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Update langchain-pinecone dependency and add Pinecone API key (#1854)

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* Update langchain-pinecone dependency and related code

* Add Pinecone API key to environment variables

* Fix commented out code in codeTabsComponent, parameterComponent, and editNodeModal

* Add PineconeSearchComponent to PineconeSearch.py

* Update PineconeComponent to accept pinecone_api_key as optional parameter
This commit is contained in:
Gabriel Luiz Freitas Almeida 2024-05-07 17:46:54 -03:00 • committed by GitHub
commit 21be1268ae
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9 changed files with 131 additions and 33 deletions
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30
src/backend/base/langflow/components/vectorsearch/PineconeSearch.py
View file

@ -1,5 +1,7 @@
from typing import List, Optional
from langchain_pinecone._utilities import DistanceStrategy
from langflow.components.vectorstores.base.model import LCVectorStoreComponent
from langflow.components.vectorstores.Pinecone import PineconeComponent
from langflow.field_typing import Embeddings, Text
@ -11,8 +13,11 @@ class PineconeSearchComponent(PineconeComponent, LCVectorStoreComponent):
display_name = "Pinecone Search"
description = "Search a Pinecone Vector Store for similar documents."
icon = "Pinecone"
field_order = ["index_name", "namespace", "distance_strategy", "pinecone_api_key", "input_value", "embedding"]
def build_config(self):
distance_options = [e.value.title().replace("_", " ") for e in DistanceStrategy]
distance_value = distance_options[0]
return {
"search_type": {
"display_name": "Search Type",
@ -21,17 +26,19 @@ class PineconeSearchComponent(PineconeComponent, LCVectorStoreComponent):
"input_value": {"display_name": "Input"},
"embedding": {"display_name": "Embedding"},
"index_name": {"display_name": "Index Name"},
"namespace": {"display_name": "Namespace"},
"namespace": {"display_name": "Namespace", "advanced": True},
"distance_strategy": {
"display_name": "Distance Strategy",
# get values from enum
# and make them title case for display
"options": distance_options,
"advanced": True,
"value": distance_value,
},
"pinecone_api_key": {
"display_name": "Pinecone API Key",
"default": "",
"password": True,
"required": True,
},
"pinecone_env": {
"display_name": "Pinecone Environment",
"default": "",
"required": True,
},
"pool_threads": {
"display_name": "Pool Threads",
@ -43,13 +50,18 @@ class PineconeSearchComponent(PineconeComponent, LCVectorStoreComponent):
"info": "Number of results to return.",
"advanced": True,
},
"text_key": {
"display_name": "Text Key",
"info": "Key in the record to use as text.",
"advanced": True,
},
}
def build( # type: ignore[override]
self,
input_value: Text,
embedding: Embeddings,
pinecone_env: str,
distance_strategy: str,
text_key: str = "text",
number_of_results: int = 4,
pool_threads: int = 4,
@ -61,7 +73,7 @@ class PineconeSearchComponent(PineconeComponent, LCVectorStoreComponent):
) -> List[Record]: # type: ignore[override]
vector_store = super().build(
embedding=embedding,
pinecone_env=pinecone_env,
distance_strategy=distance_strategy,
inputs=[],
text_key=text_key,
pool_threads=pool_threads,

107
src/backend/base/langflow/components/vectorstores/Pinecone.py
View file

@ -1,10 +1,10 @@
import os
from typing import List, Optional, Union
import pinecone # type: ignore
from langchain.schema import BaseRetriever
from langchain_community.vectorstores import VectorStore
from langchain_community.vectorstores.pinecone import Pinecone
from langchain_core.documents import Document
from langchain_pinecone._utilities import DistanceStrategy
from langchain_pinecone.vectorstores import PineconeVectorStore
from langflow.field_typing import Embeddings
from langflow.interface.custom.custom_component import CustomComponent
@ -15,24 +15,31 @@ class PineconeComponent(CustomComponent):
display_name = "Pinecone"
description = "Construct Pinecone wrapper from raw documents."
icon = "Pinecone"
field_order = ["index_name", "namespace", "distance_strategy", "pinecone_api_key", "documents", "embedding"]
def build_config(self):
distance_options = [e.value.title().replace("_", " ") for e in DistanceStrategy]
distance_value = distance_options[0]
return {
"inputs": {"display_name": "Input", "input_types": ["Document", "Record"]},
"embedding": {"display_name": "Embedding"},
"index_name": {"display_name": "Index Name"},
"namespace": {"display_name": "Namespace"},
"text_key": {"display_name": "Text Key"},
"distance_strategy": {
"display_name": "Distance Strategy",
# get values from enum
# and make them title case for display
"options": distance_options,
"advanced": True,
"value": distance_value,
},
"pinecone_api_key": {
"display_name": "Pinecone API Key",
"default": "",
"password": True,
"required": True,
},
"pinecone_env": {
"display_name": "Pinecone Environment",
"default": "",
"required": True,
},
"pool_threads": {
"display_name": "Pool Threads",
"default": 1,
@ -40,23 +47,79 @@ class PineconeComponent(CustomComponent):
},
}
def from_existing_index(
self,
index_name: str,
embedding: Embeddings,
pinecone_api_key: str | None,
text_key: str = "text",
namespace: Optional[str] = None,
distance_strategy: DistanceStrategy = DistanceStrategy.COSINE,
pool_threads: int = 4,
) -> PineconeVectorStore:
"""Load pinecone vectorstore from index name."""
pinecone_index = PineconeVectorStore.get_pinecone_index(
index_name, pool_threads, pinecone_api_key=pinecone_api_key
)
return PineconeVectorStore(
index=pinecone_index,
embedding=embedding,
text_key=text_key,
namespace=namespace,
distance_strategy=distance_strategy,
)
def from_documents(
self,
documents: List[Document],
embedding: Embeddings,
index_name: str,
pinecone_api_key: str | None,
text_key: str = "text",
namespace: Optional[str] = None,
pool_threads: int = 4,
distance_strategy: DistanceStrategy = DistanceStrategy.COSINE,
batch_size: int = 32,
upsert_kwargs: Optional[dict] = None,
embeddings_chunk_size: int = 1000,
) -> PineconeVectorStore:
"""Create a new pinecone vectorstore from documents."""
texts = [d.page_content for d in documents]
metadatas = [d.metadata for d in documents]
pinecone = self.from_existing_index(
index_name=index_name,
embedding=embedding,
pinecone_api_key=pinecone_api_key,
text_key=text_key,
namespace=namespace,
distance_strategy=distance_strategy,
pool_threads=pool_threads,
)
pinecone.add_texts(
texts,
metadatas=metadatas,
ids=None,
namespace=namespace,
batch_size=batch_size,
embedding_chunk_size=embeddings_chunk_size,
**(upsert_kwargs or {}),
)
return pinecone
def build(
self,
embedding: Embeddings,
pinecone_env: str,
distance_strategy: str,
inputs: Optional[List[Record]] = None,
text_key: str = "text",
pool_threads: int = 4,
index_name: Optional[str] = None,
pinecone_api_key: Optional[str] = None,
namespace: Optional[str] = "default",
) -> Union[VectorStore, Pinecone, BaseRetriever]:
if pinecone_api_key is None or pinecone_env is None:
raise ValueError("Pinecone API Key and Environment are required.")
if os.getenv("PINECONE_API_KEY") is None and pinecone_api_key is None:
raise ValueError("Pinecone API Key is required.")
pinecone.init(api_key=pinecone_api_key, environment=pinecone_env) # type: ignore
) -> Union[VectorStore, BaseRetriever]:
# get distance strategy from string
distance_strategy = distance_strategy.replace(" ", "_").upper()
_distance_strategy = DistanceStrategy[distance_strategy]
if not index_name:
raise ValueError("Index Name is required.")
documents = []
@ -66,19 +129,23 @@ class PineconeComponent(CustomComponent):
else:
documents.append(_input)
if documents:
return Pinecone.from_documents(
return self.from_documents(
documents=documents,
embedding=embedding,
index_name=index_name,
pool_threads=pool_threads,
namespace=namespace,
pinecone_api_key=pinecone_api_key,
text_key=text_key,
namespace=namespace,
distance_strategy=_distance_strategy,
pool_threads=pool_threads,
)
return Pinecone.from_existing_index(
return self.from_existing_index(
index_name=index_name,
embedding=embedding,
pinecone_api_key=pinecone_api_key,
text_key=text_key,
namespace=namespace,
distance_strategy=_distance_strategy,
pool_threads=pool_threads,
)

1
src/backend/base/langflow/services/settings/constants.py
View file

@ -13,6 +13,7 @@ VARIABLES_TO_GET_FROM_ENVIRONMENT = [
"ASTRA_DB_API_ENDPOINT",
"COHERE_API_KEY",
"HUGGINGFACEHUB_API_TOKEN",
"PINECONE_API_KEY",
"SEARCHAPI_API_KEY",
"SERPAPI_API_KEY",
"VECTARA_CUSTOMER_ID",

2
src/frontend/src/components/codeTabsComponent/index.tsx
View file

@ -749,7 +749,7 @@ export default function CodeTabsComponent({
templateField
].value.toString() === "{}"
? {
yourkey: "value",
// yourkey: "value",
}
: node.data.node!
.template[

2
src/frontend/src/customNodes/genericNode/components/parameterComponent/index.tsx
View file

@ -715,7 +715,7 @@ export default function ParameterComponent({
!data.node!.template[name].value ||
data.node!.template[name].value?.toString() === "{}"
? {
yourkey: "value",
// yourkey: "value",
}
: data.node!.template[name].value
}

2
src/frontend/src/modals/editNodeModal/index.tsx
View file

@ -285,7 +285,7 @@ const EditNodeModal = forwardRef(
templateParam
]?.value?.toString() === "{}"
? {
yourkey: "value",
// yourkey: "value",
}
: myData.node!.template[templateParam]
.value