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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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4
templates/rag-fusion/ingest.py
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@@ -1,5 +1,5 @@
from langchain_community.embeddings import OpenAIEmbeddings
from langchain_community.vectorstores import Pinecone
from langchain_pinecone import PineconeVectorStore
all_documents = {
"doc1": "Climate change and economic impact.",
@@ -14,6 +14,6 @@ all_documents = {
"doc10": "The history of climate change activism.",
}
Pinecone.from_texts(
PineconeVectorStore.from_texts(
list(all_documents.values()), OpenAIEmbeddings(), index_name="rag-fusion"
)

4
templates/rag-fusion/rag_fusion/chain.py
View File

@@ -2,9 +2,9 @@ from langchain import hub
from langchain.load import dumps, loads
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.pydantic_v1 import BaseModel
from langchain_pinecone import PineconeVectorStore
def reciprocal_rank_fusion(results: list[list], k=60):
@@ -30,7 +30,7 @@ generate_queries = (
prompt | ChatOpenAI(temperature=0) | StrOutputParser() | (lambda x: x.split("\n"))
)
vectorstore = Pinecone.from_existing_index("rag-fusion", OpenAIEmbeddings())
vectorstore = PineconeVectorStore.from_existing_index("rag-fusion", OpenAIEmbeddings())
retriever = vectorstore.as_retriever()
chain = (