langchain/docs/integrations/vectara.md

Vectara

What is Vectara?

Vectara Overview:

• Vectara is developer-first API platform for building conversational search applications
• To use Vectara - first sign up and create an account. Then create a corpus and an API key for indexing and searching.
• You can use Vectara's indexing API to add documents into Vectara's index
• You can use Vectara's Search API to query Vectara's index (which also supports Hybrid search implicitly).
• You can use Vectara's integration with LangChain as a Vector store or using the Retriever abstraction.

Installation and Setup

To use Vectara with LangChain no special installation steps are required. You just have to provide your customer_id, corpus ID, and an API key created within the Vectara console to enable indexing and searching.

VectorStore

There exists a wrapper around the Vectara platform, allowing you to use it as a vectorstore, whether for semantic search or example selection.

To import this vectorstore:

from langchain.vectorstores import Vectara

To create an instance of the Vectara vectorstore:

vectara = Vectara(
    vectara_customer_id=customer_id, 
    vectara_corpus_id=corpus_id, 
    vectara_api_key=api_key
)

The customer_id, corpus_id and api_key are optional, and if they are not supplied will be read from the environment variables VECTARA_CUSTOMER_ID, VECTARA_CORPUS_ID and VECTARA_API_KEY, respectively.

For a more detailed walkthrough of the Vectara wrapper, see one of the two example notebooks:

• Chat Over Documents with Vectara
• Vectara Text Generation