477 lines
20 KiB
Python
477 lines
20 KiB
Python
import asyncio
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import re
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from typing import Any, Dict, List, Optional, Tuple
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from letta.log import get_logger
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from letta.otel.tracing import trace_method
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from letta.schemas.agent import AgentState
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from letta.schemas.sandbox_config import SandboxConfig
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from letta.schemas.tool import Tool
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from letta.schemas.tool_execution_result import ToolExecutionResult
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from letta.schemas.user import User
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from letta.services.agent_manager import AgentManager
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from letta.services.block_manager import BlockManager
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from letta.services.file_manager import FileManager
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from letta.services.file_processor.chunker.line_chunker import LineChunker
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from letta.services.files_agents_manager import FileAgentManager
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from letta.services.job_manager import JobManager
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from letta.services.message_manager import MessageManager
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from letta.services.passage_manager import PassageManager
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from letta.services.source_manager import SourceManager
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from letta.services.tool_executor.tool_executor_base import ToolExecutor
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from letta.utils import get_friendly_error_msg
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class LettaFileToolExecutor(ToolExecutor):
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"""Executor for Letta file tools with direct implementation of functions."""
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# Production safety constants
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MAX_FILE_SIZE_BYTES = 50 * 1024 * 1024 # 50MB limit per file
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MAX_TOTAL_CONTENT_SIZE = 200 * 1024 * 1024 # 200MB total across all files
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MAX_REGEX_COMPLEXITY = 1000 # Prevent catastrophic backtracking
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MAX_MATCHES_PER_FILE = 20 # Limit matches per file
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MAX_TOTAL_MATCHES = 50 # Global match limit
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GREP_TIMEOUT_SECONDS = 30 # Max time for grep operation
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MAX_CONTEXT_LINES = 1 # Lines of context around matches
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def __init__(
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self,
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message_manager: MessageManager,
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agent_manager: AgentManager,
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block_manager: BlockManager,
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job_manager: JobManager,
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passage_manager: PassageManager,
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actor: User,
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):
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super().__init__(
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message_manager=message_manager,
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agent_manager=agent_manager,
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block_manager=block_manager,
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job_manager=job_manager,
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passage_manager=passage_manager,
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actor=actor,
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)
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# TODO: This should be passed in to for testing purposes
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self.files_agents_manager = FileAgentManager()
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self.file_manager = FileManager()
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self.source_manager = SourceManager()
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self.logger = get_logger(__name__)
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async def execute(
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self,
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function_name: str,
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function_args: dict,
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tool: Tool,
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actor: User,
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agent_state: Optional[AgentState] = None,
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sandbox_config: Optional[SandboxConfig] = None,
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sandbox_env_vars: Optional[Dict[str, Any]] = None,
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) -> ToolExecutionResult:
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if agent_state is None:
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raise ValueError("Agent state is required for file tools")
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function_map = {
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"open_file": self.open_file,
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"close_file": self.close_file,
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"grep": self.grep,
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"search_files": self.search_files,
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}
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if function_name not in function_map:
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raise ValueError(f"Unknown function: {function_name}")
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function_args_copy = function_args.copy()
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try:
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func_return = await function_map[function_name](agent_state, **function_args_copy)
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return ToolExecutionResult(
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status="success",
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func_return=func_return,
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agent_state=agent_state,
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)
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except Exception as e:
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return ToolExecutionResult(
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status="error",
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func_return=e,
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agent_state=agent_state,
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stderr=[get_friendly_error_msg(function_name=function_name, exception_name=type(e).__name__, exception_message=str(e))],
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)
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@trace_method
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async def open_file(self, agent_state: AgentState, file_name: str, view_range: Optional[Tuple[int, int]] = None) -> str:
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"""Stub for open_file tool."""
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start, end = None, None
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if view_range:
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start, end = view_range
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if start >= end:
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raise ValueError(f"Provided view range {view_range} is invalid, starting range must be less than ending range.")
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# TODO: This is inefficient. We can skip the initial DB lookup by preserving on the block metadata what the file_id is
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file_agent = await self.files_agents_manager.get_file_agent_by_file_name(
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agent_id=agent_state.id, file_name=file_name, actor=self.actor
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)
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if not file_agent:
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file_blocks = agent_state.memory.file_blocks
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file_names = [fb.label for fb in file_blocks]
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raise ValueError(
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f"{file_name} not attached - did you get the filename correct? Currently you have the following files attached: {file_names}"
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)
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file_id = file_agent.file_id
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file = await self.file_manager.get_file_by_id(file_id=file_id, actor=self.actor, include_content=True)
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# TODO: Inefficient, maybe we can pre-compute this
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# TODO: This is also not the best way to split things - would be cool to have "content aware" splitting
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# TODO: Split code differently from large text blurbs
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content_lines = LineChunker().chunk_text(text=file.content, file_metadata=file, start=start, end=end)
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visible_content = "\n".join(content_lines)
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# Efficiently handle LRU eviction and file opening in a single transaction
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closed_files, was_already_open = await self.files_agents_manager.enforce_max_open_files_and_open(
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agent_id=agent_state.id, file_id=file_id, file_name=file_name, actor=self.actor, visible_content=visible_content
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)
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success_msg = f"Successfully opened file {file_name}, lines {start} to {end} are now visible in memory block <{file_name}>"
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if closed_files:
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success_msg += (
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f"\nNote: Closed {len(closed_files)} least recently used file(s) due to open file limit: {', '.join(closed_files)}"
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)
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return success_msg
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@trace_method
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async def close_file(self, agent_state: AgentState, file_name: str) -> str:
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"""Stub for close_file tool."""
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await self.files_agents_manager.update_file_agent_by_name(
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agent_id=agent_state.id, file_name=file_name, actor=self.actor, is_open=False
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)
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return f"Successfully closed file {file_name}, use function calls to re-open file"
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def _validate_regex_pattern(self, pattern: str) -> None:
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"""Validate regex pattern to prevent catastrophic backtracking."""
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if len(pattern) > self.MAX_REGEX_COMPLEXITY:
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raise ValueError(f"Pattern too complex: {len(pattern)} chars > {self.MAX_REGEX_COMPLEXITY} limit")
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# Test compile the pattern to catch syntax errors early
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try:
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re.compile(pattern, re.IGNORECASE | re.MULTILINE)
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except re.error as e:
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raise ValueError(f"Invalid regex pattern: {e}")
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def _get_context_lines(
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self,
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formatted_lines: List[str],
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match_line_num: int,
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context_lines: int,
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) -> List[str]:
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"""Get context lines around a match from already-chunked lines.
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Args:
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formatted_lines: Already chunked lines from LineChunker (format: "line_num: content")
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match_line_num: The 1-based line number of the match
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context_lines: Number of context lines before and after
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"""
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if not formatted_lines or context_lines < 0:
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return []
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# Find the index of the matching line in the formatted_lines list
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match_formatted_idx = None
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for i, line in enumerate(formatted_lines):
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if line and ":" in line:
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try:
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line_num = int(line.split(":", 1)[0].strip())
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if line_num == match_line_num:
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match_formatted_idx = i
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break
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except ValueError:
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continue
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if match_formatted_idx is None:
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return []
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# Calculate context range with bounds checking
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start_idx = max(0, match_formatted_idx - context_lines)
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end_idx = min(len(formatted_lines), match_formatted_idx + context_lines + 1)
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# Extract context lines and add match indicator
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context_lines_with_indicator = []
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for i in range(start_idx, end_idx):
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line = formatted_lines[i]
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prefix = ">" if i == match_formatted_idx else " "
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context_lines_with_indicator.append(f"{prefix} {line}")
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return context_lines_with_indicator
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@trace_method
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async def grep(self, agent_state: AgentState, pattern: str, include: Optional[str] = None, context_lines: Optional[int] = 3) -> str:
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"""
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Search for pattern in all attached files and return matches with context.
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Args:
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agent_state: Current agent state
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pattern: Regular expression pattern to search for
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include: Optional 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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Formatted string with search results, file names, line numbers, and context
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"""
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if not pattern or not pattern.strip():
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raise ValueError("Empty search pattern provided")
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pattern = pattern.strip()
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self._validate_regex_pattern(pattern)
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# Validate include pattern if provided
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include_regex = None
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if include and include.strip():
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include = include.strip()
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# Convert glob pattern to regex if it looks like a glob pattern
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if "*" in include and not any(c in include for c in ["^", "$", "(", ")", "[", "]", "{", "}", "\\", "+"]):
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# Simple glob to regex conversion
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include_pattern = include.replace(".", r"\.").replace("*", ".*").replace("?", ".")
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if not include_pattern.endswith("$"):
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include_pattern += "$"
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else:
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include_pattern = include
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self._validate_regex_pattern(include_pattern)
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include_regex = re.compile(include_pattern, re.IGNORECASE)
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# Get all attached files for this agent
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file_agents = await self.files_agents_manager.list_files_for_agent(agent_id=agent_state.id, actor=self.actor)
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if not file_agents:
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return "No files are currently attached to search"
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# Filter files by filename pattern if include is specified
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if include_regex:
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original_count = len(file_agents)
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file_agents = [fa for fa in file_agents if include_regex.search(fa.file_name)]
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if not file_agents:
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return f"No files match the filename pattern '{include}' (filtered {original_count} files)"
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# Compile regex pattern with appropriate flags
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regex_flags = re.MULTILINE
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regex_flags |= re.IGNORECASE
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pattern_regex = re.compile(pattern, regex_flags)
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results = []
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total_matches = 0
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total_content_size = 0
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files_processed = 0
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files_skipped = 0
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files_with_matches = set() # Track files that had matches for LRU policy
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# Use asyncio timeout to prevent hanging
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async def _search_files():
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nonlocal results, total_matches, total_content_size, files_processed, files_skipped, files_with_matches
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for file_agent in file_agents:
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# Load file content
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file = await self.file_manager.get_file_by_id(file_id=file_agent.file_id, actor=self.actor, include_content=True)
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if not file or not file.content:
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files_skipped += 1
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self.logger.warning(f"Grep: Skipping file {file_agent.file_name} - no content available")
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continue
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# Check individual file size
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content_size = len(file.content.encode("utf-8"))
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if content_size > self.MAX_FILE_SIZE_BYTES:
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files_skipped += 1
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self.logger.warning(
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f"Grep: Skipping file {file.file_name} - too large ({content_size:,} bytes > {self.MAX_FILE_SIZE_BYTES:,} limit)"
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)
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results.append(f"[SKIPPED] {file.file_name}: File too large ({content_size:,} bytes)")
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continue
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# Check total content size across all files
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total_content_size += content_size
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if total_content_size > self.MAX_TOTAL_CONTENT_SIZE:
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files_skipped += 1
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self.logger.warning(
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f"Grep: Skipping file {file.file_name} - total content size limit exceeded ({total_content_size:,} bytes > {self.MAX_TOTAL_CONTENT_SIZE:,} limit)"
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)
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results.append(f"[SKIPPED] {file.file_name}: Total content size limit exceeded")
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break
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files_processed += 1
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file_matches = 0
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# Use LineChunker to get all lines with proper formatting
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chunker = LineChunker()
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formatted_lines = chunker.chunk_text(file.content, file_metadata=file)
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# Remove metadata header
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if formatted_lines and formatted_lines[0].startswith("[Viewing"):
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formatted_lines = formatted_lines[1:]
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# Convert 0-based line numbers to 1-based for grep compatibility
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corrected_lines = []
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for line in formatted_lines:
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if line and ":" in line:
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try:
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line_parts = line.split(":", 1)
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line_num = int(line_parts[0].strip())
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line_content = line_parts[1] if len(line_parts) > 1 else ""
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corrected_lines.append(f"{line_num + 1}:{line_content}")
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except (ValueError, IndexError):
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corrected_lines.append(line)
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else:
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corrected_lines.append(line)
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formatted_lines = corrected_lines
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# Search for matches in formatted lines
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for formatted_line in formatted_lines:
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if total_matches >= self.MAX_TOTAL_MATCHES:
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results.append(f"[TRUNCATED] Maximum total matches ({self.MAX_TOTAL_MATCHES}) reached")
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return
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if file_matches >= self.MAX_MATCHES_PER_FILE:
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results.append(f"[TRUNCATED] {file.file_name}: Maximum matches per file ({self.MAX_MATCHES_PER_FILE}) reached")
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break
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# Extract line number and content from formatted line
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if ":" in formatted_line:
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try:
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line_parts = formatted_line.split(":", 1)
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line_num = int(line_parts[0].strip())
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line_content = line_parts[1].strip() if len(line_parts) > 1 else ""
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except (ValueError, IndexError):
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continue
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if pattern_regex.search(line_content):
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# Mark this file as having matches for LRU tracking
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files_with_matches.add(file.file_name)
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context = self._get_context_lines(formatted_lines, match_line_num=line_num, context_lines=context_lines or 0)
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# Format the match result
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match_header = f"\n=== {file.file_name}:{line_num} ==="
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match_content = "\n".join(context)
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results.append(f"{match_header}\n{match_content}")
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file_matches += 1
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total_matches += 1
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# Break if global limits reached
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if total_matches >= self.MAX_TOTAL_MATCHES:
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break
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# Execute with timeout
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await asyncio.wait_for(_search_files(), timeout=self.GREP_TIMEOUT_SECONDS)
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# Mark access for files that had matches
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if files_with_matches:
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await self.files_agents_manager.mark_access_bulk(agent_id=agent_state.id, file_names=list(files_with_matches), actor=self.actor)
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# Format final results
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if not results or total_matches == 0:
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summary = f"No matches found for pattern: '{pattern}'"
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if include:
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summary += f" in files matching '{include}'"
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if files_skipped > 0:
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summary += f" (searched {files_processed} files, skipped {files_skipped})"
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return summary
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# Add summary header
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summary_parts = [f"Found {total_matches} matches"]
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if files_processed > 0:
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summary_parts.append(f"in {files_processed} files")
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if files_skipped > 0:
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summary_parts.append(f"({files_skipped} files skipped)")
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summary = " ".join(summary_parts) + f" for pattern: '{pattern}'"
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if include:
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summary += f" in files matching '{include}'"
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# Combine all results
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formatted_results = [summary, "=" * len(summary)] + results
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return "\n".join(formatted_results)
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@trace_method
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async def search_files(self, agent_state: AgentState, query: str, limit: int = 10) -> str:
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"""
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Search for text within attached files using semantic search and return passages with their source filenames.
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Args:
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agent_state: Current agent state
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query: Search query for semantic matching
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limit: Maximum number of results to return (default: 10)
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Returns:
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Formatted string with search results in IDE/terminal style
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"""
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if not query or not query.strip():
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raise ValueError("Empty search query provided")
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query = query.strip()
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# Apply reasonable limit
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limit = min(limit, self.MAX_TOTAL_MATCHES)
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self.logger.info(f"Semantic search started for agent {agent_state.id} with query '{query}' (limit: {limit})")
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# Get semantic search results
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passages = await self.agent_manager.list_source_passages_async(actor=self.actor, agent_id=agent_state.id, query_text=query)
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if not passages:
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return f"No semantic matches found for query: '{query}'"
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# Limit results
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passages = passages[:limit]
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# Group passages by file for better organization
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files_with_passages = {}
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for p in passages:
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file_name = p.file_name if p.file_name else "Unknown File"
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if file_name not in files_with_passages:
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files_with_passages[file_name] = []
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files_with_passages[file_name].append(p)
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results = []
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total_passages = 0
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for file_name, file_passages in files_with_passages.items():
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for passage in file_passages:
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total_passages += 1
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# Format each passage with terminal-style header
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passage_header = f"\n=== {file_name} (passage #{total_passages}) ==="
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# Format the passage text with some basic formatting
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passage_text = passage.text.strip()
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# Format the passage text without line numbers
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lines = passage_text.splitlines()
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formatted_lines = []
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for line in lines[:20]: # Limit to first 20 lines per passage
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formatted_lines.append(f" {line}")
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if len(lines) > 20:
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formatted_lines.append(f" ... [truncated {len(lines) - 20} more lines]")
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passage_content = "\n".join(formatted_lines)
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results.append(f"{passage_header}\n{passage_content}")
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# Mark access for files that had matches
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if files_with_passages:
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matched_file_names = [name for name in files_with_passages.keys() if name != "Unknown File"]
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if matched_file_names:
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await self.files_agents_manager.mark_access_bulk(agent_id=agent_state.id, file_names=matched_file_names, actor=self.actor)
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# Create summary header
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file_count = len(files_with_passages)
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summary = f"Found {total_passages} semantic matches in {file_count} file{'s' if file_count != 1 else ''} for query: '{query}'"
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# Combine all results
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formatted_results = [summary, "=" * len(summary)] + results
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self.logger.info(f"Semantic search completed: {total_passages} matches across {file_count} files")
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|
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return "\n".join(formatted_results)
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