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124 lines
3.9 KiB
Python
124 lines
3.9 KiB
Python
import tiktoken
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import openai
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import json
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import os
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openai.api_key = os.getenv("OPENAI_API_KEY")
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def encode(text: str, model: str):
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import tiktoken
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enc = tiktoken.get_encoding("cl100k_base")
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assert enc.decode(enc.encode("hello world")) == "hello world"
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# To get the tokeniser corresponding to a specific model in the OpenAI API:
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enc = tiktoken.encoding_for_model(model)
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return enc.encode(text)
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# def ask(prompt: str, model: str = "gpt-3.5-turbo"):
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# # To get the tokeniser corresponding to a specific model in the OpenAI API:
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# enc = tiktoken.encoding_for_model(model)
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# resp = openai.ChatCompletion.create(
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# model=model,
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# messages=[
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# {
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# "role": "user",
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# "content": prompt
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# }
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# ]
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# )
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# return enc.encode(prompt), enc.encode(resp['choices'][0]['message']['content']), resp
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def ask(
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messages: list,
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model: str = "gpt-3.5-turbo"
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):
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enc = tiktoken.encoding_for_model(model)
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resp = openai.ChatCompletion.create(
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model=model,
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messages=messages
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)
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txt = ""
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for r in messages:
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txt += r['role'] + r['content'] + "\n"
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txt += "assistant: "
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return enc.encode(txt), enc.encode(resp['choices'][0]['message']['content']), resp
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def num_tokens_from_messages(messages, model="gpt-3.5-turbo-0613"):
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"""Return the number of tokens used by a list of messages."""
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try:
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encoding = tiktoken.encoding_for_model(model)
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except KeyError:
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print("Warning: model not found. Using cl100k_base encoding.")
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encoding = tiktoken.get_encoding("cl100k_base")
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if model in {
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"gpt-3.5-turbo-0613",
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"gpt-3.5-turbo-16k-0613",
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"gpt-4-0314",
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"gpt-4-32k-0314",
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"gpt-4-0613",
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"gpt-4-32k-0613",
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}:
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tokens_per_message = 3
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tokens_per_name = 1
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elif model == "gpt-3.5-turbo-0301":
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tokens_per_message = 4 # every message follows <|start|>{role/name}\n{content}<|end|>\n
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tokens_per_name = -1 # if there's a name, the role is omitted
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elif "gpt-3.5-turbo" in model:
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print("Warning: gpt-3.5-turbo may update over time. Returning num tokens assuming gpt-3.5-turbo-0613.")
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return num_tokens_from_messages(messages, model="gpt-3.5-turbo-0613")
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elif "gpt-4" in model:
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print("Warning: gpt-4 may update over time. Returning num tokens assuming gpt-4-0613.")
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return num_tokens_from_messages(messages, model="gpt-4-0613")
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else:
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raise NotImplementedError(
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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."""
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)
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num_tokens = 0
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for message in messages:
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num_tokens += tokens_per_message
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for key, value in message.items():
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num_tokens += len(encoding.encode(value))
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if key == "name":
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num_tokens += tokens_per_name
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num_tokens += 3 # every reply is primed with <|start|>assistant<|message|>
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return num_tokens
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messages = [
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{
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"role": "user",
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"content": "你叫什么名字？"
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},{
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"role": "assistant",
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"content": "我是AI助手，没有具体的名字。你可以叫我GPT-3。有什么可以帮到你的吗？"
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},{
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"role": "user",
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"content": "你是由谁开发的？"
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},{
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"role": "assistant",
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"content": "我是由OpenAI开发的，一家人工智能研究实验室。OpenAI的使命是促进人工智能的发展，使其为全人类带来积极影响。我是由OpenAI团队使用GPT-3模型训练而成的。"
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},{
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"role": "user",
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"content": "很高兴见到你。"
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}
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]
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pro, rep, resp=ask(messages)
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print(len(pro), len(rep))
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print(resp)
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print(resp['choices'][0]['message']['content'])
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print(num_tokens_from_messages(messages, model="gpt-3.5-turbo")) |