#Tokens usage tracking

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granite osprey
#

@old heron suppose i have a assistant with id asst_SWdjgL4zEE53gIv7t0ZueSx5 and i want to track the tokens used by this assistant
how can i track it
if not assistant can i track it via a thread?

old heronBOT
#

Hi @granite osprey. I'm kapa.ai, your friendly support bot. I will try to answer your question by searching through the knowledge base. :wave:

#

You can track the token usage of your assistant in two main ways:

  1. Usage Dashboard: OpenAI provides a usage dashboard (https://beta.openai.com/account/usage) that displays your API usage during the current and past monthly billing cycles. However, this dashboard does not provide a breakdown by individual assistants or threads.

  2. API Response: Token usage information is included in responses from OpenAI's endpoints under the usage key. For example, when you make a call to the API, the response will include a usage field that shows the number of tokens used. Here's an example of what the response might look like:

{  
    "id": "chatcmpl-abc123",  
    "object": "chat.completion",  
    "created": 1677858242,  
    "model": "gpt-3.5-turbo",  
    "usage": {  
        "prompt_tokens": 13,  
        "completion_tokens": 7,  
        "total_tokens": 20  
    },  
    "choices": [  
        {  
            "message": {  
                "role": "assistant",  
                "content": "This is a test!"  
            }  
        }  
    ]  
}

In this example, prompt_tokens is the number of tokens in the prompt, completion_tokens is the number of tokens in the completion, and total_tokens is the sum of the two.

If you're using the Assistant API, you can find token usage information in the Run Steps (https://platform.openai.com/docs/api-reference/run-steps). If you're using the streaming API, the run step completed (https://platform.openai.com/docs/api-reference/assistants-streaming/events#assistants-streaming/events-thread-run-step-completed) and run completed (https://platform.openai.com/docs/api-reference/assistants-streaming/events#assistants-streaming/events-thread-run-completed) events will include usage statistics.

#

Please note that the token usage can be high if you're using the same thread for multiple runs, as the messages are saved in a thread and grow as long as the chat session continues. If you want to minimize token usage, you might want to consider creating a new thread for each request, unless you need to maintain the context from previous messages.

Sources:

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#

@granite osprey kapa.ai is still learning and improving, please let us know how it did by reacting below

granite osprey
#

@old heron can you write a code get the token usage for this specific assistant asst_SWdjgL4zEE53gIv7t0ZueSx5

old heronBOT
#

Let me check the knowledge base for you. One moment! :books:

#

Sure, here's an example of how you can retrieve an assistant's response and check the token usage. This example uses the OpenAI Python SDK. Please replace YOUR_OPENAI_API_KEY with your actual OpenAI API key.

from openai import OpenAI

openai = OpenAI("YOUR_OPENAI_API_KEY")

response = openai.Assistant.create(
  model="gpt-3.5-turbo",
  messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Who won the world series in 2020?"},
    ],
  assistant="asst_SWdjgL4zEE53gIv7t0ZueSx5"
)

print(response['usage'])

In this example, the response['usage'] will print out the token usage for this specific assistant interaction.

Please note that this code is a general example and might need to be adjusted based on your specific use case and environment.

Also, remember that the token usage can be high if you're using the same thread for multiple runs, as the messages are saved in a thread and grow as long as the chat session continues. If you want to minimize token usage, you might want to consider creating a new thread for each request, unless you need to maintain the context from previous messages.

Sources:

Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:

#

@granite osprey kapa.ai is still learning and improving, please let us know how it did by reacting below

granite osprey
#

Traceback (most recent call last):
File "d:\Tryzent\assistants-api\try.py", line 7, in <module>
response = openai.Assistant.create(
^^^^^^^^^^^^^^^^
AttributeError: 'OpenAI' object has no attribute 'Assistant'

#

@old heron
Traceback (most recent call last):
File "d:\Tryzent\assistants-api\try.py", line 7, in <module>
response = openai.Assistant.create(
^^^^^^^^^^^^^^^^
AttributeError: 'OpenAI' object has no attribute 'Assistant'

old heronBOT
#

Let me check the knowledge base for you. One moment! :books:

#

The error message you're seeing, AttributeError: 'OpenAI' object has no attribute 'Assistant', suggests that the Assistant attribute is not available in the openai module you're using. This could be due to a few reasons:

  1. You might be using an outdated version of the OpenAI Python library. Make sure you have the latest version installed. You can update it using pip:
pip install --upgrade openai
  1. The Assistant class might not be available in the version of the OpenAI Python library you're using. In the OpenAI Python library, the method to create a chat model is openai.ChatCompletion.create(). Here's an example:
import openai

openai.api_key = 'YOUR_OPENAI_API_KEY'

response = openai.ChatCompletion.create(
  model="gpt-3.5-turbo",
  messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Who won the world series in 2020?"},
    ]
)

print(response['usage'])

Please replace 'YOUR_OPENAI_API_KEY' with your actual OpenAI API key.

Remember to check the OpenAI API documentation (https://platform.openai.com/docs/api-reference) for the most accurate and up-to-date information.

Sources:

Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:

#

@granite osprey kapa.ai is still learning and improving, please let us know how it did by reacting below

granite osprey
#

@old heron can assistant api perform RAG on pdfs in hindi text

old heronBOT
#

Let me check the knowledge base for you. One moment! :books:

#

The Assistant API from OpenAI can process and generate text in various languages, including Hindi. However, the ability to directly extract and process text from PDFs, especially in languages other than English, might not be perfect.

In a forum post (https://community.openai.com/t/732448), a user reported issues with the Assistant API V2 not extracting text from PDFs as well as V1. The user mentioned that even after migrating to V2 with Vector Store, the assistant struggled to extract the required text from the PDF.

As a workaround, it was suggested in another forum post (https://community.openai.com/t/793805) to manually extract the text from the PDF and convert it to markdown. This way, you have control over what data is being fed into the model.

For a more advanced solution, you could consider building a Retrieval-Augmented Generation (RAG) pipeline based on PDF documents. This involves parsing the PDF documents, processing the extracted content, embedding the processed content using OpenAI embeddings, retrieving content relevant to an input query, and using a language model to generate an answer using the retrieved content as context. This process is explained in detail in an OpenAI Cookbook example (https://cookbook.openai.com/examples/parse_pdf_docs_for_rag#wrapping-up).

Please note that while OpenAI's models have been trained on a diverse range of internet text, they might not perform as well on languages other than English due to the training data distribution.

#

@granite osprey kapa.ai is still learning and improving, please let us know how it did by reacting below

granite osprey
#

@old heron Request too large for gpt-4o in organization org-KiOnKxiX16tzT9CWl1e9v6CG on tokens per min (TPM): Limit 30000, Requested 33361. The input or output tokens must be reduced in order to run successfully. Visit https://platform.openai.com/account/rate-limits to learn more.

how can fix this error its showing this error after searching the file in vector store how can i make it such that it will fetch the required file only?

old heronBOT
#

Let me check the knowledge base for you. One moment! :books:

#

The error message you're seeing is due to exceeding the token limit for the model you're using. In this case, the model gpt-4o has a limit of 30,000 tokens per minute, and your request is exceeding this limit with 33,361 tokens.

Here are a few ways you can address this issue:

  1. Reduce the size of your input: If your input text is too long, you might need to shorten it to fit within the model's token limit.

  2. Chunk your data: If you're dealing with large files in the vector store, you might need to chunk your data into smaller pieces. In a forum post (https://community.openai.com/t/843825), a user suggested dividing a large JSON file into smaller 1MB files to avoid exceeding the token limit.

  3. Specify files in the vector store: If you're using the vector store, you can specify which files the assistant should use to answer questions. In a forum post (https://community.openai.com/t/802201), a user asked if it's possible to direct the assistant to answer questions using a single file or a subset of files within a vector store. The answer suggested that when files are uploaded within messages, a new vector_store is created associated with the thread, and the file search tool will query both the vector_store from your assistant and the vector_store on the thread.

  4. Use a different model: If reducing the size of your input or chunking your data is not feasible, you might need to consider using a different model that has a higher token limit.

Remember to check the OpenAI API documentation (https://platform.openai.com/docs/api-reference) and your OpenAI account rate limits (https://platform.openai.com/account/rate-limits) for the most accurate and up-to-date information.

#

@granite osprey kapa.ai is still learning and improving, please let us know how it did by reacting below

granite osprey
#

@old heron

old heronBOT
#

Let me check the knowledge base for you. One moment! :books:

#

Sorry @granite osprey, I seem to be having a bit of trouble. Don't worry though, I've pinged my support and they will try to fix me up! :technologist:

Perhaps try again in 15mins?

granite osprey
#

@old heron can i disable chat memory in a thread

old heronBOT
#

Let me check the knowledge base for you. One moment! :books:

#

Yes, you can disable memory for a specific chat thread. The memory feature in ChatGPT can be turned on or off at any time by toggling the Memory setting under the Personalization section of Settings. Turning Memory off does not delete your memories, and deleting a chat doesn’t erase memories from that chat. You can delete memories conversationally or by clicking Manage.

For ChatGPT Enterprise workspace owners, they can toggle memories on and off for all users in their workspace in their Admin Settings.

Please note that if you'd like to have a conversation without memory, you can use Temporary Chat. Temporary Chats are deleted from OpenAI's systems within 30 days and won't be used for model training.

Sources:

Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:

#

@granite osprey kapa.ai is still learning and improving, please let us know how it did by reacting below

granite osprey
#

@old heron no in assistant api thread calling can i disable chat history in thread

old heronBOT
#

Let me check the knowledge base for you. One moment! :books:

#

In the Assistant API, there isn't a direct way to "disable" chat history within a thread. However, you can effectively achieve this by creating a new thread for each conversation.

In a forum post (https://community.openai.com/t/841242), a user asked about creating a new conversation, getting the assistant's output for the last message, and then deleting it as fast as possible to ensure that no message can influence another. The official response suggested creating a new thread every time a message is sent, thereby isolating each message to a thread.

Here's an example of how you can create a new thread for each conversation:

thread = client.beta.threads.create()

By doing this, you ensure that each conversation is isolated and doesn't influence subsequent conversations. This is effectively the same as "disabling" chat history within a thread.

Please note that this approach might not be suitable for all use cases. If you need to maintain the context from previous messages, you might want to continue using the same thread.

Sources:

Note: you can ask me a follow up question by @ mentioning me again :speech_balloon: