extract json

.gitignore

@@ -161,7 +161,7 @@ cython_debug/
 
 # folders
 records
-
+save
 backup
 results
 

gpt_setting.py

@@ -6,6 +6,7 @@
 import openai
 import time
 import os
+import re
 import random
 
 from utils import *
@@ -71,13 +72,20 @@ def print_prompt(inputs, response):
     return
 
 def gpt_request(model, inputs):
+    json_format = r'({.*})'
+
     if model == 'text-davinci-003':
         response = completion(model, inputs).strip()
         print_prompt(inputs, response)
-        return response
+        match = re.search(json_format, response, re.DOTALL)
+        return str(match)
     elif model in ['gpt-3.5-turbo', 'gpt-4']:
         response = chat(model, inputs).strip()
         print_prompt(inputs, response)
-        return response
-    else:
+        match = re.search(json_format, response, re.DOTALL)
+        if match:
+            return match.group(1).strip()
+        else:
+            ""
+
         raise ValueError("The model is not supported or does not exist.")

main.py

@@ -15,7 +15,8 @@
     En: English, Zh: Simplified Chinese, Ko: Korean, Es: Spanish, Fr: France,
     De: Deutsch, It: Italian, Ar: Arabic, Ru: Russian, Ja: Japanese
 '''
-language = ['Zh', 'Ko', 'Es', 'Fr', 'De', 'It', 'Ar', 'Ru', 'Ja']
+language = ['En', 'Zh', 'Ko', 'Es', 'Fr', 'De', 'It', 'Ar', 'Ru', 'Ja']
+language = ['Zh']
 
 '''
 Label:
@@ -36,13 +37,13 @@
 
 '================================================================================================='
 questionnaire_name = 'BFI'
-name_exp = 'save'
+name_exp = 'save_zh'
 
 # Start a server and generate pre-testing cases
 bfi_test = Server(questionnaire_name, template, version, language, label, order, name_exp=name_exp)
 
 # Load and continue a test
-# bfi_test = load('<filename>', '<new-filename>')
+# bfi_test = load('save/save_en.json', 'save_en1')
 
 # Run the pre-testing cases
 bfi_test.run()

server.py

@@ -155,16 +155,14 @@ def start_request(self, scale_details, level_description, statement_description,
             prompt = get_prompt(f'prompt_template/{language}/{self.questionnaire_name}_{language}_{template}.txt', 
                                 [symbol_min, symbol_max, level_description, statement_str])
             inputs.append({"role": "user", "content": prompt})
-            while True:
-                try:
-                    gpt_responses = gpt_request(self.model, inputs).strip()
-                    parsed_responses = json.loads(gpt_responses)
-                    parsed_responses = [convert_symbol(label, value) for value in parsed_responses.values()]
-                    if order == 'r':
-                        parsed_responses = [scale_max-score+1 for score in parsed_responses]
-                    break
-                except ValueError:
-                    pass
+            try:
+                gpt_responses = gpt_request(self.model, inputs)
+                parsed_responses = json.loads(gpt_responses)
+                parsed_responses = [convert_symbol(label, value) for value in parsed_responses.values()]
+                if order == 'r':
+                    parsed_responses = [scale_max-score+1 for score in parsed_responses]
+            except ValueError:
+                return None
             responses += parsed_responses
             inputs.append({"role": "assistant", "content": gpt_responses})
         return responses
@@ -187,7 +185,11 @@ def start(self, test_case):
         statement_indices, statement_details, statement_description = self.get_statements(questions, version)
 
         responses = self.start_request(scale_details, level_description, statement_description, questions, **test_case)
-        data = {k: v for k, v in zip(statement_indices, responses)}
+
+        if responses and len(responses) == len(statement_indices):
+            data = {k: v for k, v in zip(statement_indices, responses)}
+        else:
+            data = self.start(test_case)
 
         return data