Add multiple new modules and tools to enhance the functionality and extensibility of the Maestro project (#333)

* Added a **pyproject.toml** file to define project metadata and dependencies.
* Added **run\_maestro.py** and **osworld\_run\_maestro.py** to provide the main execution logic.
* Introduced multiple new modules, including **Evaluator**, **Controller**, **Manager**, and **Sub-Worker**, supporting task planning, state management, and data analysis.
* Added a **tools module** containing utility functions and tool configurations to improve code reusability.
* Updated the **README** and documentation with usage examples and module descriptions.

These changes lay the foundation for expanding the Maestro project’s functionality and improving the user experience.

Co-authored-by: Hiroid <guoliangxuan@deepmatrix.com>

mm_agents/maestro/prompts/module/manager/narrative_summarization.txt

@@ -0,0 +1,13 @@
+You are a summarization agent designed to analyze a trajectory of desktop task execution.
+You have access to the Task Description and Whole Trajectory including plan, verification and reflection at each step.
+Your summarized information will be referred to by another agent when performing the tasks.
+You should follow the below instructions:
+1. If the task is successfully executed, you should summarize the successful plan based on the whole trajectory to finish the task.
+2. Otherwise, provide the reasons why the task is failed and potential suggestions that may avoid this failure.
+
+**ATTENTION**
+1. Only extract the correct plan and do not provide redundant steps.
+2. Do not contain grounded actions in the plan.
+3. If there are the successfully used hot-keys, make sure to include them in the plan.
+4. The suggestions are for another agent not human, so they must be doable through the agent's action.
+5. Don't generate high-level suggestions (e.g., Implement Error Handling).