Ensure that an embedding function conforms to LangChain's Embeddings interface.
This function wraps arbitrary embedding functions to make them compatible with LangChain's Embeddings interface. It handles both synchronous and asynchronous functions.
ensure_embeddings(
embed: Embeddings | EmbeddingsFunc | AEmbeddingsFunc | str | None
) -> EmbeddingsWrap a synchronous embedding function:
def my_embed_fn(texts):
return [[0.1, 0.2] for _ in texts]
embeddings = ensure_embeddings(my_embed_fn)
result = embeddings.embed_query("hello") # Returns [0.1, 0.2]Wrap an asynchronous embedding function:
async def my_async_fn(texts):
return [[0.1, 0.2] for _ in texts]
embeddings = ensure_embeddings(my_async_fn)
result = await embeddings.aembed_query("hello") # Returns [0.1, 0.2]Initialize embeddings using a provider string:
# Requires langchain>=0.3.9 and langgraph-checkpoint>=2.0.11
embeddings = ensure_embeddings("openai:text-embedding-3-small")
result = embeddings.embed_query("hello")| Name | Type | Description |
|---|---|---|
embed* | Embeddings | EmbeddingsFunc | AEmbeddingsFunc | str | None | Either an existing Embeddings instance, or a function that converts text to embeddings. If the function is async, it will be used for both sync and async operations. |