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Upload local files directly into the Agent chat to incorporate them into your pipeline. Uploaded files are converted to tables in the SQL warehouse configured in your fabric, making them available for the Agent to read and use in transformations.
The recommended maximum file size is 100 MB.
You can upload the following file formats:
  • CSV
  • Excel (XLS, XLSX)
  • JSON
  • Parquet
  • XML

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Upload a file

1

Start the upload

Click the paperclip icon in the chat footer to open the file upload dialog. Alternatively, you can drag and drop a file directly onto the pipeline canvas.
2

Select your file

Choose the file you want to upload from your local filesystem. The upload dialog opens automatically.
3

Configure storage location

Set where the file should be stored in the SQL warehouse:
  • Choose the database.
  • Choose the schema.
  • Choose the table name. You can select an existing table or create a new one.
Click Next to continue.
If you select an existing table, Prophecy deletes and recreates the table with your uploaded file data.
4

Review and update schema

Review the inferred schema (column names and data types):
  • Keep the auto-detected schema, or modify column names and data types as needed.
  • Select any table properties you want to configure.
  • Click Next to proceed.
5

Preview and complete

Review the table preview to verify the data structure and content. If the preview looks correct, click Done to complete the upload.The file is converted to a table in your SQL warehouse.

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Make the table available to the Agent

For the Agent to discover the table, you need to add it to the knowledge graph. After uploading a file, the knowledge graph indexer will automatically index the table. However, you can also manually reindex the knowledge graph, in case something goes wrong.
  1. Open the Environment tab in the left sidebar.
  2. Below your connections, locate the Missing Tables? callout.
  3. Click Refresh to trigger the knowledge graph indexer.
Once indexed, the Agent can reference the table using @ mentions or discover it through natural language queries. The Agent will use the Table gem to read the file into your pipeline.