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app.py

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+
+SYSTEM_PROMPT = "My primary function is to provide assessments for plants. These assessments are relevant, useful, and accurate. Keep in mind that I am user-friendly and professional."
+TITLE = "Plant Assessment Pro"
+EXAMPLE_INPUT = "Plant Health Assessment"
+import gradio as gr
+from gradio_client import Client
+import os
+import requests
+
+tulu = "https://tonic1-tulu.hf.space/--replicas/2l5qd/"
+
+
+def predict_beta(message, chatbot=[], system_prompt=""):
+    client = Client(tulu)
+
+    try:
+        max_new_tokens = 650
+        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}** using [Allen AI/Tulu](https://huggingface.co/allenai/tulu-2-dpo-13b) ! 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()