- `Vectara` is developer-first API platform for building GenAI applications
- `Vectara` is developer-first API platform for building GenAI applications
- To use Vectara - first [sign up](https://console.vectara.com/signup) and create an account. Then create a corpus and an API key for indexing and searching.
- To use Vectara - first [sign up](https://vectara.com/integrations/langchain) and create an account. Then create a corpus and an API key for indexing and searching.
- You can use Vectara's [indexing API](https://docs.vectara.com/docs/indexing-apis/indexing) to add documents into Vectara's index
- You can use Vectara's [indexing API](https://docs.vectara.com/docs/indexing-apis/indexing) to add documents into Vectara's index
- You can use Vectara's [Search API](https://docs.vectara.com/docs/search-apis/search) to query Vectara's index (which also supports Hybrid search implicitly).
- You can use Vectara's [Search API](https://docs.vectara.com/docs/search-apis/search) 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.
- You can use Vectara's integration with LangChain as a Vector store or using the Retriever abstraction.
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## Installation and Setup
## Installation and Setup
To use `Vectara` with LangChain no special installation steps are required.
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.
To get started, [sign up](https://vectara.com/integrations/langchain) and follow our [quickstart](https://docs.vectara.com/docs/quickstart) guide to create 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.
Once you have these, you can provide them as arguments to the Vectara vectorstore, or you can set them as environment variables.