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feat: update counting tokens for new models

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lanvent 1 年之前
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共有 2 個檔案被更改,包括 9 行新增8 行删除
  1. +1
    -0
      bot/chatgpt/chat_gpt_bot.py
  2. +8
    -8
      bot/chatgpt/chat_gpt_session.py

+ 1
- 0
bot/chatgpt/chat_gpt_bot.py 查看文件

@@ -121,6 +121,7 @@ class ChatGPTBot(Bot, OpenAIImage):
if args is None:
args = self.args
response = openai.ChatCompletion.create(api_key=api_key, messages=session.messages, **args)
# logger.debug("[CHATGPT] response={}".format(response))
# logger.info("[ChatGPT] reply={}, total_tokens={}".format(response.choices[0]['message']['content'], response["usage"]["total_tokens"]))
return {
"total_tokens": response["usage"]["total_tokens"],


+ 8
- 8
bot/chatgpt/chat_gpt_session.py 查看文件

@@ -57,25 +57,25 @@ def num_tokens_from_messages(messages, model):
"""Returns the number of tokens used by a list of messages."""
import tiktoken

if model == "gpt-3.5-turbo" or model == "gpt-35-turbo":
return num_tokens_from_messages(messages, model="gpt-3.5-turbo-0301")
elif model == "gpt-4":
return num_tokens_from_messages(messages, model="gpt-4-0314")
if model in ["gpt-3.5-turbo-0301", "gpt-3.5-turbo-0613", "gpt-35-turbo", "gpt-3.5-turbo-16k", "gpt-3.5-turbo-16k-0613"]:
return num_tokens_from_messages(messages, model="gpt-3.5-turbo")
elif model in ["gpt-4-0314", "gpt-4-0613", "gpt-4-32k", "gpt-4-32k-0613"]:
return num_tokens_from_messages(messages, model="gpt-4")

try:
encoding = tiktoken.encoding_for_model(model)
except KeyError:
logger.debug("Warning: model not found. Using cl100k_base encoding.")
encoding = tiktoken.get_encoding("cl100k_base")
if model == "gpt-3.5-turbo-0301":
if model == "gpt-3.5-turbo":
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":
elif model == "gpt-4":
tokens_per_message = 3
tokens_per_name = 1
else:
logger.warn(f"num_tokens_from_messages() is not implemented for model {model}. Returning num tokens assuming gpt-3.5-turbo-0301.")
return num_tokens_from_messages(messages, model="gpt-3.5-turbo-0301")
logger.warn(f"num_tokens_from_messages() is not implemented for model {model}. Returning num tokens assuming gpt-3.5-turbo.")
return num_tokens_from_messages(messages, model="gpt-3.5-turbo")
num_tokens = 0
for message in messages:
num_tokens += tokens_per_message


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