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59 lines
1.7 KiB
Python
59 lines
1.7 KiB
Python
"""Test embaas embeddings."""
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import responses
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from langchain.embeddings.embaas import EMBAAS_API_URL, EmbaasEmbeddings
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def test_embaas_embed_documents() -> None:
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"""Test embaas embeddings with multiple texts."""
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texts = ["foo bar", "bar foo", "foo"]
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embedding = EmbaasEmbeddings()
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output = embedding.embed_documents(texts)
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assert len(output) == 3
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assert len(output[0]) == 1024
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assert len(output[1]) == 1024
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assert len(output[2]) == 1024
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def test_embaas_embed_query() -> None:
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"""Test embaas embeddings with multiple texts."""
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text = "foo"
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embeddings = EmbaasEmbeddings()
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output = embeddings.embed_query(text)
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assert len(output) == 1024
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def test_embaas_embed_query_instruction() -> None:
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"""Test embaas embeddings with a different instruction."""
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text = "Test"
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instruction = "query"
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embeddings = EmbaasEmbeddings(instruction=instruction)
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output = embeddings.embed_query(text)
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assert len(output) == 1024
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def test_embaas_embed_query_model() -> None:
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"""Test embaas embeddings with a different model."""
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text = "Test"
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model = "instructor-large"
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instruction = "Represent the query for retrieval"
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embeddings = EmbaasEmbeddings(model=model, instruction=instruction)
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output = embeddings.embed_query(text)
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assert len(output) == 768
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@responses.activate
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def test_embaas_embed_documents_response() -> None:
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"""Test embaas embeddings with multiple texts."""
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responses.add(
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responses.POST,
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EMBAAS_API_URL,
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json={"data": [{"embedding": [0.0] * 1024}]},
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status=200,
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)
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text = "asd"
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embeddings = EmbaasEmbeddings()
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output = embeddings.embed_query(text)
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assert len(output) == 1024
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