Update app.py

app.py

@@ -1,116 +1,46 @@
-# import gradio as gr
-# import whisper
-# import os
-# from groq import Groq
-
-# # 🔐 Get Groq API key securely from Hugging Face Secrets
-# GROQ_API_KEY = os.getenv("GROQ_API_KEY")
-# groq_client = Groq(api_key=GROQ_API_KEY)
-# MODEL_NAME = "llama3-8b-8192"
-
-# # 🎙 Load Whisper
-# transcriber = whisper.load_model("base")
-
-# def transcribe_and_summarize(audio):
-#     # Step 1: Transcribe + Detect Language
-#     result = transcriber.transcribe(audio)
-#     transcript = result["text"]
-#     detected_lang = result["language"]
-
-#     # Step 2: Summarize in the same language
-#     if detected_lang == "en":
-#         system_prompt = "You are an expert English summarizer."
-#         user_prompt = f"Please summarize the following English text:\n\n{transcript}"
-#     elif detected_lang == "ur":
-#         system_prompt = "آپ ایک ماہر خلاصہ نگار ہیں جو اردو میں خلاصہ فراہم کرتے ہیں۔"
-#         user_prompt = f"براہ کرم مندرجہ ذیل اردو متن کا خلاصہ فراہم کریں:\n\n{transcript}"
-#     else:
-#         system_prompt = "You are a helpful summarizer."
-#         user_prompt = f"Summarize this text:\n\n{transcript}"
-
-#     response = groq_client.chat.completions.create(
-#         model=MODEL_NAME,
-#         messages=[
-#             {"role": "system", "content": system_prompt},
-#             {"role": "user", "content": user_prompt}
-#         ]
-#     )
-#     summary = response.choices[0].message.content.strip()
-
-#     lang_label = "English" if detected_lang == "en" else "Urdu" if detected_lang == "ur" else detected_lang.upper()
-
-#     return f"[{lang_label}] {transcript}", f"[{lang_label}] {summary}"
-
-# demo = gr.Interface(
-#     fn=transcribe_and_summarize,
-#     inputs=gr.Audio(type="filepath", label="🎧 Upload Audio (English or Urdu)"),
-#     outputs=[
-#         gr.Textbox(label="📝 Transcript"),
-#         gr.Textbox(label="🧠 Summary")
-#     ],
-#     title="🗣️ Multilingual Audio Summarizer",
-#     description="Upload English or Urdu audio. The app transcribes and summarizes in the same language using Whisper + Groq."
-# )
-
-# demo.launch()
-
-
 import gradio as gr
+import whisper
 import os
 from groq import Groq
-from transformers import pipeline
-import torchaudio
 
-# 🔐 Groq API key from environment
+# 🔐 Get Groq API key securely from Hugging Face Secrets
 GROQ_API_KEY = os.getenv("GROQ_API_KEY")
 groq_client = Groq(api_key=GROQ_API_KEY)
 MODEL_NAME = "llama3-8b-8192"
 
-# ⚡ Use fast Whisper Tiny ASR model from Hugging Face
-asr = pipeline("automatic-speech-recognition", model="openai/whisper-tiny")
-
-# Limit audio duration to 5 mins (300 seconds)
-MAX_DURATION = 300
-
-def transcribe_and_summarize(audio_path):
-    try:
-        # Check audio duration
-        info = torchaudio.info(audio_path)
-        duration = info.num_frames / info.sample_rate
-        if duration > MAX_DURATION:
-            return "❌ Audio too long. Please upload audio under 5 minutes.", ""
-
-        # Transcribe using Whisper-tiny
-        result = asr(audio_path)
-        transcript = result["text"]
-        detected_lang = result.get("language", "en")  # fallback to 'en' if missing
-
-        # Summarize with Groq
-        if detected_lang == "en":
-            system_prompt = "You are an expert English summarizer."
-            user_prompt = f"Please summarize the following English text:\n\n{transcript}"
-        elif detected_lang == "ur":
-            system_prompt = "آپ ایک ماہر خلاصہ نگار ہیں جو اردو میں خلاصہ فراہم کرتے ہیں۔"
-            user_prompt = f"براہ کرم مندرجہ ذیل اردو متن کا خلاصہ فراہم کریں:\n\n{transcript}"
-        else:
-            system_prompt = "You are a helpful summarizer."
-            user_prompt = f"Summarize this text:\n\n{transcript}"
+# 🎙 Load Whisper
+transcriber = whisper.load_model("base")
+
+def transcribe_and_summarize(audio):
+    # Step 1: Transcribe + Detect Language
+    result = transcriber.transcribe(audio)
+    transcript = result["text"]
+    detected_lang = result["language"]
+
+    # Step 2: Summarize in the same language
+    if detected_lang == "en":
+        system_prompt = "You are an expert English summarizer."
+        user_prompt = f"Please summarize the following English text:\n\n{transcript}"
+    elif detected_lang == "ur":
+        system_prompt = "آپ ایک ماہر خلاصہ نگار ہیں جو اردو میں خلاصہ فراہم کرتے ہیں۔"
+        user_prompt = f"براہ کرم مندرجہ ذیل اردو متن کا خلاصہ فراہم کریں:\n\n{transcript}"
+    else:
+        system_prompt = "You are a helpful summarizer."
+        user_prompt = f"Summarize this text:\n\n{transcript}"
+
+    response = groq_client.chat.completions.create(
+        model=MODEL_NAME,
+        messages=[
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": user_prompt}
+        ]
+    )
+    summary = response.choices[0].message.content.strip()
+
+    lang_label = "English" if detected_lang == "en" else "Urdu" if detected_lang == "ur" else detected_lang.upper()
+
+    return f"[{lang_label}] {transcript}", f"[{lang_label}] {summary}"
 
-        response = groq_client.chat.completions.create(
-            model=MODEL_NAME,
-            messages=[
-                {"role": "system", "content": system_prompt},
-                {"role": "user", "content": user_prompt}
-            ]
-        )
-        summary = response.choices[0].message.content.strip()
-        lang_label = "English" if detected_lang == "en" else "Urdu" if detected_lang == "ur" else detected_lang.upper()
-        return f"[{lang_label}] {transcript}", f"[{lang_label}] {summary}"
-
-    except Exception as e:
-        return "❌ Error processing audio. Please try again.", str(e)
-
-# Gradio UI
 demo = gr.Interface(
     fn=transcribe_and_summarize,
     inputs=gr.Audio(type="filepath", label="🎧 Upload Audio (English or Urdu)"),
@@ -119,7 +49,9 @@ demo = gr.Interface(
         gr.Textbox(label="🧠 Summary")
     ],
     title="🗣️ Multilingual Audio Summarizer",
-    description="Upload English or Urdu audio (max 5 minutes). The app transcribes and summarizes using Whisper-Tiny + Groq."
+    description="Upload English or Urdu audio. The app transcribes and summarizes in the same language using Whisper + Groq."
 )
 
 demo.launch()
+
+