Create app.py

app.py

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+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model_id = "komal/depression-chatbot-model"  # replace with your model path
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id).to(device)
+model.eval()
+
+user_history = []
+turn_counter = 0
+MAX_TURNS_FOR_PREDICTION = 8
+
+def chat(user_input):
+    global user_history, turn_counter
+    turn_counter += 1
+
+    user_history.append(f"Human: {user_input}")
+    last_turns = user_history[-4:]
+    prompt = "\n".join(last_turns) + "\nAI:"
+
+    inputs = tokenizer(prompt, return_tensors="pt").to(device)
+    output_ids = model.generate(
+        **inputs,
+        max_new_tokens=50,
+        do_sample=False,
+        pad_token_id=tokenizer.eos_token_id,
+        eos_token_id=tokenizer.eos_token_id,
+    )
+    response_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
+    response = response_text.split("AI:")[-1].strip()
+    user_history.append(f"AI: {response}")
+
+    depression_prob = None
+    if turn_counter == MAX_TURNS_FOR_PREDICTION:
+        prediction_prompt = (
+            "\n".join(user_history[-8:]) +
+            "\nAI: Based on this conversation, what is the probability that the human has depression? "
+            "Please answer with a number between 0 and 1."
+        )
+        inputs_pred = tokenizer(prediction_prompt, return_tensors="pt").to(device)
+        output_pred_ids = model.generate(
+            **inputs_pred,
+            max_new_tokens=10,
+            do_sample=False,
+            pad_token_id=tokenizer.eos_token_id,
+            eos_token_id=tokenizer.eos_token_id,
+        )
+        pred_text = tokenizer.decode(output_pred_ids[0], skip_special_tokens=True)
+
+        import re
+        match = re.search(r"0?\.\d+", pred_text)
+        if match:
+            try:
+                depression_prob = float(match.group(0))
+            except:
+                depression_prob = None
+
+    return response, depression_prob
+
+chat_interface = gr.Interface(
+    fn=chat,
+    inputs=gr.Textbox(label="User Input"),
+    outputs=[
+        gr.Textbox(label="Bot Response"),
+        gr.Textbox(label="Depression Probability (after 8 turns)")
+    ],
+    title="Depression Detection Chatbot",
+    description="This chatbot detects depression by conversing for multiple turns. After 8 turns, it estimates the probability of depression."
+)
+
+chat_interface.launch()