Redundant implementations of get_chat_response

[mattmazzola]

There is an implementation in utilities#get_chat_response and models/gpt#get_response.
These could be unified

MathVista/utilities.py

Lines 159 to 199 in 82f68d0

	def get_chat_response(promot, api_key, model="gpt-3.5-turbo", temperature=0, max_tokens=256, n=1, patience=10000000,
	sleep_time=0):
	messages = [
	{"role": "user", "content": promot},
	]
	# print("I am here")
	while patience > 0:
	patience -= 1
	try:
	response = openai.ChatCompletion.create(model=model,
	messages=messages,
	api_key=api_key,
	temperature=temperature,
	max_tokens=max_tokens,
	n=n)
	if n == 1:
	prediction = response['choices'][0]['message']['content'].strip()
	if prediction != "" and prediction != None:
	return prediction
	else:
	prediction = [choice['message']['content'].strip() for choice in response['choices']]
	if prediction[0] != "" and prediction[0] != None:
	return prediction
	except Exception as e:
	if "Rate limit" not in str(e):
	print(e)
	if "Please reduce the length of the messages" in str(e):
	print("!!Reduce promot size")
	# reduce input prompt and keep the tail
	new_size = int(len(promot) * 0.9)
	new_start = len(promot) - new_size
	promot = promot[new_start:]
	messages = [
	{"role": "user", "content": promot},
	]
	if sleep_time > 0:
	time.sleep(sleep_time)
	return ""

MathVista/models/gpt.py

Lines 16 to 55 in 82f68d0

	def get_response(self, image_path, user_prompt):
	patience = self.patience
	max_tokens = self.max_tokens
	messages = [
	{"role": "user", "content": user_prompt},
	]
	while patience > 0:
	patience -= 1
	try:
	# print("self.model", self.model)
	response = openai.ChatCompletion.create(model=self.model,
	messages=messages,
	api_key=self.api_key,
	temperature=self.temperature,
	max_tokens=max_tokens,
	n=self.n
	)
	if self.n == 1:
	prediction = response['choices'][0]['message']['content'].strip()
	if prediction != "" and prediction != None:
	return prediction
	else:
	prediction = [choice['message']['content'].strip() for choice in response['choices']]
	if prediction[0] != "" and prediction[0] != None:
	return prediction
	except Exception as e:
	if "limit" not in str(e):
	print(e)
	if "Please reduce the length of the messages or completion" in str(e):
	max_tokens = int(max_tokens * 0.9)
	print("!!Reduce max_tokens to", max_tokens)
	if max_tokens < 8:
	return ""
	if "Please reduce the length of the messages." in str(e):
	print("!!Reduce user_prompt to", user_prompt[:-1])
	return ""
	if self.sleep_time > 0:
	time.sleep(self.sleep_time)
	return ""