Update src/main.py

src/main.py

@@ -73,6 +73,10 @@ app.include_router(prompt_injection.router, prefix="/api", tags=["prompt_injecti
 # Routes - Mitigation Reports
 app.include_router(mitigation.router, prefix="/api", tags=["mitigation"])
 
+# Routes - Authentication
+from .api import auth
+app.include_router(auth.router, prefix="/auth", tags=["auth"])
+
 from .services.voice_history_manager import voice_history_manager
 
 @app.get("/api/voice/history", tags=["Voice"])
@@ -84,9 +88,16 @@ async def get_voice_history():
         logger.error(f"Error fetching voice history: {e}")
         raise HTTPException(status_code=500, detail="Failed to fetch voice history")
 
-# Routes - Authentication
-from .api import auth
-app.include_router(auth.router, prefix="/auth", tags=["auth"])
+
+@app.get("/api/events", tags=["Real-time"])
+async def stream_events():
+    """
+    Server-Sent Events (SSE) endpoint to stream real-time threat alerts.
+    """
+    return StreamingResponse(
+        event_hub.subscribe(),
+        media_type="text/event-stream"
+    )
 
 
 # Routes - Deepfake Detection
@@ -127,7 +138,10 @@ async def detect_audio_deepfake(file: UploadFile = File(...)):
 
         # Detect deepfake
         logger.info(f"Analyzing audio file: {file.filename}")
-        result = detector.detect_audio_deepfake(temp_file)
+        loop = asyncio.get_event_loop()
+        result = await loop.run_in_executor(
+            None, detector.detect_audio_deepfake, temp_file
+        )
 
         return DeepfakeResponse(
             is_deepfake=result.get("is_deepfake"),
@@ -191,7 +205,10 @@ async def detect_video_deepfake(file: UploadFile = File(...)):
 
         # Detect deepfake
         logger.info(f"Analyzing video file: {file.filename}")
-        result = detector.detect_video_deepfake(temp_file)
+        loop = asyncio.get_event_loop()
+        result = await loop.run_in_executor(
+            None, detector.detect_video_deepfake, temp_file
+        )
 
         return DeepfakeResponse(
             is_deepfake=result.get("is_deepfake"),
@@ -254,7 +271,10 @@ async def detect_image_deepfake(file: UploadFile = File(...)):
 
         # Detect deepfake
         logger.info(f"Analyzing image file: {file.filename}")
-        result = detector.detect_image_deepfake(temp_file)
+        loop = asyncio.get_event_loop()
+        result = await loop.run_in_executor(
+            None, detector.detect_image_deepfake, temp_file
+        )
 
         return DeepfakeResponse(
             is_deepfake=result.get("is_deepfake"),
@@ -306,12 +326,19 @@ async def detect_deepfake(file: UploadFile = File(...)):
         file_ext = Path(file.filename).suffix.lower()
         logger.info(f"Detecting type for: {file.filename} ({file_ext})")
 
+        loop = asyncio.get_event_loop()
         if file_ext in [".mp3", ".wav", ".ogg", ".m4a", ".flac"]:
-            result = detector.detect_audio_deepfake(temp_file)
+            result = await loop.run_in_executor(
+                None, detector.detect_audio_deepfake, temp_file
+            )
         elif file_ext in [".mp4", ".avi", ".mkv", ".mov", ".webm"]:
-            result = detector.detect_video_deepfake(temp_file)
+            result = await loop.run_in_executor(
+                None, detector.detect_video_deepfake, temp_file
+            )
         elif file_ext in [".jpg", ".jpeg", ".png", ".webp", ".avif"]:
-            result = detector.detect_image_deepfake(temp_file)
+            result = await loop.run_in_executor(
+                None, detector.detect_image_deepfake, temp_file
+            )
         else:
             return DeepfakeResponse(
                 is_deepfake=None,
@@ -319,16 +346,33 @@ async def detect_deepfake(file: UploadFile = File(...)):
                 error=f"Unsupported file format: {file_ext}",
             )
 
+        # Determine media type for reasoning engine
+        audio_exts = [".mp3", ".wav", ".ogg", ".m4a", ".flac"]
+        video_exts = [".mp4", ".avi", ".mkv", ".mov", ".webm"]
+        image_exts = [".jpg", ".jpeg", ".png", ".webp", ".avif"]
+        if file_ext in audio_exts:
+            media_type = "audio"
+        elif file_ext in video_exts:
+            media_type = "video"
+        elif file_ext in image_exts:
+            media_type = "image"
+        else:
+            media_type = "unknown"
+
+        # Run LLM reasoning on top of ML detection
+        result = await analyze_with_reasoning(result, media_type)
 
         return DeepfakeResponse(
             is_deepfake=result.get("is_deepfake"),
             confidence=result.get("confidence", 0.0),
             message=result.get("message"),
             error=result.get("error"),
+            reasoning=result.get("reasoning"),
+            key_factors=result.get("key_factors"),
             details={
                 k: v
                 for k, v in result.items()
-                if k not in ["is_deepfake", "confidence", "message", "error"]
+                if k not in ["is_deepfake", "confidence", "message", "error", "reasoning", "key_factors"]
             },
         )