p

app.py

@@ -11,12 +11,17 @@ _ = load_dotenv(find_dotenv())
 databricks_token  = os.getenv('DATABRICKS_TOKEN')
 model_uri  = "https://dbc-eb788f31-6c73.cloud.databricks.com/serving-endpoints/Mpt-7b-tester/invocations"
 
-def score_model(model_uri, databricks_token, data):
+def score_model(model_uri, databricks_token, prompt):
+  dataset=pd.DataFrame({
+            "prompt":[prompt],
+            "temperature": [0.5],
+            "max_tokens": [100]})
   headers = {
     "Authorization": f"Bearer {databricks_token}",
     "Content-Type": "application/json",
   }
-  data_json = '{"dataframe_split": {"index": [0], "columns": ["prompt", "temperature", "max_tokens"], "data": [["Loop is a company which converts fruit waste into juice to help retail stores reduce food loss by buying up fruits which were designated for trash.", 0.5, 500]]}}'
+  ds_dict = {'dataframe_split': dataset.to_dict(orient='split')} if isinstance(dataset, pd.DataFrame) else create_tf_serving_json(dataset)
+  data_json = json.dumps(ds_dict, allow_nan=True)
   print("***data_json: ")
 
   print(data_json)