Update app.py

app.py

@@ -1,30 +1,23 @@
 import gradio as gr
 from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, pipeline
 
-# Path to the uploaded model folder
-model_path = "model"
-
-# Load model and tokenizer
+# Load your model
+model_path = "./model"  # your uploaded folder
 tokenizer = AutoTokenizer.from_pretrained(model_path)
 model = AutoModelForSeq2SeqLM.from_pretrained(model_path)
+chat_pipeline = pipeline("text2text-generation", model=model, tokenizer=tokenizer)
 
-# Create text2text-generation pipeline
-generator = pipeline("text2text-generation", model=model, tokenizer=tokenizer)
-
-# Define Gradio interface function
-def ask_question(question):
-    result = generator(question, max_new_tokens=100)
-    return result[0]['generated_text']
+# Function to handle chat
+def chat_with_bot(history, user_message):
+    response = chat_pipeline(user_message)[0]['generated_text']
+    history.append((user_message, response))
+    return history, ""
 
-# Gradio interface
-iface = gr.Interface(
-    fn=ask_question,
-    inputs=gr.Textbox(lines=2, placeholder="Ask anything..."),
-    outputs=gr.Textbox(),
-    title="FPV2 Chatbot",
-    description="Ask questions and get answers from the FPV2 model."
-)
+# Gradio UI
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox(placeholder="Type your message here...")
+    msg.submit(chat_with_bot, [chatbot, msg], [chatbot, msg])
 
-# Launch the interface
-iface.launch(server_name="0.0.0.0", server_port=7860)
+demo.launch(server_name="0.0.0.0", server_port=7860)