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This release is a pre-release and may not be stable for production use.

AIDA — AI Data Assistant

Status: beta (0.1.0b5). Everything described below works today and is in daily use. Config formats and CLI commands are stable enough to build on; breaking changes before 1.0 will be called out in CHANGELOG.md. Bug reports and rough edges are exactly what this beta is for — open an issue.

AIDA is a local scientific agent workbench: a simple, reliable desktop GUI (and CLI) for using AI agents in scientific work — conversation with local or cloud LLMs, correct use of domain MCP servers (pyIrena, bait_mcp, ...), correct display of rich tool results (especially PNG plots), reading and producing documents, and controlled access to your own data folders.

It is built for pyIrena and USAXS-instrument users and is deliberately not a general-purpose AI platform — see PLAN.md §1 for the rationale.

What it does

  • Chat with any model you can reach — Ollama / LM Studio / any OpenAI-compatible endpoint, OpenAI itself, Claude direct, or Claude through the ANL Argo proxy. Named profiles, switchable mid-conversation.
  • Use MCP servers properly — a PNG a tool returns is decoded and shown as an image, not flattened to text. Servers are grouped so a small local model isn't drowned in 100+ tool schemas.
  • Work in your folders — named workspaces bundle source folders, a target folder, a provider profile, an MCP group, and skills. The agent reads, writes, searches, and (optionally) runs scripts there under a safety model you configure.
  • Produce documents — Markdown in Obsidian layout (images in a sidecar folder, linked relatively) or DOCX, written into your target folder.
  • Search your own documentation — optional local RAG over folders you choose, with local or cloud embeddings.
  • Keep the documents you attach — an attached paper is copied into the conversation's own folder with the text that was extracted from it, and deleted again with the conversation. Ask about a figure and the agent fetches that one by label rather than being handed every image in the file. Optional Mistral OCR makes those labels reliable on multi-column journal PDFs — off by default, per workspace, and it asks before a document leaves your machine.
  • Keep conversations sorted — label them by person on a shared beamline machine, or by project on a laptop, and filter the list by it. Labels are organization, not security.
  • Stay out of black boxes — token counts and cost estimates per session, a tool-call log, a raw MCP result inspector, and aida doctor.

Install

From PyPI (recommended):

pip install "aida-workbench[gui,docs]"
aida doctor
aida-gui

The PyPI distribution name is aida-workbench; the import package and the console scripts are aida / aida-gui. Extras: gui (PySide6 desktop app), docs (PDF/DOCX/XLSX/PPTX reading, image handling), ocr (the optional Mistral OCR backend for figure extraction).

Already using pyIrena? Install both — in either order, in one environment or two — and wire up its MCP tools with a single command:

pip install "aida-workbench[gui,docs]" "pyirena[all]"
aida mcp add-pyirena

See docs/pyirena.md for the compatibility details and the GUI equivalent.

From a git checkout, for development:

git clone https://github.com/jilavsky/aida.git
cd aida
conda env create -f environment.yml   # or: pip install -e ".[dev,gui,docs]"
conda activate aida
aida doctor

First run

  1. aida doctor — confirms Python, config files, keychain, and folders.
  2. Launch aida-gui. On a fresh install it offers to set up a provider profile and a first workspace; you can also do both from the toolbar (Providers…, Workspaces…) or from the CLI (aida workspace new).
  3. Pick a workspace and profile in the toolbar and start typing.

docs/installation.mddocs/providers-and-secrets.mddocs/workspaces.md is the full path from nothing to a working session.

Documentation

Task-oriented setup and configuration guides — providers, workspaces, the safety model, MCP servers, scripting, RAG, a GUI tour — live in docs/. Fully-commented example config files are in examples/config/.

Status and roadmap

Phases 1–10 of PLAN.md are implemented: config and diagnostics, the provider layer and agent loop, MCP with typed artifacts, persistence and workspaces, the PySide6 GUI, documents and the safety model, MCP management UI, RAG, coding/scripting, and headless automation — aida run, stored workflows, and the in-app scheduler (see docs/workflows.md). Distribution (real PyPI/conda release automation) is what remains open. Completed per-phase checklists live in planning/; what is still open is at the top of PLAN.md.

Released and unreleased changes, version by version, are in CHANGELOG.md.

Requirements

Python >= 3.11. Tested on macOS, Windows, and Linux.

License

MIT — see LICENSE.

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