Files
Luigi Pederzani f08e870e09 feat: Upgrade to Langchain 1.0.0 (#393)
* chore: update imports

* refactor(mcpagent): update agent creation logic and imports

- Replaced `create_tool_calling_agent` with `create_agent` for improved agent instantiation.
- Simplified the `_create_agent` method by removing the `AgentExecutor` and directly returning the created agent.
- Adjusted type annotations for `_agent_executor` to initialize as `None` instead of using a union type.

* feat(mcpagent): migrate to LangChain 1.0.0 and simplify agent methods

- Updated MCPAgent to utilize LangChain 1.0.0's `create_agent()` for improved agent instantiation.
- Introduced new methods `astream_simplified()` and `run_v2()` that leverage the built-in `astream()` for internal agent loop handling.
- Retained legacy methods `stream()` and `run()` for backward compatibility with manual execution.
- Enhanced documentation to reflect changes and provide clearer usage examples.

* feat(mcpagent): implement dynamic tool updates during agent execution

- Enhanced the MCPAgent to support dynamic tool updates when using server_manager mode.
- Implemented logic to check for tool changes before and during execution, allowing for immediate updates and safe restarts.
- Introduced a maximum restart limit to prevent infinite loops during tool updates.
- Updated documentation to reflect the new behavior and usage of dynamic tool management.

* refactor(mcpagent): clean up imports and streamline logging

- Removed unused imports and organized existing ones for better clarity in `mcpagent.py`.
- Simplified logging statements for consistency and improved readability.
- Enhanced the overall structure of the code by eliminating unnecessary whitespace.
- Updated unit tests to reflect changes in imports and ensure compatibility with the refactored code.

* feat(mcpagent): enhance agent execution with step tracking and middleware

- Introduced `ModelCallLimitMiddleware` to enforce a maximum number of model calls during agent execution.
- Updated the `_consume_and_return` method to return a tuple of the final result and the number of steps taken.
- Enhanced telemetry tracking to include steps taken and execution time for better performance insights.
- Simplified agent creation logic by integrating middleware directly into the `create_agent` function.
- Improved logging for agent execution details, including steps and tool usage.

* fix(mcpagent): add null check for node output messages extraction

- Updated the MCPAgent to include a null check for `node_output` before attempting to access the "messages" key, preventing potential errors during message extraction.

* minor

* feat(mcpagent): filter out ToolMessage from history

- Updated the MCPAgent to exclude ToolMessage instances from being added to the message history, ensuring that only relevant messages are recorded.
- This change helps maintain a cleaner history by avoiding intermediate tool execution details.

* fix(mcpagent): set max_steps assignment

* ruff

* docs

* e2e tests for agent

* key in tests

* fix manager test and split ci tests

* telemetry off for tests

* fix server manager test

* feat(mcpagent): delegate query streaming to remote agent in remote mode

- recreated functionality to the MCPAgent to yield results from a remote agent when operating in remote mode, enhancing the agent's capability to handle queries efficiently.

* fix: agent unit tests

* Print inputs

* rollback, wrong repo

* fix streaming output

* stricter streaming test

* pass observability callbacks

* fix tests mock

---------

Co-authored-by: pietrozullo <pietro.zullo@gmail.com>
2025-10-27 14:26:01 +01:00

159 lines
4.9 KiB
Python

"""
Logger module for mcp_use.
This module provides a centralized logging configuration for the mcp_use library,
with customizable log levels and formatters.
"""
import logging
import os
import sys
from langchain_core.globals import set_debug as langchain_set_debug
# Global debug flag - can be set programmatically or from environment
MCP_USE_DEBUG = 1
class Logger:
"""Centralized logger for mcp_use.
This class provides logging functionality with configurable levels,
formatters, and handlers.
"""
# Default log format
DEFAULT_FORMAT = "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
# Module-specific loggers
_loggers = {}
@classmethod
def get_logger(cls, name: str = "mcp_use") -> logging.Logger:
"""Get a logger instance for the specified name.
Args:
name: Logger name, usually the module name (defaults to 'mcp_use')
Returns:
Configured logger instance
"""
if name in cls._loggers:
return cls._loggers[name]
# Create new logger
logger = logging.getLogger(name)
cls._loggers[name] = logger
return logger
@classmethod
def configure(
cls,
level: int | str = None,
format_str: str | None = None,
log_to_console: bool = True,
log_to_file: str | None = None,
) -> None:
"""Configure the root mcp_use logger.
Args:
level: Log level (default: DEBUG if MCP_USE_DEBUG is 2,
INFO if MCP_USE_DEBUG is 1,
otherwise WARNING)
format_str: Log format string (default: DEFAULT_FORMAT)
log_to_console: Whether to log to console (default: True)
log_to_file: Path to log file (default: None)
"""
root_logger = cls.get_logger()
# Set level based on debug settings if not explicitly provided
if level is None:
if MCP_USE_DEBUG == 2:
level = logging.DEBUG
elif MCP_USE_DEBUG == 1:
level = logging.INFO
else:
level = logging.WARNING
elif isinstance(level, str):
level = getattr(logging, level.upper())
root_logger.setLevel(level)
# Set propagate to True to ensure child loggers inherit settings
root_logger.propagate = True
# Clear existing handlers
for handler in root_logger.handlers[:]:
root_logger.removeHandler(handler)
# Set formatter
formatter = logging.Formatter(format_str or cls.DEFAULT_FORMAT)
# Add console handler if requested
if log_to_console:
console_handler = logging.StreamHandler(sys.stdout)
console_handler.setFormatter(formatter)
console_handler.setLevel(level) # Ensure handler respects the level
root_logger.addHandler(console_handler)
# Add file handler if requested
if log_to_file:
# Ensure directory exists
log_dir = os.path.dirname(log_to_file)
if log_dir and not os.path.exists(log_dir):
os.makedirs(log_dir)
file_handler = logging.FileHandler(log_to_file)
file_handler.setFormatter(formatter)
file_handler.setLevel(level) # Ensure handler respects the level
root_logger.addHandler(file_handler)
@classmethod
def set_debug(cls, debug_level: int = 2) -> None:
"""Set the debug flag and update the log level accordingly.
Args:
debug_level: Debug level (0=off, 1=info, 2=debug)
"""
global MCP_USE_DEBUG
MCP_USE_DEBUG = debug_level
# Determine the target level
if debug_level == 2:
target_level = logging.DEBUG
langchain_set_debug(True)
elif debug_level == 1:
target_level = logging.INFO
langchain_set_debug(False)
else:
target_level = logging.WARNING
langchain_set_debug(False)
# Update log level for existing loggers in our registry
for logger in cls._loggers.values():
logger.setLevel(target_level)
# Also update handler levels
for handler in logger.handlers:
handler.setLevel(target_level)
# Also update all mcp_use child loggers that might exist
# This ensures loggers created with logging.getLogger() are also updated
base_logger = logging.getLogger("mcp_use")
base_logger.setLevel(target_level)
for handler in base_logger.handlers:
handler.setLevel(target_level)
# Check environment variable for debug flag
debug_env = os.environ.get("MCP_USE_DEBUG", "").lower() or os.environ.get("DEBUG", "").lower()
if debug_env == "2":
MCP_USE_DEBUG = 2
elif debug_env == "1":
MCP_USE_DEBUG = 1
# Configure default logger
Logger.configure()
logger = Logger.get_logger()