DEDUPED Hot AI repos, turned into use cases Get 5 a day

What you can do with Forest

FOREST is an open-source research agent framework that takes a research question through literature review, hypotheses, real experiments, analysis, and a full manuscript, keeping the work in an editable research graph.

Trended earlier

mikamikasuki/forest on GitHub

Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk.

What do you want to do?

4 use cases

  • Run a research project from question to draft paper

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

    View prompt
    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.

  • Run a research project from the terminal without the Web build

    Use the FOREST CLI and API service to create and monitor a research project on a server or in scripts.

    View prompt
    In the FOREST repository at <repo path>, run the headless install, start the service with a data directory of <data dir>, and initialize a project with the goal <research goal>. Report the output of the status command. Verify that the project name in the status output matches the name you passed to init.

  • Clone a public GitHub repo and inspect its run diagnostics

    Bring a public GitHub codebase into a FOREST project and check the source commit and run diagnostics.

    View prompt
    Using the FOREST CLI in <repo path>, clone the public repository <repository URL> into the selected project and wait for it to finish. Then run the inspect and diagnostics commands on the returned run ID and report the source commit. Verify that the commit reported by inspect matches the commit you expected from the repository.

  • Verify the exact CSV bytes behind a paired statistics run

    Retrieve the retained input file and provenance record for a paired statistics analysis in FOREST.

    View prompt
    Using the FOREST API on <base URL>, fetch run <run ID> for project <project ID>, download its retained paired-input.csv, and compute the SHA-256 of the downloaded bytes. Report whether it matches the input_provenance hash in the run record. Verify that the downloaded path is runs/<run ID>/paired-input.csv.

How to use Forest

  1. Check you have what it needs: Python 3.11 or newer; Node.js 22 or newer for the Web workspace; Git installed on the worker machine.
  2. Open mikamikasuki/forest on GitHub and read the README and license.
  3. Clone the repository with git clone https://github.com/mikamikasuki/FOREST.git and enter it with cd FOREST.
  4. Install dependencies with python3.11 scripts/install.py.
  5. Start FOREST with .venv/bin/forest serve.
  6. 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.

These steps come from our top use case, Run a research project from question to draft paper, which also has a copy-paste agent prompt.

Forest alternatives · Best AI repos for Research

About this repo

  • Who it is forResearchers and scientific teams with a question, a compute setup, and a model provider who want an agent to run an evidence-tracked project end to end.
  • Why it is hot
  • LanguagePython
  • Sourcegithub.com/mikamikasuki/forest · Back to Hot repos

Requirements

  • 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
Maintain Forest? Add the Featured on Deduped badge

Paste this into your README:

[![Featured on Deduped](https://dedupedai.com/badge/mikamikasuki-forest.svg)](https://dedupedai.com/use-cases/mikamikasuki-forest/?ref=badge)

More badge styles and HTML

Questions about Forest

What is Forest?

FOREST is an open-source research agent framework that takes a research question through literature review, hypotheses, real experiments, analysis, and a full manuscript, keeping the work in an editable research graph. It is an open-source project on GitHub: https://github.com/mikamikasuki/forest.

Who is Forest for?

Researchers and scientific teams with a question, a compute setup, and a model provider who want an agent to run an evidence-tracked project end to end.

What can I do with Forest?

4 use cases so far, for example: Run a research project from question to draft paper; Run a research project from the terminal without the Web build; Clone a public GitHub repo and inspect its run diagnostics. Each has steps and a copy-paste agent prompt.

What do I need to run Forest?

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.

What are alternatives to Forest?

Other hot AI repos in Research: Scientific Agent Skills, Speaker Mem R1, DSH Council, Evo Bot, AI Engineering Course.

Is Forest safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.