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37 lines
1018 B
37 lines
1018 B
1 year ago
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This example demonstrates how to vectorize a PDF of the [Attention Is All You Need](https://arxiv.org/pdf/1706.03762.pdf) paper 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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import io
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import requests
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from swarms.engines import VectorQueryEngine
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from swarms.loaders import PdfLoader
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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 = "attention"
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response = requests.get("https://arxiv.org/pdf/1706.03762.pdf")
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engine = VectorQueryEngine()
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engine.vector_store_driver.upsert_text_artifacts(
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{
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namespace: PdfLoader().load(
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io.BytesIO(response.content)
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)
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}
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)
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kb_client = KnowledgeBaseClient(
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description="Contains information about the Attention Is All You Need paper. "
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"Use it to answer any 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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tools=[kb_client]
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)
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Chat(agent).start()
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```
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