Delete app.py

app.py

@@ -1,134 +0,0 @@
-import gradio as gr
-from src.response.gpt import gpt_response
-from src.SpeechToText.sr import transcribe_audio, clear_history
-from src.SpeechToText.hamsa import transcribe_audio_hamsa
-from datetime import datetime
-from loguru import logger
-
-
-# Create Gradio Interface
-with gr.Blocks(title="Multilingual Speech to Text") as iface:
-    gr.Markdown("# 🎙️ Multilingual Speech to Text (Arabic & English)")
-    gr.Markdown("Speak in Arabic or English, or let the system auto-detect the language!")
-    
-    with gr.Row():
-        with gr.Column(scale=1):
-            language_selector = gr.Dropdown(
-                choices=[
-                    "English", 
-                    "Arabic", 
-                    "Arabic (Egypt)", 
-                    "Arabic (UAE)", 
-                    "Arabic (Lebanon)",
-                    "Arabic (Saudi Arabia)",
-                    "Arabic (Kuwait)",
-                    "Arabic (Jordan)",
-                    "Auto-detect"
-                ],
-                value="Auto-detect",
-                label="Select Language"
-            )
-            
-            audio_input = gr.Audio(
-                sources=["microphone", "upload"], 
-                type="filepath", 
-                label="🎤 Speak or Upload Audio"
-            )
-            
-            with gr.Row():
-                submit_btn = gr.Button("🔄 Transcribe", variant="primary")
-                clear_btn = gr.Button("🗑️ Clear History", variant="secondary")
-        
-        with gr.Column(scale=1):
-            current_output = gr.Textbox(
-                label="Current Transcription", 
-                placeholder="Your transcribed text will appear here...",
-                lines=3,
-                rtl=True  # Right-to-left for Arabic text
-            )
-            
-            gpt_output = gr.Textbox(
-                label="AI Therapeutic Response", 
-                placeholder="AI response will appear here...",
-                lines=5,
-                rtl=True,
-                interactive=False
-            )
-            
-            history_output = gr.Textbox(
-                label="Conversation History", 
-                placeholder="All transcriptions will be saved here with timestamps...",
-                lines=10,
-                max_lines=20,
-                interactive=False
-            )
-    
-    # State to maintain history
-    history_state = gr.State("")
-    
-    # Function to process transcription and get GPT response
-    def process_audio_and_respond(audio, language, history):
-        # Get transcription
-        try:
-            updated_history, current_text = transcribe_audio(audio, language, history)
-            logger.info(f"Transcription successful: {current_text}")
-        except Exception as e:
-            updated_history, current_text = transcribe_audio_hamsa(audio, language, history)
-            logger.error(f"Transcription failed. Apply Fallback with Hamsa API: {e}")
-            if not current_text:
-                current_text = "Transcription failed. Please try again."
-        
-        # Get GPT response if there's transcribed text
-        gpt_result = ""
-        if current_text and current_text.strip():
-            response = gpt_response(current_text)
-            gpt_result = f"Response: {response['response']} \n\nEmotion: {response['emotional_state']}"
-            
-            # Update history with both query and answer
-            
-            timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
-            detected_lang = response.get('detected_language', 'Unknown')
-            
-            # Format the history entry
-            history_entry = f"[{timestamp}] [{language}] [{detected_lang}]\n"
-            history_entry += f"Query: {current_text}\n"
-            history_entry += f"Answer: {response['response']}"
-            history_entry += "-----------------------\n\n"
-            
-            # Add to history
-            if updated_history:
-                updated_history = history_entry + updated_history
-            else:
-                updated_history = history_entry
-        
-        return updated_history, current_text, gpt_result
-    
-    # Event handlers
-    submit_btn.click(
-        fn=process_audio_and_respond,
-        inputs=[audio_input, language_selector, history_state],
-        outputs=[history_state, current_output, gpt_output]
-    ).then(
-        fn=lambda h: h,
-        inputs=[history_state],
-        outputs=[history_output]
-    )
-    
-    clear_btn.click(
-        fn=clear_history,
-        outputs=[history_state, history_output]
-    )
-    
-    # Auto-submit when audio is uploaded/recorded
-    audio_input.change(
-        fn=process_audio_and_respond,
-        inputs=[audio_input, language_selector, history_state],
-        outputs=[history_state, current_output, gpt_output]
-    ).then(
-        fn=lambda h: h,
-        inputs=[history_state],
-        outputs=[history_output]
-    )
-
-if __name__ == "__main__":
-    iface.launch(server_name="0.0.0.0", server_port=7860, share=True)