Update app.py

app.py

@@ -1,5 +1,7 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM
+import os
+import time
 
 # Load model and tokenizer
 tokenizer = AutoTokenizer.from_pretrained("TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T")
@@ -23,38 +25,44 @@ def generate_text(prompt, max_length=100, min_length=20, temperature=1.0):
 
     return generated_text
 
-with gr.Blocks() as demo:
-    chat_history = []
+def print_like_dislike(x: gr.LikeData):
+    print(x.index, x.value, x.liked)
+
+def add_text(history, text):
+    history = history + [(text, None)]
+    return history, gr.Textbox(value="", interactive=False)
+
+def bot(history):
+    user_input = history[-1][0]
+    generated_response = generate_text(user_input)
+    history[-1][1] = generated_response
+    time.sleep(0.5)
+    yield history
+
 
+with gr.Blocks() as demo:
     chatbot = gr.Chatbot(
-        chat_history,
+        [],
         elem_id="chatbot",
         bubble_full_width=False,
-        avatar_images=(None, None),  # You can add avatars if needed
-    )
-
-    user_input = gr.Textbox(
-        scale=4,
-        show_label=False,
-        placeholder="Type your message and press enter...",
-        container=False,
+        avatar_images=(None, (os.path.join(os.path.dirname(__file__), "avatar.png"))),
     )
 
-    def process_user_input(history, text):
-        history.append(("User", text))
-        return history, gr.Textbox(value="", interactive=False)
+    with gr.Row():
+        txt = gr.Textbox(
+            scale=4,
+            show_label=False,
+            placeholder="Enter text and press enter, or upload an image",
+            container=False,
+        )
 
-    user_input_msg = user_input.submit(
-        process_user_input, [chat_history, user_input], [chatbot, user_input], queue=False
+    txt_msg = txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
+        bot, chatbot, chatbot, api_name="bot_response"
     )
+    txt_msg.then(lambda: gr.Textbox(interactive=True), None, [txt], queue=False)
 
-    def generate_response(history):
-        last_user_input = [msg for msg in history if msg[0] == "User"][-1][1]
-        generated_response = generate_text(last_user_input)
-        history.append(("Chatbot", generated_response))
-        return history
-
-    user_input_msg.then(generate_response, [chat_history], queue=False)
+    chatbot.like(print_like_dislike, None, None)
 
+demo.queue()
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()