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@@ -115,6 +115,7 @@ def gpt():
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use_video = False
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suggest = False
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summarize = False
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+ predict_q = 0
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max_char_msg = 500
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max_resp_token = 600
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category = []
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@@ -128,6 +129,8 @@ def gpt():
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if isinstance(json_payload, dict):
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has_named_params = 'payload' in json_payload
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if 'payload' in json_payload:
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+ if 'predict_q' in json_payload:
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+ predict_q = int(json_payload['predict_q'])
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if 'num_choices' in json_payload:
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num_choices = 5 if json_payload['num_choices'] > 5 else json_payload['num_choices']
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if 'use_video' in json_payload:
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@@ -218,7 +221,7 @@ def gpt():
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result = {}
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try:
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n = num_choices
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- json_response = app.openai_client.chat.completions.create(model=chat_model, # GPT-3.5 Turbo engine
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+ json_response = app.openai_client.chat.completions.create(model=chat_model,
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messages=chat_messages,
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max_tokens=max_resp_token, temperature=0.7, n=n)
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app.logger.info(json_response.choices[0].message)
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@@ -230,12 +233,33 @@ def gpt():
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for message in messages:
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json_formatted.append({"role": "assistant", "content": message.content})
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result = {"url": "", "message": json_formatted}
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- elif use_video:
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- # TODO: to be implemented
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- result = {"url": url_for('download_file', name="test.mp4", _external=True),
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- "message": {"role": "assistant", "content": json_response.choices[0].message.content}}
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else:
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- result = {"role": "assistant", "content": json_response.choices[0].message.content}
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+ if use_video:
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+ # TODO: to be implemented
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+ result = {"url": url_for('download_file', name="test.mp4", _external=True),
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+ "message": {"role": "assistant", "content": json_response.choices[0].message.content}}
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+ else:
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+ result = {"role": "assistant", "content": json_response.choices[0].message.content}
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+ if predict_q:
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+ query_q = {
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+ "role": "user",
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+ "content": f"Berikan {predict_q} pertanyaan lain yang akan saya ajukan berdasarkan percakapan kali ini dalam bentuk json array"
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+ }
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+ chat_messages.append(result)
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+ chat_messages.append(query_q)
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+ json_response_q = app.openai_client.chat.completions.create(model=chat_model,
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+ messages=chat_messages,
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+ max_tokens=max_resp_token,
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+ temperature=0.2, response_format={"type": "json_object"})
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+ json_response_dict = json.loads(json_response_q.choices[0].message.content)
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+ print(json_response_dict)
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+ if json_response_dict is not None:
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+ if isinstance(json_response_dict, dict):
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+ first_key = next(iter(json_response_dict))
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+ json_response_dict = json_response_dict[first_key]
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+ elif isinstance(json_response_dict, str):
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+ json_response_dict = [json_response_dict]
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+ result["predict_q"] = json_response_dict
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else:
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result = {"role": "assistant", "content": json_response.choices[0].message.content}
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except Exception as error_print:
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