Vector stores enable efficient similarity search.
Store and retrieve document embeddings.
Popular Vector Stores
✅ Pinecone
✅ Chroma
✅ Weaviate
✅ FAISS
✅ Milvus
Example with Chroma
from langchain.vectorstores import Chroma
from langchain.embeddings import OpenAIEmbeddings
embeddings = OpenAIEmbeddings()
vectorstore = Chroma.from_texts(texts, embeddings)
results = vectorstore.similarity_search(“query”, k=3)
Benefits
✅ Fast similarity search
✅ Scalable
✅ Persistent storage
Conclusion
Vector stores power semantic search!