Update requirements.txt

requirements.txt

@@ -1,55 +1,10 @@
 huggingface_hub==0.25.2
 
-
-# app.py
-import gradio as gr
-from eeg_model import simulate_eeg_data, predict_mental_state
-from generative_model import generate_response
-from audio_utils import record_audio
-from tts_utils import nigerian_accent_tts
-from conversation_memory import ConversationMemory
-
-memory = ConversationMemory()
-
-# Logic
-def chat(user_text=None, record_audio_flag=False):
-    if record_audio_flag:
-        user_text = record_audio()
-
-    if not user_text:
-        return "No input detected.", None
-
-    # 1. Predict mental state
-    eeg_features = simulate_eeg_data()
-    mental_state = predict_mental_state(eeg_features)
-
-    # 2. Generate response with memory
-    history = memory.get_formatted_history()
-    ai_response = generate_response(mental_state, user_text, history)
-    
-    # 3. Update memory
-    memory.add_exchange(user_input=user_text, bot_response=ai_response)
-    
-    # 4. Nigerian Accent TTS
-    nigerian_accent_tts(ai_response, mental_state)
-
-    return ai_response, "response.mp3"
-
-# Gradio app
-with gr.Blocks() as demo:
-    gr.Markdown("# EEG Mental State Chatbot with Nigerian Voice (Upgraded)")
-    
-    with gr.Row():
-        user_input = gr.Textbox(label="Type your message")
-        record_audio_flag = gr.Checkbox(label="Use Microphone?", value=False)
-    
-    with gr.Row():
-        submit_btn = gr.Button("Send")
-    
-    with gr.Row():
-        chatbot_response = gr.Textbox(label="Chatbot response")
-        chatbot_audio = gr.Audio(label="Chatbot voice", type="filepath")
-
-    submit_btn.click(chat, inputs=[user_input, record_audio_flag], outputs=[chatbot_response, chatbot_audio])
-
-demo.launch()
+gradio
+speechrecognition
+pyaudio
+gtts
+playsound
+joblib
+scikit-learn
+transformers