mirror of
https://github.com/hwchase17/langchain.git
synced 2025-08-16 08:06:14 +00:00
Use Embeddings in pinecone (#8982)
cc @eyurtsev @olivier-lacroix @jamescalam redo of #2741
This commit is contained in:
parent
8eea46ed0e
commit
16bd328aab
@ -3,7 +3,8 @@ from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import uuid
|
||||
from typing import Any, Callable, Iterable, List, Optional, Tuple
|
||||
import warnings
|
||||
from typing import Any, Callable, Iterable, List, Optional, Tuple, Union
|
||||
|
||||
import numpy as np
|
||||
|
||||
@ -38,7 +39,7 @@ class Pinecone(VectorStore):
|
||||
def __init__(
|
||||
self,
|
||||
index: Any,
|
||||
embedding_function: Callable,
|
||||
embedding: Union[Embeddings, Callable],
|
||||
text_key: str,
|
||||
namespace: Optional[str] = None,
|
||||
distance_strategy: Optional[DistanceStrategy] = DistanceStrategy.COSINE,
|
||||
@ -47,7 +48,7 @@ class Pinecone(VectorStore):
|
||||
try:
|
||||
import pinecone
|
||||
except ImportError:
|
||||
raise ValueError(
|
||||
raise ImportError(
|
||||
"Could not import pinecone python package. "
|
||||
"Please install it with `pip install pinecone-client`."
|
||||
)
|
||||
@ -56,17 +57,36 @@ class Pinecone(VectorStore):
|
||||
f"client should be an instance of pinecone.index.Index, "
|
||||
f"got {type(index)}"
|
||||
)
|
||||
if not isinstance(embedding, Embeddings):
|
||||
warnings.warn(
|
||||
"Passing in `embedding` as a Callable is deprecated. Please pass in an"
|
||||
" Embeddings object instead."
|
||||
)
|
||||
self._index = index
|
||||
self._embedding_function = embedding_function
|
||||
self._embedding = embedding
|
||||
self._text_key = text_key
|
||||
self._namespace = namespace
|
||||
self.distance_strategy = distance_strategy
|
||||
|
||||
@property
|
||||
def embeddings(self) -> Optional[Embeddings]:
|
||||
# TODO: Accept this object directly
|
||||
"""Access the query embedding object if available."""
|
||||
if isinstance(self._embedding, Embeddings):
|
||||
return self._embedding
|
||||
return None
|
||||
|
||||
def _embed_documents(self, texts: Iterable[str]) -> List[List[float]]:
|
||||
"""Embed search docs."""
|
||||
if isinstance(self._embedding, Embeddings):
|
||||
return self._embedding.embed_documents(list(texts))
|
||||
return [self._embedding(t) for t in texts]
|
||||
|
||||
def _embed_query(self, text: str) -> List[float]:
|
||||
"""Embed query text."""
|
||||
if isinstance(self._embedding, Embeddings):
|
||||
return self._embedding.embed_query(text)
|
||||
return self._embedding(text)
|
||||
|
||||
def add_texts(
|
||||
self,
|
||||
texts: Iterable[str],
|
||||
@ -93,8 +113,8 @@ class Pinecone(VectorStore):
|
||||
# Embed and create the documents
|
||||
docs = []
|
||||
ids = ids or [str(uuid.uuid4()) for _ in texts]
|
||||
for i, text in enumerate(texts):
|
||||
embedding = self._embedding_function(text)
|
||||
embeddings = self._embed_documents(texts)
|
||||
for i, (text, embedding) in enumerate(zip(texts, embeddings)):
|
||||
metadata = metadatas[i] if metadatas else {}
|
||||
metadata[self._text_key] = text
|
||||
docs.append((ids[i], embedding, metadata))
|
||||
@ -124,7 +144,7 @@ class Pinecone(VectorStore):
|
||||
"""
|
||||
if namespace is None:
|
||||
namespace = self._namespace
|
||||
query_obj = self._embedding_function(query)
|
||||
query_obj = self._embed_query(query)
|
||||
docs = []
|
||||
results = self._index.query(
|
||||
[query_obj],
|
||||
@ -265,7 +285,7 @@ class Pinecone(VectorStore):
|
||||
Returns:
|
||||
List of Documents selected by maximal marginal relevance.
|
||||
"""
|
||||
embedding = self._embedding_function(query)
|
||||
embedding = self._embed_query(query)
|
||||
return self.max_marginal_relevance_search_by_vector(
|
||||
embedding, k, fetch_k, lambda_mult, filter, namespace
|
||||
)
|
||||
@ -356,7 +376,7 @@ class Pinecone(VectorStore):
|
||||
# upsert to Pinecone
|
||||
_upsert_kwargs = upsert_kwargs or {}
|
||||
index.upsert(vectors=list(to_upsert), namespace=namespace, **_upsert_kwargs)
|
||||
return cls(index, embedding.embed_query, text_key, namespace, **kwargs)
|
||||
return cls(index, embedding, text_key, namespace, **kwargs)
|
||||
|
||||
@classmethod
|
||||
def from_existing_index(
|
||||
@ -375,9 +395,7 @@ class Pinecone(VectorStore):
|
||||
"Please install it with `pip install pinecone-client`."
|
||||
)
|
||||
|
||||
return cls(
|
||||
pinecone.Index(index_name), embedding.embed_query, text_key, namespace
|
||||
)
|
||||
return cls(pinecone.Index(index_name), embedding, text_key, namespace)
|
||||
|
||||
def delete(
|
||||
self,
|
||||
|
Loading…
Reference in New Issue
Block a user