Update audio.py

tasks/audio.py

@@ -4,6 +4,7 @@ from datasets import load_dataset
 from sklearn.metrics import accuracy_score
 import random
 import os
+import joblib
 
 from .utils.evaluation import AudioEvaluationRequest
 from .utils.emissions import tracker, clean_emissions_data, get_space_info
@@ -13,7 +14,7 @@ load_dotenv()
 
 router = APIRouter()
 
-DESCRIPTION = "Random Baseline"
+DESCRIPTION = "Random Forest"
 ROUTE = "/audio"
 
 
@@ -54,8 +55,14 @@ async def evaluate_audio(request: AudioEvaluationRequest):
     #--------------------------------------------------------------------------------------------   
     
     # Make random predictions (placeholder for actual model inference)
-    true_labels = test_dataset["label"]
-    predictions = [random.randint(0, 1) for _ in range(len(true_labels))]
+    true_labels = np.array(test_dataset["label"])
+
+    # Extract audio samples from test_dataset
+    x_test = [sample["audio"]["array"] for sample in test_dataset]
+    
+    clf = joblib.load()
+    predictions = clf.predict(x_test)
+
     
     #--------------------------------------------------------------------------------------------
     # YOUR MODEL INFERENCE STOPS HERE