Update app.py

app.py

@@ -84,7 +84,7 @@ def analyze_sentiment(text):
     response = grog_client.chat.completions.create(
         model="llama3-8b-8192",    # Specify the model to be used for generating the completion
         messages=[
-            {"role": "system", "content": "Analyze the sentiment of this text and return only 'Positive', 'Negative', or 'Neutral'."},
+            {"role": "system", "content": "You are an expert in text sentiment analysis. Analyze the sentiment of this text and return only 'Positive', 'Negative', or 'Neutral'."},
             {"role": "user", "content": text}
         ],
         temperature=0.0,  # Control the randomness of the output (0.0 means deterministic output)
@@ -404,6 +404,9 @@ def process_video_gradio(video_path):
 
         segment_text = transcribe_audio(segment_path)         # CALL transcribe audio using Groq Whisper
         #segment_text = transcribe_audio_azure(segment_path)  # CALL transcribe audio using Azure Whisper
+
+        # Insert segment number inside the text for easy comparison with Sentiment Trend
+        segment_text = f"[{i}] {segment_text}"  
         transcribed_text += segment_text + "\n"   # added new line for display purpose
         preprocess_text(segment_text)