Grounded Ask

Upload docs, ask one question, read the answer plus the passages it used.

Domain language: CONTEXT.md · product ADR: docs/adr/0001-separate-app-tenant-profiles.md · API Sources: tamasino-ai-api ADR-0023

Prerequisites

1. tamasino-ai-api running
2. A tenant API key with upload scopes and threads:run:

cd ../tamasino-ai-api
uv run python -m src.cli.provision_tenant --slug acme --domain fire \
  --scopes files:write,domains:read,domains:write,points:read,points:write,retrieval:read,threads:run

How to use (local)

1. Open the app (usually http://localhost:8502).
2. Connect — paste an API key that includes files:write, domains:read, domains:write, and threads:run (Hybrid Console’s key is fine if it has those).
3. Add documents — create or pick a topic (domain), upload CSV / Excel / Word, wait for “chunks indexed”.
4. Ask — type a question → read the answer and Passages used.

Each ask is single-turn (no chat history). Questions search the whole tenant corpus.

Setup

cd tamasino-ai-grounded-ask
cp .env.example .env
uv sync
uv run streamlit run app.py

Connections are stored locally in data/tenant_profiles.json (gitignored).