1

app.py

@@ -7,6 +7,7 @@ import tempfile
 import os
 import warnings
 from pydub import AudioSegment
+from datetime import datetime
 
 warnings.filterwarnings("ignore")
 
@@ -52,7 +53,7 @@ def analyze_voice_stress(audio_file_path):
     z_energy = (mean_energy - norm_mean_energy) / norm_std_energy
     z_speech_rate = (speech_rate - norm_speech_rate) / norm_std_speech_rate
     stress_score = (0.4 * z_f0) + (0.4 * z_speech_rate) + (0.2 * z_energy)
-    stress_level = float(1 / (1 + np.exp(-stress_score)) * 100)
+    stress_level = round(float(1 / (1 + np.exp(-stress_score)) * 100), 2)  # Rounded to 2 decimal places
     categories = ["Very Low Stress", "Low Stress", "Moderate Stress", "High Stress", "Very High Stress"]
     category_idx = min(int(stress_level / 20), 4)
     stress_category = categories[category_idx]
@@ -71,6 +72,9 @@ class StressResponse(BaseModel):
     stress_level: float
     category: str
     gender: str = None  # Optional, only for audio analysis
+    status: str
+    time: str
+    size: str
 
 @app.post("/analyze-stress/", response_model=StressResponse)
 async def analyze_stress(
@@ -89,12 +93,14 @@ async def analyze_stress(
             with tempfile.NamedTemporaryFile(delete=False, suffix=os.path.splitext(file.filename)[-1]) as temp_file:
                 temp_file.write(await file.read())
                 temp_audio_path = temp_file.name
+                file_size = os.path.getsize(temp_audio_path)
         else:
             if not (file_path.endswith(".wav") or file_path.endswith(".mp3")):
                 raise HTTPException(status_code=400, detail="Only .wav and .mp3 files are supported.")
             if not os.path.exists(file_path):
                 raise HTTPException(status_code=400, detail="File path does not exist.")
             temp_audio_path = file_path
+            file_size = os.path.getsize(file_path)
 
         # Convert MP3 to WAV if needed
         if temp_audio_path.endswith(".mp3"):
@@ -102,6 +108,11 @@ async def analyze_stress(
 
         try:
             result = analyze_voice_stress(temp_audio_path)
+            result.update({
+                "status": "Success",
+                "time": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
+                "size": f"{round(file_size / 1024, 2)} KB"  # Convert size to KB and round to 2 decimal places
+            })
             return JSONResponse(content=result)
         except Exception as e:
             raise HTTPException(status_code=500, detail=str(e))
@@ -113,6 +124,11 @@ async def analyze_stress(
     # Handle text analysis
     elif text:
         result = analyze_text_stress(text)
+        result.update({
+            "status": "Success",
+            "time": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
+            "size": "N/A"  # Size is not applicable for text input
+        })
         return JSONResponse(content=result)
 
 if __name__ == "__main__":