Update app.py

app.py

@@ -1,26 +1,50 @@
 import gradio as gr
-from transformers import pipeline
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
 
-# Create text-generation pipeline with explicit truncation.
-generator = pipeline(
-    "text-generation",
-    model="gpt2",
-    max_length=100,
-    truncation=True  # important
-)
+# Load the DeepSeek R1 model and tokenizer
+model_name = "deepseek-ai/deepseek-r1"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
 
-def chatbot(prompt):
-    # Generate text with the pipeline, also specifying truncation at call time (optional).
-    responses = generator(prompt, max_length=100, truncation=True)
-    return responses[0]["generated_text"]
+def chat_with_deepseek(user_input, history):
+    # Combine the history with the new user input
+    full_input = "\n".join(history + [user_input])
+    
+    # Tokenize the input
+    inputs = tokenizer(full_input, return_tensors="pt")
+    
+    # Generate a response
+    outputs = model.generate(inputs.input_ids, max_length=150, num_return_sequences=1)
+    
+    # Decode the response
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    
+    # Update the history with the new interaction
+    history.append(user_input)
+    history.append(response)
+    
+    return response, history
 
-demo = gr.Interface(
-    fn=chatbot,
-    inputs="text",
-    outputs="text",
-    title="Hugging Face GPT-2 Chatbot",
-    description="Ask anything to the GPT-2-based model!"
-)
+# Create the Gradio interface
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox()
+    clear = gr.Button("Clear")
+    
+    def user(user_message, history):
+        return "", history + [[user_message, None]]
+    
+    def bot(history):
+        user_message = history[-1][0]
+        response, _ = chat_with_deepseek(user_message, [h[0] for h in history])
+        history[-1][1] = response
+        return history
+    
+    msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
+        bot, chatbot, chatbot
+    )
+    clear.click(lambda: None, None, chatbot, queue=False)
 
-if __name__ == "__main__":
-    demo.launch()
+# Launch the Gradio app
+demo.launch()