mirror of
https://github.com/hwchase17/langchain
synced 2024-11-10 01:10:59 +00:00
ed58eeb9c5
Moved the following modules to new package langchain-community in a backwards compatible fashion: ``` mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community ``` Moved the following to core ``` mv langchain/langchain/utils/json_schema.py core/langchain_core/utils mv langchain/langchain/utils/html.py core/langchain_core/utils mv langchain/langchain/utils/strings.py core/langchain_core/utils cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py rm langchain/langchain/utils/env.py ``` See .scripts/community_split/script_integrations.sh for all changes
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_community.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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