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How to run a research project from question to draft paper with Forest

Start a FOREST project in the browser and let it move from research goal to experiments and manuscript.

  • Top pick
  • Research
  • Intermediate
  • 1 hour
  • From the README
  • Any agent

Credentials. Model provider credentials must be kept outside the repository and entered only in the local Settings configuration.

Who it is forA researcher with an early question who wants a guided, visual workspace for planning and running experiments with a set budget.

The problemKeeping ideas, experiments, results, and paper sections connected across weeks of work is hard in a long chat history.

The outcomeA project with a research goal, a budget, an editable research graph, and saved runs, logs, metrics, and artifacts that you can inspect and redirect.

What you need first

  • Python 3.11 or newer
  • Node.js 22 or newer for the Web workspace
  • Git installed on the worker machine
  • A model provider configured in Settings or through the API
  • An explicit spending budget and execution limits set before unattended runs
  • tectonic or pdflatex if you want PDF compilation

Steps

  1. Clone the repository with git clone https://github.com/mikamikasuki/FOREST.git and enter it with cd FOREST.
  2. Install dependencies with python3.11 scripts/install.py.
  3. Start FOREST with .venv/bin/forest serve.
  4. Open http://127.0.0.1:8000/, configure a model provider in Settings, and create a project with a research goal and an explicit spending budget.
  5. Choose a research mode (Manual, Assisted, or Auto) and review the research graph before letting tasks execute.

Prompt for your agent

Using the FOREST repository at <repo path>, install the Web workspace and start it with the project's serve command. Create a project with the research goal <research goal> and a spending budget of <budget>, then report the project ID and the first graph nodes that were created. Verify that the budget and goal appear in the project settings before any task runs.

Caveat. Local execution runs generated code with the worker account's permissions, and a separate working directory does not isolate it at the operating-system level.

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