chat_message empty if assistant_id exists

main.py

@@ -147,6 +147,7 @@ def gpt():
     use_video = False
     suggest = False
     summarize = False
+    expression = False
     predict_q = 0
     max_char_msg = 500
     max_resp_token = 600
@@ -172,6 +173,8 @@ def gpt():
             if 'chat_model' in json_payload and 'assistant_id' not in json_payload:
                 chat_model = json_payload['chat_model']
                 max_resp_token = 2048
+            if 'expression' in json_payload:
+                expression = json_payload['expression'] == "1"
             if 'translate' in json_payload:
                 chat_messages = app.translate_messages.copy()
                 json_payload['payload'][-1]['content'] = json_payload['payload'][-1][
@@ -273,12 +276,18 @@ def gpt():
                     "messages": chat_messages
                 }
             )
-            messages = list(app.openai_client.beta.threads.messages.list(thread_id=runs.thread_id, run_id=runs.id))
-            message_content = messages[0].content[0].text
-            app.logger.info(message_content.value)
-            pattern = re.compile(r"【\d+:\d+†\(?source\)?】")
-            filtered_message = pattern.sub("", message_content.value)
-            result = {"role": "assistant", "content": filtered_message}
+            if runs.status != "completed":
+                result = {"role": "assistant", "content": "Maaf, saat ini saya sedang sibuk. Coba beberapa saat lagi."}
+            else:
+                messages = list(app.openai_client.beta.threads.messages.list(thread_id=runs.thread_id, run_id=runs.id))
+                try:
+                    message_content = messages[0].content[0].text
+                    app.logger.info(message_content.value)
+                    pattern = re.compile(r"【\d+:\d+†\(?source\)?】")
+                    filtered_message = pattern.sub("", message_content.value)
+                    result = {"role": "assistant", "content": filtered_message}
+                except IndexError:
+                    result = {"role": "assistant", "content": "Saat ini saya tidak memiliki informasi yang diperlukan untuk menjawab pertanyaan Anda."}
         else:
             json_response = app.openai_client.chat.completions.create(model=chat_model,
                                                                       messages=chat_messages,
@@ -301,6 +310,9 @@ def gpt():
                         result = {"role": "assistant", "content": json_response.choices[0].message.content}
             else:
                 result = {"role": "assistant", "content": json_response.choices[0].message.content}
+        if expression:
+            exprr = expresso(text=result['content'])
+            result['expression'] = exprr['expression']
         if predict_q:
             if assistant_id:
                 query_q = {
@@ -319,7 +331,9 @@ def gpt():
                     assistant_id=assistant_id,
                     thread={
                         "messages": chat_messages
-                    }
+                    },
+                    max_completion_tokens=600,
+                    max_prompt_tokens=600
                 )
                 messages = list(app.openai_client.beta.threads.messages.list(thread_id=runs.thread_id, run_id=runs.id))
                 message_content = messages[0].content[0].text
@@ -643,6 +657,27 @@ def speech(text=""):
             res.stream_to_file(os.path.join(app.config['UPLOAD_FOLDER'], f"{uu_id}.mp3"))
         return download_file(f"{uu_id}.mp3")
 
+@app.route('/expression', methods=['POST'])
+def expresso(text=""):
+    if not text:
+        if 'text' in request.form:
+            text = request.form['text']
+        else:
+            return {"status": "error", "message": "No text for expression"}
+    response = app.openai_client.chat.completions.create(
+        model="gpt-4o-mini",
+        messages=[
+            {
+                "role": "user",
+                "content": f"What is the closest expression of this text, choose between happy, sad, indifferent, fear, anger, surprise, or disgust, output json with key 'expression':\n\n{text}\n\n"
+            }
+        ],
+        response_format={"type": "json_object"}
+    )
+    response_message = response.choices[0].message.content
+    return json.loads(response_message)
+
+
 
 # Press the green button in the gutter to run the script.
 if __name__ == '__main__':

requirements.txt

@@ -1,5 +1,5 @@
 requests~=2.32.3
-openai~=1.35.10
+openai>=1.37.1
 Flask~=3.0.3
 pandas~=2.2.2
 jsonlines~=4.0.0