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app.py

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+
+SYSTEM_PROMPT = "Your bot's primary function is to have meaningful conversations about scooped bagels. Your prompts should be engaging, and should help users explore their thoughts and feelings about this delicious breakfast food."
+TITLE = "Bagel Buddy"
+EXAMPLE_INPUT = "How do you like your scooped bagels topped?"
+import gradio as gr
+from gradio_client import Client
+import os
+import requests
+
+tulu = "https://tonic1-tulu.hf.space/--replicas/ndrrr/"
+
+
+def predict_beta(message, chatbot=[], system_prompt=""):
+    client = Client(tulu)
+
+    try:
+        max_new_tokens = 800
+        temperature = 0.4
+        top_p = 0.9
+        repetition_penalty = 0.9
+        advanced = True
+
+        # Making the prediction
+        result = client.predict(
+            message,
+            system_prompt,
+            max_new_tokens,
+            temperature,
+            top_p,
+            repetition_penalty,
+            advanced,
+            fn_index=0
+        )
+        print("Raw API Response:", result)  # Debugging print
+        if result is not None:
+            print("Processed bot_message:", result)  # Debugging print
+            return result
+        else:
+            print("No response or empty response from the model.")  # Debugging print
+            return None
+            
+    except Exception as e:
+        error_msg = f"An error occurred: {str(e)}"
+        print(error_msg)  # Debugging print
+        return None
+
+def test_preview_chatbot(message, history):
+    response = predict_beta(message, history, SYSTEM_PROMPT)
+    return response
+
+
+welcome_preview_message = f"""
+Welcome to **{TITLE}**! Say something like: 
+
+''{EXAMPLE_INPUT}''
+"""
+
+chatbot_preview = gr.Chatbot(layout="panel", value=[(None, welcome_preview_message)])
+textbox_preview = gr.Textbox(scale=7, container=False, value=EXAMPLE_INPUT)
+
+demo = gr.ChatInterface(test_preview_chatbot, chatbot=chatbot_preview, textbox=textbox_preview)
+
+demo.launch()