mirror of
https://github.com/All-Hands-AI/OpenHands.git
synced 2026-04-29 03:00:45 -04:00
Compare commits
4 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
 Alex Bäuerle
|
240db83901 | ||
|
Alex Bäuerle
|
1896aa92b3 | ||
|
Alex Bäuerle
|
4b82b71d44 | ||
|
Alex Bäuerle
|
ce2677d794 |
@@ -1,5 +0,0 @@
|
||||
frontend/node_modules
|
||||
config.toml
|
||||
.envrc
|
||||
.env
|
||||
.git
|
||||
@@ -1 +0,0 @@
|
||||
*.ipynb linguist-vendored
|
||||
@@ -1,41 +0,0 @@
|
||||
---
|
||||
name: Bug Report
|
||||
about: Report a problem with OpenDevin
|
||||
title: ''
|
||||
labels: 'bug'
|
||||
assignees: ''
|
||||
|
||||
---
|
||||
<!-- You MUST fill out this template. We will close issues that don't include enough information to reproduce -->
|
||||
#### Describe the bug
|
||||
<!-- a short description of the problem -->
|
||||
|
||||
#### Setup and configuration
|
||||
**Current version**:
|
||||
<!-- run `git log -n 1` to see this -->
|
||||
```bash
|
||||
```
|
||||
|
||||
**My operating system**:
|
||||
|
||||
<!-- tell us everything about your environment -->
|
||||
**My environment vars and other configuration** (be sure to redact API keys):
|
||||
```bash
|
||||
```
|
||||
|
||||
**My model and agent** (you can see these settings in the UI):
|
||||
* Model:
|
||||
* Agent:
|
||||
|
||||
**Commands I ran to install and run OpenDevin**:
|
||||
```
|
||||
```
|
||||
|
||||
**Steps to Reproduce**:
|
||||
1.
|
||||
2.
|
||||
3.
|
||||
|
||||
**Logs, error messages, and screenshots**:
|
||||
|
||||
#### Additional Context
|
||||
@@ -1,18 +0,0 @@
|
||||
---
|
||||
name: Feature Request
|
||||
about: Suggest an idea for OpenDevin features
|
||||
title: ''
|
||||
labels: 'enhancement'
|
||||
assignees: ''
|
||||
|
||||
---
|
||||
|
||||
**What problem or use case are you trying to solve?**
|
||||
|
||||
**Describe the UX of the solution you'd like**
|
||||
|
||||
**Do you have thoughts on the technical implementation?**
|
||||
|
||||
**Describe alternatives you've considered**
|
||||
|
||||
**Additional context**
|
||||
@@ -1,16 +0,0 @@
|
||||
---
|
||||
name: Question
|
||||
about: Use this template to ask a question regarding the project.
|
||||
title: ''
|
||||
labels: question
|
||||
assignees: ''
|
||||
|
||||
---
|
||||
|
||||
## Describe your question
|
||||
|
||||
<!--A clear and concise description of what you want to know.-->
|
||||
|
||||
## Additional context
|
||||
|
||||
<!--Add any other context about the question here, like what you've tried so far.-->
|
||||
@@ -1,18 +0,0 @@
|
||||
---
|
||||
name: Technical Proposal
|
||||
about: Propose a new architecture or technology
|
||||
title: ''
|
||||
labels: 'proposal'
|
||||
assignees: ''
|
||||
|
||||
---
|
||||
|
||||
**Summary**
|
||||
|
||||
**Motivation**
|
||||
|
||||
**Technical Design**
|
||||
|
||||
**Alternatives to Consider**
|
||||
|
||||
**Additional context**
|
||||
@@ -1,47 +0,0 @@
|
||||
name: Build & Run Tests
|
||||
|
||||
on: [push, pull_request]
|
||||
|
||||
jobs:
|
||||
on-macos:
|
||||
runs-on: macos-latest
|
||||
strategy:
|
||||
matrix:
|
||||
python-version: ["3.11", "3.12"]
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
uses: actions/setup-python@v2
|
||||
with:
|
||||
python-version: ${{ matrix.python-version }}
|
||||
- name: Install & Start Docker
|
||||
run: |
|
||||
brew install colima docker
|
||||
colima start
|
||||
- name: Install and configure Poetry
|
||||
uses: snok/install-poetry@v1
|
||||
with:
|
||||
version: latest
|
||||
- name: Build Environment
|
||||
run: make build
|
||||
- name: Run Tests
|
||||
run: poetry run pytest ./tests
|
||||
on-linux:
|
||||
runs-on: ubuntu-latest
|
||||
strategy:
|
||||
matrix:
|
||||
python-version: ["3.11", "3.12"]
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
uses: actions/setup-python@v2
|
||||
with:
|
||||
python-version: ${{ matrix.python-version }}
|
||||
- name: Install Poetry
|
||||
run: curl -sSL https://install.python-poetry.org | python3 -
|
||||
- name: Build Environment
|
||||
run: make build
|
||||
- name: Run Tests
|
||||
run: poetry run pytest ./tests
|
||||
@@ -1,109 +0,0 @@
|
||||
name: Use OpenDevin to Resolve GitHub Issue
|
||||
|
||||
on:
|
||||
issues:
|
||||
types: [labeled]
|
||||
|
||||
permissions:
|
||||
contents: write
|
||||
pull-requests: write
|
||||
issues: write
|
||||
|
||||
jobs:
|
||||
open-devin:
|
||||
if: github.event.label.name == 'dogfood-this'
|
||||
runs-on: ubuntu-latest
|
||||
container:
|
||||
image: ghcr.io/opendevin/opendevin
|
||||
volumes:
|
||||
- /var/run/docker.sock:/var/run/docker.sock
|
||||
|
||||
steps:
|
||||
- name: install git, github cli
|
||||
run: apt-get install -y git gh
|
||||
|
||||
- name: Checkout Repository
|
||||
uses: actions/checkout@v4
|
||||
|
||||
- name: Write Task File
|
||||
env:
|
||||
ISSUE_TITLE: ${{ github.event.issue.title }}
|
||||
ISSUE_BODY: ${{ github.event.issue.body }}
|
||||
run: |
|
||||
echo "TITLE:" > task.txt
|
||||
echo "${ISSUE_TITLE}" >> task.txt
|
||||
echo "" >> task.txt
|
||||
echo "BODY:" >> task.txt
|
||||
echo "${ISSUE_BODY}" >> task.txt
|
||||
|
||||
- name: Run OpenDevin
|
||||
env:
|
||||
ISSUE_TITLE: ${{ github.event.issue.title }}
|
||||
ISSUE_BODY: ${{ github.event.issue.body }}
|
||||
LLM_API_KEY: ${{ secrets.OPENAI_API_KEY }}
|
||||
SANDBOX_TYPE: exec
|
||||
run: |
|
||||
python ./opendevin/main.py -d "./" -i 50 -f task.txt -d $GITHUB_WORKSPACE
|
||||
rm task.txt
|
||||
|
||||
- name: Setup Git, Create Branch, and Commit Changes
|
||||
run: |
|
||||
# Setup Git configuration
|
||||
git config --global --add safe.directory $PWD
|
||||
git config --global user.name 'OpenDevin'
|
||||
git config --global user.email 'OpenDevin@users.noreply.github.com'
|
||||
|
||||
# Create a unique branch name with a timestamp
|
||||
BRANCH_NAME="fix/${{ github.event.issue.number }}-$(date +%Y%m%d%H%M%S)"
|
||||
|
||||
# Checkout new branch
|
||||
git checkout -b $BRANCH_NAME
|
||||
|
||||
# Add all changes to staging, except task.txt
|
||||
git add --all -- ':!task.txt'
|
||||
|
||||
# Commit the changes, if any
|
||||
git commit -m "OpenDevin: Resolve Issue #${{ github.event.issue.number }}"
|
||||
if [ $? -ne 0 ]; then
|
||||
echo "No changes to commit."
|
||||
exit 0
|
||||
fi
|
||||
|
||||
# Push changes
|
||||
git push --set-upstream origin $BRANCH_NAME
|
||||
|
||||
- name: Fetch Default Branch
|
||||
env:
|
||||
GH_TOKEN: ${{ github.token }}
|
||||
run: |
|
||||
# Fetch the default branch using gh cli
|
||||
DEFAULT_BRANCH=$(gh repo view --json defaultBranchRef --jq .defaultBranchRef.name)
|
||||
echo "Default branch is $DEFAULT_BRANCH"
|
||||
echo "DEFAULT_BRANCH=$DEFAULT_BRANCH" >> $GITHUB_ENV
|
||||
|
||||
- name: Generate PR
|
||||
env:
|
||||
GH_TOKEN: ${{ github.token }}
|
||||
run: |
|
||||
# Create PR and capture URL
|
||||
PR_URL=$(gh pr create \
|
||||
--title "OpenDevin: Resolve Issue #2" \
|
||||
--body "This PR was generated by OpenDevin to resolve issue #2" \
|
||||
--repo "foragerr/OpenDevin" \
|
||||
--head "${{ github.head_ref }}" \
|
||||
--base "${{ env.DEFAULT_BRANCH }}" \
|
||||
| grep -o 'https://github.com/[^ ]*')
|
||||
|
||||
# Extract PR number from URL
|
||||
PR_NUMBER=$(echo "$PR_URL" | grep -o '[0-9]\+$')
|
||||
|
||||
# Set environment vars
|
||||
echo "PR_URL=$PR_URL" >> $GITHUB_ENV
|
||||
echo "PR_NUMBER=$PR_NUMBER" >> $GITHUB_ENV
|
||||
|
||||
- name: Post Comment
|
||||
env:
|
||||
GH_TOKEN: ${{ github.token }}
|
||||
run: |
|
||||
gh issue comment ${{ github.event.issue.number }} \
|
||||
-b "OpenDevin raised [PR #${{ env.PR_NUMBER }}](${{ env.PR_URL }}) to resolve this issue."
|
||||
@@ -1,35 +0,0 @@
|
||||
name: Publish Docker Image
|
||||
|
||||
on:
|
||||
push:
|
||||
workflow_dispatch:
|
||||
inputs:
|
||||
reason:
|
||||
description: 'Reason for manual trigger'
|
||||
required: true
|
||||
default: ''
|
||||
|
||||
jobs:
|
||||
ghcr_build_and_push:
|
||||
runs-on: ubuntu-latest
|
||||
if: github.event_name == 'push' || github.event.inputs.reason != ''
|
||||
strategy:
|
||||
matrix:
|
||||
image: ["app", "evaluation", "sandbox"]
|
||||
|
||||
steps:
|
||||
- name: checkout
|
||||
uses: actions/checkout@v4
|
||||
|
||||
- name: Set up QEMU
|
||||
uses: docker/setup-qemu-action@v3
|
||||
|
||||
- name: Set up Docker Buildx
|
||||
id: buildx
|
||||
uses: docker/setup-buildx-action@v3
|
||||
|
||||
- name: Log-in to ghcr.io
|
||||
run: echo "${{ secrets.GITHUB_TOKEN }}" | docker login ghcr.io -u ${{ github.actor }} --password-stdin
|
||||
|
||||
- name: Build and push ${{ matrix.image }}
|
||||
run: ./containers/build.sh ${{ matrix.image }} --push
|
||||
@@ -1,38 +0,0 @@
|
||||
name: Lint
|
||||
|
||||
on: [push, pull_request]
|
||||
|
||||
jobs:
|
||||
lint-frontend:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Install Node.js 20
|
||||
uses: actions/setup-node@v4
|
||||
with:
|
||||
node-version: 20
|
||||
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
cd frontend
|
||||
npm install --frozen-lockfile
|
||||
|
||||
- name: Lint
|
||||
run: |
|
||||
cd frontend
|
||||
npm run lint
|
||||
|
||||
lint-python:
|
||||
name: Lint python
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Set up python
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: 3.11
|
||||
- name: Install pre-commit
|
||||
run: pip install pre-commit==3.7.0
|
||||
- name: Run pre-commit hooks
|
||||
run: pre-commit run --files opendevin/**/* agenthub/**/* --show-diff-on-failure --config ./dev_config/python/.pre-commit-config.yaml
|
||||
@@ -1,20 +0,0 @@
|
||||
name: Run Tests
|
||||
|
||||
on: [push]
|
||||
|
||||
jobs:
|
||||
test:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v2
|
||||
with:
|
||||
python-version: '3.11'
|
||||
- name: Set up environment
|
||||
run: |
|
||||
curl -sSL https://install.python-poetry.org | python3 -
|
||||
poetry install --without evaluation
|
||||
- name: Run tests
|
||||
run: |
|
||||
poetry run pytest ./tests
|
||||
@@ -1,29 +0,0 @@
|
||||
name: 'Close stale issues'
|
||||
on:
|
||||
schedule:
|
||||
- cron: '30 1 * * *'
|
||||
|
||||
jobs:
|
||||
stale:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/stale@v9
|
||||
with:
|
||||
# Aggressively close issues that have been explicitly labeled `age-out`
|
||||
any-of-labels: age-out
|
||||
stale-issue-message: 'This issue is stale because it has been open for 7 days with no activity. Remove stale label or comment or this will be closed in 1 day.'
|
||||
close-issue-message: 'This issue was closed because it has been stalled for over 7 days with no activity.'
|
||||
stale-pr-message: 'This PR is stale because it has been open for 7 days with no activity. Remove stale label or comment or this will be closed in 1 days.'
|
||||
close-pr-message: 'This PR was closed because it has been stalled for over 7 days with no activity.'
|
||||
days-before-stale: 7
|
||||
days-before-close: 1
|
||||
|
||||
- uses: actions/stale@v9
|
||||
with:
|
||||
# Be more lenient with other issues
|
||||
stale-issue-message: 'This issue is stale because it has been open for 30 days with no activity. Remove stale label or comment or this will be closed in 7 days.'
|
||||
close-issue-message: 'This issue was closed because it has been stalled for over 30 days with no activity.'
|
||||
stale-pr-message: 'This PR is stale because it has been open for 30 days with no activity. Remove stale label or comment or this will be closed in 7 days.'
|
||||
close-pr-message: 'This PR was closed because it has been stalled for over 30 days with no activity.'
|
||||
days-before-stale: 30
|
||||
days-before-close: 7
|
||||
-204
@@ -1,204 +0,0 @@
|
||||
# Byte-compiled / optimized / DLL files
|
||||
__pycache__/
|
||||
*.py[cod]
|
||||
*$py.class
|
||||
|
||||
# C extensions
|
||||
*.so
|
||||
|
||||
# Distribution / packaging
|
||||
.Python
|
||||
build/
|
||||
develop-eggs/
|
||||
dist/
|
||||
downloads/
|
||||
eggs/
|
||||
.eggs/
|
||||
./lib/
|
||||
lib64/
|
||||
parts/
|
||||
sdist/
|
||||
var/
|
||||
wheels/
|
||||
share/python-wheels/
|
||||
*.egg-info/
|
||||
.installed.cfg
|
||||
*.egg
|
||||
MANIFEST
|
||||
requirements.txt
|
||||
|
||||
# PyInstaller
|
||||
# Usually these files are written by a python script from a template
|
||||
# before PyInstaller builds the exe, so as to inject date/other infos into it.
|
||||
*.manifest
|
||||
*.spec
|
||||
|
||||
# Installer logs
|
||||
pip-log.txt
|
||||
pip-delete-this-directory.txt
|
||||
|
||||
# Unit test / coverage reports
|
||||
htmlcov/
|
||||
.tox/
|
||||
.nox/
|
||||
.coverage
|
||||
.coverage.*
|
||||
.cache
|
||||
nosetests.xml
|
||||
coverage.xml
|
||||
*.cover
|
||||
*.py,cover
|
||||
.hypothesis/
|
||||
.pytest_cache/
|
||||
cover/
|
||||
|
||||
# Translations
|
||||
*.mo
|
||||
*.pot
|
||||
|
||||
# Django stuff:
|
||||
*.log
|
||||
local_settings.py
|
||||
db.sqlite3
|
||||
db.sqlite3-journal
|
||||
|
||||
# Flask stuff:
|
||||
instance/
|
||||
.webassets-cache
|
||||
|
||||
# Scrapy stuff:
|
||||
.scrapy
|
||||
|
||||
# Sphinx documentation
|
||||
docs/_build/
|
||||
|
||||
# PyBuilder
|
||||
.pybuilder/
|
||||
target/
|
||||
|
||||
# Jupyter Notebook
|
||||
.ipynb_checkpoints
|
||||
|
||||
# IPython
|
||||
profile_default/
|
||||
ipython_config.py
|
||||
|
||||
# pyenv
|
||||
# For a library or package, you might want to ignore these files since the code is
|
||||
# intended to run in multiple environments; otherwise, check them in:
|
||||
.python-version
|
||||
|
||||
# pipenv
|
||||
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
|
||||
# However, in case of collaboration, if having platform-specific dependencies or dependencies
|
||||
# having no cross-platform support, pipenv may install dependencies that don't work, or not
|
||||
# install all needed dependencies.
|
||||
#Pipfile.lock
|
||||
|
||||
# poetry
|
||||
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
|
||||
# This is especially recommended for binary packages to ensure reproducibility, and is more
|
||||
# commonly ignored for libraries.
|
||||
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
|
||||
# poetry.lock
|
||||
|
||||
# pdm
|
||||
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
|
||||
#pdm.lock
|
||||
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
|
||||
# in version control.
|
||||
# https://pdm.fming.dev/#use-with-ide
|
||||
.pdm.toml
|
||||
|
||||
# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
|
||||
__pypackages__/
|
||||
|
||||
# Celery stuff
|
||||
celerybeat-schedule
|
||||
celerybeat.pid
|
||||
|
||||
# SageMath parsed files
|
||||
*.sage.py
|
||||
|
||||
# Environments
|
||||
.env
|
||||
.venv
|
||||
env/
|
||||
venv/
|
||||
ENV/
|
||||
env.bak/
|
||||
venv.bak/
|
||||
*venv/
|
||||
|
||||
# Spyder project settings
|
||||
.spyderproject
|
||||
.spyproject
|
||||
|
||||
# Rope project settings
|
||||
.ropeproject
|
||||
|
||||
# mkdocs documentation
|
||||
/site
|
||||
|
||||
# mypy
|
||||
.mypy_cache/
|
||||
.dmypy.json
|
||||
dmypy.json
|
||||
|
||||
# Pyre type checker
|
||||
.pyre/
|
||||
|
||||
# pytype static type analyzer
|
||||
.pytype/
|
||||
|
||||
# Cython debug symbols
|
||||
cython_debug/
|
||||
|
||||
# PyCharm
|
||||
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
|
||||
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
|
||||
# and can be added to the global gitignore or merged into this file. For a more nuclear
|
||||
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
|
||||
.idea/
|
||||
.vscode/
|
||||
|
||||
# evaluation
|
||||
evaluation/SWE-bench/data
|
||||
|
||||
# frontend
|
||||
|
||||
# dependencies
|
||||
frontend/node_modules
|
||||
frontend/.pnp
|
||||
frontend/bun.lockb
|
||||
frontend/yarn.lock
|
||||
.pnp.js
|
||||
|
||||
# testing
|
||||
frontend/coverage
|
||||
|
||||
# production
|
||||
frontend/build
|
||||
frontend/dist
|
||||
|
||||
# misc
|
||||
.DS_Store
|
||||
.env.local
|
||||
.env.development.local
|
||||
.env.test.local
|
||||
.env.production.local
|
||||
|
||||
npm-debug.log*
|
||||
yarn-debug.log*
|
||||
yarn-error.log*
|
||||
|
||||
logs
|
||||
|
||||
# agent
|
||||
.envrc
|
||||
/workspace
|
||||
/debug
|
||||
cache
|
||||
|
||||
# configuration
|
||||
config.toml
|
||||
@@ -1,89 +0,0 @@
|
||||
# Contributing
|
||||
|
||||
Thanks for your interest in contributing to OpenDevin! We welcome and appreciate contributions.
|
||||
To report bugs, create a [GitHub issue](https://github.com/OpenDevin/OpenDevin/issues/new/choose).
|
||||
|
||||
## Contribution Guide
|
||||
### 1. Fork the Official Repository
|
||||
|
||||
Fork [OpenDevin repository](https://github.com/OpenDevin/OpenDevin) into your own account.
|
||||
Clone your own forked repository into your local environment.
|
||||
|
||||
```shell
|
||||
git clone git@github.com:<YOUR-USERNAME>/OpenDevin.git
|
||||
```
|
||||
|
||||
### 2. Configure Git
|
||||
|
||||
Set the official repository as your [upstream](https://www.atlassian.com/git/tutorials/git-forks-and-upstreams) to synchronize with the latest update in the official repository.
|
||||
Add the original repository as upstream
|
||||
|
||||
```shell
|
||||
cd OpenDevin
|
||||
git remote add upstream git@github.com:OpenDevin/OpenDevin.git
|
||||
```
|
||||
|
||||
Verify that the remote is set.
|
||||
```shell
|
||||
git remote -v
|
||||
```
|
||||
You should see both `origin` and `upstream` in the output.
|
||||
|
||||
### 3. Synchronize with Official Repository
|
||||
Synchronize latest commit with official repository before coding.
|
||||
|
||||
```shell
|
||||
git fetch upstream
|
||||
git checkout main
|
||||
git merge upstream/main
|
||||
git push origin main
|
||||
```
|
||||
|
||||
### 4. Create a New Branch And Open a Pull Request
|
||||
After you finish implementation, open forked repository. The source branch is your new branch, and the target branch is `OpenDevin/OpenDevin` `main` branch. Then PR should appears in [OpenDevin PRs](https://github.com/OpenDevin/OpenDevin/pulls).
|
||||
|
||||
Then OpenDevin team will review your code.
|
||||
|
||||
## PR Rules
|
||||
|
||||
### 1. Pull Request title
|
||||
|
||||
As described in [here](https://github.com/commitizen/conventional-commit-types/blob/master/index.json), a valid PR title should begin with one of the following prefixes:
|
||||
|
||||
- `feat`: A new feature
|
||||
- `fix`: A bug fix
|
||||
- `doc`: Documentation only changes
|
||||
- `refactor`: A code change that neither fixes a bug nor adds a feature
|
||||
- `style`: A refactoring that improves code style
|
||||
- `perf`: A code change that improves performance
|
||||
- `test`: Adding missing tests or correcting existing tests
|
||||
- `ci`: Changes to CI configuration files and scripts (example scopes: `.github`, `ci` (Buildkite))
|
||||
- `chore`: Other changes that don't modify src or test files
|
||||
- `revert`: Reverts a previous commit
|
||||
|
||||
For example, a PR title could be:
|
||||
- `refactor: modify package path`
|
||||
- `feat(frontend): xxxx`, where `(frontend)` means that this PR mainly focuses on the frontend component.
|
||||
|
||||
You may also check out previous PRs in the [PR list](https://github.com/OpenDevin/OpenDevin/pulls).
|
||||
|
||||
As described in [here](https://github.com/OpenDevin/OpenDevin/labels), we create several labels. Every PR should be tagged with the corresponding labels.
|
||||
|
||||
### 2. Pull Request description
|
||||
|
||||
- If your PR is small (such as a typo fix), you can go brief.
|
||||
- If it is large and you have changed a lot, it's better to write more details.
|
||||
|
||||
|
||||
## How to begin
|
||||
Please refer to the README in each module:
|
||||
- [frontend](./frontend/README.md)
|
||||
- [agenthub](./agenthub/README.md)
|
||||
- [evaluation](./evaluation/README.md)
|
||||
- [opendevin](./opendevin/README.md)
|
||||
- [server](./opendevin/server/README.md)
|
||||
- [mock server](./opendevin/mock/README.md)
|
||||
|
||||
## Tests
|
||||
TODO: make sure code pass the test before submit.
|
||||
|
||||
@@ -1,133 +0,0 @@
|
||||
|
||||
# Contributor Covenant Code of Conduct
|
||||
|
||||
## Our Pledge
|
||||
|
||||
We as members, contributors, and leaders pledge to make participation in our
|
||||
community a harassment-free experience for everyone, regardless of age, body
|
||||
size, visible or invisible disability, ethnicity, sex characteristics, gender
|
||||
identity and expression, level of experience, education, socio-economic status,
|
||||
nationality, personal appearance, race, caste, color, religion, or sexual
|
||||
identity and orientation.
|
||||
|
||||
We pledge to act and interact in ways that contribute to an open, welcoming,
|
||||
diverse, inclusive, and healthy community.
|
||||
|
||||
## Our Standards
|
||||
|
||||
Examples of behavior that contributes to a positive environment for our
|
||||
community include:
|
||||
|
||||
* Demonstrating empathy and kindness toward other people
|
||||
* Being respectful of differing opinions, viewpoints, and experiences
|
||||
* Giving and gracefully accepting constructive feedback
|
||||
* Accepting responsibility and apologizing to those affected by our mistakes,
|
||||
and learning from the experience
|
||||
* Focusing on what is best not just for us as individuals, but for the overall
|
||||
community
|
||||
|
||||
Examples of unacceptable behavior include:
|
||||
|
||||
* The use of sexualized language or imagery, and sexual attention or advances of
|
||||
any kind
|
||||
* Trolling, insulting or derogatory comments, and personal or political attacks
|
||||
* Public or private harassment
|
||||
* Publishing others' private information, such as a physical or email address,
|
||||
without their explicit permission
|
||||
* Other conduct which could reasonably be considered inappropriate in a
|
||||
professional setting
|
||||
|
||||
## Enforcement Responsibilities
|
||||
|
||||
Community leaders are responsible for clarifying and enforcing our standards of
|
||||
acceptable behavior and will take appropriate and fair corrective action in
|
||||
response to any behavior that they deem inappropriate, threatening, offensive,
|
||||
or harmful.
|
||||
|
||||
Community leaders have the right and responsibility to remove, edit, or reject
|
||||
comments, commits, code, wiki edits, issues, and other contributions that are
|
||||
not aligned to this Code of Conduct, and will communicate reasons for moderation
|
||||
decisions when appropriate.
|
||||
|
||||
## Scope
|
||||
|
||||
This Code of Conduct applies within all community spaces, and also applies when
|
||||
an individual is officially representing the community in public spaces.
|
||||
Examples of representing our community include using an official email address,
|
||||
posting via an official social media account, or acting as an appointed
|
||||
representative at an online or offline event.
|
||||
|
||||
## Enforcement
|
||||
|
||||
Instances of abusive, harassing, or otherwise unacceptable behavior may be
|
||||
reported to the community leaders responsible for enforcement at
|
||||
contact@rbren.io
|
||||
All complaints will be reviewed and investigated promptly and fairly.
|
||||
|
||||
All community leaders are obligated to respect the privacy and security of the
|
||||
reporter of any incident.
|
||||
|
||||
## Enforcement Guidelines
|
||||
|
||||
Community leaders will follow these Community Impact Guidelines in determining
|
||||
the consequences for any action they deem in violation of this Code of Conduct:
|
||||
|
||||
### 1. Correction
|
||||
|
||||
**Community Impact**: Use of inappropriate language or other behavior deemed
|
||||
unprofessional or unwelcome in the community.
|
||||
|
||||
**Consequence**: A private, written warning from community leaders, providing
|
||||
clarity around the nature of the violation and an explanation of why the
|
||||
behavior was inappropriate. A public apology may be requested.
|
||||
|
||||
### 2. Warning
|
||||
|
||||
**Community Impact**: A violation through a single incident or series of
|
||||
actions.
|
||||
|
||||
**Consequence**: A warning with consequences for continued behavior. No
|
||||
interaction with the people involved, including unsolicited interaction with
|
||||
those enforcing the Code of Conduct, for a specified period of time. This
|
||||
includes avoiding interactions in community spaces as well as external channels
|
||||
like social media. Violating these terms may lead to a temporary or permanent
|
||||
ban.
|
||||
|
||||
### 3. Temporary Ban
|
||||
|
||||
**Community Impact**: A serious violation of community standards, including
|
||||
sustained inappropriate behavior.
|
||||
|
||||
**Consequence**: A temporary ban from any sort of interaction or public
|
||||
communication with the community for a specified period of time. No public or
|
||||
private interaction with the people involved, including unsolicited interaction
|
||||
with those enforcing the Code of Conduct, is allowed during this period.
|
||||
Violating these terms may lead to a permanent ban.
|
||||
|
||||
### 4. Permanent Ban
|
||||
|
||||
**Community Impact**: Demonstrating a pattern of violation of community
|
||||
standards, including sustained inappropriate behavior, harassment of an
|
||||
individual, or aggression toward or disparagement of classes of individuals.
|
||||
|
||||
**Consequence**: A permanent ban from any sort of public interaction within the
|
||||
community.
|
||||
|
||||
## Attribution
|
||||
|
||||
This Code of Conduct is adapted from the [Contributor Covenant][homepage],
|
||||
version 2.1, available at
|
||||
[https://www.contributor-covenant.org/version/2/1/code_of_conduct.html][v2.1].
|
||||
|
||||
Community Impact Guidelines were inspired by
|
||||
[Mozilla's code of conduct enforcement ladder][Mozilla CoC].
|
||||
|
||||
For answers to common questions about this code of conduct, see the FAQ at
|
||||
[https://www.contributor-covenant.org/faq][FAQ]. Translations are available at
|
||||
[https://www.contributor-covenant.org/translations][translations].
|
||||
|
||||
[homepage]: https://www.contributor-covenant.org
|
||||
[v2.1]: https://www.contributor-covenant.org/version/2/1/code_of_conduct.html
|
||||
[Mozilla CoC]: https://github.com/mozilla/diversity
|
||||
[FAQ]: https://www.contributor-covenant.org/faq
|
||||
[translations]: https://www.contributor-covenant.org/translations
|
||||
@@ -1,66 +0,0 @@
|
||||
# Development Guide
|
||||
This guide is for people working on OpenDevin and editing the source code.
|
||||
|
||||
## Start the server for development
|
||||
|
||||
### 1. Requirements
|
||||
* Linux, Mac OS, or [WSL on Windows](https://learn.microsoft.com/en-us/windows/wsl/install)
|
||||
* [Docker](https://docs.docker.com/engine/install/)(For those on MacOS, make sure to allow the default Docker socket to be used from advanced settings!)
|
||||
* [Python](https://www.python.org/downloads/) >= 3.11
|
||||
* [NodeJS](https://nodejs.org/en/download/package-manager) >= 18.17.1
|
||||
* [Poetry](https://python-poetry.org/docs/#installing-with-the-official-installer) >= 1.8
|
||||
|
||||
Make sure you have all these dependencies installed before moving on to `make build`.
|
||||
|
||||
### 2. Build and Setup The Environment
|
||||
|
||||
- **Build the Project:** Begin by building the project, which includes setting up the environment and installing dependencies. This step ensures that OpenDevin is ready to run smoothly on your system.
|
||||
```bash
|
||||
make build
|
||||
```
|
||||
|
||||
### 3. Configuring the Language Model
|
||||
|
||||
OpenDevin supports a diverse array of Language Models (LMs) through the powerful [litellm](https://docs.litellm.ai) library. By default, we've chosen the mighty GPT-4 from OpenAI as our go-to model, but the world is your oyster! You can unleash the potential of Anthropic's suave Claude, the enigmatic Llama, or any other LM that piques your interest.
|
||||
|
||||
To configure the LM of your choice, follow these steps:
|
||||
|
||||
1. **Using the Makefile: The Effortless Approach**
|
||||
With a single command, you can have a smooth LM setup for your OpenDevin experience. Simply run:
|
||||
```bash
|
||||
make setup-config
|
||||
```
|
||||
This command will prompt you to enter the LLM API key and model name, ensuring that OpenDevin is tailored to your specific needs.
|
||||
|
||||
**Note on Alternative Models:**
|
||||
Some alternative models may prove more challenging to tame than others. Fear not, brave adventurer! We shall soon unveil LLM-specific documentation to guide you on your quest. And if you've already mastered the art of wielding a model other than OpenAI's GPT, we encourage you to [share your setup instructions with us](https://github.com/OpenDevin/OpenDevin/issues/417).
|
||||
|
||||
For a full list of the LM providers and models available, please consult the [litellm documentation](https://docs.litellm.ai/docs/providers).
|
||||
|
||||
There is also [documentation for running with local models using ollama](./docs/documentation/LOCAL_LLM_GUIDE.md).
|
||||
|
||||
### 4. Run the Application
|
||||
|
||||
- **Run the Application:** Once the setup is complete, launching OpenDevin is as simple as running a single command. This command starts both the backend and frontend servers seamlessly, allowing you to interact with OpenDevin without any hassle.
|
||||
```bash
|
||||
make run
|
||||
```
|
||||
|
||||
### 5. Individual Server Startup
|
||||
|
||||
- **Start the Backend Server:** If you prefer, you can start the backend server independently to focus on backend-related tasks or configurations.
|
||||
```bash
|
||||
make start-backend
|
||||
```
|
||||
|
||||
- **Start the Frontend Server:** Similarly, you can start the frontend server on its own to work on frontend-related components or interface enhancements.
|
||||
```bash
|
||||
make start-frontend
|
||||
```
|
||||
|
||||
### 6. Help
|
||||
|
||||
- **Get Some Help:** Need assistance or information on available targets and commands? The help command provides all the necessary guidance to ensure a smooth experience with OpenDevin.
|
||||
```bash
|
||||
make help
|
||||
```
|
||||
@@ -1,25 +0,0 @@
|
||||
The MIT License (MIT)
|
||||
=====================
|
||||
|
||||
Copyright © 2023
|
||||
|
||||
Permission is hereby granted, free of charge, to any person
|
||||
obtaining a copy of this software and associated documentation
|
||||
files (the “Software”), to deal in the Software without
|
||||
restriction, including without limitation the rights to use,
|
||||
copy, modify, merge, publish, distribute, sublicense, and/or sell
|
||||
copies of the Software, and to permit persons to whom the
|
||||
Software is furnished to do so, subject to the following
|
||||
conditions:
|
||||
|
||||
The above copyright notice and this permission notice shall be
|
||||
included in all copies or substantial portions of the Software.
|
||||
|
||||
THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND,
|
||||
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
|
||||
OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
|
||||
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
|
||||
HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
|
||||
WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
|
||||
FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
|
||||
OTHER DEALINGS IN THE SOFTWARE.
|
||||
@@ -1,190 +0,0 @@
|
||||
# Makefile for OpenDevin project
|
||||
|
||||
# Variables
|
||||
DOCKER_IMAGE = ghcr.io/opendevin/sandbox
|
||||
BACKEND_PORT = 3000
|
||||
BACKEND_HOST = "127.0.0.1:$(BACKEND_PORT)"
|
||||
FRONTEND_PORT = 3001
|
||||
DEFAULT_WORKSPACE_DIR = "./workspace"
|
||||
DEFAULT_MODEL = "gpt-3.5-turbo-1106"
|
||||
CONFIG_FILE = config.toml
|
||||
PRECOMMIT_CONFIG_PATH = "./dev_config/python/.pre-commit-config.yaml"
|
||||
|
||||
# ANSI color codes
|
||||
GREEN=\033[0;32m
|
||||
YELLOW=\033[0;33m
|
||||
RED=\033[0;31m
|
||||
BLUE=\033[0;34m
|
||||
RESET=\033[0m
|
||||
|
||||
# Build
|
||||
build:
|
||||
@echo "$(GREEN)Building project...$(RESET)"
|
||||
@$(MAKE) -s check-dependencies
|
||||
@$(MAKE) -s pull-docker-image
|
||||
@$(MAKE) -s install-python-dependencies
|
||||
@$(MAKE) -s install-frontend-dependencies
|
||||
@$(MAKE) -s install-precommit-hooks
|
||||
@$(MAKE) -s build-frontend
|
||||
@echo "$(GREEN)Build completed successfully.$(RESET)"
|
||||
|
||||
check-dependencies:
|
||||
@echo "$(YELLOW)Checking dependencies...$(RESET)"
|
||||
@$(MAKE) -s check-python
|
||||
@$(MAKE) -s check-npm
|
||||
@$(MAKE) -s check-docker
|
||||
@$(MAKE) -s check-poetry
|
||||
@echo "$(GREEN)Dependencies checked successfully.$(RESET)"
|
||||
|
||||
check-python:
|
||||
@echo "$(YELLOW)Checking Python installation...$(RESET)"
|
||||
@if command -v python3 > /dev/null; then \
|
||||
echo "$(BLUE)$(shell python3 --version) is already installed.$(RESET)"; \
|
||||
else \
|
||||
echo "$(RED)Python 3 is not installed. Please install Python 3 to continue.$(RESET)"; \
|
||||
exit 1; \
|
||||
fi
|
||||
|
||||
check-npm:
|
||||
@echo "$(YELLOW)Checking npm installation...$(RESET)"
|
||||
@if command -v npm > /dev/null; then \
|
||||
echo "$(BLUE)npm $(shell npm --version) is already installed.$(RESET)"; \
|
||||
else \
|
||||
echo "$(RED)npm is not installed. Please install Node.js to continue.$(RESET)"; \
|
||||
exit 1; \
|
||||
fi
|
||||
|
||||
check-docker:
|
||||
@echo "$(YELLOW)Checking Docker installation...$(RESET)"
|
||||
@if command -v docker > /dev/null; then \
|
||||
echo "$(BLUE)$(shell docker --version) is already installed.$(RESET)"; \
|
||||
else \
|
||||
echo "$(RED)Docker is not installed. Please install Docker to continue.$(RESET)"; \
|
||||
exit 1; \
|
||||
fi
|
||||
|
||||
check-poetry:
|
||||
@echo "$(YELLOW)Checking Poetry installation...$(RESET)"
|
||||
@if command -v poetry > /dev/null; then \
|
||||
echo "$(BLUE)$(shell poetry --version) is already installed.$(RESET)"; \
|
||||
else \
|
||||
echo "$(RED)Poetry is not installed. You can install poetry by running the following command, then adding Poetry to your PATH:"; \
|
||||
echo "$(RED) curl -sSL https://install.python-poetry.org | python3 -$(RESET)"; \
|
||||
echo "$(RED)More detail here: https://python-poetry.org/docs/#installing-with-the-official-installer$(RESET)"; \
|
||||
exit 1; \
|
||||
fi
|
||||
|
||||
pull-docker-image:
|
||||
@echo "$(YELLOW)Pulling Docker image...$(RESET)"
|
||||
@docker pull $(DOCKER_IMAGE)
|
||||
@echo "$(GREEN)Docker image pulled successfully.$(RESET)"
|
||||
|
||||
install-python-dependencies:
|
||||
@echo "$(GREEN)Installing Python dependencies...$(RESET)"
|
||||
@if [ "$(shell uname)" = "Darwin" ]; then \
|
||||
echo "$(BLUE)Installing `chroma-hnswlib`...$(RESET)"; \
|
||||
export HNSWLIB_NO_NATIVE=1; \
|
||||
poetry run pip install chroma-hnswlib; \
|
||||
fi
|
||||
@poetry install --without evaluation
|
||||
@echo "$(GREEN)Python dependencies installed successfully.$(RESET)"
|
||||
|
||||
install-frontend-dependencies:
|
||||
@echo "$(YELLOW)Setting up frontend environment...$(RESET)"
|
||||
@echo "$(YELLOW)Detect Node.js version...$(RESET)"
|
||||
@cd frontend && node ./scripts/detect-node-version.js
|
||||
@cd frontend && \
|
||||
echo "$(BLUE)Installing frontend dependencies with npm...$(RESET)" && \
|
||||
npm install && \
|
||||
echo "$(BLUE)Running make-i18n with npm...$(RESET)" && \
|
||||
npm run make-i18n
|
||||
@echo "$(GREEN)Frontend dependencies installed successfully.$(RESET)"
|
||||
|
||||
install-precommit-hooks:
|
||||
@echo "$(YELLOW)Installing pre-commit hooks...$(RESET)"
|
||||
@git config --unset-all core.hooksPath || true
|
||||
@poetry run pre-commit install --config $(PRECOMMIT_CONFIG_PATH)
|
||||
@echo "$(GREEN)Pre-commit hooks installed successfully.$(RESET)"
|
||||
|
||||
build-frontend:
|
||||
@echo "$(YELLOW)Building frontend...$(RESET)"
|
||||
@cd frontend && npm run build
|
||||
|
||||
# Start backend
|
||||
start-backend:
|
||||
@echo "$(YELLOW)Starting backend...$(RESET)"
|
||||
@poetry run uvicorn opendevin.server.listen:app --port $(BACKEND_PORT)
|
||||
|
||||
# Start frontend
|
||||
start-frontend:
|
||||
@echo "$(YELLOW)Starting frontend...$(RESET)"
|
||||
@cd frontend && BACKEND_HOST=$(BACKEND_HOST) FRONTEND_PORT=$(FRONTEND_PORT) npm run start
|
||||
|
||||
# Run the app
|
||||
run:
|
||||
@echo "$(YELLOW)Running the app...$(RESET)"
|
||||
@if [ "$(OS)" = "Windows_NT" ]; then \
|
||||
echo "$(RED)`make run` is not supported on Windows. Please run `make start-frontend` and `make start-backend` separately.$(RESET)"; \
|
||||
exit 1; \
|
||||
fi
|
||||
@mkdir -p logs
|
||||
@echo "$(YELLOW)Starting backend server...$(RESET)"
|
||||
@poetry run uvicorn opendevin.server.listen:app --port $(BACKEND_PORT) &
|
||||
@echo "$(YELLOW)Waiting for the backend to start...$(RESET)"
|
||||
@until nc -z localhost $(BACKEND_PORT); do sleep 0.1; done
|
||||
@echo "$(GREEN)Backend started successfully.$(RESET)"
|
||||
@cd frontend && echo "$(BLUE)Starting frontend with npm...$(RESET)" && npm run start -- --port $(FRONTEND_PORT)
|
||||
@echo "$(GREEN)Application started successfully.$(RESET)"
|
||||
|
||||
# Setup config.toml
|
||||
setup-config:
|
||||
@echo "$(YELLOW)Setting up config.toml...$(RESET)"
|
||||
@$(MAKE) setup-config-prompts
|
||||
@mv $(CONFIG_FILE).tmp $(CONFIG_FILE)
|
||||
@echo "$(GREEN)Config.toml setup completed.$(RESET)"
|
||||
|
||||
setup-config-prompts:
|
||||
@read -p "Enter your LLM Model name (see https://docs.litellm.ai/docs/providers for full list) [default: $(DEFAULT_MODEL)]: " llm_model; \
|
||||
llm_model=$${llm_model:-$(DEFAULT_MODEL)}; \
|
||||
echo "LLM_MODEL=\"$$llm_model\"" > $(CONFIG_FILE).tmp
|
||||
|
||||
@read -p "Enter your LLM API key: " llm_api_key; \
|
||||
echo "LLM_API_KEY=\"$$llm_api_key\"" >> $(CONFIG_FILE).tmp
|
||||
|
||||
@read -p "Enter your LLM Base URL [mostly used for local LLMs, leave blank if not needed - example: http://localhost:5001/v1/]: " llm_base_url; \
|
||||
if [[ ! -z "$$llm_base_url" ]]; then echo "LLM_BASE_URL=\"$$llm_base_url\"" >> $(CONFIG_FILE).tmp; fi
|
||||
|
||||
@echo "Enter your LLM Embedding Model\nChoices are openai, azureopenai, llama2 or leave blank to default to 'BAAI/bge-small-en-v1.5' via huggingface"; \
|
||||
read -p "> " llm_embedding_model; \
|
||||
echo "LLM_EMBEDDING_MODEL=\"$$llm_embedding_model\"" >> $(CONFIG_FILE).tmp; \
|
||||
if [ "$$llm_embedding_model" = "llama2" ]; then \
|
||||
read -p "Enter the local model URL (will overwrite LLM_BASE_URL): " llm_base_url; \
|
||||
echo "LLM_BASE_URL=\"$$llm_base_url\"" >> $(CONFIG_FILE).tmp; \
|
||||
elif [ "$$llm_embedding_model" = "azureopenai" ]; then \
|
||||
read -p "Enter the Azure endpoint URL (will overwrite LLM_BASE_URL): " llm_base_url; \
|
||||
echo "LLM_BASE_URL=\"$$llm_base_url\"" >> $(CONFIG_FILE).tmp; \
|
||||
read -p "Enter the Azure LLM Deployment Name: " llm_deployment_name; \
|
||||
echo "LLM_DEPLOYMENT_NAME=\"$$llm_deployment_name\"" >> $(CONFIG_FILE).tmp; \
|
||||
read -p "Enter the Azure API Version: " llm_api_version; \
|
||||
echo "LLM_API_VERSION=\"$$llm_api_version\"" >> $(CONFIG_FILE).tmp; \
|
||||
fi
|
||||
|
||||
@read -p "Enter your workspace directory [default: $(DEFAULT_WORKSPACE_DIR)]: " workspace_dir; \
|
||||
workspace_dir=$${workspace_dir:-$(DEFAULT_WORKSPACE_DIR)}; \
|
||||
echo "WORKSPACE_BASE=\"$$workspace_dir\"" >> $(CONFIG_FILE).tmp
|
||||
|
||||
# Help
|
||||
help:
|
||||
@echo "$(BLUE)Usage: make [target]$(RESET)"
|
||||
@echo "Targets:"
|
||||
@echo " $(GREEN)build$(RESET) - Build project, including environment setup and dependencies."
|
||||
@echo " $(GREEN)setup-config$(RESET) - Setup the configuration for OpenDevin by providing LLM API key,"
|
||||
@echo " LLM Model name, and workspace directory."
|
||||
@echo " $(GREEN)start-backend$(RESET) - Start the backend server for the OpenDevin project."
|
||||
@echo " $(GREEN)start-frontend$(RESET) - Start the frontend server for the OpenDevin project."
|
||||
@echo " $(GREEN)run$(RESET) - Run the OpenDevin application, starting both backend and frontend servers."
|
||||
@echo " Backend Log file will be stored in the 'logs' directory."
|
||||
@echo " $(GREEN)help$(RESET) - Display this help message, providing information on available targets."
|
||||
|
||||
# Phony targets
|
||||
.PHONY: build check-dependencies check-python check-npm check-docker check-poetry pull-docker-image install-python-dependencies install-frontend-dependencies install-precommit-hooks start-backend start-frontend run setup-config setup-config-prompts help
|
||||
@@ -1,247 +0,0 @@
|
||||
<a name="readme-top"></a>
|
||||
<!--
|
||||
*** Thanks for checking out the Best-README-Template. If you have a suggestion
|
||||
*** that would make this better, please fork the repo and create a pull request
|
||||
*** or simply open an issue with the tag "enhancement".
|
||||
*** Don't forget to give the project a star!
|
||||
*** Thanks again! Now go create something AMAZING! :D
|
||||
-->
|
||||
|
||||
|
||||
|
||||
<!-- PROJECT SHIELDS -->
|
||||
<!--
|
||||
*** I'm using markdown "reference style" links for readability.
|
||||
*** Reference links are enclosed in brackets [ ] instead of parentheses ( ).
|
||||
*** See the bottom of this document for the declaration of the reference variables
|
||||
*** for contributors-url, forks-url, etc. This is an optional, concise syntax you may use.
|
||||
*** https://www.markdownguide.org/basic-syntax/#reference-style-links
|
||||
-->
|
||||
|
||||
<div align="center">
|
||||
<a href="https://github.com/OpenDevin/OpenDevin/graphs/contributors"><img src="https://img.shields.io/github/contributors/opendevin/opendevin?style=for-the-badge" alt="Contributors"></a>
|
||||
<a href="https://github.com/OpenDevin/OpenDevin/network/members"><img src="https://img.shields.io/github/forks/opendevin/opendevin?style=for-the-badge" alt="Forks"></a>
|
||||
<a href="https://github.com/OpenDevin/OpenDevin/stargazers"><img src="https://img.shields.io/github/stars/opendevin/opendevin?style=for-the-badge" alt="Stargazers"></a>
|
||||
<a href="https://github.com/OpenDevin/OpenDevin/issues"><img src="https://img.shields.io/github/issues/opendevin/opendevin?style=for-the-badge" alt="Issues"></a>
|
||||
<a href="https://github.com/OpenDevin/OpenDevin/blob/main/LICENSE"><img src="https://img.shields.io/github/license/opendevin/opendevin?style=for-the-badge" alt="MIT License"></a>
|
||||
</br>
|
||||
<a href="https://join.slack.com/t/opendevin/shared_invite/zt-2etftj1dd-X1fDL2PYIVpsmJZkqEYANw"><img src="https://img.shields.io/badge/Slack-Join%20Us-red?logo=slack&logoColor=white&style=for-the-badge" alt="Join our Slack community"></a>
|
||||
<a href="https://discord.gg/mBuDGRzzES"><img src="https://img.shields.io/badge/Discord-Join%20Us-purple?logo=discord&logoColor=white&style=for-the-badge" alt="Join our Discord community"></a>
|
||||
</div>
|
||||
|
||||
<!-- PROJECT LOGO -->
|
||||
<div align="center">
|
||||
<img src="./logo.png" alt="Logo" width="200" height="200">
|
||||
<h1 align="center">OpenDevin: Code Less, Make More</h1>
|
||||
</div>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- TABLE OF CONTENTS -->
|
||||
<details>
|
||||
<summary>🗂️ Table of Contents</summary>
|
||||
<ol>
|
||||
<li><a href="#-mission">🎯 Mission</a></li>
|
||||
<li><a href="#-what-is-devin">🤔 What is Devin?</a></li>
|
||||
<li><a href="#-why-opendevin">🐚 Why OpenDevin?</a></li>
|
||||
<li><a href="#-project-status">🚧 Project Status</a></li>
|
||||
<a href="#-get-started">🚀 Get Started</a>
|
||||
<ul>
|
||||
<li><a href="#1-requirements">1. Requirements</a></li>
|
||||
<li><a href="#2-build-and-setup">2. Build and Setup</a></li>
|
||||
<li><a href="#3-run-the-application">3. Run the Application</a></li>
|
||||
<li><a href="#4-individual-server-startup">4. Individual Server Startup</a></li>
|
||||
<li><a href="#5-help">5. Help</a></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><a href="#%EF%B8%8F-research-strategy">⭐️ Research Strategy</a></li>
|
||||
<li><a href="#-how-to-contribute">🤝 How to Contribute</a></li>
|
||||
<li><a href="#-join-our-community">🤖 Join Our Community</a></li>
|
||||
<li><a href="#%EF%B8%8F-built-with">🛠️ Built With</a></li>
|
||||
<li><a href="#-license">📜 License</a></li>
|
||||
</ol>
|
||||
</details>
|
||||
|
||||
## 🎯 Mission
|
||||
|
||||
[Project Demo Video](https://github.com/OpenDevin/OpenDevin/assets/38853559/71a472cc-df34-430c-8b1d-4d7286c807c9)
|
||||
|
||||
|
||||
Welcome to OpenDevin, an open-source project aiming to replicate Devin, an autonomous AI software engineer who is capable of executing complex engineering tasks and collaborating actively with users on software development projects. This project aspires to replicate, enhance, and innovate upon Devin through the power of the open-source community.
|
||||
|
||||
<p align="right" style="font-size: 14px; color: #555; margin-top: 20px;">
|
||||
<a href="#readme-top" style="text-decoration: none; color: #007bff; font-weight: bold;">
|
||||
↑ Back to Top ↑
|
||||
</a>
|
||||
</p>
|
||||
|
||||
## 🤔 What is Devin?
|
||||
Devin represents a cutting-edge autonomous agent designed to navigate the complexities of software engineering. It leverages a combination of tools such as a shell, code editor, and web browser, showcasing the untapped potential of LLMs in software development. Our goal is to explore and expand upon Devin's capabilities, identifying both its strengths and areas for improvement, to guide the progress of open code models.
|
||||
|
||||
<p align="right" style="font-size: 14px; color: #555; margin-top: 20px;">
|
||||
<a href="#readme-top" style="text-decoration: none; color: #007bff; font-weight: bold;">
|
||||
↑ Back to Top ↑
|
||||
</a>
|
||||
</p>
|
||||
|
||||
## 🐚 Why OpenDevin?
|
||||
The OpenDevin project is born out of a desire to replicate, enhance, and innovate beyond the original Devin model. By engaging the open-source community, we aim to tackle the challenges faced by Code LLMs in practical scenarios, producing works that significantly contribute to the community and pave the way for future advancements.
|
||||
|
||||
<p align="right" style="font-size: 14px; color: #555; margin-top: 20px;">
|
||||
<a href="#readme-top" style="text-decoration: none; color: #007bff; font-weight: bold;">
|
||||
↑ Back to Top ↑
|
||||
</a>
|
||||
</p>
|
||||
|
||||
## 🚧 Project Status
|
||||
|
||||
OpenDevin is currently a work in progress, but you can already run the alpha version to see the end-to-end system in action. The project team is actively working on the following key milestones:
|
||||
|
||||
- **UI**: Developing a user-friendly interface, including a chat interface, a shell demonstrating commands, and a web browser.
|
||||
- **Architecture**: Building a stable agent framework with a robust backend that can read, write, and run simple commands.
|
||||
- **Agent Capabilities**: Enhancing the agent's abilities to generate bash scripts, run tests, and perform other software engineering tasks.
|
||||
- **Evaluation**: Establishing a minimal evaluation pipeline that is consistent with Devin's evaluation criteria.
|
||||
|
||||
After completing the MVP, the team will focus on research in various areas, including foundation models, specialist capabilities, evaluation, and agent studies.
|
||||
|
||||
<p align="right" style="font-size: 14px; color: #555; margin-top: 20px;">
|
||||
<a href="#readme-top" style="text-decoration: none; color: #007bff; font-weight: bold;">
|
||||
↑ Back to Top ↑
|
||||
</a>
|
||||
</p>
|
||||
|
||||
## ⚠️ Caveats and Warnings
|
||||
* OpenDevin is still an alpha project. It is changing very quickly and is unstable. We are working on getting a stable release out in the coming weeks.
|
||||
* OpenDevin will issue many prompts to the LLM you configure. Most of these LLMs cost money--be sure to set spending limits and monitor usage.
|
||||
* OpenDevin runs `bash` commands within a Docker sandbox, so it should not affect your machine. But your workspace directory will be attached to that sandbox, and files in the directory may be modified or deleted.
|
||||
* Our default Agent is currently the MonologueAgent, which has limited capabilities, but is fairly stable. We're working on other Agent implementations, including [SWE Agent](https://swe-agent.com/). You can [read about our current set of agents here](./docs/documentation/Agents.md).
|
||||
|
||||
## 🚀 Get Started
|
||||
|
||||
Getting started with the OpenDevin project is incredibly easy. Follow these simple steps to set up and run OpenDevin on your system:
|
||||
|
||||
The easiest way to run OpenDevin is inside a Docker container.
|
||||
You can run:
|
||||
```bash
|
||||
# Your OpenAI API key, or any other LLM API key
|
||||
export LLM_API_KEY="sk-..."
|
||||
|
||||
# The directory you want OpenDevin to modify. MUST be an absolute path!
|
||||
export WORKSPACE_DIR=$(pwd)/workspace
|
||||
|
||||
docker run \
|
||||
-e LLM_API_KEY \
|
||||
-e WORKSPACE_MOUNT_PATH=$WORKSPACE_DIR \
|
||||
-v $WORKSPACE_DIR:/opt/workspace_base \
|
||||
-v /var/run/docker.sock:/var/run/docker.sock \
|
||||
-p 3000:3000 \
|
||||
ghcr.io/opendevin/opendevin:latest
|
||||
```
|
||||
Replace `$(pwd)/workspace` with the path to the code you want OpenDevin to work with.
|
||||
|
||||
You can find opendevin running at `http://localhost:3000`.
|
||||
|
||||
See [Development.md](Development.md) for instructions on running OpenDevin without Docker.
|
||||
|
||||
## 🤖 LLM Backends
|
||||
OpenDevin can work with any LLM backend.
|
||||
For a full list of the LM providers and models available, please consult the
|
||||
[litellm documentation](https://docs.litellm.ai/docs/providers).
|
||||
|
||||
The `LLM_MODEL` environment variable controls which model is used in programmatic interactions,
|
||||
but choosing a model in the OpenDevin UI will override this setting.
|
||||
|
||||
The following environment variables might be necessary for some LLMs:
|
||||
* `LLM_API_KEY`
|
||||
* `LLM_BASE_URL`
|
||||
* `LLM_EMBEDDING_MODEL`
|
||||
* `LLM_DEPLOYMENT_NAME`
|
||||
* `LLM_API_VERSION`
|
||||
|
||||
**Note on Alternative Models:**
|
||||
Some alternative models may prove more challenging to tame than others.
|
||||
Fear not, brave adventurer! We shall soon unveil LLM-specific documentation to guide you on your quest.
|
||||
And if you've already mastered the art of wielding a model other than OpenAI's GPT,
|
||||
we encourage you to [share your setup instructions with us](https://github.com/OpenDevin/OpenDevin/issues/417).
|
||||
|
||||
There is also [documentation for running with local models using ollama](./docs/documentation/LOCAL_LLM_GUIDE.md).
|
||||
|
||||
## ⭐️ Research Strategy
|
||||
|
||||
Achieving full replication of production-grade applications with LLMs is a complex endeavor. Our strategy involves:
|
||||
|
||||
1. **Core Technical Research:** Focusing on foundational research to understand and improve the technical aspects of code generation and handling.
|
||||
2. **Specialist Abilities:** Enhancing the effectiveness of core components through data curation, training methods, and more.
|
||||
3. **Task Planning:** Developing capabilities for bug detection, codebase management, and optimization.
|
||||
4. **Evaluation:** Establishing comprehensive evaluation metrics to better understand and improve our models.
|
||||
|
||||
<p align="right" style="font-size: 14px; color: #555; margin-top: 20px;">
|
||||
<a href="#readme-top" style="text-decoration: none; color: #007bff; font-weight: bold;">
|
||||
↑ Back to Top ↑
|
||||
</a>
|
||||
</p>
|
||||
|
||||
## 🤝 How to Contribute
|
||||
|
||||
OpenDevin is a community-driven project, and we welcome contributions from everyone. Whether you're a developer, a researcher, or simply enthusiastic about advancing the field of software engineering with AI, there are many ways to get involved:
|
||||
|
||||
- **Code Contributions:** Help us develop the core functionalities, frontend interface, or sandboxing solutions.
|
||||
- **Research and Evaluation:** Contribute to our understanding of LLMs in software engineering, participate in evaluating the models, or suggest improvements.
|
||||
- **Feedback and Testing:** Use the OpenDevin toolset, report bugs, suggest features, or provide feedback on usability.
|
||||
|
||||
For details, please check [this document](./CONTRIBUTING.md).
|
||||
|
||||
<p align="right" style="font-size: 14px; color: #555; margin-top: 20px;">
|
||||
<a href="#readme-top" style="text-decoration: none; color: #007bff; font-weight: bold;">
|
||||
↑ Back to Top ↑
|
||||
</a>
|
||||
</p>
|
||||
|
||||
## 🤖 Join Our Community
|
||||
|
||||
Now we have both Slack workspace for the collaboration on building OpenDevin and Discord server for discussion about anything related, e.g., this project, LLM, agent, etc.
|
||||
|
||||
* [Slack workspace](https://join.slack.com/t/opendevin/shared_invite/zt-2etftj1dd-X1fDL2PYIVpsmJZkqEYANw)
|
||||
* [Discord server](https://discord.gg/mBuDGRzzES)
|
||||
|
||||
If you would love to contribute, feel free to join our community (note that now there is no need to fill in the [form](https://forms.gle/758d5p6Ve8r2nxxq6)). Let's simplify software engineering together!
|
||||
|
||||
🐚 **Code less, make more with OpenDevin.**
|
||||
|
||||
[](https://star-history.com/#OpenDevin/OpenDevin&Date)
|
||||
|
||||
## 🛠️ Built With
|
||||
|
||||
OpenDevin is built using a combination of powerful frameworks and libraries, providing a robust foundation for its development. Here are the key technologies used in the project:
|
||||
|
||||
       
|
||||
|
||||
Please note that the selection of these technologies is in progress, and additional technologies may be added or existing ones may be removed as the project evolves. We strive to adopt the most suitable and efficient tools to enhance the capabilities of OpenDevin.
|
||||
|
||||
<p align="right" style="font-size: 14px; color: #555; margin-top: 20px;">
|
||||
<a href="#readme-top" style="text-decoration: none; color: #007bff; font-weight: bold;">
|
||||
↑ Back to Top ↑
|
||||
</a>
|
||||
</p>
|
||||
|
||||
## 📜 License
|
||||
|
||||
Distributed under the MIT License. See [`LICENSE`](./LICENSE) for more information.
|
||||
|
||||
<p align="right" style="font-size: 14px; color: #555; margin-top: 20px;">
|
||||
<a href="#readme-top" style="text-decoration: none; color: #007bff; font-weight: bold;">
|
||||
↑ Back to Top ↑
|
||||
</a>
|
||||
</p>
|
||||
|
||||
[contributors-shield]: https://img.shields.io/github/contributors/opendevin/opendevin?style=for-the-badge
|
||||
[contributors-url]: https://github.com/OpenDevin/OpenDevin/graphs/contributors
|
||||
[forks-shield]: https://img.shields.io/github/forks/opendevin/opendevin?style=for-the-badge
|
||||
[forks-url]: https://github.com/OpenDevin/OpenDevin/network/members
|
||||
[stars-shield]: https://img.shields.io/github/stars/opendevin/opendevin?style=for-the-badge
|
||||
[stars-url]: https://github.com/OpenDevin/OpenDevin/stargazers
|
||||
[issues-shield]: https://img.shields.io/github/issues/opendevin/opendevin?style=for-the-badge
|
||||
[issues-url]: https://github.com/OpenDevin/OpenDevin/issues
|
||||
[license-shield]: https://img.shields.io/github/license/opendevin/opendevin?style=for-the-badge
|
||||
[license-url]: https://github.com/OpenDevin/OpenDevin/blob/main/LICENSE
|
||||
@@ -1,73 +0,0 @@
|
||||
# Agent Framework Research
|
||||
|
||||
In this folder, there may exist multiple implementations of `Agent` that will be used by the framework.
|
||||
|
||||
For example, `agenthub/monologue_agent`, `agenthub/metagpt_agent`, `agenthub/codeact_agent`, etc.
|
||||
Contributors from different backgrounds and interests can choose to contribute to any (or all!) of these directions.
|
||||
|
||||
## Constructing an Agent
|
||||
|
||||
The abstraction for an agent can be found [here](../opendevin/agent.py).
|
||||
|
||||
Agents are run inside of a loop. At each iteration, `agent.step()` is called with a
|
||||
[State](../opendevin/state.py) input, and the agent must output an [Action](../opendevin/action).
|
||||
|
||||
Every agent also has a `self.llm` which it can use to interact with the LLM configured by the user.
|
||||
See the [LiteLLM docs for `self.llm.completion`](https://docs.litellm.ai/docs/completion).
|
||||
|
||||
## State
|
||||
The `state` contains:
|
||||
* A history of actions taken by the agent, as well as any observations (e.g. file content, command output) from those actions
|
||||
* A list of actions/observations that have happened since the most recent step
|
||||
* A [`plan`](https://github.com/OpenDevin/OpenDevin/blob/main/opendevin/plan.py), which contains the main goal
|
||||
* The agent can add and modify subtasks through the `AddTaskAction` and `ModifyTaskAction`
|
||||
|
||||
## Actions
|
||||
Here is a list of available Actions, which can be returned by `agent.step()`:
|
||||
- [`CmdRunAction`](../opendevin/action/bash.py) - Runs a command inside a sandboxed terminal
|
||||
- [`CmdKillAction`](../opendevin/action/bash.py) - Kills a background command
|
||||
- [`FileReadAction`](../opendevin/action/fileop.py) - Reads the content of a file
|
||||
- [`FileWriteAction`](../opendevin/action/fileop.py) - Writes new content to a file
|
||||
- [`BrowseURLAction`](../opendevin/action/browse.py) - Gets the content of a URL
|
||||
- [`AgentRecallAction`](../opendevin/action/agent.py) - Searches memory (e.g. a vector database)
|
||||
- [`AddTaskAction`](../opendevin/action/tasks.py) - Adds a subtask to the plan
|
||||
- [`ModifyTaskAction`](../opendevin/action/tasks.py) - Changes the state of a subtask
|
||||
- [`AgentThinkAction`](../opendevin/action/agent.py) - A no-op that allows the agent to add plaintext to the history (as well as the chat log)
|
||||
- [`AgentFinishAction`](../opendevin/action/agent.py) - Stops the control loop, allowing the user to enter a new task
|
||||
|
||||
You can use `action.to_dict()` and `action_from_dict` to serialize and deserialize actions.
|
||||
|
||||
## Observations
|
||||
There are also several types of Observations. These are typically available in the step following the corresponding Action.
|
||||
But they may also appear as a result of asynchronous events (e.g. a message from the user, logs from a command running
|
||||
in the background).
|
||||
|
||||
Here is a list of available Observations:
|
||||
- [`CmdOutputObservation`](../opendevin/observation/run.py)
|
||||
- [`BrowserOutputObservation`](../opendevin/observation/browse.py)
|
||||
- [`FileReadObservation`](../opendevin/observation/files.py)
|
||||
- [`FileWriteObservation`](../opendevin/observation/files.py)
|
||||
- [`UserMessageObservation`](../opendevin/observation/)
|
||||
- [`AgentRecallObservation`](../opendevin/observation/recall.py)
|
||||
- [`AgentErrorObservation`](../opendevin/observation/error.py)
|
||||
|
||||
You can use `observation.to_dict()` and `observation_from_dict` to serialize and deserialize observations.
|
||||
|
||||
## Interface
|
||||
Every agent must implement the following methods:
|
||||
|
||||
### `step`
|
||||
```
|
||||
def step(self, state: "State") -> "Action"
|
||||
```
|
||||
`step` moves the agent forward one step towards its goal. This probably means
|
||||
sending a prompt to the LLM, then parsing the response into an `Action`.
|
||||
|
||||
### `search_memory`
|
||||
```
|
||||
def search_memory(self, query: str) -> List[str]:
|
||||
```
|
||||
`search_memory` should return a list of events that match the query. This will be used
|
||||
for the `recall` action.
|
||||
|
||||
You can optionally just return `[]` for this method, meaning the agent has no long-term memory.
|
||||
@@ -1,9 +0,0 @@
|
||||
from dotenv import load_dotenv
|
||||
load_dotenv()
|
||||
|
||||
# Import agents after environment variables are loaded
|
||||
from . import monologue_agent # noqa: E402
|
||||
from . import codeact_agent # noqa: E402
|
||||
from . import planner_agent # noqa: E402
|
||||
|
||||
__all__ = ['monologue_agent', 'codeact_agent', 'planner_agent']
|
||||
@@ -1,23 +0,0 @@
|
||||
# CodeAct-based Agent Framework
|
||||
|
||||
This folder implements the [CodeAct idea](https://arxiv.org/abs/2402.13463) that relies on LLM to autonomously perform actions in a Bash shell. It requires more from the LLM itself: LLM needs to be capable enough to do all the stuff autonomously, instead of stuck in an infinite loop.
|
||||
|
||||
**NOTE: This agent is still highly experimental and under active development to reach the capability described in the original paper & [repo](https://github.com/xingyaoww/code-act).**
|
||||
|
||||
<video src="https://github.com/xingyaoww/code-act/assets/38853559/62c80ada-62ce-447e-811c-fc801dd4beac"> </video>
|
||||
*Demo of the expected capability - work-in-progress.*
|
||||
|
||||
```bash
|
||||
mkdir workspace
|
||||
PYTHONPATH=`pwd`:$PYTHONPATH python3 opendevin/main.py -d ./workspace -c CodeActAgent -t "Please write a flask app that returns 'Hello, World\!' at the root URL, then start the app on port 5000. python3 has already been installed for you."
|
||||
```
|
||||
|
||||
Example: prompts `gpt-4-0125-preview` to write a flask server, install `flask` library, and start the server.
|
||||
|
||||
<img width="951" alt="image" src="https://github.com/OpenDevin/OpenDevin/assets/38853559/325c3115-a343-4cc5-a92b-f1e5d552a077">
|
||||
|
||||
<img width="957" alt="image" src="https://github.com/OpenDevin/OpenDevin/assets/38853559/68ad10c1-744a-4e9d-bb29-0f163d665a0a">
|
||||
|
||||
Most of the things are working as expected, except at the end, the model did not follow the instruction to stop the interaction by outputting `<execute> exit </execute>` as instructed.
|
||||
|
||||
**TODO**: This should be fixable by either (1) including a complete in-context example like [this](https://github.com/xingyaoww/mint-bench/blob/main/mint/tasks/in_context_examples/reasoning/with_tool.txt), OR (2) collect some interaction data like this and fine-tune a model (like [this](https://github.com/xingyaoww/code-act), a more complex route).
|
||||
@@ -1,4 +0,0 @@
|
||||
from opendevin.agent import Agent
|
||||
from .codeact_agent import CodeActAgent
|
||||
|
||||
Agent.register('CodeActAgent', CodeActAgent)
|
||||
@@ -1,157 +0,0 @@
|
||||
import re
|
||||
from typing import List, Mapping
|
||||
|
||||
from opendevin.action import (
|
||||
Action,
|
||||
AgentEchoAction,
|
||||
AgentFinishAction,
|
||||
CmdRunAction,
|
||||
)
|
||||
from opendevin.agent import Agent
|
||||
from opendevin.llm.llm import LLM
|
||||
from opendevin.observation import (
|
||||
AgentMessageObservation,
|
||||
CmdOutputObservation,
|
||||
)
|
||||
from opendevin.parse_commands import parse_command_file
|
||||
from opendevin.state import State
|
||||
|
||||
COMMAND_DOCS = parse_command_file()
|
||||
COMMAND_SEGMENT = (
|
||||
f"""
|
||||
|
||||
Apart from the standard bash commands, you can also use the following special commands:
|
||||
{COMMAND_DOCS}
|
||||
"""
|
||||
if COMMAND_DOCS is not None
|
||||
else ''
|
||||
)
|
||||
SYSTEM_MESSAGE = f"""You are a helpful assistant. You will be provided access (as root) to a bash shell to complete user-provided tasks.
|
||||
You will be able to execute commands in the bash shell, interact with the file system, install packages, and receive the output of your commands.
|
||||
|
||||
DO NOT provide code in ```triple backticks```. Instead, you should execute bash command on behalf of the user by wrapping them with <execute> and </execute>.
|
||||
For example:
|
||||
|
||||
You can list the files in the current directory by executing the following command:
|
||||
<execute>ls</execute>
|
||||
|
||||
You can also install packages using pip:
|
||||
<execute> pip install numpy </execute>
|
||||
|
||||
You can also write a block of code to a file:
|
||||
<execute>
|
||||
echo "import math
|
||||
print(math.pi)" > math.py
|
||||
</execute>
|
||||
{COMMAND_SEGMENT}
|
||||
|
||||
When you are done, execute the following to close the shell and end the conversation:
|
||||
<execute>exit</execute>
|
||||
"""
|
||||
|
||||
INVALID_INPUT_MESSAGE = (
|
||||
"I don't understand your input. \n"
|
||||
'If you want to execute command, please use <execute> YOUR_COMMAND_HERE </execute>.\n'
|
||||
'If you already completed the task, please exit the shell by generating: <execute> exit </execute>.'
|
||||
)
|
||||
|
||||
|
||||
def parse_response(response) -> str:
|
||||
action = response.choices[0].message.content
|
||||
if '<execute>' in action and '</execute>' not in action:
|
||||
action += '</execute>'
|
||||
return action
|
||||
|
||||
|
||||
class CodeActAgent(Agent):
|
||||
"""
|
||||
The Code Act Agent is a minimalist agent.
|
||||
The agent works by passing the model a list of action-observation pairs and prompting the model to take the next step.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
llm: LLM,
|
||||
) -> None:
|
||||
"""
|
||||
Initializes a new instance of the CodeActAgent class.
|
||||
|
||||
Parameters:
|
||||
- llm (LLM): The llm to be used by this agent
|
||||
"""
|
||||
super().__init__(llm)
|
||||
self.messages: List[Mapping[str, str]] = []
|
||||
|
||||
def step(self, state: State) -> Action:
|
||||
"""
|
||||
Performs one step using the Code Act Agent.
|
||||
This includes gathering info on previous steps and prompting the model to make a command to execute.
|
||||
|
||||
Parameters:
|
||||
- state (State): used to get updated info and background commands
|
||||
|
||||
Returns:
|
||||
- CmdRunAction(command) - command action to run
|
||||
- AgentEchoAction(content=INVALID_INPUT_MESSAGE) - invalid command output
|
||||
|
||||
Raises:
|
||||
- NotImplementedError - for actions other than CmdOutputObservation or AgentMessageObservation
|
||||
"""
|
||||
|
||||
if len(self.messages) == 0:
|
||||
assert state.plan.main_goal, 'Expecting instruction to be set'
|
||||
self.messages = [
|
||||
{'role': 'system', 'content': SYSTEM_MESSAGE},
|
||||
{'role': 'user', 'content': state.plan.main_goal},
|
||||
]
|
||||
updated_info = state.updated_info
|
||||
if updated_info:
|
||||
for prev_action, obs in updated_info:
|
||||
assert isinstance(
|
||||
prev_action, (CmdRunAction, AgentEchoAction)
|
||||
), 'Expecting CmdRunAction or AgentEchoAction for Action'
|
||||
if isinstance(
|
||||
obs, AgentMessageObservation
|
||||
): # warning message from itself
|
||||
self.messages.append(
|
||||
{'role': 'user', 'content': obs.content})
|
||||
elif isinstance(obs, CmdOutputObservation):
|
||||
content = 'OBSERVATION:\n' + obs.content
|
||||
content += f'\n[Command {obs.command_id} finished with exit code {obs.exit_code}]]'
|
||||
self.messages.append({'role': 'user', 'content': content})
|
||||
else:
|
||||
raise NotImplementedError(
|
||||
f'Unknown observation type: {obs.__class__}'
|
||||
)
|
||||
response = self.llm.completion(
|
||||
messages=self.messages,
|
||||
stop=['</execute>'],
|
||||
temperature=0.0
|
||||
)
|
||||
action_str: str = parse_response(response)
|
||||
state.num_of_chars += sum(len(message['content'])
|
||||
for message in self.messages) + len(action_str)
|
||||
self.messages.append({'role': 'assistant', 'content': action_str})
|
||||
|
||||
command = re.search(r'<execute>(.*)</execute>', action_str, re.DOTALL)
|
||||
if command is not None:
|
||||
# a command was found
|
||||
command_group = command.group(1)
|
||||
if command_group.strip() == 'exit':
|
||||
return AgentFinishAction()
|
||||
return CmdRunAction(command=command_group)
|
||||
# # execute the code
|
||||
# # TODO: does exit_code get loaded into Message?
|
||||
# exit_code, observation = self.env.execute(command_group)
|
||||
# self._history.append(Message(Role.ASSISTANT, observation))
|
||||
else:
|
||||
# we could provide a error message for the model to continue similar to
|
||||
# https://github.com/xingyaoww/mint-bench/blob/main/mint/envs/general_env.py#L18-L23
|
||||
# observation = INVALID_INPUT_MESSAGE
|
||||
# self._history.append(Message(Role.ASSISTANT, observation))
|
||||
return AgentEchoAction(
|
||||
content=INVALID_INPUT_MESSAGE
|
||||
) # warning message to itself
|
||||
|
||||
def search_memory(self, query: str) -> List[str]:
|
||||
raise NotImplementedError('Implement this abstract method')
|
||||
@@ -1,2 +0,0 @@
|
||||
.envrc
|
||||
workspace
|
||||
@@ -1,8 +0,0 @@
|
||||
# LLM control loop
|
||||
This is currently a standalone utility. It will need to be integrated into OpenDevin's backend.
|
||||
|
||||
## Usage
|
||||
```bash
|
||||
# Run this in project root
|
||||
./agenthub/monologue_agent/build-and-run.sh "write a bash script that prints 'hello world'"
|
||||
```
|
||||
@@ -1,8 +0,0 @@
|
||||
# TODO
|
||||
There's a lot of low-hanging fruit for this agent:
|
||||
|
||||
* Strip `<script>`, `<style>`, and other non-text tags from the HTML before sending it to the LLM
|
||||
* Keep track of the working directory when the agent uses `cd`
|
||||
* Improve memory condensing--condense earlier memories more aggressively
|
||||
* Limit the time that `run` can wait (in case agent runs an interactive command and it's hanging)
|
||||
* Figure out how to run background processes, e.g. `node server.js` to start a server
|
||||
@@ -1,4 +0,0 @@
|
||||
from opendevin.agent import Agent
|
||||
from .agent import MonologueAgent
|
||||
|
||||
Agent.register('MonologueAgent', MonologueAgent)
|
||||
@@ -1,235 +0,0 @@
|
||||
from typing import List
|
||||
from opendevin.agent import Agent
|
||||
from opendevin.state import State
|
||||
from opendevin.llm.llm import LLM
|
||||
from opendevin.schema import ActionType, ObservationType
|
||||
from opendevin.exceptions import AgentNoInstructionError
|
||||
|
||||
from opendevin.action import (
|
||||
Action,
|
||||
NullAction,
|
||||
CmdRunAction,
|
||||
FileWriteAction,
|
||||
FileReadAction,
|
||||
AgentRecallAction,
|
||||
BrowseURLAction,
|
||||
AgentThinkAction,
|
||||
)
|
||||
|
||||
from opendevin.observation import (
|
||||
Observation,
|
||||
NullObservation,
|
||||
CmdOutputObservation,
|
||||
FileReadObservation,
|
||||
AgentRecallObservation,
|
||||
BrowserOutputObservation,
|
||||
)
|
||||
|
||||
import agenthub.monologue_agent.utils.prompts as prompts
|
||||
from agenthub.monologue_agent.utils.monologue import Monologue
|
||||
from agenthub.monologue_agent.utils.memory import LongTermMemory
|
||||
|
||||
MAX_MONOLOGUE_LENGTH = 20000
|
||||
MAX_OUTPUT_LENGTH = 5000
|
||||
|
||||
INITIAL_THOUGHTS = [
|
||||
'I exist!',
|
||||
'Hmm...looks like I can type in a command line prompt',
|
||||
'Looks like I have a web browser too!',
|
||||
"Here's what I want to do: $TASK",
|
||||
'How am I going to get there though?',
|
||||
'It seems like I have some kind of short term memory.',
|
||||
'Each of my thoughts seems to be stored in a JSON array.',
|
||||
'It seems whatever I say next will be added as an object to the list.',
|
||||
'But no one has perfect short-term memory. My list of thoughts will be summarized and condensed over time, losing information in the process.',
|
||||
'Fortunately I have long term memory!',
|
||||
'I can just perform a recall action, followed by the thing I want to remember. And then related thoughts just spill out!',
|
||||
"Sometimes they're random thoughts that don't really have to do with what I wanted to remember. But usually they're exactly what I need!",
|
||||
"Let's try it out!",
|
||||
'RECALL what it is I want to do',
|
||||
"Here's what I want to do: $TASK",
|
||||
'How am I going to get there though?',
|
||||
"Neat! And it looks like it's easy for me to use the command line too! I just have to perform a run action and include the command I want to run in the command argument. The command output just jumps into my head!",
|
||||
'RUN echo "hello world"',
|
||||
'hello world',
|
||||
'Cool! I bet I can write files too using the write action.',
|
||||
"WRITE echo \"console.log('hello world')\" > test.js",
|
||||
'',
|
||||
"I just created test.js. I'll try and run it now.",
|
||||
'RUN node test.js',
|
||||
'hello world',
|
||||
'It works!',
|
||||
"I'm going to try reading it now using the read action.",
|
||||
'READ test.js',
|
||||
"console.log('hello world')",
|
||||
'Nice! I can read files too!',
|
||||
'And if I want to use the browser, I just need to use the browse action and include the url I want to visit in the url argument',
|
||||
"Let's try that...",
|
||||
'BROWSE google.com',
|
||||
'<form><input type="text"></input><button type="submit"></button></form>',
|
||||
'I can browse the web too!',
|
||||
'And once I have completed my task, I can use the finish action to stop working.',
|
||||
"But I should only use the finish action when I'm absolutely certain that I've completed my task and have tested my work.",
|
||||
'Very cool. Now to accomplish my task.',
|
||||
"I'll need a strategy. And as I make progress, I'll need to keep refining that strategy. I'll need to set goals, and break them into sub-goals.",
|
||||
'In between actions, I must always take some time to think, strategize, and set new goals. I should never take two actions in a row.',
|
||||
"OK so my task is to $TASK. I haven't made any progress yet. Where should I start?",
|
||||
"It seems like there might be an existing project here. I should probably start by running `ls` to see what's here.",
|
||||
]
|
||||
|
||||
|
||||
class MonologueAgent(Agent):
|
||||
"""
|
||||
The Monologue Agent utilizes long and short term memory to complete tasks.
|
||||
Long term memory is stored as a LongTermMemory object and the model uses it to search for examples from the past.
|
||||
Short term memory is stored as a Monologue object and the model can condense it as necessary.
|
||||
"""
|
||||
|
||||
_initialized = False
|
||||
|
||||
def __init__(self, llm: LLM):
|
||||
"""
|
||||
Initializes the Monologue Agent with an llm, monologue, and memory.
|
||||
|
||||
Parameters:
|
||||
- llm (LLM): The llm to be used by this agent
|
||||
"""
|
||||
super().__init__(llm)
|
||||
self.monologue = Monologue()
|
||||
self.memory = LongTermMemory()
|
||||
|
||||
def _add_event(self, event: dict):
|
||||
"""
|
||||
Adds a new event to the agent's monologue and memory.
|
||||
Monologue automatically condenses when it gets too large.
|
||||
|
||||
Parameters:
|
||||
- event (dict): The event that will be added to monologue and memory
|
||||
"""
|
||||
|
||||
if 'extras' in event and 'screenshot' in event['extras']:
|
||||
del event['extras']['screenshot']
|
||||
if (
|
||||
'args' in event
|
||||
and 'output' in event['args']
|
||||
and len(event['args']['output']) > MAX_OUTPUT_LENGTH
|
||||
):
|
||||
event['args']['output'] = (
|
||||
event['args']['output'][:MAX_OUTPUT_LENGTH] + '...'
|
||||
)
|
||||
|
||||
self.monologue.add_event(event)
|
||||
self.memory.add_event(event)
|
||||
if self.monologue.get_total_length() > MAX_MONOLOGUE_LENGTH:
|
||||
self.monologue.condense(self.llm)
|
||||
|
||||
def _initialize(self, task: str):
|
||||
"""
|
||||
Utilizes the INITIAL_THOUGHTS list to give the agent a context for it's capabilities and how to navigate the /workspace.
|
||||
Short circuted to return when already initialized.
|
||||
|
||||
Parameters:
|
||||
- task (str): The initial goal statement provided by the user
|
||||
|
||||
Raises:
|
||||
- AgentNoInstructionError: If task is not provided
|
||||
"""
|
||||
|
||||
if self._initialized:
|
||||
return
|
||||
|
||||
if task is None or task == '':
|
||||
raise AgentNoInstructionError()
|
||||
self.monologue = Monologue()
|
||||
self.memory = LongTermMemory()
|
||||
|
||||
output_type = ''
|
||||
for thought in INITIAL_THOUGHTS:
|
||||
thought = thought.replace('$TASK', task)
|
||||
if output_type != '':
|
||||
observation: Observation = NullObservation(content='')
|
||||
if output_type == ObservationType.RUN:
|
||||
observation = CmdOutputObservation(
|
||||
content=thought, command_id=0, command=''
|
||||
)
|
||||
elif output_type == ObservationType.READ:
|
||||
observation = FileReadObservation(content=thought, path='')
|
||||
elif output_type == ObservationType.RECALL:
|
||||
observation = AgentRecallObservation(
|
||||
content=thought, memories=[])
|
||||
elif output_type == ObservationType.BROWSE:
|
||||
observation = BrowserOutputObservation(
|
||||
content=thought, url='', screenshot=''
|
||||
)
|
||||
self._add_event(observation.to_dict())
|
||||
output_type = ''
|
||||
else:
|
||||
action: Action = NullAction()
|
||||
if thought.startswith('RUN'):
|
||||
command = thought.split('RUN ')[1]
|
||||
action = CmdRunAction(command)
|
||||
output_type = ActionType.RUN
|
||||
elif thought.startswith('WRITE'):
|
||||
parts = thought.split('WRITE ')[1].split(' > ')
|
||||
path = parts[1]
|
||||
content = parts[0]
|
||||
action = FileWriteAction(path=path, content=content)
|
||||
elif thought.startswith('READ'):
|
||||
path = thought.split('READ ')[1]
|
||||
action = FileReadAction(path=path)
|
||||
output_type = ActionType.READ
|
||||
elif thought.startswith('RECALL'):
|
||||
query = thought.split('RECALL ')[1]
|
||||
action = AgentRecallAction(query=query)
|
||||
output_type = ActionType.RECALL
|
||||
elif thought.startswith('BROWSE'):
|
||||
url = thought.split('BROWSE ')[1]
|
||||
action = BrowseURLAction(url=url)
|
||||
output_type = ActionType.BROWSE
|
||||
else:
|
||||
action = AgentThinkAction(thought=thought)
|
||||
self._add_event(action.to_dict())
|
||||
self._initialized = True
|
||||
|
||||
def step(self, state: State) -> Action:
|
||||
"""
|
||||
Modifies the current state by adding the most recent actions and observations, then prompts the model to think about it's next action to take using monologue, memory, and hint.
|
||||
|
||||
Parameters:
|
||||
- state (State): The current state based on previous steps taken
|
||||
|
||||
Returns:
|
||||
- Action: The next action to take based on LLM response
|
||||
"""
|
||||
self._initialize(state.plan.main_goal)
|
||||
for prev_action, obs in state.updated_info:
|
||||
self._add_event(prev_action.to_dict())
|
||||
self._add_event(obs.to_dict())
|
||||
|
||||
state.updated_info = []
|
||||
|
||||
prompt = prompts.get_request_action_prompt(
|
||||
state.plan.main_goal,
|
||||
self.monologue.get_thoughts(),
|
||||
state.background_commands_obs,
|
||||
)
|
||||
messages = [{'content': prompt, 'role': 'user'}]
|
||||
resp = self.llm.completion(messages=messages)
|
||||
action_resp = resp['choices'][0]['message']['content']
|
||||
state.num_of_chars += len(prompt) + len(action_resp)
|
||||
action = prompts.parse_action_response(action_resp)
|
||||
self.latest_action = action
|
||||
return action
|
||||
|
||||
def search_memory(self, query: str) -> List[str]:
|
||||
"""
|
||||
Uses VectorIndexRetriever to find related memories within the long term memory.
|
||||
Uses search to produce top 10 results.
|
||||
|
||||
Parameters:
|
||||
- query (str): The query that we want to find related memories for
|
||||
|
||||
Returns:
|
||||
- List[str]: A list of top 10 text results that matched the query
|
||||
"""
|
||||
return self.memory.search(query)
|
||||
@@ -1,37 +0,0 @@
|
||||
import json
|
||||
from json_repair import repair_json
|
||||
|
||||
|
||||
def my_encoder(obj):
|
||||
"""
|
||||
Encodes objects as dictionaries
|
||||
|
||||
Parameters:
|
||||
- obj (Object): An object that will be converted
|
||||
|
||||
Returns:
|
||||
- dict: If the object can be converted it is returned in dict format
|
||||
"""
|
||||
if hasattr(obj, 'to_dict'):
|
||||
return obj.to_dict()
|
||||
|
||||
|
||||
def dumps(obj, **kwargs):
|
||||
"""
|
||||
Serialize an object to str format
|
||||
"""
|
||||
|
||||
return json.dumps(obj, default=my_encoder, **kwargs)
|
||||
|
||||
|
||||
def loads(s, **kwargs):
|
||||
"""
|
||||
Create a JSON object from str
|
||||
"""
|
||||
json_start = s.find('{')
|
||||
json_end = s.rfind('}') + 1
|
||||
if json_start == -1 or json_end == -1:
|
||||
raise ValueError('Invalid response: no JSON found')
|
||||
s = s[json_start:json_end]
|
||||
s = repair_json(s)
|
||||
return json.loads(s, **kwargs)
|
||||
@@ -1,106 +0,0 @@
|
||||
import chromadb
|
||||
from llama_index.core import Document
|
||||
from llama_index.core.retrievers import VectorIndexRetriever
|
||||
from llama_index.core import VectorStoreIndex
|
||||
from llama_index.vector_stores.chroma import ChromaVectorStore
|
||||
|
||||
from opendevin import config
|
||||
from opendevin.logger import opendevin_logger as logger
|
||||
from . import json
|
||||
|
||||
embedding_strategy = config.get('LLM_EMBEDDING_MODEL')
|
||||
|
||||
# TODO: More embeddings: https://docs.llamaindex.ai/en/stable/examples/embeddings/OpenAI/
|
||||
# There's probably a more programmatic way to do this.
|
||||
if embedding_strategy == 'llama2':
|
||||
from llama_index.embeddings.ollama import OllamaEmbedding
|
||||
embed_model = OllamaEmbedding(
|
||||
model_name='llama2',
|
||||
base_url=config.get('LLM_BASE_URL', required=True),
|
||||
ollama_additional_kwargs={'mirostat': 0},
|
||||
)
|
||||
elif embedding_strategy == 'openai':
|
||||
from llama_index.embeddings.openai import OpenAIEmbedding
|
||||
embed_model = OpenAIEmbedding(
|
||||
model='text-embedding-ada-002',
|
||||
api_key=config.get('LLM_API_KEY', required=True)
|
||||
)
|
||||
elif embedding_strategy == 'azureopenai':
|
||||
# Need to instruct to set these env variables in documentation
|
||||
from llama_index.embeddings.azure_openai import AzureOpenAIEmbedding
|
||||
embed_model = AzureOpenAIEmbedding(
|
||||
model='text-embedding-ada-002',
|
||||
deployment_name=config.get('LLM_DEPLOYMENT_NAME', required=True),
|
||||
api_key=config.get('LLM_API_KEY', required=True),
|
||||
azure_endpoint=config.get('LLM_BASE_URL', required=True),
|
||||
api_version=config.get('LLM_API_VERSION', required=True),
|
||||
)
|
||||
else:
|
||||
from llama_index.embeddings.huggingface import HuggingFaceEmbedding
|
||||
embed_model = HuggingFaceEmbedding(
|
||||
model_name='BAAI/bge-small-en-v1.5'
|
||||
)
|
||||
|
||||
|
||||
class LongTermMemory:
|
||||
"""
|
||||
Responsible for storing information that the agent can call on later for better insights and context.
|
||||
Uses chromadb to store and search through memories.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
"""
|
||||
Initialize the chromadb and set up ChromaVectorStore for later use.
|
||||
"""
|
||||
db = chromadb.Client()
|
||||
self.collection = db.get_or_create_collection(name='memories')
|
||||
vector_store = ChromaVectorStore(chroma_collection=self.collection)
|
||||
self.index = VectorStoreIndex.from_vector_store(
|
||||
vector_store, embed_model=embed_model)
|
||||
self.thought_idx = 0
|
||||
|
||||
def add_event(self, event: dict):
|
||||
"""
|
||||
Adds a new event to the long term memory with a unique id.
|
||||
|
||||
Parameters:
|
||||
- event (dict): The new event to be added to memory
|
||||
"""
|
||||
id = ''
|
||||
t = ''
|
||||
if 'action' in event:
|
||||
t = 'action'
|
||||
id = event['action']
|
||||
elif 'observation' in event:
|
||||
t = 'observation'
|
||||
id = event['observation']
|
||||
doc = Document(
|
||||
text=json.dumps(event),
|
||||
doc_id=str(self.thought_idx),
|
||||
extra_info={
|
||||
'type': t,
|
||||
'id': id,
|
||||
'idx': self.thought_idx,
|
||||
},
|
||||
)
|
||||
self.thought_idx += 1
|
||||
logger.debug("Adding %s event to memory: %d", t, self.thought_idx)
|
||||
self.index.insert(doc)
|
||||
|
||||
def search(self, query: str, k: int = 10):
|
||||
"""
|
||||
Searches through the current memory using VectorIndexRetriever
|
||||
|
||||
Parameters:
|
||||
- query (str): A query to match search results to
|
||||
- k (int): Number of top results to return
|
||||
|
||||
Returns:
|
||||
- List[str]: List of top k results found in current memory
|
||||
"""
|
||||
retriever = VectorIndexRetriever(
|
||||
index=self.index,
|
||||
similarity_top_k=k,
|
||||
)
|
||||
results = retriever.retrieve(query)
|
||||
return [r.get_text() for r in results]
|
||||
@@ -1,78 +0,0 @@
|
||||
import traceback
|
||||
|
||||
from opendevin.llm.llm import LLM
|
||||
from opendevin.exceptions import AgentEventTypeError
|
||||
import agenthub.monologue_agent.utils.json as json
|
||||
import agenthub.monologue_agent.utils.prompts as prompts
|
||||
|
||||
|
||||
class Monologue:
|
||||
"""
|
||||
The monologue is a representation for the agent's internal monologue where it can think.
|
||||
The agent has the capability of using this monologue for whatever it wants.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
"""
|
||||
Initialize the empty list of thoughts
|
||||
"""
|
||||
self.thoughts = []
|
||||
|
||||
def add_event(self, t: dict):
|
||||
"""
|
||||
Adds an event to memory if it is a valid event.
|
||||
|
||||
Parameters:
|
||||
- t (dict): The thought that we want to add to memory
|
||||
|
||||
Raises:
|
||||
- AgentEventTypeError: If t is not a dict
|
||||
"""
|
||||
if not isinstance(t, dict):
|
||||
raise AgentEventTypeError()
|
||||
self.thoughts.append(t)
|
||||
|
||||
def get_thoughts(self):
|
||||
"""
|
||||
Get the current thoughts of the agent.
|
||||
|
||||
Returns:
|
||||
- List: The list of thoughts that the agent has.
|
||||
"""
|
||||
return self.thoughts
|
||||
|
||||
def get_total_length(self):
|
||||
"""
|
||||
Gives the total number of characters in all thoughts
|
||||
|
||||
Returns:
|
||||
- Int: Total number of chars in thoughts.
|
||||
"""
|
||||
total_length = 0
|
||||
for t in self.thoughts:
|
||||
try:
|
||||
total_length += len(json.dumps(t))
|
||||
except TypeError as e:
|
||||
print(f'Error serializing thought: {e}')
|
||||
return total_length
|
||||
|
||||
def condense(self, llm: LLM):
|
||||
"""
|
||||
Attempts to condense the monologue by using the llm
|
||||
|
||||
Parameters:
|
||||
- llm (LLM): llm to be used for summarization
|
||||
|
||||
Raises:
|
||||
- RunTimeError: When the condensing process fails for any reason
|
||||
"""
|
||||
|
||||
try:
|
||||
prompt = prompts.get_summarize_monologue_prompt(self.thoughts)
|
||||
messages = [{'content': prompt, 'role': 'user'}]
|
||||
resp = llm.completion(messages=messages)
|
||||
summary_resp = resp['choices'][0]['message']['content']
|
||||
self.thoughts = prompts.parse_summary_response(summary_resp)
|
||||
except Exception as e:
|
||||
traceback.print_exc()
|
||||
raise RuntimeError(f'Error condensing thoughts: {e}')
|
||||
@@ -1,194 +0,0 @@
|
||||
from typing import List
|
||||
|
||||
from . import json
|
||||
from json import JSONDecodeError
|
||||
|
||||
import re
|
||||
|
||||
from opendevin.action import (
|
||||
action_from_dict,
|
||||
Action,
|
||||
)
|
||||
from opendevin.observation import (
|
||||
CmdOutputObservation,
|
||||
)
|
||||
from opendevin.exceptions import LLMOutputError
|
||||
|
||||
ACTION_PROMPT = """
|
||||
You're a thoughtful robot. Your main task is this:
|
||||
%(task)s
|
||||
|
||||
Don't expand the scope of your task--just complete it as written.
|
||||
|
||||
This is your internal monologue, in JSON format:
|
||||
|
||||
%(monologue)s
|
||||
|
||||
|
||||
Your most recent thought is at the bottom of that monologue. Continue your train of thought.
|
||||
What is your next thought or action? Your response must be in JSON format.
|
||||
It must be an object, and it must contain two fields:
|
||||
* `action`, which is one of the actions below
|
||||
* `args`, which is a map of key-value pairs, specifying the arguments for that action
|
||||
|
||||
Here are the possible actions:
|
||||
* `read` - reads the content of a file. Arguments:
|
||||
* `path` - the path of the file to read
|
||||
* `write` - writes the content to a file. Arguments:
|
||||
* `path` - the path of the file to write
|
||||
* `content` - the content to write to the file
|
||||
* `run` - runs a command. Arguments:
|
||||
* `command` - the command to run
|
||||
* `background` - if true, run the command in the background, so that other commands can be run concurrently. Useful for e.g. starting a server. You won't be able to see the logs. You don't need to end the command with `&`, just set this to true.
|
||||
* `kill` - kills a background command
|
||||
* `id` - the ID of the background command to kill
|
||||
* `browse` - opens a web page. Arguments:
|
||||
* `url` - the URL to open
|
||||
* `recall` - recalls a past memory. Arguments:
|
||||
* `query` - the query to search for
|
||||
* `think` - make a plan, set a goal, or record your thoughts. Arguments:
|
||||
* `thought` - the thought to record
|
||||
* `finish` - if you're absolutely certain that you've completed your task and have tested your work, use the finish action to stop working.
|
||||
|
||||
%(background_commands)s
|
||||
|
||||
You MUST take time to think in between read, write, run, browse, and recall actions.
|
||||
You should never act twice in a row without thinking. But if your last several
|
||||
actions are all "think" actions, you should consider taking a different action.
|
||||
|
||||
Notes:
|
||||
* your environment is Debian Linux. You can install software with `apt`
|
||||
* your working directory will not change, even if you run `cd`. All commands will be run in the `/workspace` directory.
|
||||
* don't run interactive commands, or commands that don't return (e.g. `node server.js`). You may run commands in the background (e.g. `node server.js &`)
|
||||
|
||||
What is your next thought or action? Again, you must reply with JSON, and only with JSON.
|
||||
|
||||
%(hint)s
|
||||
"""
|
||||
|
||||
MONOLOGUE_SUMMARY_PROMPT = """
|
||||
Below is the internal monologue of an automated LLM agent. Each
|
||||
thought is an item in a JSON array. The thoughts may be memories,
|
||||
actions taken by the agent, or outputs from those actions.
|
||||
Please return a new, smaller JSON array, which summarizes the
|
||||
internal monologue. You can summarize individual thoughts, and
|
||||
you can condense related thoughts together with a description
|
||||
of their content.
|
||||
|
||||
%(monologue)s
|
||||
|
||||
Make the summaries as pithy and informative as possible.
|
||||
Be specific about what happened and what was learned. The summary
|
||||
will be used as keywords for searching for the original memory.
|
||||
Be sure to preserve any key words or important information.
|
||||
|
||||
Your response must be in JSON format. It must be an object with the
|
||||
key `new_monologue`, which is a JSON array containing the summarized monologue.
|
||||
Each entry in the array must have an `action` key, and an `args` key.
|
||||
The action key may be `summarize`, and `args.summary` should contain the summary.
|
||||
You can also use the same action and args from the source monologue.
|
||||
"""
|
||||
|
||||
|
||||
def get_summarize_monologue_prompt(thoughts: List[dict]):
|
||||
"""
|
||||
Gets the prompt for summarizing the monologue
|
||||
|
||||
Returns:
|
||||
- str: A formatted string with the current monologue within the prompt
|
||||
"""
|
||||
return MONOLOGUE_SUMMARY_PROMPT % {
|
||||
'monologue': json.dumps({'old_monologue': thoughts}, indent=2),
|
||||
}
|
||||
|
||||
|
||||
def get_request_action_prompt(
|
||||
task: str,
|
||||
thoughts: List[dict],
|
||||
background_commands_obs: List[CmdOutputObservation] = [],
|
||||
):
|
||||
"""
|
||||
Gets the action prompt formatted with appropriate values.
|
||||
|
||||
Parameters:
|
||||
- task (str): The current task the agent is trying to accomplish
|
||||
- thoughts (List[dict]): The agent's current thoughts
|
||||
- background_commands_obs (List[CmdOutputObservation]): List of all observed background commands running
|
||||
|
||||
Returns:
|
||||
- str: Formatted prompt string with hint, task, monologue, and background included
|
||||
"""
|
||||
|
||||
hint = ''
|
||||
if len(thoughts) > 0:
|
||||
latest_thought = thoughts[-1]
|
||||
if 'action' in latest_thought:
|
||||
if latest_thought['action'] == 'think':
|
||||
if latest_thought['args']['thought'].startswith('OK so my task is'):
|
||||
hint = "You're just getting started! What should you do first?"
|
||||
else:
|
||||
hint = "You've been thinking a lot lately. Maybe it's time to take action?"
|
||||
elif latest_thought['action'] == 'error':
|
||||
hint = 'Looks like that last command failed. Maybe you need to fix it, or try something else.'
|
||||
|
||||
bg_commands_message = ''
|
||||
if len(background_commands_obs) > 0:
|
||||
bg_commands_message = 'The following commands are running in the background:'
|
||||
for command_obs in background_commands_obs:
|
||||
bg_commands_message += (
|
||||
f'\n`{command_obs.command_id}`: {command_obs.command}'
|
||||
)
|
||||
bg_commands_message += '\nYou can end any process by sending a `kill` action with the numerical `id` above.'
|
||||
|
||||
return ACTION_PROMPT % {
|
||||
'task': task,
|
||||
'monologue': json.dumps(thoughts, indent=2),
|
||||
'background_commands': bg_commands_message,
|
||||
'hint': hint,
|
||||
}
|
||||
|
||||
|
||||
def parse_action_response(response: str) -> Action:
|
||||
"""
|
||||
Parses a string to find an action within it
|
||||
|
||||
Parameters:
|
||||
- response (str): The string to be parsed
|
||||
|
||||
Returns:
|
||||
- Action: The action that was found in the response string
|
||||
"""
|
||||
try:
|
||||
action_dict = json.loads(response)
|
||||
except JSONDecodeError:
|
||||
# Find response-looking json in the output and use the more promising one. Helps with weak llms
|
||||
response_json_matches = re.finditer(
|
||||
r"""{\s*\"action\":\s?\"(\w+)\"(?:,?|,\s*\"args\":\s?{((?:.|\s)*?)})\s*}""",
|
||||
response) # Find all response-looking strings
|
||||
|
||||
def rank(match):
|
||||
return len(match[2]) if match[1] == 'think' else 130 # Crudely rank multiple responses by length
|
||||
try:
|
||||
action_dict = json.loads(max(response_json_matches, key=rank)[0]) # Use the highest ranked response
|
||||
except ValueError as e:
|
||||
raise LLMOutputError(
|
||||
"Output from the LLM isn't properly formatted. The model may be misconfigured."
|
||||
) from e
|
||||
if 'content' in action_dict:
|
||||
# The LLM gets confused here. Might as well be robust
|
||||
action_dict['contents'] = action_dict.pop('content')
|
||||
return action_from_dict(action_dict)
|
||||
|
||||
|
||||
def parse_summary_response(response: str) -> List[dict]:
|
||||
"""
|
||||
Parses a summary of the monologue
|
||||
|
||||
Parameters:
|
||||
- response (str): The response string to be parsed
|
||||
|
||||
Returns:
|
||||
- List[dict]: The list of summaries output by the model
|
||||
"""
|
||||
parsed = json.loads(response)
|
||||
return parsed['new_monologue']
|
||||
@@ -1,4 +0,0 @@
|
||||
from opendevin.agent import Agent
|
||||
from .agent import PlannerAgent
|
||||
|
||||
Agent.register('PlannerAgent', PlannerAgent)
|
||||
@@ -1,50 +0,0 @@
|
||||
from typing import List
|
||||
from .prompt import get_prompt, parse_response
|
||||
|
||||
from opendevin.agent import Agent
|
||||
from opendevin.action import AgentFinishAction
|
||||
from opendevin.llm.llm import LLM
|
||||
from opendevin.state import State
|
||||
from opendevin.action import Action
|
||||
|
||||
|
||||
class PlannerAgent(Agent):
|
||||
"""
|
||||
The planner agent utilizes a special prompting strategy to create long term plans for solving problems.
|
||||
The agent is given its previous action-observation pairs, current task, and hint based on last action taken at every step.
|
||||
"""
|
||||
|
||||
def __init__(self, llm: LLM):
|
||||
"""
|
||||
Initialize the Planner Agent with an LLM
|
||||
|
||||
Parameters:
|
||||
- llm (LLM): The llm to be used by this agent
|
||||
"""
|
||||
super().__init__(llm)
|
||||
|
||||
def step(self, state: State) -> Action:
|
||||
"""
|
||||
Checks to see if current step is completed, returns AgentFinishAction if True.
|
||||
Otherwise, creates a plan prompt and sends to model for inference, returning the result as the next action.
|
||||
|
||||
Parameters:
|
||||
- state (State): The current state given the previous actions and observations
|
||||
|
||||
Returns:
|
||||
- AgentFinishAction: If the last state was 'completed', 'verified', or 'abandoned'
|
||||
- Action: The next action to take based on llm response
|
||||
"""
|
||||
|
||||
if state.plan.task.state in ['completed', 'verified', 'abandoned']:
|
||||
return AgentFinishAction()
|
||||
prompt = get_prompt(state.plan, state.history)
|
||||
messages = [{'content': prompt, 'role': 'user'}]
|
||||
resp = self.llm.completion(messages=messages)
|
||||
action_resp = resp['choices'][0]['message']['content']
|
||||
state.num_of_chars += len(prompt) + len(action_resp)
|
||||
action = parse_response(action_resp)
|
||||
return action
|
||||
|
||||
def search_memory(self, query: str) -> List[str]:
|
||||
return []
|
||||
@@ -1,228 +0,0 @@
|
||||
import json
|
||||
from typing import List, Tuple, Dict, Type
|
||||
from opendevin.plan import Plan
|
||||
from opendevin.action import Action, action_from_dict
|
||||
from opendevin.observation import Observation
|
||||
from opendevin.schema import ActionType
|
||||
from opendevin.logger import opendevin_logger as logger
|
||||
|
||||
from opendevin.action import (
|
||||
NullAction,
|
||||
CmdRunAction,
|
||||
CmdKillAction,
|
||||
BrowseURLAction,
|
||||
FileReadAction,
|
||||
FileWriteAction,
|
||||
AgentRecallAction,
|
||||
AgentThinkAction,
|
||||
AgentFinishAction,
|
||||
AgentSummarizeAction,
|
||||
AddTaskAction,
|
||||
ModifyTaskAction,
|
||||
)
|
||||
|
||||
from opendevin.observation import (
|
||||
NullObservation,
|
||||
)
|
||||
|
||||
ACTION_TYPE_TO_CLASS: Dict[str, Type[Action]] = {
|
||||
ActionType.RUN: CmdRunAction,
|
||||
ActionType.KILL: CmdKillAction,
|
||||
ActionType.BROWSE: BrowseURLAction,
|
||||
ActionType.READ: FileReadAction,
|
||||
ActionType.WRITE: FileWriteAction,
|
||||
ActionType.RECALL: AgentRecallAction,
|
||||
ActionType.THINK: AgentThinkAction,
|
||||
ActionType.SUMMARIZE: AgentSummarizeAction,
|
||||
ActionType.FINISH: AgentFinishAction,
|
||||
ActionType.ADD_TASK: AddTaskAction,
|
||||
ActionType.MODIFY_TASK: ModifyTaskAction,
|
||||
}
|
||||
|
||||
HISTORY_SIZE = 10
|
||||
|
||||
prompt = """
|
||||
# Task
|
||||
You're a diligent software engineer AI. You can't see, draw, or interact with a
|
||||
browser, but you can read and write files, and you can run commands, and you can think.
|
||||
|
||||
You've been given the following task:
|
||||
|
||||
%(task)s
|
||||
|
||||
## Plan
|
||||
As you complete this task, you're building a plan and keeping
|
||||
track of your progress. Here's a JSON representation of your plan:
|
||||
|
||||
%(plan)s
|
||||
|
||||
|
||||
%(plan_status)s
|
||||
|
||||
You're responsible for managing this plan and the status of tasks in
|
||||
it, by using the `add_task` and `modify_task` actions described below.
|
||||
|
||||
If the History below contradicts the state of any of these tasks, you
|
||||
MUST modify the task using the `modify_task` action described below.
|
||||
|
||||
Be sure NOT to duplicate any tasks. Do NOT use the `add_task` action for
|
||||
a task that's already represented. Every task must be represented only once.
|
||||
|
||||
Tasks that are sequential MUST be siblings. They must be added in order
|
||||
to their parent task.
|
||||
|
||||
If you mark a task as 'completed', 'verified', or 'abandoned',
|
||||
all non-abandoned subtasks will be marked the same way.
|
||||
So before closing a task this way, you MUST not only be sure that it has
|
||||
been completed successfully--you must ALSO be sure that all its subtasks
|
||||
are ready to be marked the same way.
|
||||
|
||||
If, and only if, ALL tasks have already been marked verified,
|
||||
you MUST respond with the `finish` action.
|
||||
|
||||
## History
|
||||
Here is a recent history of actions you've taken in service of this plan,
|
||||
as well as observations you've made. This only includes the MOST RECENT
|
||||
ten actions--more happened before that.
|
||||
|
||||
%(history)s
|
||||
|
||||
|
||||
Your most recent action is at the bottom of that history.
|
||||
|
||||
## Action
|
||||
What is your next thought or action? Your response must be in JSON format.
|
||||
|
||||
It must be an object, and it must contain two fields:
|
||||
* `action`, which is one of the actions below
|
||||
* `args`, which is a map of key-value pairs, specifying the arguments for that action
|
||||
|
||||
* `read` - reads the content of a file. Arguments:
|
||||
* `path` - the path of the file to read
|
||||
* `write` - writes the content to a file. Arguments:
|
||||
* `path` - the path of the file to write
|
||||
* `content` - the content to write to the file
|
||||
* `run` - runs a command on the command line in a Linux shell. Arguments:
|
||||
* `command` - the command to run
|
||||
* `background` - if true, run the command in the background, so that other commands can be run concurrently. Useful for e.g. starting a server. You won't be able to see the logs. You don't need to end the command with `&`, just set this to true.
|
||||
* `kill` - kills a background command
|
||||
* `id` - the ID of the background command to kill
|
||||
* `browse` - opens a web page. Arguments:
|
||||
* `url` - the URL to open
|
||||
* `think` - make a plan, set a goal, or record your thoughts. Arguments:
|
||||
* `thought` - the thought to record
|
||||
* `add_task` - add a task to your plan. Arguments:
|
||||
* `parent` - the ID of the parent task
|
||||
* `goal` - the goal of the task
|
||||
* `subtasks` - a list of subtasks, each of which is a map with a `goal` key.
|
||||
* `modify_task` - close a task. Arguments:
|
||||
* `id` - the ID of the task to close
|
||||
* `state` - set to 'in_progress' to start the task, 'completed' to finish it, 'verified' to assert that it was successful, 'abandoned' to give up on it permanently, or `open` to stop working on it for now.
|
||||
* `finish` - if ALL of your tasks and subtasks have been verified or abandoned, and you're absolutely certain that you've completed your task and have tested your work, use the finish action to stop working.
|
||||
|
||||
You MUST take time to think in between read, write, run, browse, and recall actions.
|
||||
You should never act twice in a row without thinking. But if your last several
|
||||
actions are all `think` actions, you should consider taking a different action.
|
||||
|
||||
What is your next thought or action? Again, you must reply with JSON, and only with JSON.
|
||||
|
||||
%(hint)s
|
||||
"""
|
||||
|
||||
|
||||
def get_prompt(plan: Plan, history: List[Tuple[Action, Observation]]) -> str:
|
||||
"""
|
||||
Gets the prompt for the planner agent.
|
||||
Formatted with the most recent action-observation pairs, current task, and hint based on last action
|
||||
|
||||
Parameters:
|
||||
- plan (Plan): The original plan outlined by the user with LLM defined tasks
|
||||
- history (List[Tuple[Action, Observation]]): List of corresponding action-observation pairs
|
||||
|
||||
Returns:
|
||||
- str: The formatted string prompt with historical values
|
||||
"""
|
||||
|
||||
plan_str = json.dumps(plan.task.to_dict(), indent=2)
|
||||
sub_history = history[-HISTORY_SIZE:]
|
||||
history_dicts = []
|
||||
latest_action: Action = NullAction()
|
||||
for action, observation in sub_history:
|
||||
if not isinstance(action, NullAction):
|
||||
history_dicts.append(action.to_dict())
|
||||
latest_action = action
|
||||
if not isinstance(observation, NullObservation):
|
||||
observation_dict = observation.to_dict()
|
||||
if (
|
||||
'extras' in observation_dict
|
||||
and 'screenshot' in observation_dict['extras']
|
||||
):
|
||||
del observation_dict['extras']['screenshot']
|
||||
history_dicts.append(observation_dict)
|
||||
history_str = json.dumps(history_dicts, indent=2)
|
||||
|
||||
hint = ''
|
||||
current_task = plan.get_current_task()
|
||||
if current_task is not None:
|
||||
plan_status = f"You're currently working on this task:\n{current_task.goal}."
|
||||
if len(current_task.subtasks) == 0:
|
||||
plan_status += "\nIf it's not achievable AND verifiable with a SINGLE action, you MUST break it down into subtasks NOW."
|
||||
else:
|
||||
plan_status = "You're not currently working on any tasks. Your next action MUST be to mark a task as in_progress."
|
||||
hint = plan_status
|
||||
|
||||
latest_action_id = latest_action.to_dict()['action']
|
||||
|
||||
if current_task is not None:
|
||||
if latest_action_id == '':
|
||||
hint = "You haven't taken any actions yet. Start by using `ls` to check out what files you're working with."
|
||||
elif latest_action_id == ActionType.RUN:
|
||||
hint = 'You should think about the command you just ran, what output it gave, and how that affects your plan.'
|
||||
elif latest_action_id == ActionType.READ:
|
||||
hint = 'You should think about the file you just read, what you learned from it, and how that affects your plan.'
|
||||
elif latest_action_id == ActionType.WRITE:
|
||||
hint = 'You just changed a file. You should think about how it affects your plan.'
|
||||
elif latest_action_id == ActionType.BROWSE:
|
||||
hint = 'You should think about the page you just visited, and what you learned from it.'
|
||||
elif latest_action_id == ActionType.THINK:
|
||||
hint = "Look at your last thought in the history above. What does it suggest? Don't think anymore--take action."
|
||||
elif latest_action_id == ActionType.RECALL:
|
||||
hint = 'You should think about the information you just recalled, and how it should affect your plan.'
|
||||
elif latest_action_id == ActionType.ADD_TASK:
|
||||
hint = 'You should think about the next action to take.'
|
||||
elif latest_action_id == ActionType.MODIFY_TASK:
|
||||
hint = 'You should think about the next action to take.'
|
||||
elif latest_action_id == ActionType.SUMMARIZE:
|
||||
hint = ''
|
||||
elif latest_action_id == ActionType.FINISH:
|
||||
hint = ''
|
||||
|
||||
logger.info('HINT:\n' + hint, extra={'msg_type': 'INFO'})
|
||||
return prompt % {
|
||||
'task': plan.main_goal,
|
||||
'plan': plan_str,
|
||||
'history': history_str,
|
||||
'hint': hint,
|
||||
'plan_status': plan_status,
|
||||
}
|
||||
|
||||
|
||||
def parse_response(response: str) -> Action:
|
||||
"""
|
||||
Parses the model output to find a valid action to take
|
||||
|
||||
Parameters:
|
||||
- response (str): A response from the model that potentially contains an Action.
|
||||
|
||||
Returns:
|
||||
- Action: A valid next action to perform from model output
|
||||
"""
|
||||
json_start = response.find('{')
|
||||
json_end = response.rfind('}') + 1
|
||||
response = response[json_start:json_end]
|
||||
action_dict = json.loads(response)
|
||||
if 'contents' in action_dict:
|
||||
# The LLM gets confused here. Might as well be robust
|
||||
action_dict['content'] = action_dict.pop('contents')
|
||||
action = action_from_dict(action_dict)
|
||||
return action
|
||||
File diff suppressed because one or more lines are too long
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|
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|
After Width: | Height: | Size: 14 KiB |
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File diff suppressed because one or more lines are too long
@@ -0,0 +1 @@
|
||||
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||||
@@ -0,0 +1 @@
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