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How to run the offline research sample and open its workbench with Finathink

Start the local app on bundled fixtures and inspect the staged research workbench without any external services.

  • Top pick
  • Money
  • Intermediate
  • 30 minutes
  • From the README
  • Any agent

Who it is forA new user or developer who wants to see how a full research run is recorded before using their own data.

The problemResearch tools often hide how a result was produced, so it is hard to trust or reproduce a backtest or a decision.

The outcomeA running local app serving the /workbench page, showing staged analyst, research, quant, risk and paper decision records from the sample fixtures.

What you need first

  • Python 3.11 or later
  • A local copy of the repo (inferred: git clone https://github.com/ceyyy427/finathink.git)
  • No broker, live trading account or real vendor credentials are needed for the offline sample run

Steps

  1. Run python3 -m venv .venv
  2. Run source .venv/bin/activate
  3. Run python3 -m pip install -e '.[dev]'
  4. Run PYTHONPATH=src python3 -m pytest -q to confirm the test suite passes
  5. Run python3 scripts/run_local_app.py --sample --port 8765
  6. Open the /workbench page on port 8765 and review the stages, checkpoints and manifest fingerprints

Prompt for your agent

In the finathink repo, set up the environment as described in its Quick Start, then run the local app with --sample on port 8765. Report the /workbench stage list, each stage status, and the manifest fingerprint shown. Verify that the sample run reports the stages from the research flow without requiring any external credentials.

Caveat. The README marks the offline modules as OFFLINE_PASS, but real vendors, models, browsers and production deployment are EXTERNAL_UNVERIFIED and not covered by this sample.

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