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Vectara

Quickstart Tutorial​

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Video tutorial for CiniterFlow coming soon!

We're currently creating new tutorial videos that showcase the CiniterFlow interface and features. Check back soon for updated video content.

Prerequisite​

  1. Register an account for Vectara
  2. Click Create Corpus

Name the corpus to be created and click Create Corpus then wait for the corpus to finish setting up.

Setup​

  1. Click on the "Access Control" tab in the corpus view

  1. Click on the "Create API Key" button, choose a name for the API key and pick the QueryService & IndexService option

  1. Click Create to create the API key
  2. Get your Corpus ID, API Key, and Customer ID by clicking the down-arrow under "copy" for your new API key:

  1. Back to CiniterFlow canvas, and create your chatflow. Click Create New from the Credentials dropdown ane enter your Vectara credentials.

  1. Enjoy!

Vectara Query Parameters​

For finer control over the Vectara query parameters, click on "Additional Parameters" and then you can update the following parameters from their default:

  • Metadata Filter: Vectara supports meta-data filtering. To use filtering, ensure that metadata fields you want to filter by are defined in your Vectara corpus.
  • "Sentences before" and "Sentences after": these control how many sentences before/after the matching text are returned as results from the Vectara retrieval engine
  • Lambda: defines the behavior of hybrid search in Vectara
  • Top-K: how many results to return from Vectara for the query
  • MMR-K: number of results to use for MMR (max marginal relvance)

Resources​