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Settings: Documents

Documents let Row-Bot search files you add to its local document library. This is different from attaching a file to one chat: indexed documents become reusable context for future questions. Mixedbread Embed Large v1 is the recommended local embedding model; it is separate from the chat model and normal use loads it only from Row-Bot's private cache.

Settings: Documents in Row-Bot.
The Documents page sets where search runs and its model, shows index health with its download, retry, repair and rebuild actions, and lists your documents.

Where To Find It​

Open Settings, then choose Documents in the Knowledge group, or search for it with Find a setting.

Controls​

  • Search runs chooses where search works: This computer (your documents never leave it) or Cloud (document text goes to the embedding provider). Switching to Cloud asks first.
  • Search model chooses the embedding model. Mixedbread Embed Large v1 is the recommended local one.
  • Free memory when idle releases the local search model's memory after heavy document work.
  • Index health and maintenance shows the state of your document vectors and memory index:
    • Index size is for advanced search models that need a fixed number of dimensions.
    • Document index and Memory index each offer Rebuild, which recreates them with the current search settings.
    • Search model files offers Download to install the selected local model, Retry to load an already cached copy again, and Repair to replace a damaged download. Download and Repair need network access.
  • Upload documents adds files to Row-Bot-managed storage for indexing.
  • Your documents lists what Row-Bot has processed, with each document's status and progress, and can remove a document after review.

Common Workflow​

  1. Under Search model files, choose Download before adding a large document library.
  2. Upload a small test document and wait until it is indexed.
  3. Ask a question in a chat that should require the document.
  4. Rebuild vectors only when you change the search model or suspect stale results.

What Is Saved​

Uploaded files, extracted text, vectors, and local embedding model caches are stored under the active Row-Bot data directory. In Docker, the named /data volume preserves the cache. The active chat only sees relevant results when document search is enabled. A cloud embedding provider is opt-in and sends indexed text to that provider; the recommended local model does not.

Privacy And Safety​

Review credential, account, channel, provider, or tool settings before enabling features that can contact outside services. Local-only features stay on your machine until you ask Row-Bot to use a provider, account, channel, MCP server, plugin, or tool that sends data elsewhere.

Control-Level Reference​

The generated Settings Controls reference lists every searchable setting on this page with its deep link, search keywords, and any dependency or security notes.

Troubleshooting​

  • If search misses obvious content, rebuild vectors and check the embedding provider.
  • If the local model is missing, use Download under Search model files. Use Retry for a cached model or Repair for a damaged download.
  • If local indexing uses too much memory, turn on Free memory when idle.
  • If a document contains private material, remove it from the document library before sharing screenshots or logs.