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The core feature of the TextQL platform is Ana, TextQL’s AI agent for data science. When prompted with a question, Ana uses tools to address the user’s concern. Common tools are
  • Text2SQL, fetching data from warehouse and loading to Python sandbox
  • Python Analysis, for transforming and visualizing data, as well as communicating with external APIs using secrets, and
  • WebSearch, for querying public data and current events.

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Getting Started with Ana

To start with Ana, connect your data warehouse via the Connectors page. If you don’t have a warehouse, you can use Ana with flat file uploads on the New Thread page.

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Important Pages for Using Ana

  • The Connectors page is where you add data sources to make them available to Ana. Connect your warehouse or other data sources here.
  • The New Thread page is where you start new chats with Ana.
  • Visit Settings > Secrets to add organization secrets, personal access tokens, and API keys. Ana will be able to use these secrets later through the python tool.
  • Visit Settings > Organization Context for TextQL’s native context library. Context can be entered directly or uploaded as files (pdf, csv), and may be attached at the level of your organization, connectors, or roles.
  • The Ontology page allows you to optionally build ontologies for Ana. The ontology is TextQL’s semantic layer and allows for attaching context to tables, columns, or links/joins.

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Additional Resources