Working on a fix for this right this second, hang tight.

from auto-gpt.

This error should be mitigated by #3646 (a patch rather than a fix). Currently I'm working on improving and fixing the entire memory system which should fix all of these errors.

from auto-gpt.

@Torantulino The problem stems from split_text in browse.py, you should be calculating token length instead of character length using something like

from transformers import GPT2TokenizerFast
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2")

def split_text(text, max_length=2000):
    tokenized_text = tokenizer(text)['input_ids']

then you can guarantee that you wont go over.

from auto-gpt.

I tried to increase token limit with this in .env file:
FAST_TOKEN_LIMIT=16000
SMART_TOKEN_LIMIT=32000

but the chat crash with: openai.error.InvalidRequestError: This model's maximum context length is 4097 tokens. However, you requested 15997 tokens (960 in the messages, 15037 in the completion). Please reduce the length of the messages or completion.

How to allow more token ? What I have to do on openai website ? How to change openai model to use ?

from auto-gpt.

still facing the same issue

from auto-gpt.

It looks like we might need to tokenize each row of the text and save the number of tokens to a new column in a DataFrame with the tokenizer.encode() method from OpenAI''s TikToken library.

Or, just upgrade your OpenAi Plan....

I retrieved the technical answer here: https://www.mlq.ai/gpt-4-pinecone-website-ai-assistant/

Question: Should we edit the split_text in browse.py to calculate token length instead of character length, like @PhilipAD mentioned above?

from auto-gpt.

Same here:

raise self.handle_error_response(
openai.error.InvalidRequestError: This model's maximum context length is 8192 tokens. However, your messages resulted in 8272 tokens. Please reduce the length of the messages.

from auto-gpt.

Quite a few other issues have been opened on this topic:

• #38
• #3367
• #3681
• #3742
• #3892
• #3979
• #4012
• #4019

Also, please consider these relevant pull requests:

• #3266
• #3588
• #4498

Furthermore, since PRs are on hold and the core contributors are rearchitecting Auto-GPT, these issues may auto-resolve with the new release.

See also: https://github.com/Significant-Gravitas/Nexus/wiki/Architecting

from auto-gpt.

I also get this error. Not sure what to do about it. It's possible to count tokens using tiktoken, but, what then? Just truncate the prompt?

from auto-gpt.

I have the same error. Don't know how to solve...

from auto-gpt.

Try setting your token_limit to a lower value

from auto-gpt.

Try setting your token_limit to a lower value

what file to modify?

from auto-gpt.

I tried to increase token limit with this in .env file: FAST_TOKEN_LIMIT=16000 SMART_TOKEN_LIMIT=32000

but the chat crash with: openai.error.InvalidRequestError: This model's maximum context length is 4097 tokens. However, you requested 15997 tokens (960 in the messages, 15037 in the completion). Please reduce the length of the messages or completion.

How to allow more token ? What I have to do on openai website ? How to change openai model to use ?

Ok, I found https://platform.openai.com/docs/models/gpt-3-5 I upgrade gpt-4 to gpt-4-32k . gpt-3.5-turbo cannot be upgraded because lack in this source code.

from auto-gpt.

I tried to increase token limit with this in .env file: FAST_TOKEN_LIMIT=16000 SMART_TOKEN_LIMIT=32000
but the chat crash with: openai.error.InvalidRequestError: This model's maximum context length is 4097 tokens. However, you requested 15997 tokens (960 in the messages, 15037 in the completion). Please reduce the length of the messages or completion.
How to allow more token ? What I have to do on openai website ? How to change openai model to use ?

Ok, I found https://platform.openai.com/docs/models/gpt-3-5 I upgrade gpt-4 to gpt-4-32k . gpt-3.5-turbo cannot be upgraded because lack in this source code.

but not gpt-4-32k not work:
SYSTEM: Command evaluate_code returned: Error: The model: gpt-4-32k does not exist

how to use it ??

from auto-gpt.

mannnn

NEXT ACTION: COMMAND = message_agent ARGUMENTS = {'key': 18, 'message': "Can you help us develop the character's romance subplot in a way that ties in with the established themes of the story? Please limit your response to 2000 characters or less. Additionally, can you provide us with some ideas for the love interests and their motivations?"}
Enter 'y' to authorise command, 'y -N' to run N continuous commands, 'n' to exit program, or enter feedback for authorGPT...
Input:y
-=-=-=-=-=-=-= COMMAND AUTHORISED BY USER -=-=-=-=-=-=-=
SYSTEM: Command message_agent returned: Error: This model's maximum context length is 4097 tokens. However, your messages resulted in 4563 tokens.

NEXT ACTION: COMMAND = message_agent ARGUMENTS = {'key': 18, 'message': "Can you help us develop the character's romance subplot while making sure that the actions and motivations of the character tie in with the established themes of the story? Can you also provide us with some ideas for the love interests? Please summarize your response to ensure we understand your ideas clearly. Thank you!"}
Enter 'y' to authorise command, 'y -N' to run N continuous commands, 'n' to exit program, or enter feedback for authorGPT...
Input:y
-=-=-=-=-=-=-= COMMAND AUTHORISED BY USER -=-=-=-=-=-=-=
SYSTEM: Command message_agent returned: Error: This model's maximum context length is 4097 tokens. However, your messages resulted in 4627 tokens.

from auto-gpt.

Input:Request failed with status code: 401
Response content: b'{"detail":{"status":"quota_exceeded","message":"This request exceeds your quota. You have 68 characters remaining, while 92 characters are required for this request.","character_used":10024,"character_limit":10000}}'
how to adjust character_limit?
SYSTEM: Human feedback: how to adjust character_limit?
Warning: Failed to parse AI output, attempting to fix.
If you see this warning frequently, it's likely that your prompt is confusing the AI. Try changing it up slightly.
Failed to fix AI output, telling the AI.
Error: Invalid JSON
The character limit can be adjusted in the OpenAI API settings when creating an API key. You can set the maximum length of tokens (words) generated by the API in a single response. Keep in mind that a shorter character limit may result in more concise or lower quality responses, while a longer character limit may result in more verbose or higher quality responses.
AUTO JOB HUNTER THOUGHTS:
REASONING:
CRITICISM:
Warning: Failed to parse AI output, attempting to fix.
If you see this warning frequently, it's likely that your prompt is confusing the AI. Try changing it up slightly.
Failed to fix AI output, telling the AI.
NEXT ACTION: COMMAND = Error: ARGUMENTS = Missing 'command' object in JSON
Enter 'y' to authorise command, 'y -N' to run N continuous commands, 'n' to exit program, or enter feedback for Auto Job Hunter...
Input:truncate responses google commands to be less than character limit
SYSTEM: Human feedback: truncate responses google commands to be less than character limit
Warning: Failed to parse AI output, attempting to fix.
If you see this warning frequently, it's likely that your prompt is confusing the AI. Try changing it up slightly.
AUTO JOB HUNTER THOUGHTS: thought
REASONING: reasoning
PLAN:

• short bulleted
• list that conveys
• long-term plan
  CRITICISM: constructive self-criticism
  Warning: Failed to parse AI output, attempting to fix.

from auto-gpt.

^ read more about this and it appears to be tokens for ElevenLabs (#263)

from auto-gpt.

I asked Auto-GPT to help with this problem and it found out that the correct model to use for a larger context length is gpt-4-13b

SMART_LLM_MODEL=gpt-4-13b

It seems to be working! More expensive though.

I am also using SMART_TOKEN_LIMIT=25000 for now while the token length estimation is off.

from auto-gpt.

I asked Auto-GPT to help with this problem and it found out that the correct model to use for a larger context length is gpt-4-13b

SMART_LLM_MODEL=gpt-4-13b

It seems to be working! More expensive though.

I am also using SMART_TOKEN_LIMIT=25000 for now while the token length estimation is off.

Might have spoken too soon, I am now seeing this error...
SYSTEM: Command evaluate_code returned: Error: The model gpt-4-13b does not exist

Does this mean it has been using the "fast" model (gpt-3.5) up to this point? Or is this error specific to "Command evaluate_code"?

from auto-gpt.

@Torantulino The problem stems from split_text in browse.py, you should be calculating token length instead of character length using something like

from transformers import GPT2TokenizerFast
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2")

def split_text(text, max_length=2000):
    tokenized_text = tokenizer(text)['input_ids']

then you can guarantee that you wont go over.

does this work? if so, where do I put that code, and what does it replace?

from auto-gpt.

Same issue. Any fix?

from auto-gpt.

I tried to increase token limit with this in .env file: FAST_TOKEN_LIMIT=16000 SMART_TOKEN_LIMIT=32000
but the chat crash with: openai.error.InvalidRequestError: This model's maximum context length is 4097 tokens. However, you requested 15997 tokens (960 in the messages, 15037 in the completion). Please reduce the length of the messages or completion.
How to allow more token ? What I have to do on openai website ? How to change openai model to use ?

Ok, I found https://platform.openai.com/docs/models/gpt-3-5 I upgrade gpt-4 to gpt-4-32k . gpt-3.5-turbo cannot be upgraded because lack in this source code.

but not gpt-4-32k not work:
SYSTEM: Command evaluate_code returned: Error: The model: gpt-4-32k does not exist

how to use it ??

@giovannimanzoni I saw the same yesterday when trying to use this model with Postman. I guess it's because of the license. I guess you don't have access to GPTPlus/GPT-4, which is the case for me as well. I will get my GPTPlus licence on Monday, I could try and keep you posted.

from auto-gpt.

I tried to increase token limit with this in .env file: FAST_TOKEN_LIMIT=16000 SMART_TOKEN_LIMIT=32000
but the chat crash with: openai.error.InvalidRequestError: This model's maximum context length is 4097 tokens. However, you requested 15997 tokens (960 in the messages, 15037 in the completion). Please reduce the length of the messages or completion.
How to allow more token ? What I have to do on openai website ? How to change openai model to use ?

Ok, I found https://platform.openai.com/docs/models/gpt-3-5 I upgrade gpt-4 to gpt-4-32k . gpt-3.5-turbo cannot be upgraded because lack in this source code.

but not gpt-4-32k not work:
SYSTEM: Command evaluate_code returned: Error: The model: gpt-4-32k does not exist

how to use it ??

@giovannimanzoni I saw the same yesterday when trying to use this model with Postman. I guess it's because of the license. I guess you don't have access to GPTPlus/GPT-4, which is the case for me as well. I will get my GPTPlus licence on Monday, I could try and keep you posted.

Yes, that's right. We need v4 API . I'm waiting my license.

from auto-gpt.

Should be fixed in #2542 just now.

from auto-gpt.

Should be fixed in #2542 just now.

Unfortunately reproduced in #2906

from auto-gpt.

Repurposing this issue as a collection issue for the following:

• #796
• #1841
• #2420
• #2801
• #2871
• #2906
• #3244

from auto-gpt.

Continuous Mode:  ENABLED
WARNING:  Continuous mode is not recommended. It is potentially dangerous and may cause your AI to run forever or carry out actions you would not usually authorise. Use at your own risk.
GPT3.5 Only Mode:  ENABLED
WARNING: Plugin SystemInformationPlugin found. But not in the allowlist... Load? (y/n):
WARNING: Plugin AutoGPT_YouTube found. But not in the allowlist... Load? (y/n):
Welcome back!  Would you like me to return to being EarningsReportGPT?
Continue with the last settings?
Name:  EarningsReportGPT
Role:  an AI assistant that specializes in providing detailed and highly readable summaries of earnings reports, along with a sentiment rating, to help businesses make informed decisions.
Goals: ['Retrieve the latest earnings report using the API keys provided in APIkeys.txt.', 'Analyze the report and provide a detailed summary that highlights the most important information in a highly readable format.', 'Assign a sentiment rating from 1 to 10 based on the overall tone of the report, with 1 being very negative and 10 being very positive.', 'Ensure that the summary and sentiment rating are delivered in a timely manner to allow for quick decision-making.', 'Continuously learn and improve its analysis and reporting capabilities to provide even more valuable insights to its users.']
API Budget: infinite
Continue (y/n):
EarningsReportGPT  has been created with the following details:
Name:  EarningsReportGPT
Role:  an AI assistant that specializes in providing detailed and highly readable summaries of earnings reports, along with a sentiment rating, to help businesses make informed decisions.
Goals:
-  Retrieve the latest earnings report using the API keys provided in APIkeys.txt.
-  Analyze the report and provide a detailed summary that highlights the most important information in a highly readable format.
-  Assign a sentiment rating from 1 to 10 based on the overall tone of the report, with 1 being very negative and 10 being very positive.
-  Ensure that the summary and sentiment rating are delivered in a timely manner to allow for quick decision-making.
-  Continuously learn and improve its analysis and reporting capabilities to provide even more valuable insights to its users.
Using memory of type:  PineconeMemory
Using Browser:  chrome
 THOUGHTS:  I need to retrieve the latest earnings report using the API keys provided in APIkeys.txt. I will start by reading the API keys from the file and then use them to make a request to the API endpoint.
REASONING:  I need to retrieve the latest earnings report to analyze and provide a summary with a sentiment rating. This will help businesses make informed decisions.
PLAN:
-  Read API keys from APIkeys.txt
-  Make request to API endpoint using the keys
-  Retrieve the latest earnings report
-  Analyze the report and provide a summary with a sentiment rating
-  Deliver the summary and sentiment rating in a timely manner
CRITICISM:  I need to ensure that I am using the correct API keys and that the request to the API endpoint is successful. I also need to make sure that the summary and sentiment rating are accurate and useful to the user.
NEXT ACTION:  COMMAND = read_file ARGUMENTS = {'filename': 'D:\\GPT\\Autogpt\\autogpt\\auto_gpt_workspace\\APIkeys.txt'}
SYSTEM:  Command read_file returned: 
 THOUGHTS:  Now that I have the API keys, I will use them to make a request to the API endpoint and retrieve the latest earnings report.
REASONING:  I need to retrieve the latest earnings report to analyze and provide a summary with a sentiment rating. This will help businesses make informed decisions.
PLAN:
-  Make request to API endpoint using the keys
-  Retrieve the latest earnings report
-  Analyze the report and provide a summary with a sentiment rating
-  Deliver the summary and sentiment rating in a timely manner
CRITICISM:  I need to ensure that the request to the API endpoint is successful and that I am retrieving the correct information. I also need to make sure that the summary and sentiment rating are accurate and useful to the user.
NEXT ACTION:  COMMAND = execute_shell ARGUMENTS = {'command_line': 'curl -H "Authorization: Bearer " -H "Content-Type: application/json" "https://newsapi.org/v2/everything?q=earnings%20report&sortBy=publishedAt&apiKey="'}
Executing command 'curl -H "Authorization: Bearer " -H "Content-Type: application/json" "https://newsapi.org/v2/everything?q=earnings%20report&sortBy=publishedAt&apiKey="' in working directory 'D:\GPT\Autogpt\autogpt\auto_gpt_workspace'
Traceback (most recent call last):
  File "<frozen runpy>", line 198, in _run_module_as_main
  File "<frozen runpy>", line 88, in _run_code
  File "D:\GPT\Autogpt\autogpt\__main__.py", line 5, in <module>
    autogpt.cli.main()
  File "C:\Python311\Lib\site-packages\click\core.py", line 1130, in __call__
    return self.main(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Python311\Lib\site-packages\click\core.py", line 1055, in main
    rv = self.invoke(ctx)
         ^^^^^^^^^^^^^^^^
  File "C:\Python311\Lib\site-packages\click\core.py", line 1635, in invoke
    rv = super().invoke(ctx)
         ^^^^^^^^^^^^^^^^^^^
  File "C:\Python311\Lib\site-packages\click\core.py", line 1404, in invoke
    return ctx.invoke(self.callback, **ctx.params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Python311\Lib\site-packages\click\core.py", line 760, in invoke
    return __callback(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Python311\Lib\site-packages\click\decorators.py", line 26, in new_func
    return f(get_current_context(), *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\GPT\Autogpt\autogpt\cli.py", line 90, in main
    run_auto_gpt(
  File "D:\GPT\Autogpt\autogpt\main.py", line 154, in run_auto_gpt
    agent.start_interaction_loop()
  File "D:\GPT\Autogpt\autogpt\agent\agent.py", line 242, in start_interaction_loop
    self.memory.add(memory_to_add)
  File "D:\GPT\Autogpt\autogpt\memory\pinecone.py", line 47, in add
    vector = get_ada_embedding(data)
             ^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\GPT\Autogpt\autogpt\llm_utils.py", line 231, in get_ada_embedding
    embedding = create_embedding(text, **kwargs)
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\GPT\Autogpt\autogpt\llm_utils.py", line 46, in _wrapped
    return func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^
  File "D:\GPT\Autogpt\autogpt\llm_utils.py", line 257, in create_embedding
    return openai.Embedding.create(
           ^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Python311\Lib\site-packages\openai\api_resources\embedding.py", line 33, in create
    response = super().create(*args, **kwargs)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Python311\Lib\site-packages\openai\api_resources\abstract\engine_api_resource.py", line 153, in create
    response, _, api_key = requestor.request(
                           ^^^^^^^^^^^^^^^^^^
  File "C:\Python311\Lib\site-packages\openai\api_requestor.py", line 226, in request
    resp, got_stream = self._interpret_response(result, stream)
                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Python311\Lib\site-packages\openai\api_requestor.py", line 619, in _interpret_response
    self._interpret_response_line(
  File "C:\Python311\Lib\site-packages\openai\api_requestor.py", line 682, in _interpret_response_line
    raise self.handle_error_response(
**openai.error.InvalidRequestError: This model's maximum context length is 8191 tokens, however you requested 26735 tokens (26735 in your prompt; 0 for the completion). Please reduce your prompt; or completion length.**

from auto-gpt.

import nltk
nltk.download('punkt')

def process_text(text):
# Dividir el texto en oraciones usando la librería nltk
sentences = nltk.sent_tokenize(text)

# Inicializar una lista vacía para almacenar los resultados
results = []

# Procesar cada oración por separado
for sentence in sentences:
    # Enviar cada oración al modelo de IA para su procesamiento
    embedding = create_embedding_with_ada(sentence)
    
    # Agregar el resultado a la lista de resultados
    results.append(embedding)

# Unir los resultados en una única salida
output = ''.join(results)

return output

Código original con la función procesar_texto() añadida

def run_auto_gpt():
# ...
agent.start_interaction_loop()
# ...

def main():
run_auto_gpt()

if name == 'main':
main()

from auto-gpt.

Still occurring with latest branch
Full log

https://gist.githubusercontent.com/remriel/ea20ffcdc1afeb9876fe1c7d7bc7458d/raw/f7dd1a269aa12e85fbf3a3997b247d529ca3f369/errorlog.log

from auto-gpt.

Same error, any fixes ?

File "/usr/local/lib/python3.10/site-packages/openai/api_requestor.py", line 682, in _interpret_response_line
raise self.handle_error_response(
openai.error.InvalidRequestError: This model's maximum context length is 4097 tokens. However, your messages resulted in 5063 tokens. Please reduce the length of the messages.

from auto-gpt.

Working on a fix for this right this second, hang tight.

Any update? Need better error handling big time.

from auto-gpt.

I think the issue is that the devs have not integrated tiktoken into the platform, this is why this is happening.

TikToken will basically count the tokens needed to send your request and then we can automatically adjust the max tokens we send openAI so that it does not try to send back a response that would exceed the max token count for your model. Also there should be some left unused to accommodate the small margin of error tik token can produce.

We have developed an AutoGPT UI that we are about to release opensource and we are debating on integrating tiktoken and filing a pull request to bring it into the platform but we dont want to duplicate the effort if the core dev team is already working this.

from auto-gpt.

I think the issue is that the devs have not integrated tiktoken into the platform, this is why this is happening.

Actually, we have: we use tiktoken to count tokens, chunk and truncate the input, and limit the LLM's output in API calls.

I've been trying to debug the latest reports of this issue, because it should have been fixed in #4652 but some users are still having issues. Unfortunately, nobody has been able to provide us with a full log or other debug info which we need to figure this out, because we can't reproduce it.

from auto-gpt.

This issue was closed automatically because it has been stale for 10 days with no activity.

from auto-gpt.