Planning Agent

pip install praisonaiagents praisonai duckduckgo-search
export OPENAI_API_KEY="your-key"

from praisonaiagents import Agent
from praisonaiagents import duckduckgo

agent = Agent(
    name="TravelPlanner",
    instructions="You are a travel planning agent. Create detailed itineraries.",
    tools=[duckduckgo]
)

result = agent.start("Plan a 3-day trip to Tokyo")
print(result)

praisonai "Plan a weekend trip to Paris" --web-search

framework: praisonai
topic: Travel Planning
roles:
  travel_planner:
    role: Travel Planning Specialist
    goal: Create comprehensive travel plans
    backstory: You are an expert travel planner
    tools:
      - duckduckgo
    tasks:
      plan_trip:
        description: Plan a 3-day trip to Tokyo
        expected_output: A detailed itinerary

praisonai agents.yaml

from praisonaiagents import Agent
from praisonaiagents import duckduckgo

agent = Agent(
    name="TravelPlanner",
    instructions="You are a travel planning agent.",
    tools=[duckduckgo]
)

agent.launch(port=8080)

curl -X POST http://localhost:8080/chat \
  -H "Content-Type: application/json" \
  -d '{"message": "Plan a weekend getaway to Barcelona"}'

pip install praisonaiagents praisonai duckduckgo-search pydantic
export OPENAI_API_KEY="your-key"

from praisonaiagents import Agent, Task, Agents, Session
from praisonaiagents import duckduckgo
from pydantic import BaseModel

# Structured output schema
class Itinerary(BaseModel):
    destination: str
    duration: str
    daily_plans: list[str]
    estimated_cost: str
    recommendations: list[str]

# Create session for trip tracking
session = Session(session_id="trip-001", user_id="user-1")

# Agent with memory and tools
agent = Agent(
    name="TravelPlanner",
    instructions="Create structured travel itineraries.",
    tools=[duckduckgo],
    memory=True
)

# Task with structured output
task = Task(
    description="Plan a 3-day trip to Tokyo with budget",
    expected_output="Structured itinerary",
    agent=agent,
    output_pydantic=Itinerary
)

# Run with SQLite persistence
agents = Agents(
    agents=[agent],
    tasks=[task],
    memory=True
)

result = agents.start()
print(result)

# Resume later
session2 = Session(session_id="trip-001", user_id="user-1")
history = session2.search_memory("Tokyo")

praisonai "Plan a trip to Tokyo" --web-search --memory --verbose

framework: praisonai
topic: Travel Planning
memory: true
memory_config:
  provider: sqlite
  db_path: travel.db
roles:
  travel_planner:
    role: Travel Planning Specialist
    goal: Create structured travel plans
    backstory: You are an expert travel planner
    tools:
      - duckduckgo
    memory: true
    tasks:
      plan_trip:
        description: Plan a 3-day trip to Tokyo with budget
        expected_output: Structured itinerary
        output_json:
          destination: string
          duration: string
          daily_plans: array
          estimated_cost: string
          recommendations: array

praisonai agents.yaml --verbose

from praisonaiagents import Agent
from praisonaiagents import duckduckgo

agent = Agent(
    name="TravelPlanner",
    instructions="Create structured travel itineraries.",
    tools=[duckduckgo],
    memory=True
)

agent.launch(port=8080)

curl -X POST http://localhost:8080/chat \
  -H "Content-Type: application/json" \
  -d '{"message": "Plan a trip to Paris", "session_id": "trip-001"}'

praisonai "test planning" --web-search --verbose

rm -f travel.db