Update app.py

app.py

@@ -1,5 +1,5 @@
 from fastai.text.all import *
-from transformers import AutoModelForSequenceClassification, AutoTokenizer, AutoModelForCausalLM, BlenderbotTokenizer
+from transformers import AutoModelForSequenceClassification, AutoTokenizer, BlenderbotForConditionalGeneration, BlenderbotTokenizer
 import torch
 import gradio as gr
 
@@ -15,7 +15,7 @@ def classify_medical_text(txt):
     return dict(zip(medical_categories, map(float, probs)))
 
 # Load the psychiatric model from Hugging Face
-psychiatric_model_name = "nlp4good/psych-search"  # Replace with the appropriate model
+psychiatric_model_name = "mental/mental-bert-base-uncased"  # Replace with the appropriate model
 psychiatric_tokenizer = AutoTokenizer.from_pretrained(psychiatric_model_name)
 psychiatric_model = AutoModelForSequenceClassification.from_pretrained(psychiatric_model_name)
 
@@ -31,10 +31,10 @@ def classify_psychiatric_text(txt):
     probabilities = torch.softmax(logits, dim=1).squeeze().tolist()
     return dict(zip(psychiatric_labels, probabilities))
 
-# Load DialoGPT-medium
-model_name = "microsoft/DialoGPT-medium"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name)
+# Load BlenderBot for Lifestyle and Nutrition Chatbot
+blender_model_name = "facebook/blenderbot-3B"  # Pre-trained BlenderBot 3B model
+blender_tokenizer = BlenderbotTokenizer.from_pretrained(blender_model_name)
+blender_model = BlenderbotForConditionalGeneration.from_pretrained(blender_model_name)
 
 # Chat function for Lifestyle and Nutrition
 chat_history = []
@@ -61,7 +61,7 @@ psychiatric_text = gr.Textbox(lines=2, label='Describe your mental health concer
 psychiatric_label = gr.Label()
 psychiatric_examples = ['I feel hopeless and have no energy.', 'I am unable to concentrate and feel anxious all the time.', 'I have recurring intrusive thoughts.']
 
-lifestyle_chatbot = gr.Chatbot(label="Chat with me about your health and nutrition!")
+lifestyle_chatbot = gr.Chatbot(label="Chat with me about diet and nutrition!")
 lifestyle_msg = gr.Textbox(placeholder="Ask your question here...", label="Your Question")
 lifestyle_clear = gr.Button("Clear Chat")
 
@@ -72,6 +72,17 @@ def user_message(input_text):
     lifestyle_chatbot.append((input_text, response))
     return lifestyle_chatbot, ""
 
+# Lifestyle & Nutrition Interface
+lifestyle_interface = gr.Interface(
+    fn=user_message,
+    inputs=[lifestyle_msg],
+    outputs=[lifestyle_chatbot, lifestyle_msg],
+    live=True,
+    title="Nutritionist Chatbot",
+    description="Ask me anything about diet, food, and nutrition!"
+)
+
+# Medical Diagnosis Interface
 medical_interface = gr.Interface(
     fn=classify_medical_text,
     inputs=medical_text,
@@ -80,6 +91,7 @@ medical_interface = gr.Interface(
     description=medical_description,
 )
 
+# Psychiatric Analysis Interface
 psychiatric_interface = gr.Interface(
     fn=classify_psychiatric_text,
     inputs=psychiatric_text,
@@ -87,25 +99,11 @@ psychiatric_interface = gr.Interface(
     examples=psychiatric_examples,
     description=psychiatric_description,
 )
-lifestyle_interface = gr.Interface(
-    fn=user_message,
-    inputs=[lifestyle_msg],
-    outputs=[lifestyle_chatbot, lifestyle_msg],
-    live=True,
-    title="Lifestyle and Nutrition Chatbot",
-    description="Ask me anything about fitness, nutrition, or wellness!"
-)
-
-with gr.Blocks() as lifestyle_interface:
-    gr.Markdown("## Lifestyle and Nutrition Chatbot")
-    gr.Markdown("Ask me anything about fitness, nutrition, or wellness!")
-    lifestyle_msg.submit(user_message, inputs=[lifestyle_msg], outputs=[lifestyle_chatbot, lifestyle_msg])
-    lifestyle_clear.click(clear_chat, outputs=[lifestyle_chatbot])
 
 # Combine interfaces using Tabs
 app = gr.TabbedInterface(
     [medical_interface, psychiatric_interface, lifestyle_interface],
-    ["Medical Diagnosiss", "Psychiatric Analysis", "Lifestyle & Nutrition Chat"]
+    ["Medical Diagnosis", "Psychiatric Analysis", "Lifestyle & Nutrition Chat"]
 )
 
-app.launch(inline=False)
+app.launch(inline=False)