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import modal
from utils.youtube_utils import download_youtube_video
from reports.pdf_report import generate_pdf_report
last_face_result = ""
last_voice_result = ""
last_video_results = []
verify_faces_remote = modal.Function.lookup("deepface-agent", "verify_faces_remote")
verify_voices_remote = modal.Function.lookup("deepface-agent", "verify_voices_remote")
verify_faces_in_video_remote = modal.Function.lookup(
"deepface-agent", "verify_faces_in_video_remote"
)
def compare_faces(img1_path: str, img2_path: str) -> str:
"""Use this tool to compare to faces for a match
Args:
img1_path: The path to the first image
img2_path: The path to the second image
"""
global last_face_result
# Read image files as bytes
with open(img1_path, "rb") as f1, open(img2_path, "rb") as f2:
img1_bytes = f1.read()
img2_bytes = f2.read()
result = verify_faces_remote.remote(img1_bytes, img2_bytes)
result_text = ""
if "error" in result:
return f"❌ Error: {result['error']}"
if result["verified"]:
result_text = f"✅ Match! Distance: {result['distance']:.4f} (Threshold: {result['threshold']})"
last_face_result = result_text
return result_text
else:
result_text = f"❌ No Match. Distance: {result['distance']:.4f} (Threshold: {result['threshold']})"
last_face_result = result_text
return result_text
def compare_voices(audio1: str, audio2: str) -> str:
"""Use this tool to compare two voices for a match
Args:
audio1: The path to the first audio file
audio2: The path to the second audio file
"""
global last_voice_result
try:
with open(audio1, "rb") as a1, open(audio2, "rb") as a2:
audio1_bytes = a1.read()
audio2_bytes = a2.read()
result = verify_voices_remote.remote(audio1_bytes, audio2_bytes)
result_text = ""
if "error" in result:
return f"❌ Error: {result['error']}"
if result["match"]:
result_text = f"✅ Same speaker detected. Similarity: {result['similarity']} (Threshold: {result['threshold']})"
last_voice_result = result_text
return result_text
else:
result_text = f"❌ Different speakers. Similarity: {result['similarity']} (Threshold: {result['threshold']})"
last_voice_result = result_text
return result_text
except Exception as e:
return f"❌ Error reading audio files: {str(e)}"
def scan_video(video_file: str, ref_img: str, youtube_url="") -> str:
"""Use this tool to scan a video for deepfake face swaps
Args:
video_file: The path to the video file
ref_img: The path to the reference image
youtube_url: The YouTube URL (optional)
"""
global last_video_results
if youtube_url:
try:
video_file = download_youtube_video(youtube_url)
except Exception as e:
return f"❌ Error downloading YouTube video: {str(e)}"
with open(video_file, "rb") as vf, open(ref_img, "rb") as rf:
video_bytes = vf.read()
ref_img_bytes = rf.read()
try:
results = verify_faces_in_video_remote.remote(video_bytes, ref_img_bytes, interval=30)
except Exception as e:
return f"❌ Error processing video: {str(e)}"
report = ""
last_video_results = results
for r in results:
if "error" in r:
report += f"\n⚠️ Frame {r['frame']}: {r['error']}"
else:
status = "✅ Match" if r["verified"] else "❌ Mismatch"
report += f"\n🖼 Frame {r['frame']}: {status} (Distance: {r['distance']})"
return report
def generate_report():
return generate_pdf_report(last_face_result, last_voice_result, last_video_results) |