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56dde3ade3
This PR adds scaffolding for langchain 1.0 entry package. Most contents have been removed. Currently remaining entrypoints for: * chat models * embedding models * memory -> trimming messages, filtering messages and counting tokens [we may remove this] * prompts -> we may remove some prompts * storage: primarily to support cache backed embeddings, may remove the kv store * tools -> report tool primitives Things to be added: * Selected agent implementations * Selected workflows * Common primitives: messages, Document * Primitives for type hinting: BaseChatModel, BaseEmbeddings * Selected retrievers * Selected text splitters Things to be removed: * Globals needs to be removed (needs an update in langchain core) Todos: * TBD indexing api (requires sqlalchemy which we don't want as a dependency) * Be explicit about public/private interfaces (e.g., likely rename chat_models.base.py to something more internal) * Remove dockerfiles * Update module doc-strings and README.md
45 lines
1.3 KiB
Python
45 lines
1.3 KiB
Python
"""Test embeddings base module."""
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import importlib
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import pytest
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from langchain_core.embeddings import Embeddings
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from langchain.embeddings.base import _SUPPORTED_PROVIDERS, init_embeddings
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@pytest.mark.parametrize(
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("provider", "model"),
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[
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("openai", "text-embedding-3-large"),
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("google_vertexai", "text-embedding-gecko@003"),
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("bedrock", "amazon.titan-embed-text-v1"),
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("cohere", "embed-english-v2.0"),
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],
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)
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async def test_init_embedding_model(provider: str, model: str) -> None:
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package = _SUPPORTED_PROVIDERS[provider]
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try:
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importlib.import_module(package)
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except ImportError:
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pytest.skip(f"Package {package} is not installed")
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model_colon = init_embeddings(f"{provider}:{model}")
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assert isinstance(model_colon, Embeddings)
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model_explicit = init_embeddings(
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model=model,
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provider=provider,
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)
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assert isinstance(model_explicit, Embeddings)
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text = "Hello world"
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embedding_colon = await model_colon.aembed_query(text)
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assert isinstance(embedding_colon, list)
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assert all(isinstance(x, float) for x in embedding_colon)
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embedding_explicit = await model_explicit.aembed_query(text)
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assert isinstance(embedding_explicit, list)
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assert all(isinstance(x, float) for x in embedding_explicit)
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