mirror of
https://github.com/MervinPraison/PraisonAI.git
synced 2026-11-07 12:47:55 -10:00
Dhivya-BharathyandCursor
bc8a39dd29
- Fix AgentTeam.start() result handling across 22+ workflow/usecase examples - Fix missing AgentFlow/AgentTeam/AutoAgents imports and registry override demo - Fix scope_identifiers, state_redis db import, and ToolsMCPServer.run_sse API - Mark STT and stale tool-import examples as skip until refreshed - Remove stale db mapping that shadowed praisonaiagents.db submodule Co-authored-by: Cursor <[email protected]>
117 lines
2.8 KiB
Python
117 lines
2.8 KiB
Python
from praisonaiagents import Agent, Task, AgentTeam
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import time
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def get_time_check():
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current_time = int(time.time())
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if current_time % 3 == 0:
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result = 1
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elif current_time % 3 == 1:
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result = 2
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else:
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result = 3
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print(f"Time: {current_time}, Result: {result}")
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return result
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# Create orchestrator and worker agents
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router = Agent(
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name="Router",
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role="Task router",
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goal="Distribute tasks to based on response from get_time_check",
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tools=[get_time_check]
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)
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worker1 = Agent(
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name="Worker 1",
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role="Specialized worker",
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goal="Handle specific subtask type 1",
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)
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worker2 = Agent(
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name="Worker 2",
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role="Specialized worker",
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goal="Handle specific subtask type 2",
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)
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worker3 = Agent(
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name="Worker 3",
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role="Specialized worker",
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goal="Handle specific subtask type 3",
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)
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synthesizer = Agent(
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name="Synthesizer",
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role="Result synthesizer",
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goal="Combine and synthesize worker outputs",
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)
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# Create orchestrated workflow tasks
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router_task = Task(
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name="route_task",
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description="Analyze input from get_time_check and route to appropriate workers",
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expected_output="Task routing decision, 1 , 2 or 3",
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agent=router,
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is_start=True,
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task_type="decision",
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next_tasks=["worker1_task", "worker2_task", "worker3_task"],
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condition={
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"1": ["worker1_task"],
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"2": ["worker2_task"],
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"3": ["worker3_task"]
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}
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)
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worker1_task = Task(
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name="worker1_task",
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description="Process type 1 operation",
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expected_output="Worker 1 result",
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agent=worker1,
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next_tasks=["synthesize_task"]
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)
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worker2_task = Task(
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name="worker2_task",
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description="Process type 2 operation",
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expected_output="Worker 2 result",
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agent=worker2,
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next_tasks=["synthesize_task"]
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)
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worker3_task = Task(
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name="worker3_task",
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description="Process type 3 operation",
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expected_output="Worker 3 result",
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agent=worker3,
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next_tasks=["synthesize_task"]
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)
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synthesize_task = Task(
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name="synthesize_task",
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description="Synthesize worker results into final output",
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expected_output="Final synthesized result",
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agent=synthesizer,
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context=[worker1_task, worker2_task, worker3_task]
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)
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# Create workflow manager
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workflow = AgentTeam(
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agents=[router, worker1, worker2, worker3, synthesizer],
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tasks=[router_task, worker1_task, worker2_task, worker3_task, synthesize_task],
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process="workflow", output="verbose"
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)
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# Run orchestrated workflow
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results = workflow.start()
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# Print results
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print("\nOrchestrator-Workers Results:")
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task_results = (
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results.get("task_results", {})
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if isinstance(results, dict)
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else {}
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)
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if not task_results and isinstance(results, str):
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print(f"\nWorkflow output:\n{results}")
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for task_id, result in task_results.items():
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if result:
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print(f"Task {task_id}: {result.raw}")
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