Update main.py

main.py

@@ -28,9 +28,9 @@ class BasePromptContext:
         self.variables_list = ["question","answer","context"]
         self.base_template = """Please act as an impartial judge and evaluate the quality of the provided answer which attempts to answer the provided question based on a provided context.
 
-And you'll need to submit your grading for the correctness, comprehensiveness and readability of the answer, using the following format:
-Reasoning for correctness: [your one line step by step reasoning about the correctness of the answer]
-Score for correctness: [your score number for the correctness of the answer]
+And you'll need to submit your grading for the correctness, comprehensiveness and readability of the answer, using JSON format with the 2 items in parenthesis:
+( Reasoning: [your one line step by step reasoning about the correctness of the answer], 
+Score: [your score number for the correctness of the answer] )
 
 
 
@@ -76,6 +76,7 @@ class Evaluater:
         self.answer = item.answer
         self.domain = item.domain
         self.context = item.context
+        self.llm=HuggingFaceHub(repo_id="google/flan-t5-xxl", model_kwargs={"temperature":1, "max_length":1000000})
 
     def get_prompt_template(self):
         prompt = BasePromptContext()
@@ -85,9 +86,8 @@ class Evaluater:
         return eval_template
 
     def evaluate(self):
-        llm=HuggingFaceHub(repo_id="google/flan-t5-xxl", model_kwargs={"temperature":1, "max_length":1000000})
         prompt = self.get_prompt_template().format(question = self.question, answer = self.answer, context = self.context)
-        score = llm(prompt)
+        score = self.llm(prompt)
         return score
 
 # Create extractor instance