Adding Self-querying for Vectara (#10332)

- Description: Adding support for self-querying to Vectara integration - Issue: per customer request - Tag maintainer: @rlancemartin @baskaryan - Twitter handle: @ofermend Also updated some documentation, added self-query testing, and a demo notebook with self-query example.
langchain-ai · Sep 7, 2023 · a9eb7c6 · a9eb7c6
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diff --git a/docs/extras/integrations/providers/vectara/index.mdx b/docs/extras/integrations/providers/vectara/index.mdx
@@ -11,9 +11,10 @@ What is Vectara?
 - 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.
+To use Vectara with LangChain no special installation steps are required. 
+To get started, follow our [quickstart](https://docs.vectara.com/docs/quickstart) guide to create an account, a corpus and an API key. 
+Once you have these, you can provide them as arguments to the Vectara vectorstore, or you can set them as environment variables.
 
-Alternatively these can be provided as environment variables
 - export `VECTARA_CUSTOMER_ID`="your_customer_id"
 - export `VECTARA_CORPUS_ID`="your_corpus_id"
 - export `VECTARA_API_KEY`="your-vectara-api-key"

diff --git a/docs/extras/integrations/vectorstores/vectara.ipynb b/docs/extras/integrations/vectorstores/vectara.ipynb