Create apps.py

apps.py

@@ -0,0 +1,79 @@
+import gradio as gr
+from transformers import pipeline
+from pathlib import Path
+import pandas as pd
+import spaces
+import random
+
+
+model_checkpoint = "HuggingFaceTB/SmolLM-360M"
+model = AutoModelForCausalLM.from_pretrained(model_checkpoint)
+tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
+
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, max_new_tokens=2048, repetition_penalty=1.2, temperature=0.4)
+
+
+abs_path = Path(__file__).parent
+
+df = pd.read_csv(str(abs_path / "models.csv"))
+df.to_html("tab.html")
+
+def refreshfn() -> gr.HTML:
+    df = pd.read_csv(str(abs_path / "models.csv"))
+    df.to_html("tab.html")
+    f = open("tab.html")
+    content = f.read()
+    f.close()
+    t = gr.HTML(content)
+    return t
+
+def chatfn(text):
+    return text, text
+
+with gr.Blocks() as demo:
+    gr.Markdown("""
+    # 🥇 Leaderboard Component
+    """)
+    with gr.Tabs():
+        with gr.Tab("Demo"):
+            f = open("tab.html")
+            content = f.read()
+            f.close()
+            t = gr.HTML(content)
+            btn = gr.Button("Refresh")
+            btn.click(fn=refreshfn, inputs=None, outputs=t)
+        with gr.Tab("Chats"):
+            import random
+            import time
+            with gr.Column():
+                chatbot = gr.Chatbot()
+            with gr.Column():
+                chatbot1 = gr.Chatbot()
+            msg = gr.Textbox()
+            clear = gr.ClearButton([msg, chatbot])
+            @spaces.GPU(duration=120)
+            def respond(message, chat_history):
+                response = pipe(message)
+                bot_message = response[0]["generated_text"]
+                chat_history.append((message, bot_message))
+                return "", chat_history
+
+            import concurrent.futures
+
+            def run_functions_simultaneously():
+                with concurrent.futures.ThreadPoolExecutor() as executor:
+                    # Submit the first function
+                    future1 = executor.submit(msg.submit, respond, [msg, chatbot], [msg, chatbot])
+                    
+                    # Submit the second function
+                    future2 = executor.submit(msg.submit, respond, [msg, chatbot1], [msg, chatbot1])
+                    
+                    # Wait for both futures to complete
+                    concurrent.futures.wait([future1, future2])
+
+            
+            # Call the function to run the tasks simultaneously
+            run_functions_simultaneously()
+
+if __name__ == "__main__":
+    demo.launch()