Wikipedia Agent

pip install praisonaiagents praisonai wikipedia
export OPENAI_API_KEY="your-key"

from praisonaiagents import Agent
from praisonaiagents import wiki_search, wiki_summary, wiki_page

agent = Agent(
    name="WikiResearcher",
    instructions="Search and summarize Wikipedia content.",
    tools=[wiki_search, wiki_summary, wiki_page]
)

result = agent.start("What is the history of artificial intelligence?")
print(result)

praisonai "Explain quantum computing from Wikipedia" --tools wikipedia

framework: praisonai
topic: Wikipedia Research
roles:
  wiki_researcher:
    role: Wikipedia Research Specialist
    goal: Extract and summarize Wikipedia content
    backstory: You are an expert at finding knowledge
    tools:
      - wiki_search
      - wiki_summary
      - wiki_page
    tasks:
      research:
        description: What is the history of artificial intelligence?
        expected_output: A comprehensive summary

praisonai agents.yaml

from praisonaiagents import Agent
from praisonaiagents import wiki_search, wiki_summary, wiki_page

agent = Agent(
    name="WikiResearcher",
    instructions="You are a Wikipedia research agent.",
    tools=[wiki_search, wiki_summary, wiki_page]
)

agent.launch(port=8080)

curl -X POST http://localhost:8080/chat \
  -H "Content-Type: application/json" \
  -d '{"message": "Tell me about the Roman Empire"}'

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

from praisonaiagents import Agent, Task, Agents, Session
from praisonaiagents import wiki_search, wiki_summary, wiki_page
from pydantic import BaseModel

class WikiKnowledge(BaseModel):
    topic: str
    summary: str
    key_facts: list[str]
    related_topics: list[str]

session = Session(session_id="wiki-001", user_id="user-1")

agent = Agent(
    name="WikiResearcher",
    instructions="Extract structured knowledge from Wikipedia.",
    tools=[wiki_search, wiki_summary, wiki_page],
    memory=True
)

task = Task(
    description="What is the history of artificial intelligence?",
    expected_output="Structured knowledge summary",
    agent=agent,
    output_pydantic=WikiKnowledge
)

agents = Agents(
    agents=[agent],
    tasks=[task],
    memory=True
)

result = agents.start()
print(result)

praisonai "Explain AI history" --tools wikipedia --memory --verbose

framework: praisonai
topic: Wikipedia Research
memory: true
memory_config:
  provider: sqlite
  db_path: wiki.db
roles:
  wiki_researcher:
    role: Wikipedia Research Specialist
    goal: Extract structured knowledge
    backstory: You are an expert at finding knowledge
    tools:
      - wiki_search
      - wiki_summary
      - wiki_page
    memory: true
    tasks:
      research:
        description: What is the history of artificial intelligence?
        expected_output: Structured knowledge summary
        output_json:
          topic: string
          summary: string
          key_facts: array
          related_topics: array

praisonai agents.yaml --verbose

from praisonaiagents import Agent
from praisonaiagents import wiki_search, wiki_summary, wiki_page

agent = Agent(
    name="WikiResearcher",
    instructions="Extract structured knowledge from Wikipedia.",
    tools=[wiki_search, wiki_summary, wiki_page],
    memory=True
)

agent.launch(port=8080)

curl -X POST http://localhost:8080/chat \
  -H "Content-Type: application/json" \
  -d '{"message": "Tell me about Rome", "session_id": "wiki-001"}'

praisonai "test wikipedia" --tools wikipedia --verbose

rm -f wiki.db