while attempt < max_attempts:

app.py

@@ -422,26 +422,32 @@ def generate_paragraph_evaluate(model, sys_content, paragraph, user_generate_par
         "response_format": response_format
     }
 
-    try:
-        response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
-        content = response.choices[0].message.content
-
-        print(f"====generate_paragraph_evaluate====")
-        print(content)
-
-        data = json.loads(content)
-        table_data = [
-            ["學測架構|內容（Content）", data['content']['level'], data['content']['explanation']],
-            ["學測架構|組織（Organization）", data['organization']['level'], data['organization']['explanation']],
-            ["學測架構|文法、句構（Grammar/Sentence Structure）", data['grammar_and_usage']['level'], data['grammar_and_usage']['explanation']],
-            ["學測架構|字彙、拼字（Vocabulary/Spelling）", data['vocabulary']['level'], data['vocabulary']['explanation']],
-            ["JUTOR 架構|連貫性和連接詞（Coherence and Cohesion）", data['coherence_and_cohesion']['level'], data['coherence_and_cohesion']['explanation']]
-        ]
-        headers = ["架構", "評分", "解釋"]
-        gr_update = gr.update(value=table_data, headers=headers, visible=True)
-    except Exception as e:
-        print(f"An error occurred while generating paragraph evaluation: {e}")
-        raise gr.Error("網路塞車，請重新嘗試一次！")
+    max_attempts = 2
+    attempt = 0
+    while attempt < max_attempts:
+        try:
+            response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
+            content = response.choices[0].message.content
+
+            print(f"====generate_paragraph_evaluate====")
+            print(content)
+
+            data = json.loads(content)
+            table_data = [
+                ["學測架構|內容（Content）", data['content']['level'], data['content']['explanation']],
+                ["學測架構|組織（Organization）", data['organization']['level'], data['organization']['explanation']],
+                ["學測架構|文法、句構（Grammar/Sentence Structure）", data['grammar_and_usage']['level'], data['grammar_and_usage']['explanation']],
+                ["學測架構|字彙、拼字（Vocabulary/Spelling）", data['vocabulary']['level'], data['vocabulary']['explanation']],
+                ["JUTOR 架構|連貫性和連接詞（Coherence and Cohesion）", data['coherence_and_cohesion']['level'], data['coherence_and_cohesion']['explanation']]
+            ]
+            headers = ["架構", "評分", "解釋"]
+            gr_update = gr.update(value=table_data, headers=headers, visible=True)
+            break
+        except Exception as e:
+            print(f"An error occurred while generating paragraph evaluate: {e}")
+            attempt += 1
+            if attempt == max_attempts:
+                raise gr.Error("網路塞車，請重新嘗試一次！")
 
     return gr_update
 
@@ -467,23 +473,29 @@ def generate_correct_grammatical_spelling_errors(model, sys_content, eng_level,
         "response_format": response_format
     }
 
-    try:
-        response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
-        content = response.choices[0].message.content
-        data = json.loads(content)
-        print(f"data: {data}")
-
-        corrections_list = [
-            [item['original'], item['correction'], item['explanation']]
-            for item in data['Corrections and Explanations']
-        ]
-        headers = ["原文", "建議", "解釋"]
-
-        corrections_list_gr_update = gr.update(value=corrections_list, headers=headers, wrap=True, visible=True)
-        reverse_paragraph_gr_update = gr.update(value=data["Revised Paragraph"], visible=False)
-    except Exception as e:
-        print(f"An error occurred while generating correct grammatical and spelling errors: {e}")
-        raise gr.Error("網路塞車，請重新嘗試一次！")
+    max_attempts = 2
+    attempt = 0
+    while attempt < max_attempts:
+        try:
+            response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
+            content = response.choices[0].message.content
+            data = json.loads(content)
+            print(f"data: {data}")
+
+            corrections_list = [
+                [item['original'], item['correction'], item['explanation']]
+                for item in data['Corrections and Explanations']
+            ]
+            headers = ["原文", "建議", "解釋"]
+
+            corrections_list_gr_update = gr.update(value=corrections_list, headers=headers, wrap=True, visible=True)
+            reverse_paragraph_gr_update = gr.update(value=data["Revised Paragraph"], visible=False)
+            break
+        except Exception as e:
+            print(f"An error occurred while generating correct grammatical spelling errors: {e}")
+            attempt += 1
+            if attempt == max_attempts:
+                raise gr.Error("網路塞車，請重新嘗試一次！")
     
     return corrections_list_gr_update, reverse_paragraph_gr_update
 
@@ -537,21 +549,27 @@ def generate_refine_paragraph(model, sys_content, eng_level, paragraph, user_ref
         "response_format": response_format
     }
 
-    try:
-        response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
-        content = response.choices[0].message.content
-        data = json.loads(content)
-        headers = ["原文", "建議", "解釋"]
-        table_data = [
-            [item['origin'], item['suggestion'], item['explanation']]
-            for item in data['Suggestions and Explanations']
-        ]
-
-        refine_paragraph_gr_update = gr.update(value=table_data, headers=headers, visible=True)
-        revised_paragraph_gr_update = gr.update(value=data["Revised Paragraph"],visible=False)
-    except Exception as e:
-        print(f"An error occurred while generating refine paragraph: {e}")
-        raise gr.Error("網路塞車，請重新嘗試一次！")
+    max_attempts = 2
+    attempt = 0
+    while attempt < max_attempts:
+        try:
+            response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
+            content = response.choices[0].message.content
+            data = json.loads(content)
+            headers = ["原文", "建議", "解釋"]
+            table_data = [
+                [item['origin'], item['suggestion'], item['explanation']]
+                for item in data['Suggestions and Explanations']
+            ]
+
+            refine_paragraph_gr_update = gr.update(value=table_data, headers=headers, visible=True)
+            revised_paragraph_gr_update = gr.update(value=data["Revised Paragraph"],visible=False)
+            break
+        except Exception as e:
+            print(f"An error occurred while generating refine paragraph: {e}")
+            attempt += 1
+            if attempt == max_attempts:
+                raise gr.Error("網路塞車，請重新嘗試一次！")
 
     return refine_paragraph_gr_update, revised_paragraph_gr_update