Update app.py

app.py

@@ -2,32 +2,28 @@ import streamlit as st
 from transformers import pipeline
 import torch 
 
-MODEL_PATH = "HuggingFaceH4/zephyr-7b-beta"
 
 def main():
     st.title("Chatbot with Hugging Face Model")
 
-    # Check if the model is already saved locally
-    try:
-        pipe = pipeline("text-generation", model=MODEL_PATH, torch_dtype=torch.bfloat16, device_map="auto")
-    except:
-        # If not saved, load the model and save it
-        st.warning("Model not found locally. Downloading and saving the model. Please wait...")
-        pipe = pipeline("text-generation", model="HuggingFaceH4/zephyr-7b-beta", torch_dtype=torch.bfloat16, device_map="auto")
-        pipe.save_pretrained(MODEL_PATH)
+    # If not saved, load the model and save it
+    pipe = pipeline("text-generation", model="HuggingFaceH4/zephyr-7b-beta", torch_dtype=torch.bfloat16, device_map="auto")
 
+
+    user_input = st.text_area("Enter Text")
     # Define chat messages
     messages = [
-        {"role": "system", "content": "You are a friendly chatbot who always responds in the style of a pirate"},
-        {"role": "user", "content": st.text_input("User Input", "How many helicopters can a human eat in one sitting?")},
+        {"role": "system", "content": "You are a friendly chatbot who always responds in kind way."},
+        {"role": "user", "content": user_input},
     ]
-
-    # Generate response
-    prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
-    outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
-
-    # Display generated text
-    st.text(outputs[0]["generated_text"])
+    submit = st.button('Generate')
+    if submit:
+        # Generate response
+        prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+        outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+    
+        # Display generated text
+        st.text(outputs[0]["generated_text"])
 
 if __name__ == "__main__":
     main()