raise gr.Error("網路塞車，請重新嘗試一次！")

app.py

@@ -152,14 +152,17 @@ def generate_topics(model, max_tokens, sys_content, scenario, eng_level, user_ge
         "response_format": { "type": "json_object" }
     }
 
-    response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
-    content = response.choices[0].message.content
-    topics = json.loads(content)["topics"]
-
-    print(f"====generate_topics====")
-    print(topics)
-
-    gr_update = gr.update(choices=topics, visible=True)
+    try:
+        response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
+        content = response.choices[0].message.content
+        topics = json.loads(content)["topics"]
+        topics = json.loads(content)["error"]
+        print(f"====generate_topics====")
+        print(topics)
+        gr_update = gr.update(choices=topics, visible=True)
+    except Exception as e:
+        print(f"An error occurred while generating topics: {e}")
+        raise gr.Error("網路塞車，請重新嘗試一次！")
 
     return gr_update
 
@@ -188,10 +191,14 @@ def generate_points(model, max_tokens, sys_content, scenario, eng_level, topic,
         "max_tokens": max_tokens,
     }
 
-    response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
-    content = response.choices[0].message.content
-    points = json.loads(content)["points"]
-    gr_update = gr.update(choices=points, visible=True)
+    try:
+        response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
+        content = response.choices[0].message.content
+        points = json.loads(content)["points"]
+        gr_update = gr.update(choices=points, visible=True)
+    except Exception as e:
+        print(f"An error occurred while generating points: {e}")
+        raise gr.Error("網路塞車，請重新嘗試一次！")
 
     return gr_update
 
@@ -236,14 +243,18 @@ def generate_topic_sentences(model, max_tokens, sys_content, scenario, eng_level
         "response_format": response_format
     }
 
-    response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
-    response_content = json.loads(response.choices[0].message.content)
-    json_content = response_content["results"]
-    topic_sentences_list = [item["topic-sentence"] for item in json_content]
-    random.shuffle(topic_sentences_list)
-    
-    gr_update_json = gr.update(value=json_content)
-    gr_update_radio = gr.update(choices=topic_sentences_list, visible=True)
+    try:
+        response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
+        response_content = json.loads(response.choices[0].message.content)
+        json_content = response_content["results"]
+        topic_sentences_list = [item["topic-sentence"] for item in json_content]
+        random.shuffle(topic_sentences_list)
+        
+        gr_update_json = gr.update(value=json_content)
+        gr_update_radio = gr.update(choices=topic_sentences_list, visible=True)
+    except Exception as e:
+        print(f"An error occurred while generating topic sentences: {e}")
+        raise gr.Error("網路塞車，請重新嘗試一次！")
 
     return gr_update_json, gr_update_radio
 
@@ -272,9 +283,13 @@ def generate_topic_sentence_feedback(model, max_tokens, sys_content, scenario, e
         "max_tokens": max_tokens,
     }
 
-    response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
-    content = response.choices[0].message.content.strip()
-    gr_update = gr.update(value=content, visible=True)
+    try:
+        response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
+        content = response.choices[0].message.content.strip()
+        gr_update = gr.update(value=content, visible=True)
+    except Exception as e:
+        print(f"An error occurred while generating topic sentence feedback: {e}")
+        raise gr.Error("網路塞車，請重新嘗試一次！")
 
     return gr_update
 
@@ -326,9 +341,13 @@ def generate_supporting_sentences(model, max_tokens, sys_content, scenario, eng_
         "max_tokens": max_tokens,
     }
 
-    response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
-    content = response.choices[0].message.content.strip()
-    gr_update = gr.update(choices=[content], visible=True)
+    try:
+        response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
+        content = response.choices[0].message.content.strip()
+        gr_update = gr.update(choices=[content], visible=True)
+    except Exception as e:
+        print(f"An error occurred while generating supporting sentences: {e}")
+        raise gr.Error("網路塞車，請重新嘗試一次！")
 
     return gr_update
 
@@ -360,10 +379,14 @@ def generate_conclusion_sentences(model, max_tokens, sys_content, scenario, eng_
         "response_format": { "type": "json_object" }
     }
 
-    response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
-    response_content = json.loads(response.choices[0].message.content)
-    json_content = response_content["results"]
-    gr_update = gr.update(choices=[json_content], visible=True)
+    try:
+        response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
+        response_content = json.loads(response.choices[0].message.content)
+        json_content = response_content["results"]
+        gr_update = gr.update(choices=[json_content], visible=True)
+    except Exception as e:
+        print(f"An error occurred while generating conclusion sentences: {e}")
+        raise gr.Error("網路塞車，請重新嘗試一次！")
 
     return gr_update
 
@@ -400,22 +423,26 @@ def generate_paragraph_evaluate(model, sys_content, paragraph, user_generate_par
         "response_format": response_format
     }
 
-    response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
-    content = response.choices[0].message.content
+    try:
+        response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
+        content = response.choices[0].message.content
 
-    print(f"====generate_paragraph_evaluate====")
-    print(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)
+        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！")
 
     return gr_update
 
@@ -441,19 +468,23 @@ def generate_correct_grammatical_spelling_errors(model, sys_content, eng_level,
         "response_format": response_format
     }
 
-    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"]
+    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)
+        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！")
     
     return corrections_list_gr_update, reverse_paragraph_gr_update
 
@@ -507,17 +538,21 @@ def generate_refine_paragraph(model, sys_content, eng_level, paragraph, user_ref
         "response_format": response_format
     }
 
-    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']
-    ]
+    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)
+        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！")
 
     return refine_paragraph_gr_update, revised_paragraph_gr_update
 
@@ -627,7 +662,6 @@ def get_logs_sessions(user_data, log_type):
     else:
         file_names = []
 
-    
     # file_names sort by timestamp DESC
     file_names.sort(reverse=True)
     choices = [
@@ -1068,10 +1102,6 @@ def generate_content_by_open_ai_assistant(user_content, thread_id=None, model_na
             tools=[{"type": "file_search"}],
         )
         
-        # Wait for the response
-        # run_status = poll_run_status(run.id, thread.id, timeout=30)
-        # print(f"Run status: {run_status}")
-        
         if run.status == "completed":
             print("==============completed====================")
             print(f"Thread ID: {thread.id}")
@@ -1081,62 +1111,11 @@ def generate_content_by_open_ai_assistant(user_content, thread_id=None, model_na
             response_text = messages.data[0].content[0].text.value
             print(f"Response: {response_text}")
     except Exception as e:
-        print(f"Error: {e}")
-        response_text = " 出現錯誤，請稍後再試！"
+        print(f"An error occurred while generating content by OpenAI Assistant: {e}")
+        raise gr.Error("網路塞車，請重新嘗試一次！")
 
     return response_text
 
-def poll_run_status(run_id, thread_id, timeout=600, poll_interval=5):
-    """
-    Polls the status of a Run and handles different statuses appropriately.
-
-    :param run_id: The ID of the Run to poll.
-    :param thread_id: The ID of the Thread associated with the Run.
-    :param timeout: Maximum time to wait for the Run to complete, in seconds.
-    :param poll_interval: Time to wait between each poll, in seconds.
-    """
-    client = OPEN_AI_CLIENT
-    start_time = time.time()
-    while time.time() - start_time < timeout:
-        run = client.beta.threads.runs.retrieve(thread_id=thread_id, run_id=run_id)
-
-        if run.status in ["completed", "cancelled", "failed"]:
-            print(f"Run completed with status: {run.status}")
-            break
-        elif run.status == "requires_action":
-            print("Run requires action. Performing required action...")
-            # Here, you would perform the required action, e.g., running functions
-            # and then submitting the outputs. This is simplified for this example.
-            # After performing the required action, you'd complete the action:
-            # OPEN_AI_CLIENT.beta.threads.runs.complete_required_action(...)
-        elif run.status == "expired":
-            print("Run expired. Exiting...")
-            break
-        else:
-            print(f"Run status is {run.status}. Waiting for updates...")
-        
-        time.sleep(poll_interval)
-    else:
-        print("Timeout reached. Run did not complete in the expected time.")
-
-    # Once the Run is completed, handle the result accordingly
-    if run.status == "completed":
-        # Retrieve and handle messages or run steps as needed
-        messages = client.beta.threads.messages.list(thread_id=thread_id)
-        for message in messages.data:
-            if message.role == "assistant":
-                print(f"Assistant response: {message.content}")
-    elif run.status in ["cancelled", "failed"]:
-        # Handle cancellation or failure
-        print(f"Run ended with status: {run.status}")
-    elif run.status == "expired":
-        # Handle expired run
-        print("Run expired without completion.")
-    
-    return run.status
-
-
-
 # 小工具
 def show_elements():
     return gr.update(visible=True)
@@ -1165,8 +1144,12 @@ def generate_chinese_essay_idea(model, user_prompt, chinese_essay_title_input):
         "max_tokens": 2000,
     }
 
-    response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
-    content = response.choices[0].message.content.strip()
+    try:
+        response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
+        content = response.choices[0].message.content.strip()
+    except Exception as e:
+        print(f"An error occurred while generating Chinese essay idea: {e}")
+        raise gr.Error("網路塞車���請重新嘗試一次！")
 
     return content