嵌入

当涉及到嵌入时，用户有几个选择。

• OpenAIEmbedding：默认嵌入类。默认为“text-embedding-ada-002”

• LangchainEmbedding：Langchain嵌入模型的包装器。

我们还引入了一个:code:`LangchainEmbedding`类，它是Langchain嵌入模型的包装器。可以在这里找到完整的嵌入列表<https://langchain.readthedocs.io/en/latest/reference/modules/embeddings.html>`_。

Langchain Embedding Wrapper Module.

class llama_index.embeddings.langchain.LangchainEmbedding(langchain_embedding: Embeddings, **kwargs: Any)

External embeddings (taken from Langchain).

参数

langchain_embedding (langchain.embeddings.Embeddings) -- Langchain embeddings class.

async aget_queued_text_embeddings(text_queue: List[Tuple[str, str]]) → Tuple[List[str], List[List[float]]]

Asynchronously get a list of text embeddings.

Call async embedding API to get embeddings for all queued texts in parallel. Argument text_queue must be passed in to avoid updating it async.

get_agg_embedding_from_queries(queries: List[str], agg_fn: Optional[Callable[[...], List[float]]] = None) → List[float]

Get aggregated embedding from multiple queries.

get_query_embedding(query: str) → List[float]

Get query embedding.

get_queued_text_embeddings() → Tuple[List[str], List[List[float]]]

Get queued text embeddings.

Call embedding API to get embeddings for all queued texts.

get_text_embedding(text: str) → List[float]

Get text embedding.

property last_token_usage: int

Get the last token usage.

queue_text_for_embedding(text_id: str, text: str) → None

Queue text for embedding.

Used for batching texts during embedding calls.

similarity(embedding1: List, embedding2: List, mode: SimilarityMode = SimilarityMode.DEFAULT) → float

Get embedding similarity.

property total_tokens_used: int

Get the total tokens used so far.