Update app.py

app.py

@@ -1,28 +1,23 @@
-# app.py — Gradio Chat UI for EvoDecoder + Web Search (RAG)
 import gradio as gr
-from generate import generate_response
+import torch
+from transformers import GPT2Tokenizer
+from evo_model import EvoDecoderModel
+from generate import generate_text
 
-def chat_fn(message, history, web_flag):
-    response = generate_response(message, use_web=web_flag)
-    history.append((message, response))
-    return "", history
+# Load tokenizer and model
+tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
+vocab_size = tokenizer.vocab_size
 
-with gr.Blocks(title="EvoDecoder RAG Chat") as demo:
-    gr.Markdown("# 🤖 EvoDecoder RAG Chatbot")
-    with gr.Row():
-        chatbot = gr.Chatbot(height=450)
-        with gr.Column(scale=0.3):
-            web_toggle = gr.Checkbox(label="Use Web Search (RAG)", value=True)
-            clear_btn = gr.Button("🧹 Clear Chat")
+model = EvoDecoderModel(vocab_size)
+model.load_state_dict(torch.load("evo_decoder.pt", map_location="cpu"))
+model.eval()
 
-    with gr.Row():
-        msg_box = gr.Textbox(placeholder="Ask Evo something...", scale=4)
-        submit_btn = gr.Button("Send", scale=1)
+def chat_with_evo(prompt):
+    response = generate_text(model, tokenizer, prompt)
+    return response
 
-    history_state = gr.State([])
-
-    submit_btn.click(fn=chat_fn, inputs=[msg_box, history_state, web_toggle], outputs=[msg_box, chatbot])
-    msg_box.submit(fn=chat_fn, inputs=[msg_box, history_state, web_toggle], outputs=[msg_box, chatbot])
-    clear_btn.click(fn=lambda: ([], ""), outputs=[chatbot, history_state])
-
-demo.launch()
+gr.Interface(fn=chat_with_evo, 
+             inputs="text", 
+             outputs="text", 
+             title="🧠 EvoDecoder Chatbot",
+             description="Ask Evo anything. Powered by your trained EvoDecoder.").launch()