Update app.py

app.py

@@ -2,28 +2,41 @@ import gradio as gr
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
 # Load your fine-tuned GPT-2 model from Hugging Face
-MODEL_NAME = "hackergeek98/finetuned-gpt2"  # Replace with your model
+MODEL_NAME = "hackergeek98/therapist"  # Replace with your model
 tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
 model = AutoModelForCausalLM.from_pretrained(MODEL_NAME)
 
+# Initialize conversation history
+conversation_history = ""
+
 # Function to generate responses
 def generate_response(user_input):
-    # Tokenize the input
-    inputs = tokenizer(user_input, return_tensors="pt")
+    global conversation_history
+
+    # Update conversation history with user input
+    conversation_history += f"User: {user_input}\n"
+    
+    # Tokenize the conversation history
+    inputs = tokenizer(conversation_history, return_tensors="pt", truncation=True, max_length=1024)
 
-    # Generate a response
-    outputs = model.generate(inputs['input_ids'], max_length=1000, num_return_sequences=1, no_repeat_ngram_size=2)
+    # Generate a response from the model
+    outputs = model.generate(inputs['input_ids'], max_length=1024, num_return_sequences=1, no_repeat_ngram_size=2)
 
-    # Decode the output and return the result
+    # Decode the model's output
     response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+    # Update conversation history with the model's response
+    conversation_history += f"Therapist: {response}\n"
+
+    # Return the therapist's response
     return response
 
 # Create Gradio interface
 interface = gr.Interface(fn=generate_response,
-                         inputs=gr.Textbox(label="Enter your message"),
-                         outputs=gr.Textbox(label="Therapist Response"),
+                         inputs=gr.Textbox(label="Enter your message", lines=2),
+                         outputs=gr.Textbox(label="Therapist Response", lines=2),
                          title="Virtual Therapist",
-                         description="A fine-tuned GPT-2 model acting as a virtual therapist.")
+                         description="A fine-tuned GPT-2 model acting as a virtual therapist. Chat with the model and receive responses as if you are talking to a therapist.")
 
 # Launch the app
 interface.launch()