Update inference.py

inference.py

@@ -196,41 +196,33 @@ class CricketCommentator(nn.Module):
 
 # -------------------- PIPELINE --------------------
 
-def summarize_commentary(commentary, client):
-  prompt = f"""
+def summarize_commentary(commentary, client, video_duration, tts_speed):
+    prompt = f"""
 🔧 Final Optimized Prompt (Prompt-Engineered):
-
 You are a professional cricket commentary editor.
 You will receive raw cricket commentary text. It may contain grammar errors, unclear phrasing, or inconsistent tone.
-
 Your task is to:
-
-Rewrite it as a concise, broadcast-style commentary (1 sentence max).
-
-Keep it short and direct—describe the action and the outcome only. No exaggeration or filler.
-
-If no boundary (four/six) is mentioned, do not add one.
-
-Maintain proper punctuation and clarity for TTS (Text-to-Speech) delivery.
+- Rewrite it as a concise, broadcast-style commentary (1 sentence max).
+- Keep it short and direct—describe the action and the outcome only. No exaggeration or filler.
+- The final commentary must fit inside {(video_duration} seconds, assuming the speech rate is {tts_speed}x.
+- Maintain proper punctuation and clarity for TTS (Text-to-Speech) delivery.
 
 Output only the cleaned commentary. No extra text.
 Input:
 {commentary}
-
 Output:
 """
 
-
-
-
-  chat_completion = client.chat.completions.create(
+    chat_completion = client.chat.completions.create(
         messages=[{"role": "user", "content": prompt}],
         model="llama-3.1-8b-instant"
     )
-  print("="*50)
-  print(chat_completion.choices[0].message.content.strip())
-  print("="*50)
-  return chat_completion.choices[0].message.content.strip()
+
+    final = chat_completion.choices[0].message.content.strip()
+    print("="*50)
+    print(final)
+    print("="*50)
+    return final
 
 def text_to_speech(text, output_path, speed=1.3):
     raw_path = "raw_commentary.wav"