I’m in the Guidelines\Tactics section of the coding and got the RateLimitError below. I’m using a new API key and I’ve barely used ChatGPT3.5.
How do I fix this?
Thanks,
Reza.
RateLimitError Traceback (most recent call last)
Cell In[7], line 19
2 text = f"“”
3 You should express what you want a model to do by \
4 providing instructions that are as clear and \
(…)
12 more detailed and relevant outputs.
13 “”"
14 prompt = f"“”
15 Summarize the text delimited by triple backticks \
16 into a single sentence.
17 {text}
18 “”"
—> 19 response = get_completion(prompt)
20 print(response)
Cell In[5], line 3, in get_completion(prompt, model)
1 def get_completion(prompt, model=“gpt-3.5-turbo”):
2 messages = [{“role”: “user”, “content”: prompt}]
----> 3 response = openai.ChatCompletion.create(
4 model=model,
5 messages=messages,
6 temperature=0, # this is the degree of randomness of the model’s output
7 )
8 return response.choices[0].message[“content”]
File /usr/local/lib/python3.9/site-packages/openai/api_resources/chat_completion.py:25, in ChatCompletion.create(cls, *args, **kwargs)
23 while True:
24 try:
—> 25 return super().create(*args, **kwargs)
26 except TryAgain as e:
27 if timeout is not None and time.time() > start + timeout:
File /usr/local/lib/python3.9/site-packages/openai/api_resources/abstract/engine_api_resource.py:153, in EngineAPIResource.create(cls, api_key, api_base, api_type, request_id, api_version, organization, **params)
127 @classmethod
128 def create(
129 cls,
(…)
136 **params,
137 ):
138 (
139 deployment_id,
140 engine,
(…)
150 api_key, api_base, api_type, api_version, organization, **params
151 )
→ 153 response, _, api_key = requestor.request(
154 “post”,
155 url,
156 params=params,
157 headers=headers,
158 stream=stream,
159 request_id=request_id,
160 request_timeout=request_timeout,
161 )
163 if stream:
164 # must be an iterator
165 assert not isinstance(response, OpenAIResponse)
File /usr/local/lib/python3.9/site-packages/openai/api_requestor.py:226, in APIRequestor.request(self, method, url, params, headers, files, stream, request_id, request_timeout)
205 def request(
206 self,
207 method,
(…)
214 request_timeout: Optional[Union[float, Tuple[float, float]]] = None,
215 ) → Tuple[Union[OpenAIResponse, Iterator[OpenAIResponse]], bool, str]:
216 result = self.request_raw(
217 method.lower(),
218 url,
(…)
224 request_timeout=request_timeout,
225 )
→ 226 resp, got_stream = self._interpret_response(result, stream)
227 return resp, got_stream, self.api_key
File /usr/local/lib/python3.9/site-packages/openai/api_requestor.py:620, in APIRequestor._interpret_response(self, result, stream)
612 return (
613 self._interpret_response_line(
614 line, result.status_code, result.headers, stream=True
615 )
616 for line in parse_stream(result.iter_lines())
617 ), True
618 else:
619 return (
→ 620 self._interpret_response_line(
621 result.content.decode(“utf-8”),
622 result.status_code,
623 result.headers,
624 stream=False,
625 ),
626 False,
627 )
File /usr/local/lib/python3.9/site-packages/openai/api_requestor.py:683, in APIRequestor._interpret_response_line(self, rbody, rcode, rheaders, stream)
681 stream_error = stream and “error” in resp.data
682 if stream_error or not 200 <= rcode < 300:
→ 683 raise self.handle_error_response(
684 rbody, rcode, resp.data, rheaders, stream_error=stream_error
685 )
686 return resp
RateLimitError: You exceeded your current quota, please check your plan and billing details.
