Initial verification chat setup

app.py

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+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()

requirements.txt

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+streamlit
+torch
+transformers