mirror of
https://github.com/crewAIInc/crewAI.git
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10997dd175
* better spacing * works with llama index * works on langchain custom just need delegation to work * cleanup for custom_agent class * works with different argument expectations for agent_executor * cleanup for hierarchial process, better agent_executor args handler and added to the crew agent doc page * removed code examples for langchain + llama index, added to docs instead * added key output if return is not a str for and added some tests * added hinting for CustomAgent class * removed pass as it was not needed * closer just need to figuire ou agentTools * running agents - llamaindex and langchain with base agent * some cleanup on baseAgent * minimum for agent to run for base class and ensure it works with hierarchical process * cleanup for original agent to take on BaseAgent class * Agent takes on langchainagent and cleanup across * token handling working for usage_metrics to continue working * installed llama-index, updated docs and added better name * fixed some type errors * base agent holds token_process * heirarchail process uses proper tools and no longer relies on hasattr for token_processes * removal of test_custom_agent_executions * this fixes copying agents * leveraging an executor class for trigger llamaindex agent * llama index now has ask_human * executor mixins added * added output converter base class * type listed * cleanup for output conversions and tokenprocess eliminated redundancy * properly handling tokens * simplified token calc handling * original agent with base agent builder structure setup * better docs * no more llama-index dep * cleaner docs * test fixes * poetry reverts and better docs * base_agent_tools set for third party agents * updated task and test fix
80 lines
2.7 KiB
Python
80 lines
2.7 KiB
Python
import json
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from langchain.schema import HumanMessage, SystemMessage
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from langchain_openai import ChatOpenAI
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from pydantic import model_validator
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from crewai.agents.agent_builder.utilities.base_output_converter_base import (
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OutputConverter,
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)
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class ConverterError(Exception):
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"""Error raised when Converter fails to parse the input."""
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def __init__(self, message: str, *args: object) -> None:
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super().__init__(message, *args)
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self.message = message
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class Converter(OutputConverter):
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"""Class that converts text into either pydantic or json."""
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@model_validator(mode="after")
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def check_llm_provider(self):
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if not self._is_gpt(self.llm):
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self._is_gpt = False
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def to_pydantic(self, current_attempt=1):
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"""Convert text to pydantic."""
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try:
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if self._is_gpt:
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return self._create_instructor().to_pydantic()
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else:
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return self._create_chain().invoke({})
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except Exception as e:
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if current_attempt < self.max_attemps:
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return self.to_pydantic(current_attempt + 1)
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return ConverterError(
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f"Failed to convert text into a pydantic model due to the following error: {e}"
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)
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def to_json(self, current_attempt=1):
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"""Convert text to json."""
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try:
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if self._is_gpt:
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return self._create_instructor().to_json()
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else:
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return json.dumps(self._create_chain().invoke({}).model_dump())
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except Exception:
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if current_attempt < self.max_attemps:
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return self.to_json(current_attempt + 1)
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return ConverterError("Failed to convert text into JSON.")
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def _create_instructor(self):
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"""Create an instructor."""
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from crewai.utilities import Instructor
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inst = Instructor(
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llm=self.llm,
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max_attemps=self.max_attemps,
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model=self.model,
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content=self.text,
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instructions=self.instructions,
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)
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return inst
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def _create_chain(self):
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"""Create a chain."""
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from crewai.utilities.crew_pydantic_output_parser import (
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CrewPydanticOutputParser,
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)
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parser = CrewPydanticOutputParser(pydantic_object=self.model)
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new_prompt = SystemMessage(content=self.instructions) + HumanMessage(
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content=self.text
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)
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return new_prompt | self.llm | parser
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def _is_gpt(self, llm) -> bool: # type: ignore # BUG? Name "_is_gpt" defined on line 20 hides name from outer scope
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return isinstance(llm, ChatOpenAI) and llm.openai_api_base is None
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