DataSources

Import an Excel file or a CSV and it becomes a named table of typed columns. A workflow can loop its rows and a dashboard can chart them, from the same source. Load a leads list or a price sheet one time and every automation and board can read it.

• Excel (.xlsx) and CSV, with a per-column type pass: text, number, yes/no, date
• Drag a file onto the panel, or import inline wherever a source is picked
• Imported once, available to every workflow and dashboard
• Identifier columns stay text, so phone numbers and ids are never read as dates

Paste a feed URL, or a site home page and pick the feed it links to, and it loads as a table, one row per item. Every feed gets the same typed columns: title, link, published, author, summary, content, categories, and id. Loop it in a workflow, chart it on a dashboard, or let the AI read it, the same as any spreadsheet.

• RSS 2.0, Atom, and JSON Feed, parsed into the standard column set
• Paste a site URL and pick its feed, no hunting for the link
• Private feeds via an API Connection: key, bearer, or basic auth
• Expose all fields adds a column for every other element in the feed
• Feeds default to live, so the table stays current

A snapshot stores the rows as they were the moment you imported: offline-safe, and fixed until you refresh. Live re-reads the original file each time, so edits show up without re-importing. Set it per source and override it wherever the source is used.

• Snapshot for a one-off campaign over a fixed list
• Live for a file you keep editing in place
• Refresh from source pulls the latest rows into the snapshot on demand
• Freshness is a per-use override on the tool and in every picker

Open a source and it expands into a full-panel grid: every row paged, a search box across all columns, per-column filters in a dropdown off the search bar, and click-to-sort. Rows are fetched a page at a time from the local daemon, so a few thousand stay responsive.

• Pages of 25 to 250 rows, each fetched on demand
• Global search plus a per-column filter
• Sortable columns, ascending or descending
• Opens as a wide in-panel view with a full-screen toggle, the way a board opens

The grid is where you change the data, not just read it. Double-click a cell to fix it, open a whole row in a typed dialog, add and delete rows, and rename, retype or drop a column from its header menu. Or start a blank table and type it yourself, with no file to import.

• Double-click a cell: Enter saves, Esc discards, Tab moves on
• Add or delete rows one at a time, or check several and delete the lot
• Rename, retype, add and delete columns from the header menu
• Changing a type says how many values will not convert, and keeps them as text
• Start a blank table from the Add menu: name it, declare its columns, fill it in

A feed is never editable, because its rows are replaced on every refresh. A source that reads live from a file you own is refused rather than edited invisibly, and the banner offers to switch it to a snapshot for editing. A snapshot over your own file is editable, and the refresh button asks before it overwrites your edits.

• A feed hides its edit controls rather than greying them
• A live source offers Switch to Snapshot right where the refusal appears
• Refresh only warns once you have actually edited something
• A source your organization pushed can have its rows edited but not be deleted

Type @ in the chat input and pick a data source. The message carries its columns, row count, and first rows, and the AI reads past that with the tool when it needs more. For exact rows, check them in the preview grid and click Add to chat; the conversation then points at precisely those rows.

• A Data sources section in the @ picker, searchable by name
• A whole-source mention inlines the schema and the first 20 rows
• Check rows across pages, searches, and filters; the # column numbers them
• Row mentions read @dataset:<id>#rows=2-15,40 and inline up to 200 rows

Tell the assistant what you want and it builds the data source or changes the rows: a new list from what you just pasted, a row added, a value fixed, a test row dropped. The panel updates the moment it finishes, and a list it makes for you is an ordinary source, with the same preview, scope, and refresh.

• Create a source from rows in the conversation, named and typed
• Add, edit, or remove rows in a source you already have
• Identifier columns can be pinned as text, so a leading zero survives
• The panel, the pickers, and an open preview all refresh on their own
• A feed is never edited, and a live source backed by your own file is left alone
• Or open a chat docked beside the grid, bound to that one source, and watch it work

Give a workflow a Data source input. At run time you pick the file (or import one on the spot) and the freshness. A tool step loads the rows, a loop walks them, and each column reads as a template variable.

• Data source is a typed workflow input that resolves to {id, mode}
• A plexon_dataset tool step returns the rows
• A loop step over the rows fans the work out, one item at a time
• Each column reads as {{loop.item.<Column>}} inside the loop

In the widget editor, click Use a data source, pick the file from the list, and choose the column to show. A table widget renders the whole sheet; a metric or gauge widget shows one field. No hand-written JSON arguments required.

• Pick the data source and the field from dropdowns
• Table widgets render every column and row
• Value widgets map one column to the number they display
• Or reference a board parameter for a viewer-switchable source

A read-only built-in tool, plexon_dataset, backs the dashboard binding and the workflow step alike. It returns typed columns and column-keyed rows, with paging, a column subset, and an optional group-by count. The AI can call it from any prompt too. Writes go through a separate tool, plexon_dataset_edit, which boards and workflow steps cannot reach.

• Returns columns, rows, row_count, and an optional per-value group count
• Rows keyed by column name, so a loop and a table both read them directly
• limit, offset, columns, and group_by arguments for shaping the result
• Bindable in workflows and dashboards through the built-in tool allowlist
• Creating and editing is a separate tool, kept off the unattended path

A source lives in one project or across all of them, your choice at import. Move it between the two from its card at any time, and its id stays the same, so workflows and dashboards that already reference it keep resolving. The panel footer counts both scopes.

• This project only, or all projects
• Move a source from project to global and back, references survive
• The footer shows the count in each scope
• A sidebar badge shows how many sources you have at a glance

A persona can carry its own Data Source. Install the persona, or switch to it, and a sample CSV lands in your global sources, there to read from a workflow or a board. The copy is written only when it is missing, so once you edit the rows they stay yours through every later switch.

• A persona declares a sample CSV in its profile; install or switch drops a copy into your sources
• Seed-if-missing: written once, then your edits survive every reinstall and every switch
• Fully editable, the same as a source you imported by hand
• Lands in your global scope, available to every project

The file never leaves your machine. Imports cap at 64 MB and snapshots at 200,000 rows. Date detection is conservative on purpose, so an id or phone column is never reinterpreted. Delete a source and anything still pointing at it shows a clear message instead of failing silently.

• Files stay on disk under ~/.plexon/datasets or <project>/.plexon/datasets
• 64 MB import cap; 200,000-row snapshot cap with a note when truncated
• Conservative ISO-date detection keeps ids and phone numbers as text
• A deleted source surfaces a clear missing-source message, never a silent break