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flask_app.py β Flask web server for DeepScan (CNN-Only)
"""
import io
import json
import os
import uuid
from datetime import datetime
from pathlib import Path
import requests
from dotenv import load_dotenv
from flask import (
Flask,
jsonify,
render_template,
request,
send_from_directory,
)
from flask_cors import CORS
from werkzeug.utils import secure_filename
load_dotenv()
_HERE = Path(__file__).resolve().parent
_ROOT = _HERE.parent / "Frontend"
# ββ CONFIG ββββββββββββββββββββββββββββββββββββββββββββββββββββ
FASTAPI_BASE_URL = os.getenv("FASTAPI_BASE_URL", "http://localhost:8000")
GROQ_API_KEY = os.getenv("GROQ_API_KEY", "").strip()
FLASK_SECRET_KEY = os.getenv("FLASK_SECRET_KEY", "change-me-in-production")
HISTORY_FILE = Path(os.getenv("HISTORY_FILE", "/tmp/data/history.json"))
# ββ FILE SIZE: 5 MB hard limit (matches frontend) βββββββββββββ
MAX_UPLOAD_MB = int(os.getenv("MAX_UPLOAD_MB", "5"))
PORT = int(os.getenv("PORT", os.getenv("FLASK_PORT", 7860)))
IS_PRODUCTION = os.getenv("RENDER", "") != ""
FLASK_DEBUG = False if IS_PRODUCTION else os.getenv("FLASK_DEBUG", "true").lower() == "true"
GROQ_API_URL = "https://api.groq.com/openai/v1/chat/completions"
GROQ_MODEL_PRIMARY = "llama-3.1-8b-instant"
GROQ_MODEL_FALLBACK = "llama3-70b-8192"
GROQ_REQUEST_TIMEOUT = 30
ALLOWED_IMAGE_EXTS = {"jpg", "jpeg", "png", "webp"}
ALLOWED_VIDEO_EXTS = {"mp4", "avi", "mov", "mkv", "webm", "flv"}
IMAGE_FAKE_THRESHOLD = float(os.getenv("FAKE_THRESHOLD", "0.50"))
# ββ FACTORY βββββββββββββββββββββββββββββββββββββββββββββββββββ
def create_app() -> Flask:
app = Flask(
__name__,
static_folder=str(_ROOT / "static"),
template_folder=str(_ROOT)
)
app.secret_key = FLASK_SECRET_KEY
app.config["MAX_CONTENT_LENGTH"] = MAX_UPLOAD_MB * 1024 * 1024
HISTORY_FILE.parent.mkdir(parents=True, exist_ok=True)
# ββ CORS β allows Netlify / GitHub Pages to call this API β
CORS(app, resources={r"/api/*": {"origins": "*"}})
# ββ STATIC FRONTEND βββββββββββββββββββββββββββββββββββββββ
@app.route("/")
def index():
return send_from_directory(str(_ROOT), "index.html")
@app.route("/app")
def app_ui():
return send_from_directory(str(_ROOT), "app.html")
@app.route("/static/<path:filename>")
def static_files(filename):
return send_from_directory(str(_ROOT / "static"), filename)
# ββ HEALTH / STATUS βββββββββββββββββββββββββββββββββββββββ
@app.route("/health")
def health_check():
return jsonify({"status": "ok", "service": "flask"}), 200
@app.route("/api/status")
def api_status():
fastapi_ok = False
model_loaded = False
fastapi_detail = {}
try:
r = requests.get(f"{FASTAPI_BASE_URL}/health", timeout=4)
fastapi_detail = r.json()
fastapi_ok = r.status_code == 200
model_loaded = fastapi_detail.get("model_loaded", False)
except Exception as exc:
fastapi_detail = {"error": str(exc)}
return jsonify({
"flask": "ok",
"fastapi_url": FASTAPI_BASE_URL,
"fastapi_ok": fastapi_ok,
"model_loaded": model_loaded,
"fastapi_detail": fastapi_detail,
"groq_configured": bool(GROQ_API_KEY),
"sightengine_configured": False,
"pipeline": "cnn-only",
"fake_threshold": IMAGE_FAKE_THRESHOLD,
"max_upload_mb": MAX_UPLOAD_MB,
"environment": "production" if IS_PRODUCTION else "development",
"timestamp": datetime.utcnow().isoformat() + "Z",
})
# ββ PROXY: IMAGE ANALYSIS βββββββββββββββββββββββββββββββββ
@app.route("/api/analyse/image", methods=["POST"])
def analyse_image():
if "file" not in request.files:
return jsonify({"error": "No file part in request"}), 400
file = request.files["file"]
if not _allowed_file(file.filename, ALLOWED_IMAGE_EXTS):
return jsonify({"error": "Unsupported image type"}), 415
file_bytes = file.read()
# ββ Server-side 5 MB guard (second layer after frontend) ββ
max_bytes = MAX_UPLOAD_MB * 1024 * 1024
if len(file_bytes) > max_bytes:
return jsonify({
"error": f"File too large. Maximum allowed size is {MAX_UPLOAD_MB} MB. "
f"Received {len(file_bytes) / 1048576:.2f} MB."
}), 413
filename = secure_filename(file.filename or "upload.jpg")
try:
resp = requests.post(
f"{FASTAPI_BASE_URL}/analyse/image",
files={"file": (filename, io.BytesIO(file_bytes), file.content_type or "image/jpeg")},
timeout=60,
)
resp.raise_for_status()
result = resp.json()
_append_history(filename, result, "image")
return jsonify(result)
except requests.exceptions.ConnectionError:
return jsonify({
"error": (
"FastAPI backend is offline. "
"Start it with: uvicorn video_api:app --host 0.0.0.0 --port 8000"
)
}), 503
except requests.exceptions.Timeout:
return jsonify({"error": "CNN inference timed out."}), 504
except requests.exceptions.RequestException as exc:
return jsonify({"error": str(exc)}), 502
# ββ PROXY: VIDEO ANALYSIS βββββββββββββββββββββββββββββββββ
@app.route("/api/analyse/video", methods=["POST"])
def analyse_video():
if "file" not in request.files:
return jsonify({"error": "No file part in request"}), 400
file = request.files["file"]
if not _allowed_file(file.filename, ALLOWED_VIDEO_EXTS):
return jsonify({"error": "Unsupported video type"}), 415
file_bytes = file.read()
# ββ Server-side 5 MB guard ββββββββββββββββββββββββββββ
max_bytes = MAX_UPLOAD_MB * 1024 * 1024
if len(file_bytes) > max_bytes:
return jsonify({
"error": f"File too large. Maximum allowed size is {MAX_UPLOAD_MB} MB. "
f"Received {len(file_bytes) / 1048576:.2f} MB."
}), 413
filename = secure_filename(file.filename or "upload.mp4")
content_type = file.content_type or "video/mp4"
try:
resp = requests.post(
f"{FASTAPI_BASE_URL}/analyse/video",
files={"file": (filename, io.BytesIO(file_bytes), content_type)},
timeout=300,
)
resp.raise_for_status()
result = resp.json()
_append_history(filename, result, "video")
return jsonify(result)
except requests.exceptions.Timeout:
return jsonify({"error": "Video analysis timed out (300 s). Try a shorter clip."}), 504
except requests.exceptions.ConnectionError:
return jsonify({
"error": (
"FastAPI backend is offline. "
"Start it with: uvicorn video_api:app --host 0.0.0.0 --port 8000"
)
}), 503
except requests.exceptions.RequestException as exc:
return jsonify({"error": str(exc)}), 502
# ββ GROQ EXPLAIN ββββββββββββββββββββββββββββββββββββββββββ
@app.route("/api/groq/explain", methods=["POST"])
def groq_explain():
if not GROQ_API_KEY:
return jsonify({"error": "GROQ_API_KEY not configured on server"}), 503
data = request.get_json(silent=True) or {}
prompt = data.get("prompt", "").strip()
max_tokens = int(data.get("max_tokens", 400))
if not prompt:
return jsonify({"error": "prompt is required"}), 400
text, err = _call_groq(prompt, max_tokens)
if err:
return jsonify({"error": err}), 502
return jsonify({"text": text})
# ββ HISTORY βββββββββββββββββββββββββββββββββββββββββββββββ
@app.route("/api/history", methods=["GET"])
def get_history():
return jsonify(_load_history())
@app.route("/api/history", methods=["DELETE"])
def clear_history():
_save_history([])
return jsonify({"cleared": True})
# ββ ERROR HANDLERS ββββββββββββββββββββββββββββββββββββββββ
@app.errorhandler(413)
def too_large(e):
return jsonify({
"error": f"File too large. Maximum allowed size is {MAX_UPLOAD_MB} MB."
}), 413
@app.errorhandler(404)
def not_found(e):
return jsonify({"error": "Endpoint not found"}), 404
@app.errorhandler(500)
def server_error(e):
return jsonify({"error": "Internal server error", "detail": str(e)}), 500
return app
# ββ HELPERS βββββββββββββββββββββββββββββββββββββββββββββββββββ
def _allowed_file(filename: str, allowed: set) -> bool:
if not filename:
return False
ext = Path(filename).suffix.lstrip(".").lower()
return ext in allowed
def _call_groq(prompt: str, max_tokens: int = 400) -> tuple:
headers = {
"Authorization": f"Bearer {GROQ_API_KEY}",
"Content-Type": "application/json",
}
payload = {
"messages": [{"role": "user", "content": prompt}],
"max_tokens": max_tokens,
"temperature": 0.4,
}
for model_name in (GROQ_MODEL_PRIMARY, GROQ_MODEL_FALLBACK):
try:
r = requests.post(
GROQ_API_URL,
headers=headers,
json={**payload, "model": model_name},
timeout=GROQ_REQUEST_TIMEOUT,
)
if r.status_code in (400, 404):
continue
r.raise_for_status()
text = r.json()["choices"][0]["message"]["content"].strip()
return text, None
except requests.exceptions.HTTPError as exc:
status = exc.response.status_code
if status == 401:
return "", "Invalid GROQ_API_KEY"
if status == 429:
return "", "Groq rate limit reached β retry shortly"
if status == 503:
return "", "Groq service temporarily unavailable"
except requests.exceptions.Timeout:
return "", "Groq API request timed out"
except requests.exceptions.RequestException as exc:
return "", f"Network error: {exc}"
except (KeyError, IndexError):
return "", "Unexpected Groq response format"
return "", f"Both Groq models failed ({GROQ_MODEL_PRIMARY}, {GROQ_MODEL_FALLBACK})"
def _load_history() -> list:
try:
if HISTORY_FILE.exists():
return json.loads(HISTORY_FILE.read_text())
except Exception:
pass
return []
def _save_history(items: list) -> None:
try:
HISTORY_FILE.write_text(json.dumps(items, indent=2))
except Exception:
pass
def _append_history(filename: str, result: dict, media_type: str) -> None:
items = _load_history()
items.insert(0, {
"id": str(uuid.uuid4()),
"filename": filename,
"media_type": media_type,
"verdict": result.get("verdict", "unknown"),
"fake_prob": result.get("fake_probability", 0.0),
"timestamp": datetime.utcnow().isoformat() + "Z",
})
_save_history(items[:100])
# ββ ENTRY POINT βββββββββββββββββββββββββββββββββββββββββββββββ
if __name__ == "__main__":
app = create_app()
print(f"\nπ DeepScan Flask server starting on http://0.0.0.0:{PORT}")
print(f" Landing page : http://localhost:{PORT}/")
print(f" App interface : http://localhost:{PORT}/app")
print(f" FastAPI backend : {FASTAPI_BASE_URL}")
print(f" Groq configured : {'β
' if GROQ_API_KEY else 'β (add GROQ_API_KEY to .env)'}")
print(f" Pipeline : CNN-only (MobileNetV2 deepfake_model.h5)")
print(f" Fake threshold : {IMAGE_FAKE_THRESHOLD}")
print(f" Max upload size : {MAX_UPLOAD_MB} MB")
print(f" Environment : {'π Production (Render)' if IS_PRODUCTION else 'π» Development'}")
print(f" Debug mode : {FLASK_DEBUG}")
print(f" .env path : {_HERE / '.env'}\n")
app.run(host="0.0.0.0", port=PORT, debug=FLASK_DEBUG) |