Delete app.py

app.py

@@ -1,76 +0,0 @@
-import streamlit as st
-from transformers import AutoTokenizer, AutoModelForCausalLM
-import torch
-
-def init_page():
-    st.set_page_config(
-        page_title="Verification Chat",
-        page_icon="🔍",
-        layout="centered"
-    )
-    st.title("AI Chat with Source Verification")
-    
-    # Initialize session state
-    if "messages" not in st.session_state:
-        st.session_state.messages = [
-            {"role": "assistant", "content": "Hello! How can I help you today?"}
-        ]
-    
-    if "model_name" not in st.session_state:
-        st.session_state.model_name = "facebook/opt-350m"
-
-def load_model():
-    # Add caching to prevent reloading model
-    @st.cache_resource
-    def get_model():
-        tokenizer = AutoTokenizer.from_pretrained(st.session_state.model_name)
-        model = AutoModelForCausalLM.from_pretrained(st.session_state.model_name)
-        return tokenizer, model
-    
-    return get_model()
-
-def get_response(prompt, tokenizer, model):
-    inputs = tokenizer(prompt, return_tensors="pt", max_length=512, truncation=True)
-    
-    with torch.no_grad():
-        outputs = model.generate(
-            inputs["input_ids"],
-            max_length=200,
-            num_return_sequences=1,
-            temperature=0.7,
-            pad_token_id=tokenizer.eos_token_id
-        )
-    
-    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    return response
-
-def display_messages():
-    for message in st.session_state.messages:
-        with st.chat_message(message["role"]):
-            st.write(message["content"])
-
-def main():
-    init_page()
-    tokenizer, model = load_model()
-    
-    # Display chat messages
-    display_messages()
-    
-    # Chat input
-    if prompt := st.chat_input("What's on your mind?"):
-        # Add user message
-        st.session_state.messages.append({"role": "user", "content": prompt})
-        
-        # Display user message
-        with st.chat_message("user"):
-            st.write(prompt)
-        
-        # Generate response
-        with st.chat_message("assistant"):
-            with st.spinner("Thinking..."):
-                response = get_response(prompt, tokenizer, model)
-                st.write(response)
-                st.session_state.messages.append({"role": "assistant", "content": response})
-
-if __name__ == "__main__":
-    main()