ready1234

app.py

@@ -2,8 +2,6 @@ from fastapi import FastAPI
 from dotenv import load_dotenv
 from tasks import text, image, audio
 
-from skops.hub_utils import download
-
 # Load environment variables
 load_dotenv()
 

tasks/text.py

@@ -13,7 +13,11 @@ from huggingface_hub import hf_hub_download
 import joblib
 
 REPO_ID = "kantundpeterpan/frugal-ai-toy"
-FILENAME = "tfidf_rf.skops"
+MODEL = "tfidf_rf.skops"
+
+if not os.path.exists("tasks/model"):
+    #download model for text task
+    download(repo_id = REPO_ID, dst = "tasks/model")
 
 #add model directory to python path to be able to load tools.py
 import sys
@@ -21,18 +25,15 @@ import os
 sys.path.append(os.path.abspath('tasks/model'))
 
 
-print("### App Dir")
-print(os.listdir("./"))
-print()
-print("### Task Dir")
-print(os.listdir("./tasks"))
+# print("### App Dir")
+# print(os.listdir("./"))
+# print()
+# print("### Task Dir")
+# print(os.listdir("./tasks"))
 
-if not os.path.exists("tasks/model"):
-    #download model for text task
-    download(repo_id = "kantundpeterpan/frugal-ai-toy", dst = "tasks/model")
 
-print("### Model Dir")
-print(os.listdir("./tasks/model"))
+# print("### Model Dir")
+# print(os.listdir("./tasks/model"))
 
 import random
 
@@ -79,7 +80,12 @@ async def evaluate_text(request: TextEvaluationRequest):
     train_test = dataset["train"].train_test_split(test_size=request.test_size, seed=request.test_seed)
     test_dataset = train_test["test"]
     test_df = pd.DataFrame(test_dataset)
-    print(test_df.head())
+    # print(test_df.head())
+    
+    #get unknwown types
+    unknown = skops.io.get_untrusted_types(file = "tasks/model/" + MODEL)
+    #load model
+    model = model = load("tasks/model/" + MODEL, trusted = unknown)
     
     # Start tracking emissions
     tracker.start()
@@ -87,18 +93,10 @@ async def evaluate_text(request: TextEvaluationRequest):
 
     #--------------------------------------------------------------------------------------------
     # YOUR MODEL INFERENCE CODE HERE
-    # Update the code below to replace the random baseline by your model inference within the inference pass where the energy consumption and emissions are tracked.
+    # Update the code below to replace the random baseline by your model inference within 
+    # the inference pass where the energy consumption and emissions are tracked.
     #--------------------------------------------------------------------------------------------   
 
-    #get unknwown types
-    unknown = skops.io.get_untrusted_types(file = "tasks/model/tfidf_rf.skops")
-
-    print("### Task Dir")
-    print(os.listdir("./tasks"))
-    
-    #load model
-    model = model = load("tasks/model/tfidf_rf.skops", trusted = unknown)
-    
     # Make predictions
     true_labels = test_dataset["label"]
     predictions = [