Files
LangBot/tests/token_test/tiktoken_test.py
T
2023-07-31 16:24:39 +08:00

124 lines
3.9 KiB
Python

import tiktoken
import openai
import json
import os
openai.api_key = os.getenv("OPENAI_API_KEY")
def encode(text: str, model: str):
import tiktoken
enc = tiktoken.get_encoding("cl100k_base")
assert enc.decode(enc.encode("hello world")) == "hello world"
# To get the tokeniser corresponding to a specific model in the OpenAI API:
enc = tiktoken.encoding_for_model(model)
return enc.encode(text)
# def ask(prompt: str, model: str = "gpt-3.5-turbo"):
# # To get the tokeniser corresponding to a specific model in the OpenAI API:
# enc = tiktoken.encoding_for_model(model)
# resp = openai.ChatCompletion.create(
# model=model,
# messages=[
# {
# "role": "user",
# "content": prompt
# }
# ]
# )
# return enc.encode(prompt), enc.encode(resp['choices'][0]['message']['content']), resp
def ask(
messages: list,
model: str = "gpt-3.5-turbo"
):
enc = tiktoken.encoding_for_model(model)
resp = openai.ChatCompletion.create(
model=model,
messages=messages
)
txt = ""
for r in messages:
txt += r['role'] + r['content'] + "\n"
txt += "assistant: "
return enc.encode(txt), enc.encode(resp['choices'][0]['message']['content']), resp
def num_tokens_from_messages(messages, model="gpt-3.5-turbo-0613"):
"""Return 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 in {
"gpt-3.5-turbo-0613",
"gpt-3.5-turbo-16k-0613",
"gpt-4-0314",
"gpt-4-32k-0314",
"gpt-4-0613",
"gpt-4-32k-0613",
}:
tokens_per_message = 3
tokens_per_name = 1
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 "gpt-3.5-turbo" in model:
print("Warning: gpt-3.5-turbo may update over time. Returning num tokens assuming gpt-3.5-turbo-0613.")
return num_tokens_from_messages(messages, model="gpt-3.5-turbo-0613")
elif "gpt-4" in model:
print("Warning: gpt-4 may update over time. Returning num tokens assuming gpt-4-0613.")
return num_tokens_from_messages(messages, model="gpt-4-0613")
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
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|>
return num_tokens
messages = [
{
"role": "user",
"content": "你叫什么名字?"
},{
"role": "assistant",
"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?"
},{
"role": "user",
"content": "你是由谁开发的?"
},{
"role": "assistant",
"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。"
},{
"role": "user",
"content": "很高兴见到你。"
}
]
pro, rep, resp=ask(messages)
print(len(pro), len(rep))
print(resp)
print(resp['choices'][0]['message']['content'])
print(num_tokens_from_messages(messages, model="gpt-3.5-turbo"))