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如何在流模式下获取每个OpenAI ChatCompletion API调用的令牌使用情况？

openai-api
7
你能够添加你用于调用API的代码吗？ - Masoud Gheisari
嗨，你最终能够得到它了吗？我也在努力以流模式获取它（但是使用的是Node，而不是Python）。 - DS_web_developer
我也遇到了同样的问题；一个不同之处是我正在尝试使用Azure开放AI，而我不是一个使用SDK的消费者，我更像是一个平台团队，为一个大团队提供支持 - 谁是理想的消费者。 - Jayendran
2个回答
0

你可以使用tiktoken

pip安装tiktoken

import tiktoken

def num_tokens_from_messages(messages, model="gpt-3.5-turbo-0301"):
    """Returns the number of tokens used by a list of messages."""
    try:
        encoding = tiktoken.encoding_for_model(model)
    except KeyError:
        print("Warning: model not found. Using cl100k_base encoding.")
        encoding = tiktoken.get_encoding("cl100k_base")
    if model == "gpt-3.5-turbo":
        print("Warning: gpt-3.5-turbo may change over time. Returning num tokens assuming gpt-3.5-turbo-0301.")
        return num_tokens_from_messages(messages, model="gpt-3.5-turbo-0301")
    elif model == "gpt-4":
        print("Warning: gpt-4 may change over time. Returning num tokens assuming gpt-4-0314.")
        return num_tokens_from_messages(messages, model="gpt-4-0314")
    elif model == "gpt-3.5-turbo-0301":
        tokens_per_message = 4  # every message follows <|start|>{role/name}\n{content}<|end|>\n
        tokens_per_name = -1  # if there's a name, the role is omitted
    elif model == "gpt-4-0314":
        tokens_per_message = 3
        tokens_per_name = 1
    else:
        raise NotImplementedError(f"""num_tokens_from_messages() is not implemented for model {model}. See https://github.com/openai/openai-python/blob/main/chatml.md for information on how messages are converted to tokens.""")
    num_tokens = 0

    if type(messages) == "list":
        for message in messages:
            num_tokens += tokens_per_message
            for key, value in message.items():
                num_tokens += len(encoding.encode(value))
                if key == "name":
                    num_tokens += tokens_per_name
        num_tokens += 3  # every reply is primed with <|start|>assistant<|message|>
    elif type(messages) == "str":
        num_tokens += len(encoding.encode(messages))
    return num_tokens


import openai

result = []

for chunk in 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?"},
        {"role": "assistant", "content": "The Los Angeles Dodgers won the World Series in 2020."},
        {"role": "user", "content": "Where was it played?"}
    ], # this is prompt_tokens ex) prompt_tokens=num_tokens_from_messages(messages)
    stream=True
):
    content = chunk["choices"][0].get("delta", {}).get("content")
    if content:
        result.append(content)


# Usage of completion_tokens
completion_tokens = num_tokens_from_messages("".join(result))
-1

如果你使用Lagchain，你也可以使用get_openai_callback()

from langchain.callbacks import get_openai_callback

        with get_openai_callback() as cb:
            response = qa({"question": prompt, "chat_history": chat_history})

            print(f"Prompt Tokens: {cb.prompt_tokens}")
            print(f"Completion Tokens: {cb.completion_tokens}")
            print(f"Total Cost (USD): ${cb.total_cost}")
1
这在流媒体方面行不通，这也是问题所在。 - mcont
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