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Feature/use converter instead of manually trimming (#894)
* Exploring output being passed to tool selector to see if we can better format data * WIP. Adding JSON repair functionality * Almost done implementing JSON repair. Testing fixes vs current base case. * More action cleanup with additional tests * WIP. Trying to figure out what is going on with tool descriptions * Update tool description generation * WIP. Trying to find out what is causing the tools to duplicate * Replacing tools properly instead of duplicating them accidentally * Fixing issues for MR * Update dependencies for JSON_REPAIR * More cleaning up pull request * preppering for call * Fix type-checking issues --------- Co-authored-by: João Moura <joaomdmoura@gmail.com>
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from abc import ABC, abstractmethod
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from typing import Any, Optional
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from pydantic import BaseModel, Field
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class OutputConverter(BaseModel, ABC):
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"""
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Abstract base class for converting task results into structured formats.
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This class provides a framework for converting unstructured text into
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either Pydantic models or JSON, tailored for specific agent requirements.
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It uses a language model to interpret and structure the input text based
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on given instructions.
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Attributes:
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text (str): The input text to be converted.
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llm (Any): The language model used for conversion.
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model (Any): The target model for structuring the output.
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instructions (str): Specific instructions for the conversion process.
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max_attempts (int): Maximum number of conversion attempts (default: 3).
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"""
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text: str = Field(description="Text to be converted.")
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llm: Any = Field(description="The language model to be used to convert the text.")
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model: Any = Field(description="The model to be used to convert the text.")
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instructions: str = Field(description="Conversion instructions to the LLM.")
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max_attempts: Optional[int] = Field(
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description="Max number of attempts to try to get the output formatted.",
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default=3,
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)
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@abstractmethod
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def to_pydantic(self, current_attempt=1):
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"""Convert text to pydantic."""
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pass
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@abstractmethod
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def to_json(self, current_attempt=1):
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"""Convert text to json."""
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pass
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@property
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@abstractmethod
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def is_gpt(self) -> bool:
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"""Return if llm provided is of gpt from openai."""
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pass
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