mirror of
https://github.com/hwchase17/langchain
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52 lines
1.7 KiB
Python
52 lines
1.7 KiB
Python
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"""Test Weaviate functionality."""
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import logging
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from typing import Generator, Union
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import pytest
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from weaviate import Client
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from langchain.docstore.document import Document
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from langchain.embeddings.openai import OpenAIEmbeddings
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from langchain.vectorstores.weaviate import Weaviate
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logging.basicConfig(level=logging.DEBUG)
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"""
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cd tests/integration_tests/vectorstores/docker-compose
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docker compose -f weaviate.yml up
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"""
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class TestWeaviate:
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@pytest.fixture(scope="class", autouse=True)
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def weaviate_url(self) -> Union[str, Generator[str, None, None]]:
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"""Return the weaviate url."""
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url = "http://localhost:8080"
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yield url
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# Clear the test index
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client = Client(url)
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client.schema.delete_all()
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def test_similarity_search_without_metadata(self, weaviate_url: str) -> None:
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"""Test end to end construction and search without metadata."""
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texts = ["foo", "bar", "baz"]
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docsearch = Weaviate.from_texts(
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texts,
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OpenAIEmbeddings(),
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weaviate_url=weaviate_url,
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)
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output = docsearch.similarity_search("foo", k=1)
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assert output == [Document(page_content="foo")]
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def test_similarity_search_with_metadata(self, weaviate_url: str) -> None:
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"""Test end to end construction and search with metadata."""
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texts = ["foo", "bar", "baz"]
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metadatas = [{"page": i} for i in range(len(texts))]
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docsearch = Weaviate.from_texts(
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texts, OpenAIEmbeddings(), metadatas=metadatas, weaviate_url=weaviate_url
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)
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output = docsearch.similarity_search("foo", k=1)
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assert output == [Document(page_content="foo", metadata={"page": 0})]
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