update role atomization capacity example

examples/di/atomization_capacity_plan.py

@@ -0,0 +1,78 @@
+from metagpt.logs import logger
+from metagpt.roles.di.team_leader import TeamLeader
+import fire
+
+
+async def main():
+    tl = TeamLeader()
+    logger.info("\n=== Adding Initial Tasks ===")
+    tl.planner.plan.append_task(
+        task_id="T1",
+        dependent_task_ids=[],
+        instruction="Create Product Requirements Document (PRD)",
+        assignee="Alice"
+    )
+    tl.planner.plan.append_task(
+        task_id="T2",
+        dependent_task_ids=["T1"],
+        instruction="Design System Architecture",
+        assignee="Bob"
+    )
+
+    # 2. Add Development Tasks
+    logger.info("\n=== Adding Development Tasks ===")
+    tl.planner.plan.append_task(
+        task_id="T3",
+        dependent_task_ids=["T2"],
+        instruction="Implement Core Function Modules",
+        assignee="Alex"
+    )
+
+    tl.planner.plan.append_task(
+        task_id="T4",
+        dependent_task_ids=["T2"],
+        instruction="Implement User Interface",
+        assignee="Alex"
+    )
+
+    # 3. Complete Some Tasks
+    logger.info("\n=== Execute and Complete Tasks ===")
+    logger.info(f"Current Task: {tl.planner.plan.current_task.instruction}")
+    tl.planner.plan.finish_current_task()  # Complete T1
+
+    logger.info(f"Current Task: {tl.planner.plan.current_task.instruction}")
+    tl.planner.plan.finish_current_task()  # Complete T2
+
+    # 4. Replace Tasks
+    logger.info("\n=== Replace Task ===")
+    tl.planner.plan.replace_task(
+        task_id="T3",
+        new_dependent_task_ids=["T2"],
+        new_instruction="Implement Core Function Modules (Add New Features)",
+        new_assignee="Senior_Developer"
+    )
+
+    # 5. Add Testing Tasks
+    logger.info("\n=== Add Testing Tasks ===")
+    tl.planner.plan.append_task(
+        task_id="T5",
+        dependent_task_ids=["T3", "T4"],
+        instruction="Execute Integration Tests",
+        assignee="Edward"
+    )
+
+    # 6. Reset Task Demonstration
+    logger.info("\n=== Reset Task ===")
+    logger.info("Reset Task T3 (This will also reset T5 which depends on it)")
+    tl.planner.plan.reset_task("T3")
+
+    # Display Final Status
+    logger.info("\n=== Final Status ===")
+    logger.info(f"Completed Tasks: {len([t for t in tl.planner.plan.tasks if t.is_finished])}")
+    logger.info(f"Current Task: {tl.planner.plan.current_task.instruction}")
+    logger.info("All Tasks:")
+    for task in tl.planner.plan.tasks:
+        logger.info(f"- {task.task_id}: {task.instruction} (Completed: {task.is_finished})")
+
+if __name__ == "__main__":
+    fire.Fire(main)

examples/di/automated_planning_of_tasks.py

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+import fire
+
+from metagpt.logs import logger
+from metagpt.roles.di.team_leader import TeamLeader
+
+
+async def main():
+    # Create an instance of TeamLeader
+    tl = TeamLeader()
+
+    # Update the plan with the goal to create a 2048 game
+    # This will auto generate tasks needed to accomplish the goal
+    await tl.planner.update_plan(goal="create a 2048 game.")
+
+    # Iterate through all tasks in the plan
+    # Log each task's ID, instruction and completion status
+    for task in tl.planner.plan.tasks:
+        logger.info(f"- {task.task_id}: {task.instruction} (Completed: {task.is_finished})")
+
+
+if __name__ == "__main__":
+    fire.Fire(main)

examples/di/data_analyst_write_code.py

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+import fire
+
+from metagpt.logs import logger
+from metagpt.roles.di.data_analyst import DataAnalyst
+
+
+async def main():
+    # Create an instance of DataAnalyst role
+    analyst = DataAnalyst()
+
+    # Set the main goal for the planner - constructing a 2D array
+    analyst.planner.plan.goal = "construct a two-dimensional array"
+
+    # Add a specific task to the planner with detailed parameters:
+    # - task_id: Unique identifier for the task
+    # - dependent_task_ids: List of tasks that need to be completed before this one (empty in this case)
+    # - instruction: Description of what needs to be done
+    # - assignee: Who will execute the task (David)
+    # - task_type: Category of the task (DATA_ANALYSIS)
+    analyst.planner.plan.append_task(
+        task_id="1",
+        dependent_task_ids=[],
+        instruction="construct a two-dimensional array",
+        assignee="David",
+        task_type="DATA_ANALYSIS",
+    )
+
+    # Execute the code generation and execution for creating a 2D array
+    # The write_and_exec_code method will:
+    # 1. Generate the necessary code for creating a 2D array
+    # 2. Execute the generated code
+    # 3. Return the result
+    result = await analyst.write_and_exec_code("construct a two-dimensional array")
+
+    # Log the result of the code execution
+    logger.info(result)
+
+
+if __name__ == "__main__":
+    fire.Fire(main)

examples/di/interacting_with_human.py

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+import fire
+from metagpt.environment.mgx.mgx_env import MGXEnv
+from metagpt.logs import logger
+from metagpt.roles.di.team_leader import TeamLeader
+from metagpt.schema import Message
+
+
+async def main():
+    # Initialize the MetaGPT environment
+    env = MGXEnv()
+    # Add a TeamLeader role to the environment
+    env.add_roles([TeamLeader()])
+
+    # Get input from human user about what they want to do
+    human_rsp = await env.ask_human("What do you want to do？")
+
+    # Log the human response for tracking
+    logger.info(human_rsp)
+    # Create and publish a message with the human response in the environment
+    env.publish_message(Message(content=human_rsp, role="user"))
+
+    # Get the TeamLeader role instance named 'Mike'
+    tl = env.get_role("Mike")
+    # Execute the TeamLeader's tasks
+    await tl.run()
+
+    # Log information about each task in the TeamLeader's plan
+    for task in tl.planner.plan.tasks:
+        logger.info(f"- {task.task_id}: {task.instruction} (Completed: {task.is_finished})")
+
+    # Send an empty response back to the human and log it
+    resp = await env.reply_to_human("")
+    logger.info(resp)
+
+
+if __name__ == "__main__":
+    fire.Fire(main)