The Fabric Data Agent SDK supports programmatic access for Fabric Data Agent artifacts.

This package is released as a preview and has been tested with Microsoft Fabric Python notebooks.

Getting started

Prerequisites

• A Microsoft Fabric subscription. Or sign up for a free Microsoft Fabric (Preview) trial.
• Sign in to Microsoft Fabric.
• Create a new notebook or a new spark job to use this package. Note that semantic link is supported only within Microsoft Fabric.

Install the fabric-data-agent-sdk package

To install the most recent version fabric-data-agent-sdk in your Fabric Python notebook kernel by executing this code in a notebook cell:

%pip install -U fabric-data-agent-sdk

Key concepts

Fabric Data Agent SDK has two main entry points:

• Data plane using OpenAI SDK for conversational interaction with an existing Data Agent artifact.
• Management plane to create, update and delete Data Agent artifacts.

Change logs

0.1.18a0

• adds data source type and element type support for Mirrored DB and SQL DB
• enable Publishing Data Agent to M365 Copilot Agent Store
• update failed thread message

0.1.17a0

• add conflict detection to few-shot validation with LLM-based semantic analysis
• add file support
• replace thread_url with message_url

0.1.16a0

• add the ontology data source support

0.1.15a0

• fix get datasources error caused by None value
• fix schema selection when adding data sources
• update example notebook

0.1.14a0

• fix thread url for fabcon tenant

0.1.13a0

• add support for granular quality feedback in few-shot validation and improve Dataframe output
• fix invalid data type for delta lake

0.1.12a0

• fix python error in the release pipeline
• add robust few-shot validation utilities to SDK with dual LLM support and DataFrame output
• update parameter type in add-datasource

0.1.11a0

• upgrade OneBranch Azure Linux Build Image: Migrating from 2.0 to 3.0
• remove "AISkill" from artifact name list due to invalid item type error in openai
• make Data Agent and Data Source Creation Idempotent
• add publish description
• refactoring the evaluation apis and add code coverage
• remove AISkill artifact type in data agent api

0.1.10a0

• fix get_evaluation_summary_per_question if no question fails

0.1.9a0

• Use correct workspace context in delete_data_agent function.
• Update notebooks with data source notes
• display failed threads and fix percentage

0.1.8a0

• evaluation API enhancements including parallelizing, number of variations and single thread.
• speed-up add_ground_truth_batch and stabilise Kusto tests
• ground-truth generation for Kusto (KQL) datasources

0.1.7a0

• added Warehouse to list of artifact types.
• added Method for Updating Ground Truth before Evaluation.
• made Publish Info Optional.

0.1.6a0

• update sdk to make compatible with both python and spark.

0.1.5a0

• add PySpark support for the evaluation APIs.
• added pipeline for running unit tests.

0.1.4a0

• switch to public apis for artifact management.

0.1.3a0

• add column/table descriptions for sql data sources.
• allow selection of multiple columns at once in the datasource.
• bug fix to address the run_steps response structure change.

0.1.2a0

• bugfix for fabric_openai artifact type - should support "DataAgent".
• bugfix for data source type ("datawarehouse" should be "warehouse").

0.1.1a0

• bugfix for create_data_agent where type should support "DataAgent".

0.1.0a0

• add upload_fewshots for adding multiple fewshots to DataSource.

0.0.4a0

• add evaluation APIs to the SDK

0.0.3a1

• return fewshot id from add_fewshots
• fix the aiskill stage parameter
• return datasource display name in pretty_print
• return thread object for get_or_create_thread API.

0.0.2a0

• rename module
• support Fabric get_or_create_thread to decouple from UX thread

0.0.1a0

Initial alpha release of the package.

• add: data plane client
• add: management plane client