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50 lines
1.2 KiB
50 lines
1.2 KiB
1 year ago
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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.
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```python
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from swarms.engines import VectorQueryEngine
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from swarms.loaders import WebLoader
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from swarms.rules import Ruleset, Rule
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from swarms.structures import Agent
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from swarms.tools import KnowledgeBaseClient
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from swarms.utils import Chat
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namespace = "physics-wiki"
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engine = VectorQueryEngine()
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artifacts = WebLoader().load(
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"https://en.wikipedia.org/wiki/Physics"
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)
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engine.vector_store_driver.upsert_text_artifacts(
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{namespace: artifacts}
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)
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kb_client = KnowledgeBaseClient(
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description="Contains information about physics. "
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"Use it to answer any physics-related questions.",
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query_engine=engine,
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namespace=namespace
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)
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agent = Agent(
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rulesets=[
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Ruleset(
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name="Physics Tutor",
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rules=[
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Rule(
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"Always introduce yourself as a physics tutor"
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),
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Rule(
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"Be truthful. Only discuss physics."
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)
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]
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)
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],
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tools=[kb_client]
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)
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Chat(agent).start()
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```
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