feat: Add User-Agent attribution for Databricks Partner telemetry#42
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prasadkona wants to merge 1 commit intodatabrickslabs:mainfrom
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feat: Add User-Agent attribution for Databricks Partner telemetry#42prasadkona wants to merge 1 commit intodatabrickslabs:mainfrom
prasadkona wants to merge 1 commit intodatabrickslabs:mainfrom
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Add centralized User-Agent configuration following the Databricks Partner Well-Architected Framework guidelines for API attribution. Changes: - Create src/utils/telemetry.py with User-Agent helper functions - Add Kasal_jobs User-Agent to Databricks Jobs API calls - Add Kasal_genie User-Agent to Genie API calls - Add Kasal_vectorsearch User-Agent to Vector Search API calls - Add Kasal User-Agent to UC Volumes (SDK + REST fallback) - Add Kasal User-Agent to SQL Warehouse connection tests - Add Kasal User-Agent to MLflow SDK calls - Add Kasal user_agent to LiteLLM for Databricks models - Add Kasal application_name to Lakebase PostgreSQL connections User-Agent Format: <isv-name_product-name>/<product-version> Examples: Kasal/0.1.0, Kasal_jobs/0.1.0, Kasal_genie/0.1.0
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Summary
Add centralized User-Agent configuration following the Databricks Partner Well-Architected Framework guidelines for API attribution. This enables Databricks to track Kasal usage across all API integrations.
Changes
New File
src/backend/src/utils/telemetry.py- Centralized User-Agent module with helper functionsModified Files
databricks_jobs_tool.pyKasal_jobs/0.1.0genie_repository.pyKasal_genie/0.1.0genie_tool.pyKasal_genie/0.1.0databricks_vector_index_repository.pyKasal_vectorsearch/0.1.0databricks_volume_repository.pyKasal/0.1.0databricks_service.pyKasal/0.1.0mlflow_service.pyKasal/0.1.0llm_manager.pyKasallakebase_session.pyKasal/0.1.0User-Agent Format
Following the Databricks Partner Well-Architected Framework:
Examples:
Kasal/0.1.0- Base productKasal_jobs/0.1.0- Databricks Jobs integrationKasal_genie/0.1.0- Genie integrationKasal_vectorsearch/0.1.0- Vector Search integrationTesting