Update app.py

app.py

@@ -1,18 +1,16 @@
-# Use a pipeline as a high-level helper
-from transformers import pipeline
 import streamlit as st
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
-st.title("AI Chatbot")
+model_name = "deepseek-ai/DeepSeek-V3-Base"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True, quantization_config=None)
 
-st.write("Ask the AI a question and get an answer!")
+st.title("DeepSeek Chatbot")
 
-user_question = st.chat_input("Enter your question:")
+prompt = st.text_input("Enter your message:")
 
-messages = [
-    {"role": "user", "content": "Who are you?"},
-]
-pipe = pipeline("text-generation", model="deepseek-ai/DeepSeek-R1-Zero", trust_remote_code=True)
-pipe(messages)
-
-
-st.write(pipe(messages))
+if prompt:
+    inputs = tokenizer.encode(prompt, return_tensors="pt")
+    outputs = model.generate(inputs)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    st.write(response)