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57fc079267
* WIP. Figuring out disconnect issue. * Cleaned up logs now that I've isolated the issue to the LLM * more wip. * WIP. It looks like usage metrics has always been broken for async * Update parent crew who is managing for_each loop * Merge in main to bugfix/kickoff-for-each-usage-metrics * Clean up code for review * Add new tests * Final cleanup. Ready for review. * Moving copy functionality from Agent to BaseAgent * Fix renaming issue * Fix linting errors * use BaseAgent instead of Agent where applicable
37 lines
1.2 KiB
Python
37 lines
1.2 KiB
Python
from typing import Any, Dict, List
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import tiktoken
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from langchain.callbacks.base import BaseCallbackHandler
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from langchain.schema import LLMResult
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from crewai.agents.agent_builder.utilities.base_token_process import TokenProcess
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class TokenCalcHandler(BaseCallbackHandler):
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model_name: str = ""
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token_cost_process: TokenProcess
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def __init__(self, model_name, token_cost_process):
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self.model_name = model_name
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self.token_cost_process = token_cost_process
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def on_llm_start(
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self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any
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) -> None:
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try:
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encoding = tiktoken.encoding_for_model(self.model_name)
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except KeyError:
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encoding = tiktoken.get_encoding("cl100k_base")
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if self.token_cost_process is None:
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return
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for prompt in prompts:
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self.token_cost_process.sum_prompt_tokens(len(encoding.encode(prompt)))
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async def on_llm_new_token(self, token: str, **kwargs) -> None:
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self.token_cost_process.sum_completion_tokens(1)
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def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
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self.token_cost_process.sum_successful_requests(1)
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