evaluate update

qwen_classifier/evaluate.py

@@ -7,8 +7,8 @@ import pandas as pd
 import torch
 from datasets import Dataset
 from torch.utils.data import DataLoader
-from .config import TAG_NAMES, DEVICE
-from .predict import predict_batch
+import requests
+from .config import TAG_NAMES, DEVICE, SPACE_URL
 
 def load_data(test_data_path):
     # zip file handler
@@ -119,3 +119,20 @@ def _evaluate_local(test_data_path, hf_repo):
     report = classification_report(all_labels, all_preds, target_names=TAG_NAMES, zero_division=0)
 
     return metrics, report
+
+
+def _evaluate_hf_api(text, hf_token=None):
+    try:
+        response = requests.post(
+            f"{SPACE_URL}/evaluate",
+            json={"text": text},  # This matches the Pydantic model
+            headers={
+                "Authorization": f"Bearer {hf_token}",
+                "Content-Type": "application/json"
+            } if hf_token else {"Content-Type": "application/json"},
+            timeout=10
+        )
+        response.raise_for_status()  # Raise HTTP errors
+        return response.json()
+    except requests.exceptions.RequestException as e:
+        raise ValueError(f"API Error: {str(e)}\nResponse: {e.response.text if hasattr(e, 'response') else ''}")