InvalidRequestError: Invalid URL (POST /v1/engines/gpt-3.5-turbo/chat/completions)

[hemangjoshi37a]

Describe the bug

command :

def classify_tokens_gpt3_5_turbo_multiple_parts(email_text: str) -> list:
    # Define the prompt
    prompt = (
        f"Given the request for quotation email below, identify and classify the following information for each part: "
        f"email_Subject_Phrase, RFQ_number, Manufacturer_Part_Number, Qty_Required, Manufacturer_name, "
        f"Customer_Part_Number, Product_Description, Target_Price, Lead_Time_days, Date_Code, Packaging_Type, "
        f"Dispatch_Date, Comments, Currency, min_ord_qty, STD_PACK_QTY, SENDER_NAME, SENDER_POSITION, SENDER_COMPANY, SENDER_MOBILE, "
        f"SENDER_EMAIL, SENDER_ADDRESS, SENDER_COUNTRY, SENDER_PINCODE, SENDER_CITY, SENDER_STATE.\n\n"
        '''for example response. : {'email_Subject_Phrase':'send me your quote to following parts',
        'RFQ_number':'123455ASDJKH',
        'Manufacturer_Part_Number':['aas1d32f1','df4gs45'],
        'Qty_Required':['32','5510'],
        'Manufacturer_name':['TI','MAXIUM'],
        'Customer_Part_Number':['12UIOY3','KJHG2134'],
        'Product_Description':['PN DIODE','3W LED'],
        'Target_Price':['120','5'],
        'Lead_Time_days':['5','10'],
        'Date_Code':['12-FEB-2023','10-JAN-2023'],
        'Packaging_Type':['SMD','THOURHG HOLE'],
        'Dispatch_Date':['11-FEB-2023','10-JAN-2023'],
        'Comments':['SEND WITH MINIMUM PLASIC PACKAGING'],
        'Currency':'USD',
        'min_ord_qty':['10K','5K'],
        'STD_PACK_QTY':['2K','1K'],
        'SENDER_NAME':'HEMANG JOSHI',
        'SENDER_POSITION':'DESIGN ENGINEER',
        'SENDER_COMPANY':'HJLABS.IN', 
        'SENDER_MOBILE':'+917016525813',
        'SENDER_EMAIL':'INFO@HJLABS.IN',
        'SENDER_ADDRESS':'SHED#:180, MAHAVIR INDIUSTRIAL PARK-2, KATHVADA GIDC, AHMEDABAD', 
        'SENDER_COUNTRY':'INDIA',
        'SENDER_PINCODE':'365610', 
        'SENDER_CITY':'AHMEDABAD', 
        'SENDER_STATE':'GUJARAT'
        }'''
        f"Email:\n{email_text}\n\n"
    )

    # Call the GPT-3.5-turbo API
    response = openai.ChatCompletion.create(
#         engine="text-davinci-002",
        engine="gpt-3.5-turbo",
#         engine="gpt-4",
        prompt=prompt,
        max_tokens=1024,
        n=1,
        stop=None,
        temperature=0.1,
    )

    # Extract the generated answer from the API response
    answer = response.choices[0].text.strip()
    print(f'{answer=}')

    # Split the answer into a list of parts
    parts = re.split(r'\n\s*\n', answer)

    # Parse the individual parts into a list of dictionaries
    classified_tokens_list = []
    for part in parts:
        classified_tokens = {}
        for line in part.split('\n'):
            if ':' in line:
                key, value = line.split(':', 1)
                classified_tokens[key.strip()] = value.strip()
        classified_tokens_list.append(classified_tokens)

    return classified_tokens_list

mlemail = '''
Dear HEMANG,
Please send me your quote to following parts:
Maxim S21DF3G 210pc.
Taiyo Yuden TMK325B7226MM-TR 1k / 7k
Taiyo Yuden TMK325B7226KM-PR 1k / 7k
TI TM4C129XNCZAD 1415pc.
Maxim MAX823SEUK+T 100 / 1550pc.
Linear / Analog LT8708EUHG#PBF 2.300
Texas Instruments LP38691SD-ADJ/NOPB 2.400
Texas Instruments LP38690SD-ADJ 2.400
Texas Instruments LP38690SDX-ADJ 2.400
Texas Instruments LMP8481MM-T/NOPB 2300
UCC EMZL350ARA561MJA0G 6.900
Omron G5V-1-DC9 2.300
Thank you very much for your efforts.

Best regards,
SATYA NADELLA
--
SATYA NADELLA
Verkauf / Sales
MICROSOFT
'''

classify_tokens_gpt3_5_turbo_multiple_parts(mlemail)

ERROR :

---------------------------------------------------------------------------
InvalidRequestError                       Traceback (most recent call last)
Cell In [20], line 1
----> 1 classify_tokens_gpt3_5_turbo_multiple_parts(mlemail)

Cell In [18], line 40, in classify_tokens_gpt3_5_turbo_multiple_parts(email_text)
      3     prompt = (
      4         f"Given the request for quotation email below, identify and classify the following information for each part: "
      5         f"email_Subject_Phrase, RFQ_number, Manufacturer_Part_Number, Qty_Required, Manufacturer_name, "
   (...)
     36         f"Email:\n{email_text}\n\n"
     37     )
     39     # Call the GPT-3.5-turbo API
---> 40     response = openai.ChatCompletion.create(
     41 #         engine="text-davinci-002",
     42         engine="gpt-3.5-turbo",
     43 #         engine="gpt-4",
     44         prompt=prompt,
     45         max_tokens=1024,
     46         n=1,
     47         stop=None,
     48         temperature=0.1,
     49     )
     51     # Extract the generated answer from the API response
     52     answer = response.choices[0].text.strip()

File ~/.local/lib/python3.11/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 ~/.local/lib/python3.11/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 ~/.local/lib/python3.11/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 ~/.local/lib/python3.11/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 ~/.local/lib/python3.11/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

InvalidRequestError: Invalid URL (POST /v1/engines/gpt-3.5-turbo/chat/completions)

To Reproduce

SEE THE DESCRIBE PART

Code snippets

SEE THE DESCRIBE PART

OS

LINUX-UBUNTU-LATEST

Python version

PYTHON3.11

Library version

LATEST PYPI VERSION

[hallacy]

Hi @hemangjoshi37a, thanks for writing in.

If I had to guess, it looks like you're trying to change an existing openai.Completion call to openai.ChatCompletion. There are a couple major differences:

• From https://platform.openai.com/docs/api-reference/chat/create -> you'll want to use model, not engine
• From https://platform.openai.com/docs/api-reference/chat/create and https://platform.openai.com/docs/guides/chat -> you'll want to use messages, not prompt

Hpoe this helps!

[vviss]

Same issue, trying to use text-ada-001.

response = openai.ChatCompletion.create(
                model="text-ada-001",
                messages=[
                    {"role": "system", "content": "You are a friendly chatbot and assistant"},
                    {"role": "user", "content": " some question"},
                    {"role": "assistant", "content": "some answer"},
                    {"role": "user", "content": "Rephrase your last answer"}
                    ])

openai.error.InvalidRequestError: Invalid URL (POST /v1/chat/completions)

[vviss]

SOLVED FOR ME:

In my case it was simply because ChatCompletion is not supported with text-ada-001

[hemangjoshi37a]

Hi @hallacy, @vviss,

Thanks for your insights.

It seems there was a confusion with the OpenAI's GPT-3.5-turbo model's API usage. I was trying to use the openai.ChatCompletion.create() method similar to how openai.Completion.create() is used, but as you pointed out, there are significant differences.

To use the GPT-3.5-turbo model, I should indeed be utilizing the model parameter instead of engine, and the messages parameter instead of prompt. I appreciate the clarity, and I will make sure to modify my code accordingly.

Here is the corrected version of my function:

def classify_tokens_gpt3_5_turbo_multiple_parts(email_text: str) -> list:
    # Define the system message
    system_message = (
        "Given the request for quotation email below, identify and classify the following information for each part: "
        "email_Subject_Phrase, RFQ_number, Manufacturer_Part_Number, Qty_Required, Manufacturer_name, "
        "Customer_Part_Number, Product_Description, Target_Price, Lead_Time_days, Date_Code, Packaging_Type, "
        "Dispatch_Date, Comments, Currency, min_ord_qty, STD_PACK_QTY, SENDER_NAME, SENDER_POSITION, SENDER_COMPANY, SENDER_MOBILE, "
        "SENDER_EMAIL, SENDER_ADDRESS, SENDER_COUNTRY, SENDER_PINCODE, SENDER_CITY, SENDER_STATE."
    )

    # Create the messages list
    messages = [
        {"role": "system", "content": system_message},
        {"role": "user", "content": f"Email:\n{email_text}\n\n"}
    ]

    # Call the GPT-3.5-turbo API
    response = openai.ChatCompletion.create(
        model="gpt-3.5-turbo",
        messages=messages,
        max_tokens=1024,
        n=1,
        temperature=0.1,
    )

    # Extract the generated answer from the API response
    answer = response.choices[0].message['content'].strip()
    print(f'{answer=}')

    # Split the answer into a list of parts
    parts = re.split(r'\n\s*\n', answer)

    # Parse the individual parts into a list of dictionaries
    classified_tokens_list = []
    for part in parts:
        classified_tokens = {}
        for line in part.split('\n'):
            if ':' in line:
                key, value = line.split(':', 1)
                classified_tokens[key.strip()] = value.strip()
        classified_tokens_list.append(classified_tokens)

    return classified_tokens_list

Thanks for your patience and guidance on this matter.

Best,
@hemangjoshi37a