Company brain: company Q&A

Runs the company brain cookbook in examples/cookbooks/company_brain/company_qa/. It remembers a SQL database, a ticket export and a docs folder in the cognee dataset company_qa, extracts them with one graph model so the same person, team or project becomes one node, then answers a question across them. Setup, the scripts and what each one does are in the cookbook's README.md.

Run every command from the repo root.

Steps

1. Work out the sources. Ask the user for the ones they want: a database URL (and tables), one or more ticket export files (JSON or CSV), a docs folder. If they have none, or want to see it work first, pass no sources: the run then uses the sample company (the [setup] line says so). Tell the user the answer comes from sample data.
2. Run uv run python examples/cookbooks/company_brain/company_qa/company_qa.py --check with the sources (--database URL [--tables a,b] --tickets FILE [FILE ...] --docs FOLDER), or none for the sample.
   • Exit 0: go to step 3.
   • Exit 2: each [setup] MISSING: line names one fix. Don't create credentials yourself. Tell the user which line to fix, using the README's "What it needs" table, and stop.
3. Run the same command without --check, adding the user's question as --ask "...". On the sample with no --ask, it asks a question that needs all three sample sources.
4. The answer is everything after [ask] A:. Give it to the user. The [ingest] lines say which sources went in.
5. Later questions don't need the sources again: uv run python examples/cookbooks/company_brain/company_qa/scripts/ask.py "...".
6. If a script fails, company_qa.py exits 1 with a line naming what went wrong. Run that script from examples/cookbooks/company_brain/company_qa/scripts/ on its own to look closer.

Rules