Create app.py

app.py

@@ -4,14 +4,13 @@ import torch
 from transformers import pipeline
 import speech_recognition as sr
 from gtts import gTTS
-from pydub import AudioSegment
 from io import BytesIO
 
 # Set your Hugging Face API key
-os.environ["HUGGINGFACEHUB_API_TOKEN"] = "doctor app"
+os.environ["HUGGINGFACEHUB_API_TOKEN"] = "your_hugging_face_api_key"
 
-# Load the Hugging Face model
-chatbot = pipeline("conversational", model="thrishala/mental_health_chatbot")
+# Load the Hugging Face model using text-generation
+chatbot = pipeline("text-generation", model="thrishala/mental_health_chatbot")
 
 # Function to get voice input using Whisper
 def get_voice_input():
@@ -48,7 +47,7 @@ if st.button("Speak"):
     if user_input:
         st.write(f"You: {user_input}")
         # Get response from the chatbot
-        response = chatbot(user_input)[0]['generated_text']
+        response = chatbot(user_input, max_length=150, num_return_sequences=1)[0]['generated_text']
         st.write(f"Bot: {response}")
         # Generate voice response
         audio_output = speak(response)
@@ -60,7 +59,7 @@ if st.button("Send"):
     if user_input:
         st.write(f"You: {user_input}")
         # Get response from the chatbot
-        response = chatbot(user_input)[0]['generated_text']
+        response = chatbot(user_input, max_length=150, num_return_sequences=1)[0]['generated_text']
         st.write(f"Bot: {response}")
         # Generate voice response
         audio_output = speak(response)