Update maker.py

maker.py

@@ -3,6 +3,7 @@ import requests
 import json
 import huggingface_hub
 from huggingface_hub import HfApi
+from gradio_client import Client
 import os
 
 HF_TOKEN = os.environ["HF_TOKEN"]
@@ -70,28 +71,37 @@ def post_request_beta(payload):
 
 
 def predict_beta(message, chatbot=[], system_prompt=system_prompt):
-    input_prompt = build_input_prompt(message, chatbot, system_prompt)
-    data = {
-        "inputs": input_prompt
-    }
+    client = Client(tulu)
 
     try:
-        response_data = post_request_beta(data)
-        json_obj = response_data[0]
-        
-        if 'generated_text' in json_obj and len(json_obj['generated_text']) > 0:
-            bot_message = json_obj['generated_text']
+        # Adjust these parameters as needed
+        max_new_tokens = 880
+        temperature = 0.4
+        top_p = 0.9
+        repetition_penalty = 0.7
+        advanced = True
+
+        # Making the prediction
+        result = client.predict(
+            message,  # Your Message
+            system_prompt,  # Optional Tulu Assistant Message (can adjust if needed)
+            max_new_tokens,
+            temperature,
+            top_p,
+            repetition_penalty,
+            advanced,
+            fn_index=0
+        )
+
+        # Extracting the response
+        if result is not None and len(result) > 0:
+            bot_message = result[0]  # Assuming the response is in the first element
             return bot_message
-        elif 'error' in json_obj:
-            raise gr.Error(json_obj['error'] + ' Please refresh and try again with smaller input prompt')
         else:
-            warning_msg = f"Unexpected response: {json_obj}"
-            raise gr.Error(warning_msg)
-    except requests.HTTPError as e:
-        error_msg = f"Request failed with status code {e.response.status_code}"
-        raise gr.Error(error_msg)
-    except json.JSONDecodeError as e:
-        error_msg = f"Failed to decode response as JSON: {str(e)}"
+            raise gr.Error("No response received from the model.")
+
+    except Exception as e:
+        error_msg = f"An error occurred: {str(e)}"
         raise gr.Error(error_msg)