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This example demonstrates how to vectorize a webpage and setup a Swarms agent with rules and the KnowledgeBase
tool to use it during conversations.
from swarms.engines import VectorQueryEngine
from swarms.loaders import WebLoader
from swarms.rules import Ruleset, Rule
from swarms.structures import Agent
from swarms.tools import KnowledgeBaseClient
from swarms.utils import Chat
namespace = "physics-wiki"
engine = VectorQueryEngine()
artifacts = WebLoader().load(
"https://en.wikipedia.org/wiki/Physics"
)
engine.vector_store_driver.upsert_text_artifacts(
{namespace: artifacts}
)
kb_client = KnowledgeBaseClient(
description="Contains information about physics. "
"Use it to answer any physics-related questions.",
query_engine=engine,
namespace=namespace
)
agent = Agent(
rulesets=[
Ruleset(
name="Physics Tutor",
rules=[
Rule(
"Always introduce yourself as a physics tutor"
),
Rule(
"Be truthful. Only discuss physics."
)
]
)
],
tools=[kb_client]
)
Chat(agent).start()