage": job.current_stage,
+        "created_at": job.created_at,
+        "error": job.error,
+        "result": job.result,
+        "stages": STAGES,
+    }

backend/app/main.py

@@ -0,0 +1,107 @@
+from __future__ import annotations
+
+import hashlib
+import os
+from pathlib import Path
+
+from fastapi import FastAPI, File, HTTPException, UploadFile
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import JSONResponse
+
+from app.config import settings
+from app.jobs import JobStatus, create_job, get_job, job_to_dict
+
+app = FastAPI(
+    title=settings.app_name,
+    version=settings.app_version,
+    description="Detect-X forensic media analysis API (Alpha)",
+)
+
+origins = [o.strip() for o in settings.cors_origins.split(",") if o.strip()]
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=origins if origins != ["*"] else ["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+
+def models_ready() -> dict[str, bool]:
+    models_path = Path(settings.models_dir)
+    visual = models_path / settings.visual_model_file
+    audio = models_path / settings.audio_model_file
+    return {
+        "visual_model": visual.exists(),
+        "audio_model": audio.exists(),
+        "models_dir": str(models_path),
+    }
+
+
+@app.get("/")
+def root():
+    return {
+        "service": settings.app_name,
+        "version": settings.app_version,
+        "status": "online",
+        "docs": "/docs",
+    }
+
+
+@app.get("/health")
+def health():
+    ready = models_ready()
+    return {
+        "status": "healthy" if all(ready.values()) else "degraded",
+        "models": ready,
+        "limits": {
+            "max_upload_mb": settings.max_upload_mb,
+            "max_video_seconds": settings.max_video_seconds,
+        },
+    }
+
+
+@app.post("/analyze")
+async def analyze(file: UploadFile = File(...)):
+    if not file.filename:
+        raise HTTPException(status_code=400, detail="Filename is required")
+
+    content = await file.read()
+    size_mb = len(content) / (1024 * 1024)
+    if size_mb > settings.max_upload_mb:
+        raise HTTPException(
+            status_code=413,
+            detail=f"File exceeds {settings.max_upload_mb} MB limit",
+        )
+
+    file_hash = hashlib.sha256(content).hexdigest()
+    job = create_job(file.filename)
+    job.status = JobStatus.RUNNING
+    job.progress = 5
+    job.result = {
+        "sha256": file_hash,
+        "size_bytes": len(content),
+        "message": "Alpha stub: full pipeline will run in next build step",
+        "findings": [],
+        "dna": {"visual": None, "audio": None},
+    }
+    job.status = JobStatus.COMPLETED
+    job.progress = 100
+    job.current_stage = "report"
+
+    return JSONResponse(job_to_dict(job))
+
+
+@app.get("/jobs/{job_id}")
+def job_status(job_id: str):
+    job = get_job(job_id)
+    if not job:
+        raise HTTPException(status_code=404, detail="Job not found")
+    return job_to_dict(job)
+
+
+if os.getenv("SPACE_ID"):
+    # Hugging Face Spaces compatibility
+    @app.get("/spaces-config")
+    def spaces_config():
+        return {"ready": True}

backend/requirements.txt

@@ -0,0 +1,14 @@
+fastapi==0.115.6
+uvicorn[standard]==0.34.0
+python-multipart==0.0.20
+pydantic==2.10.4
+pydantic-settings==2.7.0
+numpy==2.2.1
+Pillow==11.1.0
+opencv-python-headless==4.10.0.84
+librosa==0.10.2.post1
+soundfile==0.13.1
+torch==2.5.1
+torchvision==0.20.1
+reportlab==4.2.5
+aiofiles==24.1.0

models/IDF_Audio_Scientific_Solid.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:aa2924731774cd3c55adf19fa8494df4f103d834b85e229746314bc37c41abb9
+size 42954421

models/IDF_Solid_Final.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1c093ef94befa540e1ec4951de4e18751da2f3153c8457d1ab6f1f30c46b0b48
+size 172464639