Update app.py

app.py

@@ -5,13 +5,13 @@ import os
 import soundfile as sf
 import numpy as np
 import scipy.io.wavfile as wav
-from groq import Groq  # UPGRADE: Using the official Groq SDK to permanently fix 405 errors
+from groq import Groq
 from f5_tts.api import F5TTS
 
 # ==========================================
 # 1. System Setup & Configuration
 # ==========================================
-# Secure your newly generated dashboard token here
+# ⚠️ REMINDER: Update this key if your Groq organization remains restricted!
 GROQ_API_KEY = "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"
 voice_file = "my_voice_fixed.wav"
 
@@ -23,7 +23,6 @@ if not os.path.exists(voice_file):
     wav.write(voice_file, sample_rate, audio_data)
 
 print("Initializing Official Groq Client Subsystem...")
-# Initializes the official SDK parser securely
 groq_client = Groq(api_key=GROQ_API_KEY)
 
 print("Loading Lightweight Whisper Engine...")
@@ -50,7 +49,6 @@ print("All Speech Systems Fully Active!")
 # ==========================================
 def get_ai_answer(question):
     try:
-        # The SDK automatically handles the correct endpoint URL and payload layout under the hood
         chat_completion = groq_client.chat.completions.create(
             messages=[
                 {"role": "system", "content": "You are a professional voice simulation assistant. Keep answers short and under 30 words."},
@@ -60,10 +58,7 @@ def get_ai_answer(question):
             max_tokens=80,
             timeout=10
         )
-        
-        # Safe object extraction provided directly by the library
         return chat_completion.choices[0].message.content.strip()
-            
     except Exception as e:
         print(f"Groq SDK Exception Details: {e}")
         return f"Inference processing error occurred: {str(e)}"
@@ -76,8 +71,9 @@ def clone_and_speak(text):
         unique_filename = f"voice_output_{uuid.uuid4().hex[:8]}.wav"
         print(f"🔊 Rendering voice cloning track for text: '{text}'")
         
-        audio_data, sample_rate = f5tts.infer(
-            ref_audio=voice_file,
+        # FIXED: Changed ref_audio= to ref_file= to match the F5TTS API layout
+        audio_data, sample_rate, spectogram = f5tts.infer(
+            ref_file=voice_file,
             ref_text=auto_reference_text,
             gen_text=text
         )
@@ -90,7 +86,6 @@ def clone_and_speak(text):
         if os.path.exists(unique_filename) and os.path.getsize(unique_filename) > 0:
             print(f"🎉 Generated track successfully saved to: {unique_filename}")
             return unique_filename
-        
         return None
     except Exception as e:
         print(f"❌ Core TTS System Exception triggered: {e}")
@@ -107,7 +102,7 @@ def chatbot_engine(text_input, audio_input):
         question = text_input
     else:
         return "System Notification: Please enter a text question or record your microphone.", None
-
+        
     ai_text_response = get_ai_answer(question)
     generated_audio_track = clone_and_speak(ai_text_response)
     
@@ -125,7 +120,6 @@ with gr.Blocks(title="Rabbani A I voice clone") as interface:
             gr.Markdown("### 💬 Input Interaction Canvas")
             text_prompt_box = gr.Textbox(placeholder="Type your custom question query here...", label="Your Written Question")
             audio_prompt_box = gr.Audio(label="Or Record/Speak Your Question Directly", type="filepath")
-            
             submit_btn = gr.Button("Send Question to AI Engine", variant="primary")
             clear_btn = gr.ClearButton(value="Clear Inputs")
             
@@ -133,11 +127,11 @@ with gr.Blocks(title="Rabbani A I voice clone") as interface:
             gr.Markdown("### 📊 Cloned Output Responses")
             text_output_box = gr.Textbox(label="AI Answer Text Output", interactive=False)
             audio_output_player = gr.Audio(
-                label="Rendered Cloned Response Audio Player", 
-                type="filepath", 
+                label="Rendered Cloned Response Audio Player",
+                type="filepath",
                 interactive=False
             )
-
+            
     submit_btn.click(
         fn=chatbot_engine,
         inputs=[text_prompt_box, audio_prompt_box],