LangChain with Upstash Vector

pip install upstash-vector langchain langchain-community python-dotenv

from dotenv import load_dotenv
from langchain_community.vectorstores.upstash import UpstashVectorStore
from langchain.schema import Document

# Load environment variables
load_dotenv()

# Create a vector store instance
store = UpstashVectorStore(
    embedding=True,  # Embedding option enabled
)

# Sample documents to upload
documents = [
    Document(page_content="Upstash Vector is a scalable vector database."),
    Document(page_content="LangChain is a framework for building intelligent apps."),
    Document(page_content="Semantic search enables advanced query matching."),
]

# Add documents to the Upstash Vector index
store.add_documents(documents)

# Perform a similarity search
query = "What is LangChain?"
results = store.similarity_search(query, k=3)

print("Similarity Search Results:")
for res in results:
    print(res.page_content)

Similarity Search Results:
LangChain is a framework for building intelligent apps.
Semantic search enables advanced query matching.
Upstash Vector is a scalable vector database.