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d718f3b6d0
Since it seems like #6111 will be blocked for a bit, I've forked @tyree731's fork and implemented the requested changes. This change adds support to the base Embeddings class for two methods, aembed_query and aembed_documents, those two methods supporting async equivalents of embed_query and embed_documents respectively. This ever so slightly rounds out async support within langchain, with an initial implementation of this functionality being implemented for openai. Implements https://github.com/hwchase17/langchain/issues/6109 --------- Co-authored-by: Stephen Tyree <tyree731@gmail.com>
72 lines
2.2 KiB
Python
72 lines
2.2 KiB
Python
"""Test openai embeddings."""
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import numpy as np
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import openai
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import pytest
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from langchain.embeddings.openai import OpenAIEmbeddings
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def test_openai_embedding_documents() -> None:
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"""Test openai embeddings."""
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documents = ["foo bar"]
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embedding = OpenAIEmbeddings()
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output = embedding.embed_documents(documents)
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assert len(output) == 1
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assert len(output[0]) == 1536
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def test_openai_embedding_documents_multiple() -> None:
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"""Test openai embeddings."""
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documents = ["foo bar", "bar foo", "foo"]
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embedding = OpenAIEmbeddings(chunk_size=2)
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embedding.embedding_ctx_length = 8191
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output = embedding.embed_documents(documents)
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assert len(output) == 3
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assert len(output[0]) == 1536
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assert len(output[1]) == 1536
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assert len(output[2]) == 1536
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@pytest.mark.asyncio
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async def test_openai_embedding_documents_async_multiple() -> None:
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"""Test openai embeddings."""
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documents = ["foo bar", "bar foo", "foo"]
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embedding = OpenAIEmbeddings(chunk_size=2)
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embedding.embedding_ctx_length = 8191
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output = await embedding.aembed_documents(documents)
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assert len(output) == 3
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assert len(output[0]) == 1536
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assert len(output[1]) == 1536
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assert len(output[2]) == 1536
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def test_openai_embedding_query() -> None:
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"""Test openai embeddings."""
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document = "foo bar"
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embedding = OpenAIEmbeddings()
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output = embedding.embed_query(document)
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assert len(output) == 1536
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@pytest.mark.asyncio
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async def test_openai_embedding_async_query() -> None:
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"""Test openai embeddings."""
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document = "foo bar"
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embedding = OpenAIEmbeddings()
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output = await embedding.aembed_query(document)
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assert len(output) == 1536
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def test_openai_embedding_with_empty_string() -> None:
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"""Test openai embeddings with empty string."""
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document = ["", "abc"]
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embedding = OpenAIEmbeddings()
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output = embedding.embed_documents(document)
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assert len(output) == 2
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assert len(output[0]) == 1536
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expected_output = openai.Embedding.create(input="", model="text-embedding-ada-002")[
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"data"
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][0]["embedding"]
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assert np.allclose(output[0], expected_output)
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assert len(output[1]) == 1536
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