diff --git a/.github/workflows/auto-release.yml b/.github/workflows/auto-release.yml new file mode 100644 index 0000000..8ed5853 --- /dev/null +++ b/.github/workflows/auto-release.yml @@ -0,0 +1,13 @@ +name: 'auto release' +on: + pull_request: + types: + - closed + branches: + - main + +jobs: + call-workflow-passing-data: + if: github.event.pull_request.merged + uses: fivetran/dbt_package_automations/.github/workflows/auto-release.yml@main + secrets: inherit \ No newline at end of file diff --git a/README.md b/README.md index 9db977c..5aa29d8 100644 --- a/README.md +++ b/README.md @@ -21,11 +21,11 @@ The main focus of this dbt package is to generate an end model and [Cortex Searc - [Zendesk](https://fivetran.com/docs/connectors/applications/zendesk): Tickets The following table provides a detailed list of all models materialized within this package by default. -> TIP: See more details about these models in the package's [dbt docs site](https://fivetran.github.io/dbt_unified_rag/#!/overview/package_name_here). +> TIP: See more details about these models in the package's [dbt docs site](https://fivetran.github.io/dbt_unified_rag/#!/overview). | **Table** | **Description** | | ------------------------- | ------------------------------------------------------------------------------------------------------------------ | -| [rag__unified_document](https://github.com/fivetran/dbt_unified_rag/blob/main/models/rag__unified_document.sql) | Each record represents a chunk of text prepared for semantic-search and additional fields for use in LLM workflows. | +| [rag__unified_document](https://fivetran.github.io/dbt_unified_rag/#!/model/model.unified_rag.rag__unified_document) | Each record represents a chunk of text prepared for semantic-search and additional fields for use in LLM workflows. | Additionally, for **Snowflake** destinations, a [Cortex Search Service](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-search/cortex-search-overview) will be generated as a result of this data model. The Cortex Search Service uses the results of the `rag__unified_document` and enables Snowflake users to take advantage of low-latency, high quality "fuzzy" search over their data for use in RAG applications leveraging LLMs. See the below table for details. @@ -58,7 +58,7 @@ packages: ### Step 3: Define database and schema variables #### Single connector -By default, this package looks for your ad platform data in your target database. If this is not where your app platform data is stored, add the relevant `_database` variables to your `dbt_project.yml` file (see below). +By default, this package looks for your HubSpot, Jira, and/or Zendesk data in your target database. If this is not where your data is stored, add the relevant `_database` variables to your `dbt_project.yml` file (see below). ```yml # dbt_project.yml diff --git a/integration_tests/dbt_project.yml b/integration_tests/dbt_project.yml index 53f5cff..6b17170 100644 --- a/integration_tests/dbt_project.yml +++ b/integration_tests/dbt_project.yml @@ -14,14 +14,6 @@ vars: rag__using_zendesk: True rag__using_hubspot: True - rag_jira_comment_identifier: jira_comment - rag_jira_issue_identifier: jira_issue - rag_jira_user_identifier: jira_user - rag_jira_priority_identifier: jira_priority - rag_jira_status_identifier: jira_status - rag_zendesk_ticket_identifier: zendesk_ticket - rag_zendesk_ticket_comment_identifier: zendesk_ticket_comment - rag_zendesk_user_identifier: zendesk_user rag_hubspot_engagement_note_identifier: "hubspot_engagement_note" rag_hubspot_engagement_email_identifier: "hubspot_engagement_email" rag_hubspot_engagement_company_identifier: "hubspot_engagement_company"