Upload app.py

app.py

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+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)