mirror of
https://github.com/MervinPraison/PraisonAI.git
synced 2026-11-07 04:35:58 -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]>
89 lines
2.5 KiB
Python
89 lines
2.5 KiB
Python
from praisonaiagents.agent import Agent
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from praisonaiagents.task import Task
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from praisonaiagents.agents import Agents, AgentTeam
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from typing import List, Dict
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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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result = "even" if current_time % 2 == 0 else "odd"
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print(f"Time check: {current_time} is {result}")
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return result
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# Create agents for each step in the chain
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agent1 = Agent(
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name="Time Checker",
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role="Time checker",
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goal="Check if the time is even or odd",
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instructions="Check if the time is even or odd",
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tools=[get_time_check]
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)
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agent2 = Agent(
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name="Advanced Analyzer",
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role="Advanced data analyzer",
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goal="Perform in-depth analysis of processed data",
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instructions="Analyze the processed data in detail"
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)
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agent3 = Agent(
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name="Final Processor",
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role="Final data processor",
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goal="Generate final output based on analysis",
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instructions="Create final output based on analyzed data"
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)
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# Create tasks for each step
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initial_task = Task(
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name="time_check",
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description="Getting time check and checking if it is even or odd",
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expected_output="Getting time check and checking if it is even or odd",
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agent=agent1,
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is_start=True, # Mark as the starting task
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task_type="decision", # This task will make a decision
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next_tasks=["advanced_analysis"], # Next task if condition passes
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condition={
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"even": ["advanced_analysis"], # If passes, go to advanced analysis
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"odd": "" # If fails, exit the chain
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}
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)
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analysis_task = Task(
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name="advanced_analysis",
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description="Perform advanced analysis on the processed data",
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expected_output="Analyzed data ready for final processing",
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agent=agent2,
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next_tasks=["final_processing"]
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)
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final_task = Task(
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name="final_processing",
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description="Generate final output",
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expected_output="Final processed result",
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agent=agent3
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)
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# Create the workflow manager
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workflow = AgentTeam(
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agents=[agent1, agent2, agent3],
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tasks=[initial_task, analysis_task, final_task],
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process="workflow", # Use workflow process type
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output="verbose"
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)
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# Run the workflow
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results = workflow.start(return_dict=True)
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# Print results
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print("\nWorkflow 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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