input format debug

handler.py

@@ -6,6 +6,6 @@ class EndpointHandler():
 
     def __call__(self, data):
 
-        _, raw_prob, _, _ = self.scorer.score(inputs=data)
+        _, raw_prob, _, _ = self.scorer.score(data=data)
             
         return raw_prob

minicheck_web/minicheck.py

@@ -18,7 +18,7 @@ class MiniCheck:
             max_input_length=max_input_length,
         )
 
-    def score(self, inputs: Dict) -> List[float]:
+    def score(self, data: Dict) -> List[float]:
         '''
         pred_labels: 0 / 1 (0: unsupported, 1: supported)
         max_support_probs: the probability of "supported" for the chunk that determin the final pred_label
@@ -26,6 +26,7 @@ class MiniCheck:
         support_prob_per_chunk: the probability of "supported" for each chunk
         '''
 
+        inputs = data['inputs']
         docs = inputs['docs']
         claims = inputs['claims']
 
@@ -35,20 +36,4 @@ class MiniCheck:
         max_support_prob, used_chunk, support_prob_per_chunk = self.model.fact_check(docs, claims)
         pred_label = [1 if prob > 0.5 else 0 for prob in max_support_prob]
 
-        return pred_label, max_support_prob, used_chunk, support_prob_per_chunk
-    
-
-if __name__ == '__main__':
-
-    path = "./"
-
-    doc = "A group of students gather in the school library to study for their upcoming final exams."
-    claim_1 = "The students are preparing for an examination."
-    claim_2 = "The students are on vacation."
-
-    # flan-t5-large
-    scorer = MiniCheck(path)
-    pred_label, raw_prob, _, _ = scorer.score(docs=[doc, doc], claims=[claim_1, claim_2])
-
-    print(pred_label) # [1, 0]
-    print(raw_prob)   # [0.9805923700332642, 0.007121307775378227]
+        return pred_label, max_support_prob, used_chunk, support_prob_per_chunk