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pinecone[patch], docs: PineconeVectorStore, release 0.0.3 (#17896)

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This commit is contained in:
Erick Friis
2024-02-22 08:24:08 -08:00
committed by GitHub
parent e5e38e89ce
commit a53370a060
22 changed files with 130 additions and 128 deletions
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8
templates/rag-conversation/rag_conversation/chain.py
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@@ -5,7 +5,6 @@ from typing import List, Tuple
from langchain.schema import AIMessage, HumanMessage, format_document
from langchain_community.chat_models import ChatOpenAI
from langchain_community.embeddings import OpenAIEmbeddings
from langchain_community.vectorstores import Pinecone
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
from langchain_core.prompts.prompt import PromptTemplate
@@ -16,6 +15,7 @@ from langchain_core.runnables import (
RunnableParallel,
RunnablePassthrough,
)
from langchain_pinecone import PineconeVectorStore
if os.environ.get("PINECONE_API_KEY", None) is None:
raise Exception("Missing `PINECONE_API_KEY` environment variable.")
@@ -37,12 +37,14 @@ PINECONE_INDEX_NAME = os.environ.get("PINECONE_INDEX", "langchain-test")
# all_splits = text_splitter.split_documents(data)
# # Add to vectorDB
# vectorstore = Pinecone.from_documents(
# vectorstore = PineconeVectorStore.from_documents(
# documents=all_splits, embedding=OpenAIEmbeddings(), index_name=PINECONE_INDEX_NAME
# )
# retriever = vectorstore.as_retriever()
vectorstore = Pinecone.from_existing_index(PINECONE_INDEX_NAME, OpenAIEmbeddings())
vectorstore = PineconeVectorStore.from_existing_index(
PINECONE_INDEX_NAME, OpenAIEmbeddings()
)
retriever = vectorstore.as_retriever()
# Condense a chat history and follow-up question into a standalone question