67 lines
2.2 KiB
Python
67 lines
2.2 KiB
Python
from typing import TYPE_CHECKING, List, Optional, Tuple
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if TYPE_CHECKING:
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from letta.schemas.agent import AgentState
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from letta.schemas.file import FileMetadata
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async def open_file(agent_state: "AgentState", file_name: str, view_range: Optional[Tuple[int, int]]) -> str:
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"""
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Open the file with name `file_name` and load the contents into files section in core memory.
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Args:
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file_name (str): Name of the file to view. Required.
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view_range (Optional[Tuple[int, int]]): Optional tuple indicating range to view.
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Returns:
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str: A status message
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"""
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raise NotImplementedError("Tool not implemented. Please contact the Letta team.")
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async def close_file(agent_state: "AgentState", file_name: str) -> str:
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"""
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Close file with name `file_name` in files section in core memory.
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Args:
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file_name (str): Name of the file to close.
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Returns:
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str: A status message
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"""
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raise NotImplementedError("Tool not implemented. Please contact the Letta team.")
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async def grep(
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agent_state: "AgentState",
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pattern: str,
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include: Optional[str] = None,
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context_lines: Optional[int] = 3,
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) -> str:
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"""
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Grep tool to search files across data sources using a keyword or regex pattern.
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Args:
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pattern (str): Keyword or regex pattern to search within file contents.
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include (Optional[str]): Optional keyword or regex pattern to filter filenames to include in the search.
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context_lines (Optional[int]): Number of lines of context to show before and after each match.
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Equivalent to `-C` in grep. Defaults to 3.
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Returns:
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str: Matching lines with optional surrounding context or a summary output.
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"""
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raise NotImplementedError("Tool not implemented. Please contact the Letta team.")
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async def search_files(agent_state: "AgentState", query: str) -> List["FileMetadata"]:
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"""
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Get list of most relevant files across all data sources using embedding search.
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Args:
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query (str): The search query.
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Returns:
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List[FileMetadata]: List of matching files.
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"""
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raise NotImplementedError("Tool not implemented. Please contact the Letta team.")
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