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Configuration error
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import tiktoken
from neollm.llm.abstract_llm import AbstractLLM
from neollm.types import (
ChatCompletion,
ChatCompletionChunk,
Message,
Messages,
OpenAIMessages,
OpenAIResponse,
OpenAIStreamResponse,
Response,
StreamResponse,
)
class AbstractGPT(AbstractLLM):
def encode(self, text: str) -> list[int]:
tokenizer = tiktoken.encoding_for_model(self.model or "gpt-3.5-turbo")
return tokenizer.encode(text)
def decode(self, encoded: list[int]) -> str:
tokenizer = tiktoken.encoding_for_model(self.model or "gpt-3.5-turbo")
return tokenizer.decode(encoded)
def count_tokens(self, messages: list[Message] | None = None, only_response: bool = False) -> int:
"""
トークン数の計測
Args:
messages (Messages): messages
Returns:
int: トークン数
"""
if messages is None:
return 0
# count tokens
num_tokens: int = 0
# messages ---------------------------------------------------------------------------v
for message in messages:
# per message -------------------------------------------
num_tokens += 4
# content -----------------------------------------------
content = message.get("content", None)
if content is None:
num_tokens += 0
elif isinstance(content, str):
num_tokens += len(self.encode(content))
continue
elif isinstance(content, list):
for content_params in content:
if content_params["type"] == "text":
num_tokens += len(self.encode(content_params["text"]))
# TODO: ChatCompletionFunctionMessageParam.name
# tokens_per_name = 1
# tool calls ------------------------------------------------
# TODO: ChatCompletionAssistantMessageParam.function_call
# TODO: ChatCompletionAssistantMessageParam.tool_calls
if only_response:
if len(messages) != 1:
raise ValueError("only_response=Trueの場合、messagesは1つのみにしてください。")
num_tokens -= 4 # per message分を消す
else:
num_tokens += 3 # every reply is primed with <|start|>assistant<|message|>
return num_tokens
def _convert_to_response(self, platform_response: OpenAIResponse) -> Response:
return ChatCompletion(**platform_response.model_dump())
def _convert_to_platform_messages(self, messages: Messages) -> OpenAIMessages:
# OpenAIのMessagesをデフォルトに置いているため、変換は不要
platform_messages: OpenAIMessages = messages
return platform_messages
def _convert_to_streamresponse(self, platform_streamresponse: OpenAIStreamResponse) -> StreamResponse:
for chunk in platform_streamresponse:
yield ChatCompletionChunk(**chunk.model_dump())
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