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 +0,0 @@
|
||||
*.ipynb linguist-vendored
|
||||
@@ -1,40 +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
|
||||
```
|
||||
|
||||
<!-- tell us everything about your environment -->
|
||||
**My config.toml and environment vars** (be sure to redact API keys):
|
||||
```toml
|
||||
```
|
||||
|
||||
**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**
|
||||
@@ -1,18 +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**
|
||||
@@ -1,17 +0,0 @@
|
||||
name: Build & Run Tests
|
||||
|
||||
on: [push, pull_request]
|
||||
|
||||
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: Run tests
|
||||
run: |
|
||||
make build
|
||||
poetry run pytest ./tests
|
||||
@@ -1,59 +0,0 @@
|
||||
name: Build and publish multi-arch container images
|
||||
|
||||
on:
|
||||
push:
|
||||
branches: [ main ]
|
||||
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 != ''
|
||||
|
||||
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 ${{ github.actor }} --password-stdin
|
||||
|
||||
- name: Build and push multi-arch container images
|
||||
run: |
|
||||
# set env for fork repo
|
||||
DOCKER_BUILD_ORG=$(echo "${{ github.repository }}" | tr '[A-Z]' '[a-z]' | cut -d '/' -f 1)
|
||||
# Find directories containing Dockerfile but not containing .dockerfileignore
|
||||
while IFS= read -r dockerfile_dir; do
|
||||
|
||||
# Check if .dockerfileignore exists in the directory
|
||||
if [ -f "$dockerfile_dir/.dockerfileignore" ]; then
|
||||
echo "$dockerfile_dir/.dockerfileignore exists, skipping build and push"
|
||||
continue
|
||||
fi
|
||||
|
||||
# Check if image was already exist in ghcr.io
|
||||
pushd "$dockerfile_dir" > /dev/null
|
||||
FULL_IMAGE=$(make get-full-image DOCKER_BUILD_ORG=$DOCKER_BUILD_ORG)
|
||||
popd > /dev/null
|
||||
EXISTS=$(docker manifest inspect "$FULL_IMAGE" > /dev/null 2>&1 && echo "true" || echo "false")
|
||||
if [ "$EXISTS" == "true" ]; then
|
||||
echo "Image $FULL_IMAGE already exists in ghcr.io, skipping build and push"
|
||||
continue
|
||||
fi
|
||||
|
||||
# Build and push the image to ghcr.io
|
||||
pushd "$dockerfile_dir" > /dev/null
|
||||
make all DOCKER_BUILD_ORG=$DOCKER_BUILD_ORG
|
||||
popd > /dev/null
|
||||
done < <(find . -type f -name Dockerfile -exec dirname {} \; | sort -u)
|
||||
@@ -1,47 +0,0 @@
|
||||
name: Lint
|
||||
|
||||
on: [push, pull_request]
|
||||
|
||||
jobs:
|
||||
lint-frontend:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v2
|
||||
|
||||
- name: Install PNPM
|
||||
uses: pnpm/action-setup@v2
|
||||
with:
|
||||
package_json_file: frontend/package.json
|
||||
|
||||
- name: Install Node.js 20
|
||||
uses: actions/setup-node@v2
|
||||
with:
|
||||
node-version: 20
|
||||
cache: 'pnpm'
|
||||
cache-dependency-path: 'frontend/pnpm-lock.yaml'
|
||||
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
cd frontend
|
||||
pnpm install --frozen-lockfile
|
||||
|
||||
- name: Lint
|
||||
run: |
|
||||
cd frontend
|
||||
pnpm run lint
|
||||
|
||||
lint-python:
|
||||
name: Lint python
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v2
|
||||
- name: Set up python
|
||||
uses: actions/setup-python@v2
|
||||
with:
|
||||
python-version: 3.11
|
||||
- name: Install dependencies
|
||||
run: pip install ruff mypy
|
||||
- name: Run ruff
|
||||
run: ruff check --config dev_config/python/ruff.toml opendevin/ agenthub/
|
||||
- name: Run mypy
|
||||
run: mypy --install-types --non-interactive --config-file dev_config/python/mypy.ini opendevin/ agenthub/
|
||||
-203
@@ -1,203 +0,0 @@
|
||||
# Byte-compiled / optimized / DLL files
|
||||
__pycache__/
|
||||
*.py[cod]
|
||||
*$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
|
||||
|
||||
# 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.
|
||||
|
||||
@@ -1,25 +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.
|
||||
@@ -1,102 +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-4-0125-preview"
|
||||
CONFIG_FILE = config.toml
|
||||
PRECOMMIT_CONFIG_PATH = "./dev_config/python/.pre-commit-config.yaml"
|
||||
|
||||
# Build
|
||||
build:
|
||||
@echo "Building project..."
|
||||
@echo "Pulling Docker image..."
|
||||
@docker pull $(DOCKER_IMAGE)
|
||||
@echo "Installing Python dependencies..."
|
||||
@curl -sSL https://install.python-poetry.org | python3 -
|
||||
@poetry install --without evaluation
|
||||
@echo "Activating Poetry shell..."
|
||||
@echo "Installing pre-commit hooks..."
|
||||
@poetry run pre-commit install --config $(PRECOMMIT_CONFIG_PATH)
|
||||
@echo "Setting up frontend environment..."
|
||||
@echo "Detect Node.js version..."
|
||||
@cd frontend && node ./scripts/detect-node-version.js
|
||||
@cd frontend && if [ -f node_modules/.package-lock.json ]; then \
|
||||
echo "This project currently uses \"pnpm\" for dependency management. It has detected that dependencies were previously installed using \"npm\" and has automatically deleted the \"node_modules\" directory to prevent unnecessary conflicts."; \
|
||||
rm -rf node_modules; \
|
||||
fi
|
||||
@which corepack > /dev/null || (echo "Installing corepack..." && npm install -g corepack)
|
||||
@cd frontend && sudo corepack enable && pnpm install && pnpm run make-i18n
|
||||
|
||||
# Start backend
|
||||
start-backend:
|
||||
@echo "Starting backend..."
|
||||
@poetry run uvicorn opendevin.server.listen:app --port $(BACKEND_PORT)
|
||||
|
||||
# Start frontend
|
||||
start-frontend:
|
||||
@echo "Starting frontend..."
|
||||
@cd frontend && BACKEND_HOST=$(BACKEND_HOST) FRONTEND_PORT=$(FRONTEND_PORT) pnpm run start
|
||||
|
||||
# Run the app
|
||||
run:
|
||||
@echo "Running the app..."
|
||||
@if [ "$(OS)" = "Windows_NT" ]; then \
|
||||
echo "`make run` is not supported on Windows. Please run `make start-frontend` and `make start-backend` separately."; \
|
||||
exit 1; \
|
||||
fi
|
||||
@mkdir -p logs
|
||||
@poetry run nohup uvicorn opendevin.server.listen:app --port $(BACKEND_PORT) > logs/backend_$(shell date +'%Y%m%d_%H%M%S').log 2>&1 &
|
||||
@echo "Waiting for the backend to start..."
|
||||
@until nc -z localhost $(BACKEND_PORT); do sleep 0.1; done
|
||||
@cd frontend && pnpm run start -- --port $(FRONTEND_PORT)
|
||||
|
||||
# Setup config.toml
|
||||
setup-config:
|
||||
@echo "Setting up config.toml..."
|
||||
@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=\"$$llm_api_key\"" >> $(CONFIG_FILE).tmp
|
||||
|
||||
@echo "Enter your LLM Embedding Model\nChoices are openai, azureopenai, llama2 or leave blank to default to 'BAAI/bge-small-en-v1.5' via huggingface"; \
|
||||
read -p "> " llm_embedding_model; \
|
||||
echo "LLM_EMBEDDING_MODEL=\"$$llm_embedding_model\"" >> $(CONFIG_FILE).tmp; \
|
||||
if [ "$$llm_embedding_model" = "llama2" ]; then \
|
||||
read -p "Enter the local model URL: " llm_base_url; \
|
||||
echo "LLM_BASE_URL=\"$$llm_base_url\"" >> $(CONFIG_FILE).tmp; \
|
||||
elif [ "$$llm_embedding_model" = "azureopenai" ]; then \
|
||||
read -p "Enter the Azure endpoint URL: " llm_base_url; \
|
||||
echo "LLM_BASE_URL=\"$$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=$${workspace_dir:-$(DEFAULT_WORKSPACE_DIR)}; \
|
||||
echo "WORKSPACE_DIR=\"$$workspace_dir\"" >> $(CONFIG_FILE).tmp
|
||||
|
||||
@mv $(CONFIG_FILE).tmp $(CONFIG_FILE)
|
||||
|
||||
# Help
|
||||
help:
|
||||
@echo "Usage: make [target]"
|
||||
@echo "Targets:"
|
||||
@echo " build - Build project, including environment setup and dependencies."
|
||||
@echo " build-eval - Build project evaluation pipeline, including environment setup and dependencies."
|
||||
@echo " start-backend - Start the backend server for the OpenDevin project."
|
||||
@echo " start-frontend - Start the frontend server for the OpenDevin project."
|
||||
@echo " run - Run the OpenDevin application, starting both backend and frontend servers."
|
||||
@echo " Backend Log file will be stored in the 'logs' directory."
|
||||
@echo " setup-config - Setup the configuration for OpenDevin by providing LLM API key, LLM Model name, and workspace directory."
|
||||
@echo " help - Display this help message, providing information on available targets."
|
||||
|
||||
# Phony targets
|
||||
.PHONY: build build-eval start-backend start-frontend run setup-config help
|
||||
@@ -1,253 +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>
|
||||
</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>
|
||||
|
||||
## 🚀 Get Started
|
||||
|
||||
Getting started with the OpenDevin project is incredibly easy. Follow these simple steps to set up and run OpenDevin on your system:
|
||||
|
||||
### 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
|
||||
|
||||
### 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.
|
||||
|
||||
2. **Manual Config: The Artisanal Touch**
|
||||
If you're feeling particularly adventurous, you can manually update the `config.toml` file located in the project's root directory. Here, you'll find the `llm_api_key` and `llm_model_name` fields, where you can set the LM of your choosing.
|
||||
|
||||
**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).
|
||||
|
||||
### 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
|
||||
```
|
||||
|
||||
<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>
|
||||
|
||||
## ⭐️ 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
|
||||
|
||||
Join our Slack workspace by filling out the [form](https://forms.gle/758d5p6Ve8r2nxxq6). Stay updated on OpenDevin's progress, share ideas, and collaborate with fellow enthusiasts and experts. 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']
|
||||
@@ -1,21 +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.
|
||||
|
||||
A minimalistic example can be found at [research/codeact/examples/run_flask_server_with_bash.py](./examples/run_flask_server_with_bash.py):
|
||||
|
||||
```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)
|
||||
@@ -1,119 +0,0 @@
|
||||
import re
|
||||
from typing import List, Mapping
|
||||
|
||||
|
||||
from opendevin.agent import Agent
|
||||
from opendevin.state import State
|
||||
from opendevin.action import (
|
||||
Action,
|
||||
CmdRunAction,
|
||||
AgentEchoAction,
|
||||
AgentFinishAction,
|
||||
)
|
||||
from opendevin.observation import (
|
||||
CmdOutputObservation,
|
||||
AgentMessageObservation,
|
||||
)
|
||||
|
||||
from opendevin.llm.llm import LLM
|
||||
|
||||
SYSTEM_MESSAGE = """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>
|
||||
|
||||
When you are done, execute "exit" to close the shell and end the conversation.
|
||||
"""
|
||||
|
||||
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):
|
||||
def __init__(
|
||||
self,
|
||||
llm: LLM,
|
||||
) -> None:
|
||||
"""
|
||||
Initializes a new instance of the CodeActAgent class.
|
||||
|
||||
Parameters:
|
||||
- instruction (str): The instruction for the agent to execute.
|
||||
- max_steps (int): The maximum number of steps to run the agent.
|
||||
"""
|
||||
super().__init__(llm)
|
||||
self.messages: List[Mapping[str, str]] = []
|
||||
|
||||
def step(self, state: State) -> Action:
|
||||
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,
|
||||
seed=42,
|
||||
)
|
||||
action_str: str = parse_response(response)
|
||||
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'"
|
||||
```
|
||||
@@ -1,9 +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)
|
||||
@@ -1,172 +0,0 @@
|
||||
from typing import List
|
||||
from opendevin.agent import Agent
|
||||
from opendevin.state import State
|
||||
from opendevin.llm.llm import LLM
|
||||
|
||||
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 $TASK. I haven't made any progress yet. Where should I start?",
|
||||
"It seems like there might be an existing project here. I should probably start by running `ls` to see what's here.",
|
||||
]
|
||||
|
||||
|
||||
class MonologueAgent(Agent):
|
||||
_initialized = False
|
||||
|
||||
def __init__(self, llm: LLM):
|
||||
super().__init__(llm)
|
||||
self.monologue = Monologue()
|
||||
self.memory = LongTermMemory()
|
||||
|
||||
def _add_event(self, event: dict):
|
||||
if "extras" in event and "screenshot" in event["extras"]:
|
||||
del event["extras"]["screenshot"]
|
||||
if 'args' in event and 'output' in event['args'] and len(event['args']['output']) > MAX_OUTPUT_LENGTH:
|
||||
event['args']['output'] = event['args']['output'][:MAX_OUTPUT_LENGTH] + "..."
|
||||
|
||||
self.monologue.add_event(event)
|
||||
self.memory.add_event(event)
|
||||
if self.monologue.get_total_length() > MAX_MONOLOGUE_LENGTH:
|
||||
self.monologue.condense(self.llm)
|
||||
|
||||
def _initialize(self, task):
|
||||
if self._initialized:
|
||||
return
|
||||
|
||||
if task is None or task == "":
|
||||
raise ValueError("Instruction must be provided")
|
||||
self.monologue = Monologue()
|
||||
self.memory = LongTermMemory()
|
||||
|
||||
output_type = ""
|
||||
for thought in INITIAL_THOUGHTS:
|
||||
thought = thought.replace("$TASK", task)
|
||||
if output_type != "":
|
||||
observation: Observation = NullObservation(content="")
|
||||
if output_type == "run":
|
||||
observation = CmdOutputObservation(content=thought, command_id=0, command="")
|
||||
elif output_type == "read":
|
||||
observation = FileReadObservation(content=thought, path="")
|
||||
elif output_type == "recall":
|
||||
observation = AgentRecallObservation(content=thought, memories=[])
|
||||
elif output_type == "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 = "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 = "read"
|
||||
elif thought.startswith("RECALL"):
|
||||
query = thought.split("RECALL ")[1]
|
||||
action = AgentRecallAction(query=query)
|
||||
output_type = "recall"
|
||||
elif thought.startswith("BROWSE"):
|
||||
url = thought.split("BROWSE ")[1]
|
||||
action = BrowseURLAction(url=url)
|
||||
output_type = "browse"
|
||||
else:
|
||||
action = AgentThinkAction(thought=thought)
|
||||
self._add_event(action.to_dict())
|
||||
self._initialized = True
|
||||
|
||||
def step(self, state: State) -> Action:
|
||||
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']
|
||||
action = prompts.parse_action_response(action_resp)
|
||||
self.latest_action = action
|
||||
return action
|
||||
|
||||
def search_memory(self, query: str) -> List[str]:
|
||||
return self.memory.search(query)
|
||||
|
||||
@@ -1,14 +0,0 @@
|
||||
import json
|
||||
from json_repair import repair_json
|
||||
|
||||
def my_encoder(obj):
|
||||
if hasattr(obj, "to_dict"):
|
||||
return obj.to_dict()
|
||||
|
||||
def dumps(obj, **kwargs):
|
||||
return json.dumps(obj, default=my_encoder, **kwargs)
|
||||
|
||||
def loads(s, **kwargs):
|
||||
s_repaired = repair_json(s)
|
||||
return json.loads(s_repaired, **kwargs)
|
||||
|
||||
@@ -1,79 +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 . 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_or_error("LLM_BASE_URL"),
|
||||
ollama_additional_kwargs={"mirostat": 0},
|
||||
)
|
||||
elif embedding_strategy == "openai":
|
||||
from llama_index.embeddings.openai import OpenAIEmbedding
|
||||
embed_model = OpenAIEmbedding(
|
||||
model="text-embedding-ada-002"
|
||||
)
|
||||
elif embedding_strategy == "azureopenai":
|
||||
from llama_index.embeddings.azure_openai import AzureOpenAIEmbedding # Need to instruct to set these env variables in documentation
|
||||
embed_model = AzureOpenAIEmbedding(
|
||||
model="text-embedding-ada-002",
|
||||
deployment_name=config.get_or_error("LLM_DEPLOYMENT_NAME"),
|
||||
api_key=config.get_or_error("LLM_API_KEY"),
|
||||
azure_endpoint=config.get_or_error("LLM_BASE_URL"),
|
||||
api_version=config.get_or_error("LLM_API_VERSION"),
|
||||
)
|
||||
else:
|
||||
from llama_index.embeddings.huggingface import HuggingFaceEmbedding
|
||||
embed_model = HuggingFaceEmbedding(
|
||||
model_name="BAAI/bge-small-en-v1.5"
|
||||
)
|
||||
|
||||
|
||||
class LongTermMemory:
|
||||
def __init__(self):
|
||||
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):
|
||||
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
|
||||
self.index.insert(doc)
|
||||
|
||||
def search(self, query, k=10):
|
||||
retriever = VectorIndexRetriever(
|
||||
index=self.index,
|
||||
similarity_top_k=k,
|
||||
)
|
||||
results = retriever.retrieve(query)
|
||||
return [r.get_text() for r in results]
|
||||
|
||||
|
||||
@@ -1,40 +0,0 @@
|
||||
import traceback
|
||||
|
||||
import agenthub.monologue_agent.utils.json as json
|
||||
import agenthub.monologue_agent.utils.prompts as prompts
|
||||
|
||||
class Monologue:
|
||||
def __init__(self):
|
||||
self.thoughts = []
|
||||
|
||||
def add_event(self, t: dict):
|
||||
if not isinstance(t, dict):
|
||||
raise ValueError("Event must be a dictionary")
|
||||
self.thoughts.append(t)
|
||||
|
||||
def get_thoughts(self):
|
||||
return self.thoughts
|
||||
|
||||
def get_total_length(self):
|
||||
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):
|
||||
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(strip_markdown(summary_resp))
|
||||
except Exception as e:
|
||||
traceback.print_exc()
|
||||
raise RuntimeError(f"Error condensing thoughts: {e}")
|
||||
|
||||
def strip_markdown(markdown_json):
|
||||
# remove markdown code block
|
||||
return markdown_json.replace('```json\n', '').replace('```', '').strip()
|
||||
@@ -1,139 +0,0 @@
|
||||
from typing import List
|
||||
|
||||
from . import json
|
||||
|
||||
from opendevin.action import (
|
||||
action_from_dict,
|
||||
Action,
|
||||
)
|
||||
from opendevin.observation import (
|
||||
CmdOutputObservation,
|
||||
)
|
||||
|
||||
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):
|
||||
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] = [],
|
||||
):
|
||||
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."
|
||||
latest_thought = thoughts[-1]
|
||||
|
||||
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:
|
||||
json_start = response.find("{")
|
||||
json_end = response.rfind("}") + 1
|
||||
response = response[json_start:json_end]
|
||||
action_dict = json.loads(response)
|
||||
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]:
|
||||
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)
|
||||
@@ -1,26 +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):
|
||||
def __init__(self, llm: LLM):
|
||||
super().__init__(llm)
|
||||
|
||||
def step(self, state: State) -> Action:
|
||||
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']
|
||||
action = parse_response(action_resp)
|
||||
return action
|
||||
|
||||
def search_memory(self, query: str) -> List[str]:
|
||||
return []
|
||||
|
||||
@@ -1,203 +0,0 @@
|
||||
import json
|
||||
from typing import List, Tuple, Dict, Type
|
||||
|
||||
from opendevin.controller.agent_controller import print_with_color
|
||||
from opendevin.plan import Plan
|
||||
from opendevin.action import Action, action_from_dict
|
||||
from opendevin.observation import Observation
|
||||
|
||||
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]] = {
|
||||
"run": CmdRunAction,
|
||||
"kill": CmdKillAction,
|
||||
"browse": BrowseURLAction,
|
||||
"read": FileReadAction,
|
||||
"write": FileWriteAction,
|
||||
"recall": AgentRecallAction,
|
||||
"think": AgentThinkAction,
|
||||
"summarize": AgentSummarizeAction,
|
||||
"finish": AgentFinishAction,
|
||||
"add_task": AddTaskAction,
|
||||
"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]]):
|
||||
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 == "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 == "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 == "write":
|
||||
hint = "You just changed a file. You should think about how it affects your plan."
|
||||
elif latest_action_id == "browse":
|
||||
hint = "You should think about the page you just visited, and what you learned from it."
|
||||
elif latest_action_id == "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 == "recall":
|
||||
hint = "You should think about the information you just recalled, and how it should affect your plan."
|
||||
elif latest_action_id == "add_task":
|
||||
hint = "You should think about the next action to take."
|
||||
elif latest_action_id == "modify_task":
|
||||
hint = "You should think about the next action to take."
|
||||
elif latest_action_id == "summarize":
|
||||
hint = ""
|
||||
elif latest_action_id == "finish":
|
||||
hint = ""
|
||||
|
||||
print_with_color("HINT:\n" + hint, "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:
|
||||
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
File diff suppressed because one or more lines are too long
|
After Width: | Height: | Size: 113 KiB |
File diff suppressed because one or more lines are too long
|
After Width: | Height: | Size: 14 KiB |
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[3396],{7729:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>a,contentTitle:()=>i,default:()=>u,frontMatter:()=>s,metadata:()=>l,toc:()=>c});var o=t(4848),r=t(8453);const s={sidebar_label:"memory",title:"agenthub.monologue_agent.utils.memory"},i=void 0,l={id:"python/agenthub/monologue_agent/utils/memory",title:"agenthub.monologue_agent.utils.memory",description:"LongTermMemory Objects",source:"@site/modules/python/agenthub/monologue_agent/utils/memory.md",sourceDirName:"python/agenthub/monologue_agent/utils",slug:"/python/agenthub/monologue_agent/utils/memory",permalink:"/OpenDevin/modules/python/agenthub/monologue_agent/utils/memory",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"memory",title:"agenthub.monologue_agent.utils.memory"},sidebar:"apiSidebar",previous:{title:"json",permalink:"/OpenDevin/modules/python/agenthub/monologue_agent/utils/json"},next:{title:"monologue",permalink:"/OpenDevin/modules/python/agenthub/monologue_agent/utils/monologue"}},a={},c=[{value:"LongTermMemory Objects",id:"longtermmemory-objects",level:2},{value:"__init__",id:"__init__",level:4},{value:"add_event",id:"add_event",level:4},{value:"search",id:"search",level:4}];function d(e){const n={code:"code",h2:"h2",h4:"h4",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,r.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(n.h2,{id:"longtermmemory-objects",children:"LongTermMemory Objects"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"class LongTermMemory()\n"})}),"\n",(0,o.jsx)(n.p,{children:"Responsible for storing information that the agent can call on later for better insights and context.\nUses chromadb to store and search through memories."}),"\n",(0,o.jsx)(n.h4,{id:"__init__",children:"__init__"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"def __init__()\n"})}),"\n",(0,o.jsx)(n.p,{children:"Initialize the chromadb and set up ChromaVectorStore for later use."}),"\n",(0,o.jsx)(n.h4,{id:"add_event",children:"add_event"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"def add_event(event: dict)\n"})}),"\n",(0,o.jsx)(n.p,{children:"Adds a new event to the long term memory with a unique id."}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Arguments"}),":"]}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsx)(n.li,{children:"event (dict): The new event to be added to memory"}),"\n"]}),"\n",(0,o.jsx)(n.h4,{id:"search",children:"search"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"def search(query: str, k: int = 10)\n"})}),"\n",(0,o.jsx)(n.p,{children:"Searches through the current memory using VectorIndexRetriever"}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Arguments"}),":"]}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsx)(n.li,{children:"query (str): A query to match search results to"}),"\n",(0,o.jsx)(n.li,{children:"k (int): Number of top results to return"}),"\n"]}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Returns"}),":"]}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsx)(n.li,{children:"List[str]: List of top k results found in current memory"}),"\n"]})]})}function u(e={}){const{wrapper:n}={...(0,r.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(d,{...e})}):d(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>i,x:()=>l});var o=t(6540);const r={},s=o.createContext(r);function i(e){const n=o.useContext(s);return o.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function l(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(r):e.components||r:i(e.components),o.createElement(s.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[4302],{1106:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>c,contentTitle:()=>i,default:()=>h,frontMatter:()=>a,metadata:()=>r,toc:()=>l});var o=t(4848),s=t(8453);const a={sidebar_label:"observation",title:"opendevin.schema.observation"},i=void 0,r={id:"python/opendevin/schema/observation",title:"opendevin.schema.observation",description:"ObservationTypeSchema Objects",source:"@site/modules/python/opendevin/schema/observation.md",sourceDirName:"python/opendevin/schema",slug:"/python/opendevin/schema/observation",permalink:"/OpenDevin/modules/python/opendevin/schema/observation",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"observation",title:"opendevin.schema.observation"},sidebar:"apiSidebar",previous:{title:"action",permalink:"/OpenDevin/modules/python/opendevin/schema/action"},next:{title:"task",permalink:"/OpenDevin/modules/python/opendevin/schema/task"}},c={},l=[{value:"ObservationTypeSchema Objects",id:"observationtypeschema-objects",level:2},{value:"READ",id:"read",level:4},{value:"BROWSE",id:"browse",level:4},{value:"RUN",id:"run",level:4},{value:"RECALL",id:"recall",level:4},{value:"CHAT",id:"chat",level:4},{value:"DELEGATE",id:"delegate",level:4}];function d(e){const n={code:"code",h2:"h2",h4:"h4",p:"p",pre:"pre",...(0,s.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(n.h2,{id:"observationtypeschema-objects",children:"ObservationTypeSchema Objects"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"class ObservationTypeSchema(BaseModel)\n"})}),"\n",(0,o.jsx)(n.h4,{id:"read",children:"READ"}),"\n",(0,o.jsx)(n.p,{children:"The content of a file"}),"\n",(0,o.jsx)(n.h4,{id:"browse",children:"BROWSE"}),"\n",(0,o.jsx)(n.p,{children:"The HTML content of a URL"}),"\n",(0,o.jsx)(n.h4,{id:"run",children:"RUN"}),"\n",(0,o.jsx)(n.p,{children:"The output of a command"}),"\n",(0,o.jsx)(n.h4,{id:"recall",children:"RECALL"}),"\n",(0,o.jsx)(n.p,{children:"The result of a search"}),"\n",(0,o.jsx)(n.h4,{id:"chat",children:"CHAT"}),"\n",(0,o.jsx)(n.p,{children:"A message from the user"}),"\n",(0,o.jsx)(n.h4,{id:"delegate",children:"DELEGATE"}),"\n",(0,o.jsx)(n.p,{children:"The result of a task delegated to another agent"})]})}function h(e={}){const{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(d,{...e})}):d(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>i,x:()=>r});var o=t(6540);const s={},a=o.createContext(s);function i(e){const n=o.useContext(a);return o.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function r(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(s):e.components||s:i(e.components),o.createElement(a.Provider,{value:n},e.children)}}}]);
|
||||
File diff suppressed because one or more lines are too long
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[4435],{3596:(n,e,i)=>{i.r(e),i.d(e,{assets:()=>r,contentTitle:()=>l,default:()=>a,frontMatter:()=>o,metadata:()=>p,toc:()=>d});var t=i(4848),s=i(8453);const o={sidebar_label:"mixin",title:"opendevin.sandbox.plugins.mixin"},l=void 0,p={id:"python/opendevin/sandbox/plugins/mixin",title:"opendevin.sandbox.plugins.mixin",description:"PluginMixin Objects",source:"@site/modules/python/opendevin/sandbox/plugins/mixin.md",sourceDirName:"python/opendevin/sandbox/plugins",slug:"/python/opendevin/sandbox/plugins/mixin",permalink:"/OpenDevin/modules/python/opendevin/sandbox/plugins/mixin",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"mixin",title:"opendevin.sandbox.plugins.mixin"},sidebar:"apiSidebar",previous:{title:"jupyter",permalink:"/OpenDevin/modules/python/opendevin/sandbox/plugins/jupyter/__init__"},next:{title:"requirement",permalink:"/OpenDevin/modules/python/opendevin/sandbox/plugins/requirement"}},r={},d=[{value:"PluginMixin Objects",id:"pluginmixin-objects",level:2},{value:"init_plugins",id:"init_plugins",level:4}];function u(n){const e={code:"code",h2:"h2",h4:"h4",p:"p",pre:"pre",...(0,s.R)(),...n.components};return(0,t.jsxs)(t.Fragment,{children:[(0,t.jsx)(e.h2,{id:"pluginmixin-objects",children:"PluginMixin Objects"}),"\n",(0,t.jsx)(e.pre,{children:(0,t.jsx)(e.code,{className:"language-python",children:"class PluginMixin()\n"})}),"\n",(0,t.jsx)(e.p,{children:"Mixin for Sandbox to support plugins."}),"\n",(0,t.jsx)(e.h4,{id:"init_plugins",children:"init_plugins"}),"\n",(0,t.jsx)(e.pre,{children:(0,t.jsx)(e.code,{className:"language-python",children:"def init_plugins(requirements: List[PluginRequirement])\n"})}),"\n",(0,t.jsx)(e.p,{children:"Load a plugin into the sandbox."})]})}function a(n={}){const{wrapper:e}={...(0,s.R)(),...n.components};return e?(0,t.jsx)(e,{...n,children:(0,t.jsx)(u,{...n})}):u(n)}},8453:(n,e,i)=>{i.d(e,{R:()=>l,x:()=>p});var t=i(6540);const s={},o=t.createContext(s);function l(n){const e=t.useContext(o);return t.useMemo((function(){return"function"==typeof n?n(e):{...e,...n}}),[e,n])}function p(n){let e;return e=n.disableParentContext?"function"==typeof n.components?n.components(s):n.components||s:l(n.components),t.createElement(o.Provider,{value:e},n.children)}}}]);
|
||||
File diff suppressed because one or more lines are too long
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[2237],{3363:(e,t,n)=>{n.d(t,{A:()=>a});n(6540);var i=n(4164),o=n(1312),s=n(1107),r=n(4848);function a(e){let{className:t}=e;return(0,r.jsx)("main",{className:(0,i.A)("container margin-vert--xl",t),children:(0,r.jsx)("div",{className:"row",children:(0,r.jsxs)("div",{className:"col col--6 col--offset-3",children:[(0,r.jsx)(s.A,{as:"h1",className:"hero__title",children:(0,r.jsx)(o.A,{id:"theme.NotFound.title",description:"The title of the 404 page",children:"Page Not Found"})}),(0,r.jsx)("p",{children:(0,r.jsx)(o.A,{id:"theme.NotFound.p1",description:"The first paragraph of the 404 page",children:"We could not find what you were looking for."})}),(0,r.jsx)("p",{children:(0,r.jsx)(o.A,{id:"theme.NotFound.p2",description:"The 2nd paragraph of the 404 page",children:"Please contact the owner of the site that linked you to the original URL and let them know their link is broken."})})]})})})}},2237:(e,t,n)=>{n.r(t),n.d(t,{default:()=>d});n(6540);var i=n(1312),o=n(1003),s=n(781),r=n(3363),a=n(4848);function d(){const e=(0,i.T)({id:"theme.NotFound.title",message:"Page Not Found"});return(0,a.jsxs)(a.Fragment,{children:[(0,a.jsx)(o.be,{title:e}),(0,a.jsx)(s.A,{children:(0,a.jsx)(r.A,{})})]})}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[1250],{7101:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>p,contentTitle:()=>i,default:()=>u,frontMatter:()=>r,metadata:()=>a,toc:()=>c});var o=t(4848),s=t(8453);const r={sidebar_label:"browse",title:"opendevin.observation.browse"},i=void 0,a={id:"python/opendevin/observation/browse",title:"opendevin.observation.browse",description:"BrowserOutputObservation Objects",source:"@site/modules/python/opendevin/observation/browse.md",sourceDirName:"python/opendevin/observation",slug:"/python/opendevin/observation/browse",permalink:"/OpenDevin/modules/python/opendevin/observation/browse",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"browse",title:"opendevin.observation.browse"},sidebar:"apiSidebar",previous:{title:"base",permalink:"/OpenDevin/modules/python/opendevin/observation/base"},next:{title:"delegate",permalink:"/OpenDevin/modules/python/opendevin/observation/delegate"}},p={},c=[{value:"BrowserOutputObservation Objects",id:"browseroutputobservation-objects",level:2}];function d(e){const n={code:"code",h2:"h2",p:"p",pre:"pre",...(0,s.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(n.h2,{id:"browseroutputobservation-objects",children:"BrowserOutputObservation Objects"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"@dataclass\nclass BrowserOutputObservation(Observation)\n"})}),"\n",(0,o.jsx)(n.p,{children:"This data class represents the output of a browser."})]})}function u(e={}){const{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(d,{...e})}):d(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>i,x:()=>a});var o=t(6540);const s={},r=o.createContext(s);function i(e){const n=o.useContext(r);return o.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function a(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(s):e.components||s:i(e.components),o.createElement(r.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[8878],{2207:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>a,contentTitle:()=>l,default:()=>h,frontMatter:()=>r,metadata:()=>i,toc:()=>c});var o=t(4848),s=t(8453);const r={sidebar_label:"agent",title:"agenthub.monologue_agent.agent"},l=void 0,i={id:"python/agenthub/monologue_agent/agent",title:"agenthub.monologue_agent.agent",description:"MonologueAgent Objects",source:"@site/modules/python/agenthub/monologue_agent/agent.md",sourceDirName:"python/agenthub/monologue_agent",slug:"/python/agenthub/monologue_agent/agent",permalink:"/OpenDevin/modules/python/agenthub/monologue_agent/agent",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"agent",title:"agenthub.monologue_agent.agent"},sidebar:"apiSidebar",previous:{title:"prompts",permalink:"/OpenDevin/modules/python/agenthub/monologue_agent/utils/prompts"},next:{title:"agent",permalink:"/OpenDevin/modules/python/agenthub/planner_agent/agent"}},a={},c=[{value:"MonologueAgent Objects",id:"monologueagent-objects",level:2},{value:"__init__",id:"__init__",level:4},{value:"step",id:"step",level:4},{value:"search_memory",id:"search_memory",level:4}];function d(e){const n={code:"code",h2:"h2",h4:"h4",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,s.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(n.h2,{id:"monologueagent-objects",children:"MonologueAgent Objects"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"class MonologueAgent(Agent)\n"})}),"\n",(0,o.jsx)(n.p,{children:"The Monologue Agent utilizes long and short term memory to complete tasks.\nLong term memory is stored as a LongTermMemory object and the model uses it to search for examples from the past.\nShort term memory is stored as a Monologue object and the model can condense it as necessary."}),"\n",(0,o.jsx)(n.h4,{id:"__init__",children:"__init__"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"def __init__(llm: LLM)\n"})}),"\n",(0,o.jsx)(n.p,{children:"Initializes the Monologue Agent with an llm, monologue, and memory."}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Arguments"}),":"]}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsx)(n.li,{children:"llm (LLM): The llm to be used by this agent"}),"\n"]}),"\n",(0,o.jsx)(n.h4,{id:"step",children:"step"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"def step(state: State) -> Action\n"})}),"\n",(0,o.jsx)(n.p,{children:"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."}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Arguments"}),":"]}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsx)(n.li,{children:"state (State): The current state based on previous steps taken"}),"\n"]}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Returns"}),":"]}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsx)(n.li,{children:"Action: The next action to take based on LLM response"}),"\n"]}),"\n",(0,o.jsx)(n.h4,{id:"search_memory",children:"search_memory"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"def search_memory(query: str) -> List[str]\n"})}),"\n",(0,o.jsx)(n.p,{children:"Uses VectorIndexRetriever to find related memories within the long term memory.\nUses search to produce top 10 results."}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Arguments"}),":"]}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsx)(n.li,{children:"query (str): The query that we want to find related memories for"}),"\n"]}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Returns"}),":"]}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsx)(n.li,{children:"List[str]: A list of top 10 text results that matched the query"}),"\n"]})]})}function h(e={}){const{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(d,{...e})}):d(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>l,x:()=>i});var o=t(6540);const s={},r=o.createContext(s);function l(e){const n=o.useContext(r);return o.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function i(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(s):e.components||s:l(e.components),o.createElement(r.Provider,{value:n},e.children)}}}]);
|
||||
File diff suppressed because one or more lines are too long
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[8659],{759:(n,e,t)=>{t.r(e),t.d(e,{assets:()=>c,contentTitle:()=>r,default:()=>l,frontMatter:()=>a,metadata:()=>s,toc:()=>p});var o=t(4848),i=t(8453);const a={sidebar_label:"action",title:"opendevin.action"},r=void 0,s={id:"python/opendevin/action/__init__",title:"opendevin.action",description:"ACTION\\TYPE\\TO\\_CLASS",source:"@site/modules/python/opendevin/action/__init__.md",sourceDirName:"python/opendevin/action",slug:"/python/opendevin/action/__init__",permalink:"/OpenDevin/modules/python/opendevin/action/__init__",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"action",title:"opendevin.action"},sidebar:"apiSidebar",previous:{title:"prompt",permalink:"/OpenDevin/modules/python/agenthub/planner_agent/prompt"},next:{title:"base",permalink:"/OpenDevin/modules/python/opendevin/action/base"}},c={},p=[{value:"ACTION_TYPE_TO_CLASS",id:"action_type_to_class",level:4}];function d(n){const e={h4:"h4",p:"p",...(0,i.R)(),...n.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(e.h4,{id:"action_type_to_class",children:"ACTION_TYPE_TO_CLASS"}),"\n",(0,o.jsx)(e.p,{children:"type: ignore[attr-defined]"})]})}function l(n={}){const{wrapper:e}={...(0,i.R)(),...n.components};return e?(0,o.jsx)(e,{...n,children:(0,o.jsx)(d,{...n})}):d(n)}},8453:(n,e,t)=>{t.d(e,{R:()=>r,x:()=>s});var o=t(6540);const i={},a=o.createContext(i);function r(n){const e=o.useContext(a);return o.useMemo((function(){return"function"==typeof n?n(e):{...e,...n}}),[e,n])}function s(n){let e;return e=n.disableParentContext?"function"==typeof n.components?n.components(i):n.components||i:r(n.components),o.createElement(a.Provider,{value:e},n.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[1865],{1790:(e,t,n)=>{n.r(t),n.d(t,{assets:()=>m,contentTitle:()=>s,default:()=>i,frontMatter:()=>u,metadata:()=>r,toc:()=>d});var a=n(4848),o=n(8453);const u={sidebar_label:"agent",title:"agenthub.dummy_agent.agent"},s=void 0,r={id:"python/agenthub/dummy_agent/agent",title:"agenthub.dummy_agent.agent",description:"Module for a Dummy agent.",source:"@site/modules/python/agenthub/dummy_agent/agent.md",sourceDirName:"python/agenthub/dummy_agent",slug:"/python/agenthub/dummy_agent/agent",permalink:"/OpenDevin/modules/python/agenthub/dummy_agent/agent",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"agent",title:"agenthub.dummy_agent.agent"},sidebar:"apiSidebar",previous:{title:"agent",permalink:"/OpenDevin/modules/python/agenthub/delegator_agent/agent"},next:{title:"agent",permalink:"/OpenDevin/modules/python/agenthub/micro/agent"}},m={},d=[{value:"DummyAgent Objects",id:"dummyagent-objects",level:2}];function c(e){const t={code:"code",h2:"h2",p:"p",pre:"pre",...(0,o.R)(),...e.components};return(0,a.jsxs)(a.Fragment,{children:[(0,a.jsx)(t.p,{children:"Module for a Dummy agent."}),"\n",(0,a.jsx)(t.h2,{id:"dummyagent-objects",children:"DummyAgent Objects"}),"\n",(0,a.jsx)(t.pre,{children:(0,a.jsx)(t.code,{className:"language-python",children:"class DummyAgent(Agent)\n"})}),"\n",(0,a.jsx)(t.p,{children:"A dummy agent that does nothing but can be used in testing."})]})}function i(e={}){const{wrapper:t}={...(0,o.R)(),...e.components};return t?(0,a.jsx)(t,{...e,children:(0,a.jsx)(c,{...e})}):c(e)}},8453:(e,t,n)=>{n.d(t,{R:()=>s,x:()=>r});var a=n(6540);const o={},u=a.createContext(o);function s(e){const t=a.useContext(u);return a.useMemo((function(){return"function"==typeof e?e(t):{...t,...e}}),[t,e])}function r(e){let t;return t=e.disableParentContext?"function"==typeof e.components?e.components(o):e.components||o:s(e.components),a.createElement(u.Provider,{value:t},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[9903],{9619:(e,n,s)=>{s.r(n),s.d(n,{assets:()=>a,contentTitle:()=>t,default:()=>u,frontMatter:()=>o,metadata:()=>l,toc:()=>d});var i=s(4848),r=s(8453);const o={sidebar_position:2},t="\ud83e\udd16 LLM Backends",l={id:"usage/llms/llms",title:"\ud83e\udd16 LLM Backends",description:"OpenDevin can work with any LLM backend.",source:"@site/modules/usage/llms/llms.md",sourceDirName:"usage/llms",slug:"/usage/llms/",permalink:"/OpenDevin/modules/usage/llms/",draft:!1,unlisted:!1,tags:[],version:"current",sidebarPosition:2,frontMatter:{sidebar_position:2},sidebar:"docsSidebar",previous:{title:"\ud83d\udcbb OpenDevin",permalink:"/OpenDevin/modules/usage/intro"},next:{title:"Azure OpenAI LLM",permalink:"/OpenDevin/modules/usage/llms/azureLLMs"}},a={},d=[{value:"Note on Alternative Models",id:"note-on-alternative-models",level:2},{value:"API retries and rate limits",id:"api-retries-and-rate-limits",level:2}];function c(e){const n={a:"a",admonition:"admonition",code:"code",h1:"h1",h2:"h2",li:"li",p:"p",ul:"ul",...(0,r.R)(),...e.components};return(0,i.jsxs)(i.Fragment,{children:[(0,i.jsx)(n.h1,{id:"-llm-backends",children:"\ud83e\udd16 LLM Backends"}),"\n",(0,i.jsxs)(n.p,{children:["OpenDevin can work with any LLM backend.\nFor a full list of the LM providers and models available, please consult the\n",(0,i.jsx)(n.a,{href:"https://docs.litellm.ai/docs/providers",children:"litellm documentation"}),"."]}),"\n",(0,i.jsx)(n.admonition,{type:"warning",children:(0,i.jsx)(n.p,{children:"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."})}),"\n",(0,i.jsxs)(n.p,{children:["The ",(0,i.jsx)(n.code,{children:"LLM_MODEL"})," environment variable controls which model is used in programmatic interactions.\nBut when using the OpenDevin UI, you'll need to choose your model in the settings window (the gear\nwheel on the bottom left)."]}),"\n",(0,i.jsx)(n.p,{children:"The following environment variables might be necessary for some LLMs:"}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsx)(n.li,{children:(0,i.jsx)(n.code,{children:"LLM_API_KEY"})}),"\n",(0,i.jsx)(n.li,{children:(0,i.jsx)(n.code,{children:"LLM_BASE_URL"})}),"\n",(0,i.jsx)(n.li,{children:(0,i.jsx)(n.code,{children:"LLM_EMBEDDING_MODEL"})}),"\n",(0,i.jsx)(n.li,{children:(0,i.jsx)(n.code,{children:"LLM_EMBEDDING_DEPLOYMENT_NAME"})}),"\n",(0,i.jsx)(n.li,{children:(0,i.jsx)(n.code,{children:"LLM_API_VERSION"})}),"\n"]}),"\n",(0,i.jsx)(n.p,{children:"We have a few guides for running OpenDevin with specific model providers:"}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsx)(n.li,{children:(0,i.jsx)(n.a,{href:"llms/localLLMs",children:"ollama"})}),"\n",(0,i.jsx)(n.li,{children:(0,i.jsx)(n.a,{href:"llms/azureLLMs",children:"Azure"})}),"\n"]}),"\n",(0,i.jsx)(n.p,{children:"If you're using another provider, we encourage you to open a PR to share your setup!"}),"\n",(0,i.jsx)(n.h2,{id:"note-on-alternative-models",children:"Note on Alternative Models"}),"\n",(0,i.jsx)(n.p,{children:"The best models are GPT-4 and Claude 3. Current local and open source models are\nnot nearly as powerful. When using an alternative model,\nyou may see long wait times between messages,\npoor responses, or errors about malformed JSON. OpenDevin\ncan only be as powerful as the models driving it--fortunately folks on our team\nare actively working on building better open source models!"}),"\n",(0,i.jsx)(n.h2,{id:"api-retries-and-rate-limits",children:"API retries and rate limits"}),"\n",(0,i.jsxs)(n.p,{children:["Some LLMs have rate limits and may require retries. OpenDevin will automatically retry requests if it receives a 429 error or API connection error.\nYou can set ",(0,i.jsx)(n.code,{children:"LLM_NUM_RETRIES"}),", ",(0,i.jsx)(n.code,{children:"LLM_RETRY_MIN_WAIT"}),", ",(0,i.jsx)(n.code,{children:"LLM_RETRY_MAX_WAIT"})," environment variables to control the number of retries and the time between retries.\nBy default, ",(0,i.jsx)(n.code,{children:"LLM_NUM_RETRIES"})," is 5 and ",(0,i.jsx)(n.code,{children:"LLM_RETRY_MIN_WAIT"}),", ",(0,i.jsx)(n.code,{children:"LLM_RETRY_MAX_WAIT"})," are 3 seconds and respectively 60 seconds."]})]})}function u(e={}){const{wrapper:n}={...(0,r.R)(),...e.components};return n?(0,i.jsx)(n,{...e,children:(0,i.jsx)(c,{...e})}):c(e)}},8453:(e,n,s)=>{s.d(n,{R:()=>t,x:()=>l});var i=s(6540);const r={},o=i.createContext(r);function t(e){const n=i.useContext(o);return i.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function l(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(r):e.components||r:t(e.components),i.createElement(o.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[8396],{6713:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>u,contentTitle:()=>r,default:()=>c,frontMatter:()=>o,metadata:()=>p,toc:()=>d});var s=t(4848),i=t(8453);const o={sidebar_label:"jupyter",title:"opendevin.sandbox.plugins.jupyter"},r=void 0,p={id:"python/opendevin/sandbox/plugins/jupyter/__init__",title:"opendevin.sandbox.plugins.jupyter",description:"JupyterRequirement Objects",source:"@site/modules/python/opendevin/sandbox/plugins/jupyter/__init__.md",sourceDirName:"python/opendevin/sandbox/plugins/jupyter",slug:"/python/opendevin/sandbox/plugins/jupyter/__init__",permalink:"/OpenDevin/modules/python/opendevin/sandbox/plugins/jupyter/__init__",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"jupyter",title:"opendevin.sandbox.plugins.jupyter"},sidebar:"apiSidebar",previous:{title:"sandbox",permalink:"/OpenDevin/modules/python/opendevin/sandbox/e2b/sandbox"},next:{title:"mixin",permalink:"/OpenDevin/modules/python/opendevin/sandbox/plugins/mixin"}},u={},d=[{value:"JupyterRequirement Objects",id:"jupyterrequirement-objects",level:2},{value:"host_src",id:"host_src",level:4}];function l(e){const n={code:"code",h2:"h2",h4:"h4",p:"p",pre:"pre",...(0,i.R)(),...e.components};return(0,s.jsxs)(s.Fragment,{children:[(0,s.jsx)(n.h2,{id:"jupyterrequirement-objects",children:"JupyterRequirement Objects"}),"\n",(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-python",children:"@dataclass\nclass JupyterRequirement(PluginRequirement)\n"})}),"\n",(0,s.jsx)(n.h4,{id:"host_src",children:"host_src"}),"\n",(0,s.jsx)(n.p,{children:"The directory of this file (sandbox/plugins/jupyter)"})]})}function c(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,s.jsx)(n,{...e,children:(0,s.jsx)(l,{...e})}):l(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>r,x:()=>p});var s=t(6540);const i={},o=s.createContext(i);function r(e){const n=s.useContext(o);return s.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function p(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(i):e.components||i:r(e.components),s.createElement(o.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[9086],{5184:(e,s,n)=>{n.r(s),n.d(s,{assets:()=>c,contentTitle:()=>r,default:()=>p,frontMatter:()=>a,metadata:()=>i,toc:()=>l});var t=n(4848),o=n(8453);const a={sidebar_label:"message",title:"opendevin.observation.message"},r=void 0,i={id:"python/opendevin/observation/message",title:"opendevin.observation.message",description:"UserMessageObservation Objects",source:"@site/modules/python/opendevin/observation/message.md",sourceDirName:"python/opendevin/observation",slug:"/python/opendevin/observation/message",permalink:"/OpenDevin/modules/python/opendevin/observation/message",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"message",title:"opendevin.observation.message"},sidebar:"apiSidebar",previous:{title:"files",permalink:"/OpenDevin/modules/python/opendevin/observation/files"},next:{title:"recall",permalink:"/OpenDevin/modules/python/opendevin/observation/recall"}},c={},l=[{value:"UserMessageObservation Objects",id:"usermessageobservation-objects",level:2},{value:"AgentMessageObservation Objects",id:"agentmessageobservation-objects",level:2}];function d(e){const s={code:"code",h2:"h2",p:"p",pre:"pre",...(0,o.R)(),...e.components};return(0,t.jsxs)(t.Fragment,{children:[(0,t.jsx)(s.h2,{id:"usermessageobservation-objects",children:"UserMessageObservation Objects"}),"\n",(0,t.jsx)(s.pre,{children:(0,t.jsx)(s.code,{className:"language-python",children:"@dataclass\nclass UserMessageObservation(Observation)\n"})}),"\n",(0,t.jsx)(s.p,{children:"This data class represents a message sent by the user."}),"\n",(0,t.jsx)(s.h2,{id:"agentmessageobservation-objects",children:"AgentMessageObservation Objects"}),"\n",(0,t.jsx)(s.pre,{children:(0,t.jsx)(s.code,{className:"language-python",children:"@dataclass\nclass AgentMessageObservation(Observation)\n"})}),"\n",(0,t.jsx)(s.p,{children:"This data class represents a message sent by the agent."})]})}function p(e={}){const{wrapper:s}={...(0,o.R)(),...e.components};return s?(0,t.jsx)(s,{...e,children:(0,t.jsx)(d,{...e})}):d(e)}},8453:(e,s,n)=>{n.d(s,{R:()=>r,x:()=>i});var t=n(6540);const o={},a=t.createContext(o);function r(e){const s=t.useContext(a);return t.useMemo((function(){return"function"==typeof e?e(s):{...s,...e}}),[s,e])}function i(e){let s;return s=e.disableParentContext?"function"==typeof e.components?e.components(o):e.components||o:r(e.components),t.createElement(a.Provider,{value:s},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[9270],{9230:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>h,contentTitle:()=>c,default:()=>a,frontMatter:()=>s,metadata:()=>r,toc:()=>l});var i=t(4848),o=t(8453);const s={sidebar_label:"github",title:"opendevin.action.github"},c=void 0,r={id:"python/opendevin/action/github",title:"opendevin.action.github",description:"GitHubPushAction Objects",source:"@site/modules/python/opendevin/action/github.md",sourceDirName:"python/opendevin/action",slug:"/python/opendevin/action/github",permalink:"/OpenDevin/modules/python/opendevin/action/github",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"github",title:"opendevin.action.github"},sidebar:"apiSidebar",previous:{title:"fileop",permalink:"/OpenDevin/modules/python/opendevin/action/fileop"},next:{title:"tasks",permalink:"/OpenDevin/modules/python/opendevin/action/tasks"}},h={},l=[{value:"GitHubPushAction Objects",id:"githubpushaction-objects",level:2},{value:"GitHubSendPRAction Objects",id:"githubsendpraction-objects",level:2}];function d(e){const n={code:"code",h2:"h2",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,o.R)(),...e.components};return(0,i.jsxs)(i.Fragment,{children:[(0,i.jsx)(n.h2,{id:"githubpushaction-objects",children:"GitHubPushAction Objects"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-python",children:"@dataclass\nclass GitHubPushAction(ExecutableAction)\n"})}),"\n",(0,i.jsx)(n.p,{children:"This pushes the current branch to github."}),"\n",(0,i.jsx)(n.p,{children:"To use this, you need to set the GITHUB_TOKEN environment variable.\nThe agent will return a message with a URL that you can click to make a pull\nrequest."}),"\n",(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.strong,{children:"Attributes"}),":"]}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.code,{children:"owner"})," - The owner of the source repo"]}),"\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.code,{children:"repo"})," - The name of the source repo"]}),"\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.code,{children:"branch"})," - The branch to push"]}),"\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.code,{children:"action"})," - The action identifier"]}),"\n"]}),"\n",(0,i.jsx)(n.h2,{id:"githubsendpraction-objects",children:"GitHubSendPRAction Objects"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-python",children:"@dataclass\nclass GitHubSendPRAction(ExecutableAction)\n"})}),"\n",(0,i.jsx)(n.p,{children:"An action to send a github PR."}),"\n",(0,i.jsx)(n.p,{children:"To use this, you need to set the GITHUB_TOKEN environment variable."}),"\n",(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.strong,{children:"Attributes"}),":"]}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.code,{children:"owner"})," - The owner of the source repo"]}),"\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.code,{children:"repo"})," - The name of the source repo"]}),"\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.code,{children:"title"})," - The title of the PR"]}),"\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.code,{children:"head"})," - The branch to send the PR from"]}),"\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.code,{children:"head_repo"})," - The repo to send the PR from"]}),"\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.code,{children:"base"})," - The branch to send the PR to"]}),"\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.code,{children:"body"})," - The body of the PR"]}),"\n"]})]})}function a(e={}){const{wrapper:n}={...(0,o.R)(),...e.components};return n?(0,i.jsx)(n,{...e,children:(0,i.jsx)(d,{...e})}):d(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>c,x:()=>r});var i=t(6540);const o={},s=i.createContext(o);function c(e){const n=i.useContext(s);return i.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function r(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(o):e.components||o:c(e.components),i.createElement(s.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[6528],{8305:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>c,contentTitle:()=>i,default:()=>g,frontMatter:()=>a,metadata:()=>o,toc:()=>d});var r=t(4848),s=t(8453);const a={sidebar_label:"manager",title:"opendevin.server.agent.manager"},i=void 0,o={id:"python/opendevin/server/agent/manager",title:"opendevin.server.agent.manager",description:"AgentManager Objects",source:"@site/modules/python/opendevin/server/agent/manager.md",sourceDirName:"python/opendevin/server/agent",slug:"/python/opendevin/server/agent/manager",permalink:"/OpenDevin/modules/python/opendevin/server/agent/manager",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"manager",title:"opendevin.server.agent.manager"},sidebar:"apiSidebar",previous:{title:"agent",permalink:"/OpenDevin/modules/python/opendevin/server/agent/"},next:{title:"auth",permalink:"/OpenDevin/modules/python/opendevin/server/auth/"}},c={},d=[{value:"AgentManager Objects",id:"agentmanager-objects",level:2},{value:"register_agent",id:"register_agent",level:4},{value:"dispatch",id:"dispatch",level:4}];function l(e){const n={code:"code",h2:"h2",h4:"h4",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,s.R)(),...e.components};return(0,r.jsxs)(r.Fragment,{children:[(0,r.jsx)(n.h2,{id:"agentmanager-objects",children:"AgentManager Objects"}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-python",children:"class AgentManager()\n"})}),"\n",(0,r.jsx)(n.h4,{id:"register_agent",children:"register_agent"}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-python",children:"def register_agent(sid: str)\n"})}),"\n",(0,r.jsx)(n.p,{children:"Registers a new agent."}),"\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.strong,{children:"Arguments"}),":"]}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.code,{children:"sid"})," - The session ID of the agent."]}),"\n"]}),"\n",(0,r.jsx)(n.h4,{id:"dispatch",children:"dispatch"}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-python",children:"async def dispatch(sid: str, action: str | None, data: dict)\n"})}),"\n",(0,r.jsx)(n.p,{children:"Dispatches actions to the agent from the client."})]})}function g(e={}){const{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,r.jsx)(n,{...e,children:(0,r.jsx)(l,{...e})}):l(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>i,x:()=>o});var r=t(6540);const s={},a=r.createContext(s);function i(e){const n=r.useContext(a);return r.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function o(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(s):e.components||s:i(e.components),r.createElement(a.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[2472],{4884:(e,n,s)=>{s.r(n),s.d(n,{assets:()=>d,contentTitle:()=>a,default:()=>p,frontMatter:()=>o,metadata:()=>i,toc:()=>c});var r=s(4848),t=s(8453);const o={sidebar_label:"manager",title:"opendevin.server.session.manager"},a=void 0,i={id:"python/opendevin/server/session/manager",title:"opendevin.server.session.manager",description:"SessionManager Objects",source:"@site/modules/python/opendevin/server/session/manager.md",sourceDirName:"python/opendevin/server/session",slug:"/python/opendevin/server/session/manager",permalink:"/OpenDevin/modules/python/opendevin/server/session/manager",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"manager",title:"opendevin.server.session.manager"},sidebar:"apiSidebar",previous:{title:"auth",permalink:"/OpenDevin/modules/python/opendevin/server/auth/"},next:{title:"msg_stack",permalink:"/OpenDevin/modules/python/opendevin/server/session/msg_stack"}},d={},c=[{value:"SessionManager Objects",id:"sessionmanager-objects",level:2},{value:"send",id:"send",level:4},{value:"send_error",id:"send_error",level:4},{value:"send_message",id:"send_message",level:4}];function l(e){const n={code:"code",h2:"h2",h4:"h4",p:"p",pre:"pre",...(0,t.R)(),...e.components};return(0,r.jsxs)(r.Fragment,{children:[(0,r.jsx)(n.h2,{id:"sessionmanager-objects",children:"SessionManager Objects"}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-python",children:"class SessionManager()\n"})}),"\n",(0,r.jsx)(n.h4,{id:"send",children:"send"}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-python",children:"async def send(sid: str, data: Dict[str, object]) -> bool\n"})}),"\n",(0,r.jsx)(n.p,{children:"Sends data to the client."}),"\n",(0,r.jsx)(n.h4,{id:"send_error",children:"send_error"}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-python",children:"async def send_error(sid: str, message: str) -> bool\n"})}),"\n",(0,r.jsx)(n.p,{children:"Sends an error message to the client."}),"\n",(0,r.jsx)(n.h4,{id:"send_message",children:"send_message"}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-python",children:"async def send_message(sid: str, message: str) -> bool\n"})}),"\n",(0,r.jsx)(n.p,{children:"Sends a message to the client."})]})}function p(e={}){const{wrapper:n}={...(0,t.R)(),...e.components};return n?(0,r.jsx)(n,{...e,children:(0,r.jsx)(l,{...e})}):l(e)}},8453:(e,n,s)=>{s.d(n,{R:()=>a,x:()=>i});var r=s(6540);const t={},o=r.createContext(t);function a(e){const n=r.useContext(o);return r.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function i(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(t):e.components||t:a(e.components),r.createElement(o.Provider,{value:n},e.children)}}}]);
|
||||
File diff suppressed because one or more lines are too long
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[7859],{1862:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>o,contentTitle:()=>i,default:()=>d,frontMatter:()=>r,metadata:()=>l,toc:()=>c});var s=t(4848),a=t(8453);const r={sidebar_label:"agent",title:"agenthub.planner_agent.agent"},i=void 0,l={id:"python/agenthub/planner_agent/agent",title:"agenthub.planner_agent.agent",description:"PlannerAgent Objects",source:"@site/modules/python/agenthub/planner_agent/agent.md",sourceDirName:"python/agenthub/planner_agent",slug:"/python/agenthub/planner_agent/agent",permalink:"/OpenDevin/modules/python/agenthub/planner_agent/agent",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"agent",title:"agenthub.planner_agent.agent"},sidebar:"apiSidebar",previous:{title:"agent",permalink:"/OpenDevin/modules/python/agenthub/monologue_agent/agent"},next:{title:"prompt",permalink:"/OpenDevin/modules/python/agenthub/planner_agent/prompt"}},o={},c=[{value:"PlannerAgent Objects",id:"planneragent-objects",level:2},{value:"__init__",id:"__init__",level:4},{value:"step",id:"step",level:4}];function p(e){const n={code:"code",h2:"h2",h4:"h4",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,a.R)(),...e.components};return(0,s.jsxs)(s.Fragment,{children:[(0,s.jsx)(n.h2,{id:"planneragent-objects",children:"PlannerAgent Objects"}),"\n",(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-python",children:"class PlannerAgent(Agent)\n"})}),"\n",(0,s.jsx)(n.p,{children:"The planner agent utilizes a special prompting strategy to create long term plans for solving problems.\nThe agent is given its previous action-observation pairs, current task, and hint based on last action taken at every step."}),"\n",(0,s.jsx)(n.h4,{id:"__init__",children:"__init__"}),"\n",(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-python",children:"def __init__(llm: LLM)\n"})}),"\n",(0,s.jsx)(n.p,{children:"Initialize the Planner Agent with an LLM"}),"\n",(0,s.jsxs)(n.p,{children:[(0,s.jsx)(n.strong,{children:"Arguments"}),":"]}),"\n",(0,s.jsxs)(n.ul,{children:["\n",(0,s.jsx)(n.li,{children:"llm (LLM): The llm to be used by this agent"}),"\n"]}),"\n",(0,s.jsx)(n.h4,{id:"step",children:"step"}),"\n",(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-python",children:"def step(state: State) -> Action\n"})}),"\n",(0,s.jsx)(n.p,{children:"Checks to see if current step is completed, returns AgentFinishAction if True.\nOtherwise, creates a plan prompt and sends to model for inference, returning the result as the next action."}),"\n",(0,s.jsxs)(n.p,{children:[(0,s.jsx)(n.strong,{children:"Arguments"}),":"]}),"\n",(0,s.jsxs)(n.ul,{children:["\n",(0,s.jsx)(n.li,{children:"state (State): The current state given the previous actions and observations"}),"\n"]}),"\n",(0,s.jsxs)(n.p,{children:[(0,s.jsx)(n.strong,{children:"Returns"}),":"]}),"\n",(0,s.jsxs)(n.ul,{children:["\n",(0,s.jsx)(n.li,{children:"AgentFinishAction: If the last state was 'completed', 'verified', or 'abandoned'"}),"\n",(0,s.jsx)(n.li,{children:"Action: The next action to take based on llm response"}),"\n"]})]})}function d(e={}){const{wrapper:n}={...(0,a.R)(),...e.components};return n?(0,s.jsx)(n,{...e,children:(0,s.jsx)(p,{...e})}):p(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>i,x:()=>l});var s=t(6540);const a={},r=s.createContext(a);function i(e){const n=s.useContext(r);return s.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function l(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(a):e.components||a:i(e.components),s.createElement(r.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[3159],{9604:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>a,contentTitle:()=>i,default:()=>u,frontMatter:()=>s,metadata:()=>c,toc:()=>l});var o=t(4848),r=t(8453);const s={sidebar_label:"agent",title:"agenthub.micro.agent"},i=void 0,c={id:"python/agenthub/micro/agent",title:"agenthub.micro.agent",description:"my\\_encoder",source:"@site/modules/python/agenthub/micro/agent.md",sourceDirName:"python/agenthub/micro",slug:"/python/agenthub/micro/agent",permalink:"/OpenDevin/modules/python/agenthub/micro/agent",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"agent",title:"agenthub.micro.agent"},sidebar:"apiSidebar",previous:{title:"agent",permalink:"/OpenDevin/modules/python/agenthub/dummy_agent/agent"},next:{title:"json",permalink:"/OpenDevin/modules/python/agenthub/monologue_agent/utils/json"}},a={},l=[{value:"my_encoder",id:"my_encoder",level:4},{value:"to_json",id:"to_json",level:4}];function d(e){const n={code:"code",h4:"h4",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,r.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(n.h4,{id:"my_encoder",children:"my_encoder"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"def my_encoder(obj)\n"})}),"\n",(0,o.jsx)(n.p,{children:"Encodes objects as dictionaries"}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Arguments"}),":"]}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsx)(n.li,{children:"obj (Object): An object that will be converted"}),"\n"]}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Returns"}),":"]}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsx)(n.li,{children:"dict: If the object can be converted it is returned in dict format"}),"\n"]}),"\n",(0,o.jsx)(n.h4,{id:"to_json",children:"to_json"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"def to_json(obj, **kwargs)\n"})}),"\n",(0,o.jsx)(n.p,{children:"Serialize an object to str format"})]})}function u(e={}){const{wrapper:n}={...(0,r.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(d,{...e})}):d(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>i,x:()=>c});var o=t(6540);const r={},s=o.createContext(r);function i(e){const n=o.useContext(s);return o.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function c(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(r):e.components||r:i(e.components),o.createElement(s.Provider,{value:n},e.children)}}}]);
|
||||
File diff suppressed because one or more lines are too long
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[2902],{3942:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>d,contentTitle:()=>s,default:()=>a,frontMatter:()=>r,metadata:()=>c,toc:()=>p});var o=t(4848),i=t(8453);const r={sidebar_label:"config",title:"opendevin.config"},s=void 0,c={id:"python/opendevin/config",title:"opendevin.config",description:"get",source:"@site/modules/python/opendevin/config.md",sourceDirName:"python/opendevin",slug:"/python/opendevin/config",permalink:"/OpenDevin/modules/python/opendevin/config",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"config",title:"opendevin.config"},sidebar:"apiSidebar",previous:{title:"agent",permalink:"/OpenDevin/modules/python/opendevin/agent"},next:{title:"files",permalink:"/OpenDevin/modules/python/opendevin/files"}},d={},p=[{value:"get",id:"get",level:4}];function l(e){const n={code:"code",h4:"h4",p:"p",pre:"pre",...(0,i.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(n.h4,{id:"get",children:"get"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"def get(key: ConfigType, required: bool = False)\n"})}),"\n",(0,o.jsx)(n.p,{children:"Get a key from the environment variables or config.toml or default configs."})]})}function a(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(l,{...e})}):l(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>s,x:()=>c});var o=t(6540);const i={},r=o.createContext(i);function s(e){const n=o.useContext(r);return o.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function c(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(i):e.components||i:s(e.components),o.createElement(r.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[9647],{7121:(e,s,r)=>{r.r(s),r.d(s,{default:()=>l});r(6540);var c=r(4164),u=r(1003),a=r(7559),d=r(2831),n=r(781),t=r(4848);function l(e){return(0,t.jsx)(u.e3,{className:(0,c.A)(a.G.wrapper.docsPages),children:(0,t.jsx)(n.A,{children:(0,d.v)(e.route.routes)})})}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[5360],{8613:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>p,contentTitle:()=>r,default:()=>c,frontMatter:()=>s,metadata:()=>a,toc:()=>d});var o=t(4848),i=t(8453);const s={sidebar_label:"observation",title:"opendevin.observation"},r=void 0,a={id:"python/opendevin/observation/__init__",title:"opendevin.observation",description:"OBSERVATION\\TYPE\\TO\\_CLASS",source:"@site/modules/python/opendevin/observation/__init__.md",sourceDirName:"python/opendevin/observation",slug:"/python/opendevin/observation/__init__",permalink:"/OpenDevin/modules/python/opendevin/observation/__init__",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"observation",title:"opendevin.observation"},sidebar:"apiSidebar",previous:{title:"llm",permalink:"/OpenDevin/modules/python/opendevin/llm/"},next:{title:"base",permalink:"/OpenDevin/modules/python/opendevin/observation/base"}},p={},d=[{value:"OBSERVATION_TYPE_TO_CLASS",id:"observation_type_to_class",level:4}];function l(e){const n={h4:"h4",p:"p",...(0,i.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(n.h4,{id:"observation_type_to_class",children:"OBSERVATION_TYPE_TO_CLASS"}),"\n",(0,o.jsx)(n.p,{children:"type: ignore[attr-defined]"})]})}function c(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(l,{...e})}):l(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>r,x:()=>a});var o=t(6540);const i={},s=o.createContext(i);function r(e){const n=o.useContext(s);return o.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function a(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(i):e.components||i:r(e.components),o.createElement(s.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[8726],{8343:(e,t,n)=>{n.r(t),n.d(t,{assets:()=>i,contentTitle:()=>o,default:()=>p,frontMatter:()=>r,metadata:()=>c,toc:()=>l});var s=n(4848),a=n(8453);const r={sidebar_label:"agent",title:"agenthub.SWE_agent.agent"},o=void 0,c={id:"python/agenthub/SWE_agent/agent",title:"agenthub.SWE_agent.agent",description:"SWEAgent Objects",source:"@site/modules/python/agenthub/SWE_agent/agent.md",sourceDirName:"python/agenthub/SWE_agent",slug:"/python/agenthub/SWE_agent/agent",permalink:"/OpenDevin/modules/python/agenthub/SWE_agent/agent",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"agent",title:"agenthub.SWE_agent.agent"},sidebar:"apiSidebar",next:{title:"parser",permalink:"/OpenDevin/modules/python/agenthub/SWE_agent/parser"}},i={},l=[{value:"SWEAgent Objects",id:"sweagent-objects",level:2},{value:"step",id:"step",level:4},{value:"reset",id:"reset",level:4}];function d(e){const t={code:"code",h2:"h2",h4:"h4",li:"li",ol:"ol",p:"p",pre:"pre",...(0,a.R)(),...e.components};return(0,s.jsxs)(s.Fragment,{children:[(0,s.jsx)(t.h2,{id:"sweagent-objects",children:"SWEAgent Objects"}),"\n",(0,s.jsx)(t.pre,{children:(0,s.jsx)(t.code,{className:"language-python",children:"class SWEAgent(Agent)\n"})}),"\n",(0,s.jsx)(t.p,{children:"An attempt to recreate swe_agent with output parsing, prompting style, and Application Computer Interface (ACI)."}),"\n",(0,s.jsx)(t.p,{children:"SWE-agent includes ACI functions like 'goto', 'search_for', 'edit', 'scroll', 'run'"}),"\n",(0,s.jsx)(t.h4,{id:"step",children:"step"}),"\n",(0,s.jsx)(t.pre,{children:(0,s.jsx)(t.code,{className:"language-python",children:"def step(state: State) -> Action\n"})}),"\n",(0,s.jsx)(t.p,{children:"SWE-Agent step:"}),"\n",(0,s.jsxs)(t.ol,{children:["\n",(0,s.jsx)(t.li,{children:"Get context - past actions, custom commands, current step"}),"\n",(0,s.jsx)(t.li,{children:"Perform think-act - prompt model for action and reasoning"}),"\n",(0,s.jsx)(t.li,{children:"Catch errors - ensure model takes action (5 attempts max)"}),"\n"]}),"\n",(0,s.jsx)(t.h4,{id:"reset",children:"reset"}),"\n",(0,s.jsx)(t.pre,{children:(0,s.jsx)(t.code,{className:"language-python",children:"def reset() -> None\n"})}),"\n",(0,s.jsx)(t.p,{children:"Used to reset the agent"})]})}function p(e={}){const{wrapper:t}={...(0,a.R)(),...e.components};return t?(0,s.jsx)(t,{...e,children:(0,s.jsx)(d,{...e})}):d(e)}},8453:(e,t,n)=>{n.d(t,{R:()=>o,x:()=>c});var s=n(6540);const a={},r=s.createContext(a);function o(e){const t=s.useContext(r);return s.useMemo((function(){return"function"==typeof e?e(t):{...t,...e}}),[t,e])}function c(e){let t;return t=e.disableParentContext?"function"==typeof e.components?e.components(a):e.components||a:o(e.components),s.createElement(r.Provider,{value:t},e.children)}}}]);
|
||||
File diff suppressed because one or more lines are too long
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[1309],{1409:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>d,contentTitle:()=>o,default:()=>p,frontMatter:()=>a,metadata:()=>s,toc:()=>l});var i=t(4848),r=t(8453);const a={sidebar_label:"main",title:"opendevin.main"},o=void 0,s={id:"python/opendevin/main",title:"opendevin.main",description:"read\\task\\from\\_file",source:"@site/modules/python/opendevin/main.md",sourceDirName:"python/opendevin",slug:"/python/opendevin/main",permalink:"/OpenDevin/modules/python/opendevin/main",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"main",title:"opendevin.main"},sidebar:"apiSidebar",previous:{title:"logger",permalink:"/OpenDevin/modules/python/opendevin/logger"},next:{title:"plan",permalink:"/OpenDevin/modules/python/opendevin/plan"}},d={},l=[{value:"read_task_from_file",id:"read_task_from_file",level:4},{value:"read_task_from_stdin",id:"read_task_from_stdin",level:4},{value:"main",id:"main",level:4}];function c(e){const n={code:"code",h4:"h4",p:"p",pre:"pre",...(0,r.R)(),...e.components};return(0,i.jsxs)(i.Fragment,{children:[(0,i.jsx)(n.h4,{id:"read_task_from_file",children:"read_task_from_file"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-python",children:"def read_task_from_file(file_path: str) -> str\n"})}),"\n",(0,i.jsx)(n.p,{children:"Read task from the specified file."}),"\n",(0,i.jsx)(n.h4,{id:"read_task_from_stdin",children:"read_task_from_stdin"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-python",children:"def read_task_from_stdin() -> str\n"})}),"\n",(0,i.jsx)(n.p,{children:"Read task from stdin."}),"\n",(0,i.jsx)(n.h4,{id:"main",children:"main"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-python",children:"async def main(task_str: str = '')\n"})}),"\n",(0,i.jsx)(n.p,{children:"Main coroutine to run the agent controller with task input flexibility."})]})}function p(e={}){const{wrapper:n}={...(0,r.R)(),...e.components};return n?(0,i.jsx)(n,{...e,children:(0,i.jsx)(c,{...e})}):c(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>o,x:()=>s});var i=t(6540);const r={},a=i.createContext(r);function o(e){const n=i.useContext(a);return i.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function s(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(r):e.components||r:o(e.components),i.createElement(a.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[8078],{4061:s=>{s.exports=JSON.parse('{"name":"docusaurus-plugin-content-pages","id":"default"}')}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[9200],{375:(e,t,n)=>{n.r(t),n.d(t,{assets:()=>r,contentTitle:()=>i,default:()=>p,frontMatter:()=>s,metadata:()=>c,toc:()=>d});var o=n(4848),a=n(8453);const s={sidebar_label:"tasks",title:"opendevin.action.tasks"},i=void 0,c={id:"python/opendevin/action/tasks",title:"opendevin.action.tasks",description:"TaskStateChangedAction Objects",source:"@site/modules/python/opendevin/action/tasks.md",sourceDirName:"python/opendevin/action",slug:"/python/opendevin/action/tasks",permalink:"/OpenDevin/modules/python/opendevin/action/tasks",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"tasks",title:"opendevin.action.tasks"},sidebar:"apiSidebar",previous:{title:"github",permalink:"/OpenDevin/modules/python/opendevin/action/github"},next:{title:"agent_controller",permalink:"/OpenDevin/modules/python/opendevin/controller/agent_controller"}},r={},d=[{value:"TaskStateChangedAction Objects",id:"taskstatechangedaction-objects",level:2}];function l(e){const t={code:"code",h2:"h2",p:"p",pre:"pre",...(0,a.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(t.h2,{id:"taskstatechangedaction-objects",children:"TaskStateChangedAction Objects"}),"\n",(0,o.jsx)(t.pre,{children:(0,o.jsx)(t.code,{className:"language-python",children:"@dataclass\nclass TaskStateChangedAction(NotExecutableAction)\n"})}),"\n",(0,o.jsx)(t.p,{children:"Fake action, just to notify the client that a task state has changed."})]})}function p(e={}){const{wrapper:t}={...(0,a.R)(),...e.components};return t?(0,o.jsx)(t,{...e,children:(0,o.jsx)(l,{...e})}):l(e)}},8453:(e,t,n)=>{n.d(t,{R:()=>i,x:()=>c});var o=n(6540);const a={},s=o.createContext(a);function i(e){const t=o.useContext(s);return o.useMemo((function(){return"function"==typeof e?e(t):{...t,...e}}),[t,e])}function c(e){let t;return t=e.disableParentContext?"function"==typeof e.components?e.components(a):e.components||a:i(e.components),o.createElement(s.Provider,{value:t},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[5289],{6771:(n,e,t)=>{t.r(e),t.d(e,{assets:()=>c,contentTitle:()=>o,default:()=>p,frontMatter:()=>a,metadata:()=>i,toc:()=>d});var r=t(4848),s=t(8453);const a={sidebar_label:"parser",title:"agenthub.SWE_agent.parser"},o=void 0,i={id:"python/agenthub/SWE_agent/parser",title:"agenthub.SWE_agent.parser",description:"get\\action\\from\\_string",source:"@site/modules/python/agenthub/SWE_agent/parser.md",sourceDirName:"python/agenthub/SWE_agent",slug:"/python/agenthub/SWE_agent/parser",permalink:"/OpenDevin/modules/python/agenthub/SWE_agent/parser",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"parser",title:"agenthub.SWE_agent.parser"},sidebar:"apiSidebar",previous:{title:"agent",permalink:"/OpenDevin/modules/python/agenthub/SWE_agent/agent"},next:{title:"codeact_agent",permalink:"/OpenDevin/modules/python/agenthub/codeact_agent/"}},c={},d=[{value:"get_action_from_string",id:"get_action_from_string",level:4},{value:"parse_command",id:"parse_command",level:4}];function l(n){const e={code:"code",em:"em",h4:"h4",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,s.R)(),...n.components};return(0,r.jsxs)(r.Fragment,{children:[(0,r.jsx)(e.h4,{id:"get_action_from_string",children:"get_action_from_string"}),"\n",(0,r.jsx)(e.pre,{children:(0,r.jsx)(e.code,{className:"language-python",children:"def get_action_from_string(command_string: str,\n path: str,\n line: int,\n thoughts: str = '') -> Action | None\n"})}),"\n",(0,r.jsx)(e.p,{children:"Parses the command string to find which command the agent wants to run\nConverts the command into a proper Action and returns"}),"\n",(0,r.jsx)(e.h4,{id:"parse_command",children:"parse_command"}),"\n",(0,r.jsx)(e.pre,{children:(0,r.jsx)(e.code,{className:"language-python",children:"def parse_command(input_str: str, path: str, line: int)\n"})}),"\n",(0,r.jsx)(e.p,{children:"Parses a given string and separates the command (enclosed in triple backticks) from any accompanying text."}),"\n",(0,r.jsxs)(e.p,{children:[(0,r.jsx)(e.strong,{children:"Arguments"}),":"]}),"\n",(0,r.jsxs)(e.ul,{children:["\n",(0,r.jsxs)(e.li,{children:[(0,r.jsx)(e.code,{children:"input_str"})," ",(0,r.jsx)(e.em,{children:"str"})," - The input string to be parsed."]}),"\n"]}),"\n",(0,r.jsxs)(e.p,{children:[(0,r.jsx)(e.strong,{children:"Returns"}),":"]}),"\n",(0,r.jsxs)(e.ul,{children:["\n",(0,r.jsxs)(e.li,{children:[(0,r.jsx)(e.code,{children:"tuple"})," - A tuple containing the command and the accompanying text (if any)."]}),"\n"]})]})}function p(n={}){const{wrapper:e}={...(0,s.R)(),...n.components};return e?(0,r.jsx)(e,{...n,children:(0,r.jsx)(l,{...n})}):l(n)}},8453:(n,e,t)=>{t.d(e,{R:()=>o,x:()=>i});var r=t(6540);const s={},a=r.createContext(s);function o(n){const e=r.useContext(a);return r.useMemo((function(){return"function"==typeof n?n(e):{...e,...n}}),[e,n])}function i(n){let e;return e=n.disableParentContext?"function"==typeof n.components?n.components(s):n.components||s:o(n.components),r.createElement(a.Provider,{value:e},n.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[5650],{3577:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>h,contentTitle:()=>i,default:()=>u,frontMatter:()=>l,metadata:()=>r,toc:()=>a});var o=t(4848),s=t(8453);const l={sidebar_label:"monologue",title:"agenthub.monologue_agent.utils.monologue"},i=void 0,r={id:"python/agenthub/monologue_agent/utils/monologue",title:"agenthub.monologue_agent.utils.monologue",description:"Monologue Objects",source:"@site/modules/python/agenthub/monologue_agent/utils/monologue.md",sourceDirName:"python/agenthub/monologue_agent/utils",slug:"/python/agenthub/monologue_agent/utils/monologue",permalink:"/OpenDevin/modules/python/agenthub/monologue_agent/utils/monologue",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"monologue",title:"agenthub.monologue_agent.utils.monologue"},sidebar:"apiSidebar",previous:{title:"memory",permalink:"/OpenDevin/modules/python/agenthub/monologue_agent/utils/memory"},next:{title:"prompts",permalink:"/OpenDevin/modules/python/agenthub/monologue_agent/utils/prompts"}},h={},a=[{value:"Monologue Objects",id:"monologue-objects",level:2},{value:"__init__",id:"__init__",level:4},{value:"add_event",id:"add_event",level:4},{value:"get_thoughts",id:"get_thoughts",level:4},{value:"get_total_length",id:"get_total_length",level:4},{value:"condense",id:"condense",level:4}];function d(e){const n={code:"code",h2:"h2",h4:"h4",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,s.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(n.h2,{id:"monologue-objects",children:"Monologue Objects"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"class Monologue()\n"})}),"\n",(0,o.jsx)(n.p,{children:"The monologue is a representation for the agent's internal monologue where it can think.\nThe agent has the capability of using this monologue for whatever it wants."}),"\n",(0,o.jsx)(n.h4,{id:"__init__",children:"__init__"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"def __init__()\n"})}),"\n",(0,o.jsx)(n.p,{children:"Initialize the empty list of thoughts"}),"\n",(0,o.jsx)(n.h4,{id:"add_event",children:"add_event"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"def add_event(t: dict)\n"})}),"\n",(0,o.jsx)(n.p,{children:"Adds an event to memory if it is a valid event."}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Arguments"}),":"]}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsx)(n.li,{children:"t (dict): The thought that we want to add to memory"}),"\n"]}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Raises"}),":"]}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsx)(n.li,{children:"AgentEventTypeError: If t is not a dict"}),"\n"]}),"\n",(0,o.jsx)(n.h4,{id:"get_thoughts",children:"get_thoughts"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"def get_thoughts()\n"})}),"\n",(0,o.jsx)(n.p,{children:"Get the current thoughts of the agent."}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Returns"}),":"]}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsx)(n.li,{children:"List: The list of thoughts that the agent has."}),"\n"]}),"\n",(0,o.jsx)(n.h4,{id:"get_total_length",children:"get_total_length"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"def get_total_length()\n"})}),"\n",(0,o.jsx)(n.p,{children:"Gives the total number of characters in all thoughts"}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Returns"}),":"]}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsx)(n.li,{children:"Int: Total number of chars in thoughts."}),"\n"]}),"\n",(0,o.jsx)(n.h4,{id:"condense",children:"condense"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"def condense(llm: LLM)\n"})}),"\n",(0,o.jsx)(n.p,{children:"Attempts to condense the monologue by using the llm"}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Arguments"}),":"]}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsx)(n.li,{children:"llm (LLM): llm to be used for summarization"}),"\n"]}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Raises"}),":"]}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsx)(n.li,{children:"Exception: the same exception as it got from the llm or processing the response"}),"\n"]})]})}function u(e={}){const{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(d,{...e})}):d(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>i,x:()=>r});var o=t(6540);const s={},l=o.createContext(s);function i(e){const n=o.useContext(l);return o.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function r(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(s):e.components||s:i(e.components),o.createElement(l.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[7127],{1519:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>l,contentTitle:()=>r,default:()=>h,frontMatter:()=>a,metadata:()=>d,toc:()=>o});var s=t(4848),i=t(8453);const a={sidebar_label:"task",title:"opendevin.schema.task"},r=void 0,d={id:"python/opendevin/schema/task",title:"opendevin.schema.task",description:"TaskState Objects",source:"@site/modules/python/opendevin/schema/task.md",sourceDirName:"python/opendevin/schema",slug:"/python/opendevin/schema/task",permalink:"/OpenDevin/modules/python/opendevin/schema/task",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"task",title:"opendevin.schema.task"},sidebar:"apiSidebar",previous:{title:"observation",permalink:"/OpenDevin/modules/python/opendevin/schema/observation"},next:{title:"agent",permalink:"/OpenDevin/modules/python/opendevin/server/agent/"}},l={},o=[{value:"TaskState Objects",id:"taskstate-objects",level:2},{value:"INIT",id:"init",level:4},{value:"RUNNING",id:"running",level:4},{value:"PAUSED",id:"paused",level:4},{value:"STOPPED",id:"stopped",level:4},{value:"FINISHED",id:"finished",level:4},{value:"ERROR",id:"error",level:4},{value:"TaskStateAction Objects",id:"taskstateaction-objects",level:2},{value:"START",id:"start",level:4},{value:"PAUSE",id:"pause",level:4},{value:"RESUME",id:"resume",level:4},{value:"STOP",id:"stop",level:4}];function c(e){const n={code:"code",h2:"h2",h4:"h4",p:"p",pre:"pre",...(0,i.R)(),...e.components};return(0,s.jsxs)(s.Fragment,{children:[(0,s.jsx)(n.h2,{id:"taskstate-objects",children:"TaskState Objects"}),"\n",(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-python",children:"class TaskState(str, Enum)\n"})}),"\n",(0,s.jsx)(n.h4,{id:"init",children:"INIT"}),"\n",(0,s.jsx)(n.p,{children:"Initial state of the task."}),"\n",(0,s.jsx)(n.h4,{id:"running",children:"RUNNING"}),"\n",(0,s.jsx)(n.p,{children:"The task is running."}),"\n",(0,s.jsx)(n.h4,{id:"paused",children:"PAUSED"}),"\n",(0,s.jsx)(n.p,{children:"The task is paused."}),"\n",(0,s.jsx)(n.h4,{id:"stopped",children:"STOPPED"}),"\n",(0,s.jsx)(n.p,{children:"The task is stopped."}),"\n",(0,s.jsx)(n.h4,{id:"finished",children:"FINISHED"}),"\n",(0,s.jsx)(n.p,{children:"The task is finished."}),"\n",(0,s.jsx)(n.h4,{id:"error",children:"ERROR"}),"\n",(0,s.jsx)(n.p,{children:"An error occurred during the task."}),"\n",(0,s.jsx)(n.h2,{id:"taskstateaction-objects",children:"TaskStateAction Objects"}),"\n",(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-python",children:"class TaskStateAction(str, Enum)\n"})}),"\n",(0,s.jsx)(n.h4,{id:"start",children:"START"}),"\n",(0,s.jsx)(n.p,{children:"Starts the task."}),"\n",(0,s.jsx)(n.h4,{id:"pause",children:"PAUSE"}),"\n",(0,s.jsx)(n.p,{children:"Pauses the task."}),"\n",(0,s.jsx)(n.h4,{id:"resume",children:"RESUME"}),"\n",(0,s.jsx)(n.p,{children:"Resumes the task."}),"\n",(0,s.jsx)(n.h4,{id:"stop",children:"STOP"}),"\n",(0,s.jsx)(n.p,{children:"Stops the task."})]})}function h(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,s.jsx)(n,{...e,children:(0,s.jsx)(c,{...e})}):c(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>r,x:()=>d});var s=t(6540);const i={},a=s.createContext(i);function r(e){const n=s.useContext(a);return s.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function d(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(i):e.components||i:r(e.components),s.createElement(a.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[1487],{4308:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>l,contentTitle:()=>c,default:()=>d,frontMatter:()=>a,metadata:()=>s,toc:()=>p});var o=t(4848),i=t(8453);const a={sidebar_label:"fileop",title:"opendevin.action.fileop"},c=void 0,s={id:"python/opendevin/action/fileop",title:"opendevin.action.fileop",description:"FileReadAction Objects",source:"@site/modules/python/opendevin/action/fileop.md",sourceDirName:"python/opendevin/action",slug:"/python/opendevin/action/fileop",permalink:"/OpenDevin/modules/python/opendevin/action/fileop",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"fileop",title:"opendevin.action.fileop"},sidebar:"apiSidebar",previous:{title:"base",permalink:"/OpenDevin/modules/python/opendevin/action/base"},next:{title:"github",permalink:"/OpenDevin/modules/python/opendevin/action/github"}},l={},p=[{value:"FileReadAction Objects",id:"filereadaction-objects",level:2}];function r(e){const n={code:"code",h2:"h2",p:"p",pre:"pre",...(0,i.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(n.h2,{id:"filereadaction-objects",children:"FileReadAction Objects"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"@dataclass\nclass FileReadAction(ExecutableAction)\n"})}),"\n",(0,o.jsx)(n.p,{children:"Reads a file from a given path.\nCan be set to read specific lines using start and end\nDefault lines 0:-1 (whole file)"})]})}function d(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(r,{...e})}):r(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>c,x:()=>s});var o=t(6540);const i={},a=o.createContext(i);function c(e){const n=o.useContext(a);return o.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function s(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(i):e.components||i:c(e.components),o.createElement(a.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[3815],{2956:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>l,contentTitle:()=>r,default:()=>p,frontMatter:()=>i,metadata:()=>a,toc:()=>c});var s=t(4848),o=t(8453);const i={sidebar_label:"files",title:"opendevin.observation.files"},r=void 0,a={id:"python/opendevin/observation/files",title:"opendevin.observation.files",description:"FileReadObservation Objects",source:"@site/modules/python/opendevin/observation/files.md",sourceDirName:"python/opendevin/observation",slug:"/python/opendevin/observation/files",permalink:"/OpenDevin/modules/python/opendevin/observation/files",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"files",title:"opendevin.observation.files"},sidebar:"apiSidebar",previous:{title:"error",permalink:"/OpenDevin/modules/python/opendevin/observation/error"},next:{title:"message",permalink:"/OpenDevin/modules/python/opendevin/observation/message"}},l={},c=[{value:"FileReadObservation Objects",id:"filereadobservation-objects",level:2},{value:"FileWriteObservation Objects",id:"filewriteobservation-objects",level:2}];function d(e){const n={code:"code",h2:"h2",p:"p",pre:"pre",...(0,o.R)(),...e.components};return(0,s.jsxs)(s.Fragment,{children:[(0,s.jsx)(n.h2,{id:"filereadobservation-objects",children:"FileReadObservation Objects"}),"\n",(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-python",children:"@dataclass\nclass FileReadObservation(Observation)\n"})}),"\n",(0,s.jsx)(n.p,{children:"This data class represents the content of a file."}),"\n",(0,s.jsx)(n.h2,{id:"filewriteobservation-objects",children:"FileWriteObservation Objects"}),"\n",(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-python",children:"@dataclass\nclass FileWriteObservation(Observation)\n"})}),"\n",(0,s.jsx)(n.p,{children:"This data class represents a file write operation"})]})}function p(e={}){const{wrapper:n}={...(0,o.R)(),...e.components};return n?(0,s.jsx)(n,{...e,children:(0,s.jsx)(d,{...e})}):d(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>r,x:()=>a});var s=t(6540);const o={},i=s.createContext(o);function r(e){const n=s.useContext(i);return s.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function a(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(o):e.components||o:r(e.components),s.createElement(i.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[9818],{421:(e,n,o)=>{o.r(n),o.d(n,{assets:()=>i,contentTitle:()=>r,default:()=>l,frontMatter:()=>d,metadata:()=>a,toc:()=>c});var t=o(4848),s=o(8453);const d={sidebar_label:"sandbox",title:"opendevin.sandbox.e2b.sandbox"},r=void 0,a={id:"python/opendevin/sandbox/e2b/sandbox",title:"opendevin.sandbox.e2b.sandbox",description:"E2BBox Objects",source:"@site/modules/python/opendevin/sandbox/e2b/sandbox.md",sourceDirName:"python/opendevin/sandbox/e2b",slug:"/python/opendevin/sandbox/e2b/sandbox",permalink:"/OpenDevin/modules/python/opendevin/sandbox/e2b/sandbox",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"sandbox",title:"opendevin.sandbox.e2b.sandbox"},sidebar:"apiSidebar",previous:{title:"process",permalink:"/OpenDevin/modules/python/opendevin/sandbox/docker/process"},next:{title:"jupyter",permalink:"/OpenDevin/modules/python/opendevin/sandbox/plugins/jupyter/__init__"}},i={},c=[{value:"E2BBox Objects",id:"e2bbox-objects",level:2},{value:"copy_to",id:"copy_to",level:4}];function p(e){const n={code:"code",h2:"h2",h4:"h4",p:"p",pre:"pre",...(0,s.R)(),...e.components};return(0,t.jsxs)(t.Fragment,{children:[(0,t.jsx)(n.h2,{id:"e2bbox-objects",children:"E2BBox Objects"}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-python",children:"class E2BBox(Sandbox)\n"})}),"\n",(0,t.jsx)(n.h4,{id:"copy_to",children:"copy_to"}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-python",children:"def copy_to(host_src: str, sandbox_dest: str, recursive: bool = False)\n"})}),"\n",(0,t.jsx)(n.p,{children:"Copies a local file or directory to the sandbox."})]})}function l(e={}){const{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,t.jsx)(n,{...e,children:(0,t.jsx)(p,{...e})}):p(e)}},8453:(e,n,o)=>{o.d(n,{R:()=>r,x:()=>a});var t=o(6540);const s={},d=t.createContext(s);function r(e){const n=t.useContext(d);return t.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function a(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(s):e.components||s:r(e.components),t.createElement(d.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[4534],{8368:(e,n,i)=>{i.r(n),i.d(n,{assets:()=>d,contentTitle:()=>r,default:()=>c,frontMatter:()=>s,metadata:()=>a,toc:()=>l});var o=i(4848),t=i(8453);const s={},r="Azure OpenAI LLM",a={id:"usage/llms/azureLLMs",title:"Azure OpenAI LLM",description:"Completion",source:"@site/modules/usage/llms/azureLLMs.md",sourceDirName:"usage/llms",slug:"/usage/llms/azureLLMs",permalink:"/OpenDevin/modules/usage/llms/azureLLMs",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{},sidebar:"docsSidebar",previous:{title:"\ud83e\udd16 LLM Backends",permalink:"/OpenDevin/modules/usage/llms/"},next:{title:"Google Gemini/Vertex LLM",permalink:"/OpenDevin/modules/usage/llms/googleLLMs"}},d={},l=[{value:"Completion",id:"completion",level:2},{value:"Azure openai configs",id:"azure-openai-configs",level:3},{value:"Embeddings",id:"embeddings",level:2},{value:"Azure openai configs",id:"azure-openai-configs-1",level:3}];function u(e){const n={a:"a",admonition:"admonition",code:"code",h1:"h1",h2:"h2",h3:"h3",p:"p",pre:"pre",...(0,t.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(n.h1,{id:"azure-openai-llm",children:"Azure OpenAI LLM"}),"\n",(0,o.jsx)(n.h2,{id:"completion",children:"Completion"}),"\n",(0,o.jsxs)(n.p,{children:["OpenDevin uses LiteLLM for completion calls. You can find their documentation on Azure ",(0,o.jsx)(n.a,{href:"https://docs.litellm.ai/docs/providers/azure",children:"here"})]}),"\n",(0,o.jsx)(n.h3,{id:"azure-openai-configs",children:"Azure openai configs"}),"\n",(0,o.jsxs)(n.p,{children:["When running the OpenDevin Docker image, you'll need to set the following environment variables using ",(0,o.jsx)(n.code,{children:"-e"}),":"]}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{children:'LLM_BASE_URL="<azure-api-base-url>" # e.g. "https://openai-gpt-4-test-v-1.openai.azure.com/"\nLLM_API_KEY="<azure-api-key>"\nLLM_MODEL="azure/<your-gpt-deployment-name>"\nLLM_API_VERSION = "<api-version>" # e.g. "2024-02-15-preview"\n'})}),"\n",(0,o.jsx)(n.admonition,{type:"note",children:(0,o.jsx)(n.p,{children:"You can find your ChatGPT deployment name on the deployments page in Azure. It could be the same with the chat model name (e.g. 'GPT4-1106-preview'), by default or initially set, but it doesn't have to be the same. Run opendevin, and when you load it in the browser, go to Settings and set model as above: \"azure/<your-actual-gpt-deployment-name>\". If it's not in the list, enter your own text and save it."})}),"\n",(0,o.jsx)(n.h2,{id:"embeddings",children:"Embeddings"}),"\n",(0,o.jsxs)(n.p,{children:["OpenDevin uses llama-index for embeddings. You can find their documentation on Azure ",(0,o.jsx)(n.a,{href:"https://docs.llamaindex.ai/en/stable/api_reference/embeddings/azure_openai/",children:"here"})]}),"\n",(0,o.jsx)(n.h3,{id:"azure-openai-configs-1",children:"Azure openai configs"}),"\n",(0,o.jsx)(n.p,{children:'The model used for Azure OpenAI embeddings is "text-embedding-ada-002".\nYou need the correct deployment name for this model in your Azure account.'}),"\n",(0,o.jsxs)(n.p,{children:["When running OpenDevin in Docker, set the following environment variables using ",(0,o.jsx)(n.code,{children:"-e"}),":"]}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{children:'LLM_EMBEDDING_MODEL="azureopenai"\nLLM_EMBEDDING_DEPLOYMENT_NAME = "<your-embedding-deployment-name>" # e.g. "TextEmbedding...<etc>"\nLLM_API_VERSION = "<api-version>" # e.g. "2024-02-15-preview"\n'})})]})}function c(e={}){const{wrapper:n}={...(0,t.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(u,{...e})}):u(e)}},8453:(e,n,i)=>{i.d(n,{R:()=>r,x:()=>a});var o=i(6540);const t={},s=o.createContext(t);function r(e){const n=o.useContext(s);return o.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function a(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(t):e.components||t:r(e.components),o.createElement(s.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[1976],{3202:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>l,contentTitle:()=>a,default:()=>p,frontMatter:()=>r,metadata:()=>i,toc:()=>c});var o=t(4848),s=t(8453);const r={sidebar_label:"recall",title:"opendevin.observation.recall"},a=void 0,i={id:"python/opendevin/observation/recall",title:"opendevin.observation.recall",description:"AgentRecallObservation Objects",source:"@site/modules/python/opendevin/observation/recall.md",sourceDirName:"python/opendevin/observation",slug:"/python/opendevin/observation/recall",permalink:"/OpenDevin/modules/python/opendevin/observation/recall",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"recall",title:"opendevin.observation.recall"},sidebar:"apiSidebar",previous:{title:"message",permalink:"/OpenDevin/modules/python/opendevin/observation/message"},next:{title:"run",permalink:"/OpenDevin/modules/python/opendevin/observation/run"}},l={},c=[{value:"AgentRecallObservation Objects",id:"agentrecallobservation-objects",level:2}];function d(e){const n={code:"code",h2:"h2",p:"p",pre:"pre",...(0,s.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(n.h2,{id:"agentrecallobservation-objects",children:"AgentRecallObservation Objects"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"@dataclass\nclass AgentRecallObservation(Observation)\n"})}),"\n",(0,o.jsx)(n.p,{children:"This data class represents a list of memories recalled by the agent."})]})}function p(e={}){const{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(d,{...e})}):d(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>a,x:()=>i});var o=t(6540);const s={},r=o.createContext(s);function a(e){const n=o.useContext(r);return o.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function i(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(s):e.components||s:a(e.components),o.createElement(r.Provider,{value:n},e.children)}}}]);
|
||||
File diff suppressed because one or more lines are too long
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[7526],{9209:(n,e,t)=>{t.r(e),t.d(e,{assets:()=>l,contentTitle:()=>i,default:()=>d,frontMatter:()=>o,metadata:()=>a,toc:()=>p});var r=t(4848),s=t(8453);const o={sidebar_label:"prompt",title:"agenthub.planner_agent.prompt"},i=void 0,a={id:"python/agenthub/planner_agent/prompt",title:"agenthub.planner_agent.prompt",description:"get\\_hint",source:"@site/modules/python/agenthub/planner_agent/prompt.md",sourceDirName:"python/agenthub/planner_agent",slug:"/python/agenthub/planner_agent/prompt",permalink:"/OpenDevin/modules/python/agenthub/planner_agent/prompt",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"prompt",title:"agenthub.planner_agent.prompt"},sidebar:"apiSidebar",previous:{title:"agent",permalink:"/OpenDevin/modules/python/agenthub/planner_agent/agent"},next:{title:"action",permalink:"/OpenDevin/modules/python/opendevin/action/__init__"}},l={},p=[{value:"get_hint",id:"get_hint",level:4},{value:"get_prompt",id:"get_prompt",level:4},{value:"parse_response",id:"parse_response",level:4}];function c(n){const e={code:"code",h4:"h4",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,s.R)(),...n.components};return(0,r.jsxs)(r.Fragment,{children:[(0,r.jsx)(e.h4,{id:"get_hint",children:"get_hint"}),"\n",(0,r.jsx)(e.pre,{children:(0,r.jsx)(e.code,{className:"language-python",children:"def get_hint(latest_action_id: str) -> str\n"})}),"\n",(0,r.jsx)(e.p,{children:"Returns action type hint based on given action_id"}),"\n",(0,r.jsx)(e.h4,{id:"get_prompt",children:"get_prompt"}),"\n",(0,r.jsx)(e.pre,{children:(0,r.jsx)(e.code,{className:"language-python",children:"def get_prompt(plan: Plan, history: List[Tuple[Action, Observation]]) -> str\n"})}),"\n",(0,r.jsx)(e.p,{children:"Gets the prompt for the planner agent.\nFormatted with the most recent action-observation pairs, current task, and hint based on last action"}),"\n",(0,r.jsxs)(e.p,{children:[(0,r.jsx)(e.strong,{children:"Arguments"}),":"]}),"\n",(0,r.jsxs)(e.ul,{children:["\n",(0,r.jsx)(e.li,{children:"plan (Plan): The original plan outlined by the user with LLM defined tasks"}),"\n",(0,r.jsx)(e.li,{children:"history (List[Tuple[Action, Observation]]): List of corresponding action-observation pairs"}),"\n"]}),"\n",(0,r.jsxs)(e.p,{children:[(0,r.jsx)(e.strong,{children:"Returns"}),":"]}),"\n",(0,r.jsxs)(e.ul,{children:["\n",(0,r.jsx)(e.li,{children:"str: The formatted string prompt with historical values"}),"\n"]}),"\n",(0,r.jsx)(e.h4,{id:"parse_response",children:"parse_response"}),"\n",(0,r.jsx)(e.pre,{children:(0,r.jsx)(e.code,{className:"language-python",children:"def parse_response(response: str) -> Action\n"})}),"\n",(0,r.jsx)(e.p,{children:"Parses the model output to find a valid action to take"}),"\n",(0,r.jsxs)(e.p,{children:[(0,r.jsx)(e.strong,{children:"Arguments"}),":"]}),"\n",(0,r.jsxs)(e.ul,{children:["\n",(0,r.jsx)(e.li,{children:"response (str): A response from the model that potentially contains an Action."}),"\n"]}),"\n",(0,r.jsxs)(e.p,{children:[(0,r.jsx)(e.strong,{children:"Returns"}),":"]}),"\n",(0,r.jsxs)(e.ul,{children:["\n",(0,r.jsx)(e.li,{children:"Action: A valid next action to perform from model output"}),"\n"]})]})}function d(n={}){const{wrapper:e}={...(0,s.R)(),...n.components};return e?(0,r.jsx)(e,{...n,children:(0,r.jsx)(c,{...n})}):c(n)}},8453:(n,e,t)=>{t.d(e,{R:()=>i,x:()=>a});var r=t(6540);const s={},o=r.createContext(s);function i(n){const e=r.useContext(o);return r.useMemo((function(){return"function"==typeof n?n(e):{...e,...n}}),[e,n])}function a(n){let e;return e=n.disableParentContext?"function"==typeof n.components?n.components(s):n.components||s:i(n.components),r.createElement(o.Provider,{value:e},n.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[8102],{1966:s=>{s.exports=JSON.parse('{"name":"docusaurus-plugin-content-docs","id":"default"}')}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[6732],{8601:(e,n,r)=>{r.r(n),r.d(n,{assets:()=>c,contentTitle:()=>i,default:()=>l,frontMatter:()=>s,metadata:()=>a,toc:()=>d});var o=r(4848),t=r(8453);const s={sidebar_label:"error",title:"opendevin.observation.error"},i=void 0,a={id:"python/opendevin/observation/error",title:"opendevin.observation.error",description:"AgentErrorObservation Objects",source:"@site/modules/python/opendevin/observation/error.md",sourceDirName:"python/opendevin/observation",slug:"/python/opendevin/observation/error",permalink:"/OpenDevin/modules/python/opendevin/observation/error",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"error",title:"opendevin.observation.error"},sidebar:"apiSidebar",previous:{title:"delegate",permalink:"/OpenDevin/modules/python/opendevin/observation/delegate"},next:{title:"files",permalink:"/OpenDevin/modules/python/opendevin/observation/files"}},c={},d=[{value:"AgentErrorObservation Objects",id:"agenterrorobservation-objects",level:2}];function p(e){const n={code:"code",h2:"h2",p:"p",pre:"pre",...(0,t.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(n.h2,{id:"agenterrorobservation-objects",children:"AgentErrorObservation Objects"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"@dataclass\nclass AgentErrorObservation(Observation)\n"})}),"\n",(0,o.jsx)(n.p,{children:"This data class represents an error encountered by the agent."})]})}function l(e={}){const{wrapper:n}={...(0,t.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(p,{...e})}):p(e)}},8453:(e,n,r)=>{r.d(n,{R:()=>i,x:()=>a});var o=r(6540);const t={},s=o.createContext(t);function i(e){const n=o.useContext(s);return o.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function a(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(t):e.components||t:i(e.components),o.createElement(s.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[9294],{7810:(e,n,i)=>{i.r(n),i.d(n,{default:()=>o});var s=i(781),t=i(4848);function o(){return(0,t.jsx)(s.A,{title:"FAQ",description:"Frequently Asked Questions",children:(0,t.jsxs)("div",{id:"faq",style:{maxWidth:"900px",margin:"0px auto",padding:"40px",textAlign:"justify"},children:[(0,t.jsx)("h1",{style:{fontSize:"3rem"},children:"Frequently Asked Questions"}),(0,t.jsx)("h2",{style:{fontSize:"2rem"},children:"Support"}),(0,t.jsx)("h3",{children:"How can I report an issue with OpenDevin?"}),(0,t.jsxs)("p",{children:["Please send us a message on our"," ",(0,t.jsx)("a",{href:"https://discord.gg/mBuDGRzzES",children:"Discord channel"})," or file a bug on"," ",(0,t.jsx)("a",{href:"https://github.com/OpenDevin/OpenDevin/issues",children:"GitHub"})," if you run into any issues!"]}),(0,t.jsx)("h2",{style:{fontSize:"2rem"},children:"General"}),(0,t.jsx)("h3",{children:"What is Devin?"}),(0,t.jsxs)("p",{children:[(0,t.jsx)("span",{style:{fontWeight:"600",color:"var(--logo)"},children:"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."]}),(0,t.jsx)("h3",{children:"Why OpenDevin?"}),(0,t.jsxs)("p",{children:["The"," ",(0,t.jsx)("span",{style:{fontWeight:"600",color:"var(--logo)"},children:"OpenDevin"})," ","project is born out of a desire to replicate, enhance, and innovate beyond the original Devin model. By engaging the"," ",(0,t.jsx)("a",{href:"https://github.com/OpenDevin/OpenDevin",children:"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."]})]})})}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[6872],{7791:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>r,contentTitle:()=>l,default:()=>c,frontMatter:()=>o,metadata:()=>a,toc:()=>p});var i=t(4848),s=t(8453);const o={sidebar_label:"system",title:"opendevin.utils.system"},l=void 0,a={id:"python/opendevin/utils/system",title:"opendevin.utils.system",description:"find\\available\\tcp\\_port",source:"@site/modules/python/opendevin/utils/system.md",sourceDirName:"python/opendevin/utils",slug:"/python/opendevin/utils/system",permalink:"/OpenDevin/modules/python/opendevin/utils/system",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"system",title:"opendevin.utils.system"},sidebar:"apiSidebar",previous:{title:"listen",permalink:"/OpenDevin/modules/python/opendevin/server/listen"},next:{title:"agent",permalink:"/OpenDevin/modules/python/opendevin/agent"}},r={},p=[{value:"find_available_tcp_port",id:"find_available_tcp_port",level:4}];function d(e){const n={code:"code",h4:"h4",p:"p",pre:"pre",...(0,s.R)(),...e.components};return(0,i.jsxs)(i.Fragment,{children:[(0,i.jsx)(n.h4,{id:"find_available_tcp_port",children:"find_available_tcp_port"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-python",children:"def find_available_tcp_port() -> int\n"})}),"\n",(0,i.jsx)(n.p,{children:"Find an available TCP port, return -1 if none available."})]})}function c(e={}){const{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,i.jsx)(n,{...e,children:(0,i.jsx)(d,{...e})}):d(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>l,x:()=>a});var i=t(6540);const s={},o=i.createContext(s);function l(e){const n=i.useContext(o);return i.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function a(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(s):e.components||s:l(e.components),i.createElement(o.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[7098],{4532:(n,e,s)=>{s.r(e),s.d(e,{default:()=>d});s(6540);var r=s(1003),o=s(2967),t=s(2252),c=s(2831),i=s(1463),u=s(4848);function a(n){const{version:e}=n;return(0,u.jsxs)(u.Fragment,{children:[(0,u.jsx)(i.A,{version:e.version,tag:(0,o.tU)(e.pluginId,e.version)}),(0,u.jsx)(r.be,{children:e.noIndex&&(0,u.jsx)("meta",{name:"robots",content:"noindex, nofollow"})})]})}function l(n){const{version:e,route:s}=n;return(0,u.jsx)(r.e3,{className:e.className,children:(0,u.jsx)(t.n,{version:e,children:(0,c.v)(s.routes)})})}function d(n){return(0,u.jsxs)(u.Fragment,{children:[(0,u.jsx)(a,{...n}),(0,u.jsx)(l,{...n})]})}}}]);
|
||||
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[4910],{9140:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>d,contentTitle:()=>r,default:()=>p,frontMatter:()=>a,metadata:()=>i,toc:()=>l});var o=t(4848),s=t(8453);const a={sidebar_label:"delegate",title:"opendevin.observation.delegate"},r=void 0,i={id:"python/opendevin/observation/delegate",title:"opendevin.observation.delegate",description:"AgentDelegateObservation Objects",source:"@site/modules/python/opendevin/observation/delegate.md",sourceDirName:"python/opendevin/observation",slug:"/python/opendevin/observation/delegate",permalink:"/OpenDevin/modules/python/opendevin/observation/delegate",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"delegate",title:"opendevin.observation.delegate"},sidebar:"apiSidebar",previous:{title:"browse",permalink:"/OpenDevin/modules/python/opendevin/observation/browse"},next:{title:"error",permalink:"/OpenDevin/modules/python/opendevin/observation/error"}},d={},l=[{value:"AgentDelegateObservation Objects",id:"agentdelegateobservation-objects",level:2}];function c(e){const n={code:"code",h2:"h2",p:"p",pre:"pre",...(0,s.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(n.h2,{id:"agentdelegateobservation-objects",children:"AgentDelegateObservation Objects"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"@dataclass\nclass AgentDelegateObservation(Observation)\n"})}),"\n",(0,o.jsx)(n.p,{children:"This data class represents a delegate observation.\nThis is used when the produced action is NOT executable."})]})}function p(e={}){const{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(c,{...e})}):c(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>r,x:()=>i});var o=t(6540);const s={},a=o.createContext(s);function r(e){const n=o.useContext(a);return o.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function i(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(s):e.components||s:r(e.components),o.createElement(a.Provider,{value:n},e.children)}}}]);
|
||||
File diff suppressed because one or more lines are too long
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[1730],{2060:(e,o,n)=>{n.r(o),n.d(o,{assets:()=>c,contentTitle:()=>t,default:()=>g,frontMatter:()=>s,metadata:()=>r,toc:()=>d});var i=n(4848),l=n(8453);const s={},t="Google Gemini/Vertex LLM",r={id:"usage/llms/googleLLMs",title:"Google Gemini/Vertex LLM",description:"Completion",source:"@site/modules/usage/llms/googleLLMs.md",sourceDirName:"usage/llms",slug:"/usage/llms/googleLLMs",permalink:"/OpenDevin/modules/usage/llms/googleLLMs",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{},sidebar:"docsSidebar",previous:{title:"Azure OpenAI LLM",permalink:"/OpenDevin/modules/usage/llms/azureLLMs"},next:{title:"Local LLM with Ollama",permalink:"/OpenDevin/modules/usage/llms/localLLMs"}},c={},d=[{value:"Completion",id:"completion",level:2},{value:"Gemini - Google AI Studio Configs",id:"gemini---google-ai-studio-configs",level:3},{value:"Vertex AI - Google Cloud Platform Configs",id:"vertex-ai---google-cloud-platform-configs",level:3}];function u(e){const o={a:"a",code:"code",h1:"h1",h2:"h2",h3:"h3",li:"li",p:"p",pre:"pre",ul:"ul",...(0,l.R)(),...e.components};return(0,i.jsxs)(i.Fragment,{children:[(0,i.jsx)(o.h1,{id:"google-geminivertex-llm",children:"Google Gemini/Vertex LLM"}),"\n",(0,i.jsx)(o.h2,{id:"completion",children:"Completion"}),"\n",(0,i.jsx)(o.p,{children:"OpenDevin uses LiteLLM for completion calls. The following resources are relevant for using OpenDevin with Google's LLMs"}),"\n",(0,i.jsxs)(o.ul,{children:["\n",(0,i.jsx)(o.li,{children:(0,i.jsx)(o.a,{href:"https://docs.litellm.ai/docs/providers/gemini",children:"Gemini - Google AI Studio"})}),"\n",(0,i.jsx)(o.li,{children:(0,i.jsx)(o.a,{href:"https://docs.litellm.ai/docs/providers/vertex",children:"VertexAI - Google Cloud Platform"})}),"\n"]}),"\n",(0,i.jsx)(o.h3,{id:"gemini---google-ai-studio-configs",children:"Gemini - Google AI Studio Configs"}),"\n",(0,i.jsxs)(o.p,{children:["To use Gemini through Google AI Studio when running the OpenDevin Docker image, you'll need to set the following environment variables using ",(0,i.jsx)(o.code,{children:"-e"}),":"]}),"\n",(0,i.jsx)(o.pre,{children:(0,i.jsx)(o.code,{children:'GEMINI_API_KEY="<your-google-api-key>"\nLLM_MODEL="gemini/gemini-1.5-pro"\n'})}),"\n",(0,i.jsx)(o.h3,{id:"vertex-ai---google-cloud-platform-configs",children:"Vertex AI - Google Cloud Platform Configs"}),"\n",(0,i.jsxs)(o.p,{children:["To use Vertex AI through Google Cloud Platform when running the OpenDevin Docker image, you'll need to set the following environment variables using ",(0,i.jsx)(o.code,{children:"-e"}),":"]}),"\n",(0,i.jsx)(o.pre,{children:(0,i.jsx)(o.code,{children:'GOOGLE_APPLICATION_CREDENTIALS="<json-dump-of-gcp-service-account-json>"\nVERTEXAI_PROJECT="<your-gcp-project-id>"\nVERTEXAI_LOCATION="<your-gcp-location>"\nLLM_MODEL="vertex_ai/<desired-llm-model>"\n'})})]})}function g(e={}){const{wrapper:o}={...(0,l.R)(),...e.components};return o?(0,i.jsx)(o,{...e,children:(0,i.jsx)(u,{...e})}):u(e)}},8453:(e,o,n)=>{n.d(o,{R:()=>t,x:()=>r});var i=n(6540);const l={},s=i.createContext(l);function t(e){const o=i.useContext(s);return i.useMemo((function(){return"function"==typeof e?e(o):{...o,...e}}),[o,e])}function r(e){let o;return o=e.disableParentContext?"function"==typeof e.components?e.components(l):e.components||l:t(e.components),i.createElement(s.Provider,{value:o},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[1707],{1788:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>d,contentTitle:()=>a,default:()=>h,frontMatter:()=>l,metadata:()=>o,toc:()=>c});var i=t(4848),s=t(8453);const l={sidebar_label:"action",title:"opendevin.schema.action"},a=void 0,o={id:"python/opendevin/schema/action",title:"opendevin.schema.action",description:"ActionTypeSchema Objects",source:"@site/modules/python/opendevin/schema/action.md",sourceDirName:"python/opendevin/schema",slug:"/python/opendevin/schema/action",permalink:"/OpenDevin/modules/python/opendevin/schema/action",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"action",title:"opendevin.schema.action"},sidebar:"apiSidebar",previous:{title:"requirement",permalink:"/OpenDevin/modules/python/opendevin/sandbox/plugins/requirement"},next:{title:"observation",permalink:"/OpenDevin/modules/python/opendevin/schema/observation"}},d={},c=[{value:"ActionTypeSchema Objects",id:"actiontypeschema-objects",level:2},{value:"INIT",id:"init",level:4},{value:"START",id:"start",level:4},{value:"READ",id:"read",level:4},{value:"WRITE",id:"write",level:4},{value:"RUN",id:"run",level:4},{value:"KILL",id:"kill",level:4},{value:"BROWSE",id:"browse",level:4},{value:"RECALL",id:"recall",level:4},{value:"THINK",id:"think",level:4},{value:"DELEGATE",id:"delegate",level:4},{value:"FINISH",id:"finish",level:4},{value:"PAUSE",id:"pause",level:4},{value:"RESUME",id:"resume",level:4},{value:"STOP",id:"stop",level:4},{value:"PUSH",id:"push",level:4},{value:"SEND_PR",id:"send_pr",level:4}];function r(e){const n={code:"code",h2:"h2",h4:"h4",p:"p",pre:"pre",...(0,s.R)(),...e.components};return(0,i.jsxs)(i.Fragment,{children:[(0,i.jsx)(n.h2,{id:"actiontypeschema-objects",children:"ActionTypeSchema Objects"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-python",children:"class ActionTypeSchema(BaseModel)\n"})}),"\n",(0,i.jsx)(n.h4,{id:"init",children:"INIT"}),"\n",(0,i.jsx)(n.p,{children:"Initializes the agent. Only sent by client."}),"\n",(0,i.jsx)(n.h4,{id:"start",children:"START"}),"\n",(0,i.jsx)(n.p,{children:"Starts a new development task. Only sent by the client."}),"\n",(0,i.jsx)(n.h4,{id:"read",children:"READ"}),"\n",(0,i.jsx)(n.p,{children:"Reads the content of a file."}),"\n",(0,i.jsx)(n.h4,{id:"write",children:"WRITE"}),"\n",(0,i.jsx)(n.p,{children:"Writes the content to a file."}),"\n",(0,i.jsx)(n.h4,{id:"run",children:"RUN"}),"\n",(0,i.jsx)(n.p,{children:"Runs a command."}),"\n",(0,i.jsx)(n.h4,{id:"kill",children:"KILL"}),"\n",(0,i.jsx)(n.p,{children:"Kills a background command."}),"\n",(0,i.jsx)(n.h4,{id:"browse",children:"BROWSE"}),"\n",(0,i.jsx)(n.p,{children:"Opens a web page."}),"\n",(0,i.jsx)(n.h4,{id:"recall",children:"RECALL"}),"\n",(0,i.jsx)(n.p,{children:"Searches long-term memory"}),"\n",(0,i.jsx)(n.h4,{id:"think",children:"THINK"}),"\n",(0,i.jsx)(n.p,{children:"Allows the agent to make a plan, set a goal, or record thoughts"}),"\n",(0,i.jsx)(n.h4,{id:"delegate",children:"DELEGATE"}),"\n",(0,i.jsx)(n.p,{children:"Delegates a task to another agent."}),"\n",(0,i.jsx)(n.h4,{id:"finish",children:"FINISH"}),"\n",(0,i.jsx)(n.p,{children:"If you're absolutely certain that you've completed your task and have tested your work,\nuse the finish action to stop working."}),"\n",(0,i.jsx)(n.h4,{id:"pause",children:"PAUSE"}),"\n",(0,i.jsx)(n.p,{children:"Pauses the task."}),"\n",(0,i.jsx)(n.h4,{id:"resume",children:"RESUME"}),"\n",(0,i.jsx)(n.p,{children:"Resumes the task."}),"\n",(0,i.jsx)(n.h4,{id:"stop",children:"STOP"}),"\n",(0,i.jsx)(n.p,{children:"Stops the task. Must send a start action to restart a new task."}),"\n",(0,i.jsx)(n.h4,{id:"push",children:"PUSH"}),"\n",(0,i.jsx)(n.p,{children:"Push a branch to github."}),"\n",(0,i.jsx)(n.h4,{id:"send_pr",children:"SEND_PR"}),"\n",(0,i.jsx)(n.p,{children:"Send a PR to github."})]})}function h(e={}){const{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,i.jsx)(n,{...e,children:(0,i.jsx)(r,{...e})}):r(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>a,x:()=>o});var i=t(6540);const s={},l=i.createContext(s);function a(e){const n=i.useContext(l);return i.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function o(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(s):e.components||s:a(e.components),i.createElement(l.Provider,{value:n},e.children)}}}]);
|
||||
File diff suppressed because one or more lines are too long
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[8750],{2464:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>l,contentTitle:()=>s,default:()=>d,frontMatter:()=>c,metadata:()=>a,toc:()=>r});var o=t(4848),i=t(8453);const c={sidebar_label:"base",title:"opendevin.action.base"},s=void 0,a={id:"python/opendevin/action/base",title:"opendevin.action.base",description:"NullAction Objects",source:"@site/modules/python/opendevin/action/base.md",sourceDirName:"python/opendevin/action",slug:"/python/opendevin/action/base",permalink:"/OpenDevin/modules/python/opendevin/action/base",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"base",title:"opendevin.action.base"},sidebar:"apiSidebar",previous:{title:"action",permalink:"/OpenDevin/modules/python/opendevin/action/__init__"},next:{title:"fileop",permalink:"/OpenDevin/modules/python/opendevin/action/fileop"}},l={},r=[{value:"NullAction Objects",id:"nullaction-objects",level:2}];function p(e){const n={code:"code",h2:"h2",p:"p",pre:"pre",...(0,i.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(n.h2,{id:"nullaction-objects",children:"NullAction Objects"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"@dataclass\nclass NullAction(NotExecutableAction)\n"})}),"\n",(0,o.jsx)(n.p,{children:"An action that does nothing."})]})}function d(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(p,{...e})}):p(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>s,x:()=>a});var o=t(6540);const i={},c=o.createContext(i);function s(e){const n=o.useContext(c);return o.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function a(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(i):e.components||i:s(e.components),o.createElement(c.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[2042],{1865:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>a,contentTitle:()=>o,default:()=>c,frontMatter:()=>l,metadata:()=>r,toc:()=>d});var s=t(4848),i=t(8453);const l={sidebar_label:"listen",title:"opendevin.server.listen"},o=void 0,r={id:"python/opendevin/server/listen",title:"opendevin.server.listen",description:"get\\litellm\\models",source:"@site/modules/python/opendevin/server/listen.md",sourceDirName:"python/opendevin/server",slug:"/python/opendevin/server/listen",permalink:"/OpenDevin/modules/python/opendevin/server/listen",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"listen",title:"opendevin.server.listen"},sidebar:"apiSidebar",previous:{title:"session",permalink:"/OpenDevin/modules/python/opendevin/server/session/"},next:{title:"system",permalink:"/OpenDevin/modules/python/opendevin/utils/system"}},a={},d=[{value:"get_litellm_models",id:"get_litellm_models",level:4},{value:"get_agents",id:"get_agents",level:4},{value:"get_token",id:"get_token",level:4}];function p(e){const n={code:"code",h4:"h4",p:"p",pre:"pre",...(0,i.R)(),...e.components};return(0,s.jsxs)(s.Fragment,{children:[(0,s.jsx)(n.h4,{id:"get_litellm_models",children:"get_litellm_models"}),"\n",(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-python",children:"@app.get('/api/litellm-models')\nasync def get_litellm_models()\n"})}),"\n",(0,s.jsx)(n.p,{children:"Get all models supported by LiteLLM."}),"\n",(0,s.jsx)(n.h4,{id:"get_agents",children:"get_agents"}),"\n",(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-python",children:"@app.get('/api/agents')\nasync def get_agents()\n"})}),"\n",(0,s.jsx)(n.p,{children:"Get all agents supported by LiteLLM."}),"\n",(0,s.jsx)(n.h4,{id:"get_token",children:"get_token"}),"\n",(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-python",children:"@app.get('/api/auth')\nasync def get_token(\n credentials: HTTPAuthorizationCredentials = Depends(security_scheme))\n"})}),"\n",(0,s.jsx)(n.p,{children:"Generate a JWT for authentication when starting a WebSocket connection. This endpoint checks if valid credentials\nare provided and uses them to get a session ID. If no valid credentials are provided, it generates a new session ID."})]})}function c(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,s.jsx)(n,{...e,children:(0,s.jsx)(p,{...e})}):p(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>o,x:()=>r});var s=t(6540);const i={},l=s.createContext(i);function o(e){const n=s.useContext(l);return s.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function r(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(i):e.components||i:o(e.components),s.createElement(l.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[8474],{7976:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>a,contentTitle:()=>l,default:()=>u,frontMatter:()=>r,metadata:()=>i,toc:()=>c});var o=t(4848),s=t(8453);const r={sidebar_label:"json",title:"agenthub.monologue_agent.utils.json"},l=void 0,i={id:"python/agenthub/monologue_agent/utils/json",title:"agenthub.monologue_agent.utils.json",description:"my\\_encoder",source:"@site/modules/python/agenthub/monologue_agent/utils/json.md",sourceDirName:"python/agenthub/monologue_agent/utils",slug:"/python/agenthub/monologue_agent/utils/json",permalink:"/OpenDevin/modules/python/agenthub/monologue_agent/utils/json",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"json",title:"agenthub.monologue_agent.utils.json"},sidebar:"apiSidebar",previous:{title:"agent",permalink:"/OpenDevin/modules/python/agenthub/micro/agent"},next:{title:"memory",permalink:"/OpenDevin/modules/python/agenthub/monologue_agent/utils/memory"}},a={},c=[{value:"my_encoder",id:"my_encoder",level:4},{value:"dumps",id:"dumps",level:4},{value:"loads",id:"loads",level:4}];function d(e){const n={code:"code",h4:"h4",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,s.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(n.h4,{id:"my_encoder",children:"my_encoder"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"def my_encoder(obj)\n"})}),"\n",(0,o.jsx)(n.p,{children:"Encodes objects as dictionaries"}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Arguments"}),":"]}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsx)(n.li,{children:"obj (Object): An object that will be converted"}),"\n"]}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Returns"}),":"]}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsx)(n.li,{children:"dict: If the object can be converted it is returned in dict format"}),"\n"]}),"\n",(0,o.jsx)(n.h4,{id:"dumps",children:"dumps"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"def dumps(obj, **kwargs)\n"})}),"\n",(0,o.jsx)(n.p,{children:"Serialize an object to str format"}),"\n",(0,o.jsx)(n.h4,{id:"loads",children:"loads"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"def loads(s, **kwargs)\n"})}),"\n",(0,o.jsx)(n.p,{children:"Create a JSON object from str"})]})}function u(e={}){const{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(d,{...e})}):d(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>l,x:()=>i});var o=t(6540);const s={},r=o.createContext(s);function l(e){const n=o.useContext(r);return o.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function i(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(s):e.components||s:l(e.components),o.createElement(r.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[2609],{6817:(e,s,n)=>{n.r(s),n.d(s,{assets:()=>c,contentTitle:()=>i,default:()=>p,frontMatter:()=>r,metadata:()=>a,toc:()=>d});var t=n(4848),o=n(8453);const r={sidebar_label:"msg_stack",title:"opendevin.server.session.msg_stack"},i=void 0,a={id:"python/opendevin/server/session/msg_stack",title:"opendevin.server.session.msg_stack",description:"Message Objects",source:"@site/modules/python/opendevin/server/session/msg_stack.md",sourceDirName:"python/opendevin/server/session",slug:"/python/opendevin/server/session/msg_stack",permalink:"/OpenDevin/modules/python/opendevin/server/session/msg_stack",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"msg_stack",title:"opendevin.server.session.msg_stack"},sidebar:"apiSidebar",previous:{title:"manager",permalink:"/OpenDevin/modules/python/opendevin/server/session/manager"},next:{title:"session",permalink:"/OpenDevin/modules/python/opendevin/server/session/"}},c={},d=[{value:"Message Objects",id:"message-objects",level:2},{value:"role",id:"role",level:4}];function l(e){const s={code:"code",h2:"h2",h4:"h4",p:"p",pre:"pre",...(0,o.R)(),...e.components};return(0,t.jsxs)(t.Fragment,{children:[(0,t.jsx)(s.h2,{id:"message-objects",children:"Message Objects"}),"\n",(0,t.jsx)(s.pre,{children:(0,t.jsx)(s.code,{className:"language-python",children:"class Message()\n"})}),"\n",(0,t.jsx)(s.h4,{id:"role",children:"role"}),"\n",(0,t.jsx)(s.p,{children:'"user"| "assistant"'})]})}function p(e={}){const{wrapper:s}={...(0,o.R)(),...e.components};return s?(0,t.jsx)(s,{...e,children:(0,t.jsx)(l,{...e})}):l(e)}},8453:(e,s,n)=>{n.d(s,{R:()=>i,x:()=>a});var t=n(6540);const o={},r=t.createContext(o);function i(e){const s=t.useContext(r);return t.useMemo((function(){return"function"==typeof e?e(s):{...s,...e}}),[s,e])}function a(e){let s;return s=e.disableParentContext?"function"==typeof e.components?e.components(o):e.components||o:i(e.components),t.createElement(r.Provider,{value:s},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[300],{4761:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>c,contentTitle:()=>i,default:()=>a,frontMatter:()=>o,metadata:()=>l,toc:()=>d});var r=t(4848),s=t(8453);const o={sidebar_label:"files",title:"opendevin.files"},i=void 0,l={id:"python/opendevin/files",title:"opendevin.files",description:"WorkspaceFile Objects",source:"@site/modules/python/opendevin/files.md",sourceDirName:"python/opendevin",slug:"/python/opendevin/files",permalink:"/OpenDevin/modules/python/opendevin/files",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"files",title:"opendevin.files"},sidebar:"apiSidebar",previous:{title:"config",permalink:"/OpenDevin/modules/python/opendevin/config"},next:{title:"logger",permalink:"/OpenDevin/modules/python/opendevin/logger"}},c={},d=[{value:"WorkspaceFile Objects",id:"workspacefile-objects",level:2},{value:"to_dict",id:"to_dict",level:4},{value:"get_folder_structure",id:"get_folder_structure",level:4}];function p(e){const n={code:"code",h2:"h2",h4:"h4",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,s.R)(),...e.components};return(0,r.jsxs)(r.Fragment,{children:[(0,r.jsx)(n.h2,{id:"workspacefile-objects",children:"WorkspaceFile Objects"}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-python",children:"class WorkspaceFile()\n"})}),"\n",(0,r.jsx)(n.h4,{id:"to_dict",children:"to_dict"}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-python",children:"def to_dict() -> Dict[str, Any]\n"})}),"\n",(0,r.jsx)(n.p,{children:"Converts the File object to a dictionary."}),"\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.strong,{children:"Returns"}),":"]}),"\n",(0,r.jsx)(n.p,{children:"The dictionary representation of the File object."}),"\n",(0,r.jsx)(n.h4,{id:"get_folder_structure",children:"get_folder_structure"}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-python",children:"def get_folder_structure(workdir: Path) -> WorkspaceFile\n"})}),"\n",(0,r.jsx)(n.p,{children:"Gets the folder structure of a directory."}),"\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.strong,{children:"Arguments"}),":"]}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.code,{children:"workdir"})," - The directory path."]}),"\n"]}),"\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.strong,{children:"Returns"}),":"]}),"\n",(0,r.jsx)(n.p,{children:"The folder structure."})]})}function a(e={}){const{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,r.jsx)(n,{...e,children:(0,r.jsx)(p,{...e})}):p(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>i,x:()=>l});var r=t(6540);const s={},o=r.createContext(s);function i(e){const n=r.useContext(o);return r.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function l(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(s):e.components||s:i(e.components),r.createElement(o.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[8176],{6677:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>d,contentTitle:()=>c,default:()=>h,frontMatter:()=>a,metadata:()=>i,toc:()=>r});var s=t(4848),o=t(8453);const a={sidebar_label:"codeact_agent",title:"agenthub.codeact_agent.codeact_agent"},c=void 0,i={id:"python/agenthub/codeact_agent/codeact_agent",title:"agenthub.codeact_agent.codeact_agent",description:"CodeActAgent Objects",source:"@site/modules/python/agenthub/codeact_agent/codeact_agent.md",sourceDirName:"python/agenthub/codeact_agent",slug:"/python/agenthub/codeact_agent/",permalink:"/OpenDevin/modules/python/agenthub/codeact_agent/",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"codeact_agent",title:"agenthub.codeact_agent.codeact_agent"},sidebar:"apiSidebar",previous:{title:"parser",permalink:"/OpenDevin/modules/python/agenthub/SWE_agent/parser"},next:{title:"agent",permalink:"/OpenDevin/modules/python/agenthub/delegator_agent/agent"}},d={},r=[{value:"CodeActAgent Objects",id:"codeactagent-objects",level:2},{value:"__init__",id:"__init__",level:4},{value:"step",id:"step",level:4}];function l(e){const n={code:"code",h2:"h2",h4:"h4",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,o.R)(),...e.components};return(0,s.jsxs)(s.Fragment,{children:[(0,s.jsx)(n.h2,{id:"codeactagent-objects",children:"CodeActAgent Objects"}),"\n",(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-python",children:"class CodeActAgent(Agent)\n"})}),"\n",(0,s.jsx)(n.p,{children:"The Code Act Agent is a minimalist agent.\nThe agent works by passing the model a list of action-observation pairs and prompting the model to take the next step."}),"\n",(0,s.jsx)(n.h4,{id:"__init__",children:"__init__"}),"\n",(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-python",children:"def __init__(llm: LLM) -> None\n"})}),"\n",(0,s.jsx)(n.p,{children:"Initializes a new instance of the CodeActAgent class."}),"\n",(0,s.jsxs)(n.p,{children:[(0,s.jsx)(n.strong,{children:"Arguments"}),":"]}),"\n",(0,s.jsxs)(n.ul,{children:["\n",(0,s.jsx)(n.li,{children:"llm (LLM): The llm to be used by this agent"}),"\n"]}),"\n",(0,s.jsx)(n.h4,{id:"step",children:"step"}),"\n",(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-python",children:"def step(state: State) -> Action\n"})}),"\n",(0,s.jsx)(n.p,{children:"Performs one step using the Code Act Agent.\nThis includes gathering info on previous steps and prompting the model to make a command to execute."}),"\n",(0,s.jsxs)(n.p,{children:[(0,s.jsx)(n.strong,{children:"Arguments"}),":"]}),"\n",(0,s.jsxs)(n.ul,{children:["\n",(0,s.jsx)(n.li,{children:"state (State): used to get updated info and background commands"}),"\n"]}),"\n",(0,s.jsxs)(n.p,{children:[(0,s.jsx)(n.strong,{children:"Returns"}),":"]}),"\n",(0,s.jsxs)(n.ul,{children:["\n",(0,s.jsx)(n.li,{children:"CmdRunAction(command) - command action to run"}),"\n",(0,s.jsx)(n.li,{children:"AgentEchoAction(content=INVALID_INPUT_MESSAGE) - invalid command output"}),"\n"]}),"\n",(0,s.jsxs)(n.p,{children:[(0,s.jsx)(n.strong,{children:"Raises"}),":"]}),"\n",(0,s.jsxs)(n.ul,{children:["\n",(0,s.jsx)(n.li,{children:"NotImplementedError - for actions other than CmdOutputObservation or AgentMessageObservation"}),"\n"]})]})}function h(e={}){const{wrapper:n}={...(0,o.R)(),...e.components};return n?(0,s.jsx)(n,{...e,children:(0,s.jsx)(l,{...e})}):l(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>c,x:()=>i});var s=t(6540);const o={},a=s.createContext(o);function c(e){const n=s.useContext(a);return s.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function i(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(o):e.components||o:c(e.components),s.createElement(a.Provider,{value:n},e.children)}}}]);
|
||||
File diff suppressed because one or more lines are too long
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[3945],{2258:(e,n,s)=>{s.r(n),s.d(n,{assets:()=>d,contentTitle:()=>a,default:()=>p,frontMatter:()=>i,metadata:()=>r,toc:()=>c});var t=s(4848),o=s(8453);const i={sidebar_label:"base",title:"opendevin.observation.base"},a=void 0,r={id:"python/opendevin/observation/base",title:"opendevin.observation.base",description:"Observation Objects",source:"@site/modules/python/opendevin/observation/base.md",sourceDirName:"python/opendevin/observation",slug:"/python/opendevin/observation/base",permalink:"/OpenDevin/modules/python/opendevin/observation/base",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"base",title:"opendevin.observation.base"},sidebar:"apiSidebar",previous:{title:"observation",permalink:"/OpenDevin/modules/python/opendevin/observation/__init__"},next:{title:"browse",permalink:"/OpenDevin/modules/python/opendevin/observation/browse"}},d={},c=[{value:"Observation Objects",id:"observation-objects",level:2},{value:"to_dict",id:"to_dict",level:4},{value:"to_memory",id:"to_memory",level:4},{value:"message",id:"message",level:4},{value:"NullObservation Objects",id:"nullobservation-objects",level:2}];function l(e){const n={code:"code",h2:"h2",h4:"h4",p:"p",pre:"pre",...(0,o.R)(),...e.components};return(0,t.jsxs)(t.Fragment,{children:[(0,t.jsx)(n.h2,{id:"observation-objects",children:"Observation Objects"}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-python",children:"@dataclass\nclass Observation()\n"})}),"\n",(0,t.jsx)(n.p,{children:"This data class represents an observation of the environment."}),"\n",(0,t.jsx)(n.h4,{id:"to_dict",children:"to_dict"}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-python",children:"def to_dict() -> dict\n"})}),"\n",(0,t.jsx)(n.p,{children:"Converts the observation to a dictionary and adds user message."}),"\n",(0,t.jsx)(n.h4,{id:"to_memory",children:"to_memory"}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-python",children:"def to_memory() -> dict\n"})}),"\n",(0,t.jsx)(n.p,{children:"Converts the observation to a dictionary."}),"\n",(0,t.jsx)(n.h4,{id:"message",children:"message"}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-python",children:"@property\ndef message() -> str\n"})}),"\n",(0,t.jsx)(n.p,{children:"Returns a message describing the observation."}),"\n",(0,t.jsx)(n.h2,{id:"nullobservation-objects",children:"NullObservation Objects"}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-python",children:"@dataclass\nclass NullObservation(Observation)\n"})}),"\n",(0,t.jsx)(n.p,{children:"This data class represents a null observation.\nThis is used when the produced action is NOT executable."})]})}function p(e={}){const{wrapper:n}={...(0,o.R)(),...e.components};return n?(0,t.jsx)(n,{...e,children:(0,t.jsx)(l,{...e})}):l(e)}},8453:(e,n,s)=>{s.d(n,{R:()=>a,x:()=>r});var t=s(6540);const o={},i=t.createContext(o);function a(e){const n=t.useContext(i);return t.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function r(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(o):e.components||o:a(e.components),t.createElement(i.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[1930],{9139:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>l,contentTitle:()=>i,default:()=>g,frontMatter:()=>r,metadata:()=>o,toc:()=>c});var s=t(4848),a=t(8453);const r={sidebar_label:"agent",title:"agenthub.delegator_agent.agent"},i=void 0,o={id:"python/agenthub/delegator_agent/agent",title:"agenthub.delegator_agent.agent",description:"DelegatorAgent Objects",source:"@site/modules/python/agenthub/delegator_agent/agent.md",sourceDirName:"python/agenthub/delegator_agent",slug:"/python/agenthub/delegator_agent/agent",permalink:"/OpenDevin/modules/python/agenthub/delegator_agent/agent",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"agent",title:"agenthub.delegator_agent.agent"},sidebar:"apiSidebar",previous:{title:"codeact_agent",permalink:"/OpenDevin/modules/python/agenthub/codeact_agent/"},next:{title:"agent",permalink:"/OpenDevin/modules/python/agenthub/dummy_agent/agent"}},l={},c=[{value:"DelegatorAgent Objects",id:"delegatoragent-objects",level:2},{value:"__init__",id:"__init__",level:4},{value:"step",id:"step",level:4}];function d(e){const n={code:"code",h2:"h2",h4:"h4",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,a.R)(),...e.components};return(0,s.jsxs)(s.Fragment,{children:[(0,s.jsx)(n.h2,{id:"delegatoragent-objects",children:"DelegatorAgent Objects"}),"\n",(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-python",children:"class DelegatorAgent(Agent)\n"})}),"\n",(0,s.jsx)(n.p,{children:"The planner agent utilizes a special prompting strategy to create long term plans for solving problems.\nThe agent is given its previous action-observation pairs, current task, and hint based on last action taken at every step."}),"\n",(0,s.jsx)(n.h4,{id:"__init__",children:"__init__"}),"\n",(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-python",children:"def __init__(llm: LLM)\n"})}),"\n",(0,s.jsx)(n.p,{children:"Initialize the Delegator Agent with an LLM"}),"\n",(0,s.jsxs)(n.p,{children:[(0,s.jsx)(n.strong,{children:"Arguments"}),":"]}),"\n",(0,s.jsxs)(n.ul,{children:["\n",(0,s.jsx)(n.li,{children:"llm (LLM): The llm to be used by this agent"}),"\n"]}),"\n",(0,s.jsx)(n.h4,{id:"step",children:"step"}),"\n",(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-python",children:"def step(state: State) -> Action\n"})}),"\n",(0,s.jsx)(n.p,{children:"Checks to see if current step is completed, returns AgentFinishAction if True.\nOtherwise, creates a plan prompt and sends to model for inference, returning the result as the next action."}),"\n",(0,s.jsxs)(n.p,{children:[(0,s.jsx)(n.strong,{children:"Arguments"}),":"]}),"\n",(0,s.jsxs)(n.ul,{children:["\n",(0,s.jsx)(n.li,{children:"state (State): The current state given the previous actions and observations"}),"\n"]}),"\n",(0,s.jsxs)(n.p,{children:[(0,s.jsx)(n.strong,{children:"Returns"}),":"]}),"\n",(0,s.jsxs)(n.ul,{children:["\n",(0,s.jsx)(n.li,{children:"AgentFinishAction: If the last state was 'completed', 'verified', or 'abandoned'"}),"\n",(0,s.jsx)(n.li,{children:"Action: The next action to take based on llm response"}),"\n"]})]})}function g(e={}){const{wrapper:n}={...(0,a.R)(),...e.components};return n?(0,s.jsx)(n,{...e,children:(0,s.jsx)(d,{...e})}):d(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>i,x:()=>o});var s=t(6540);const a={},r=s.createContext(a);function i(e){const n=s.useContext(r);return s.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function o(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(a):e.components||a:i(e.components),s.createElement(r.Provider,{value:n},e.children)}}}]);
|
||||
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[2259],{8466:(e,n,o)=>{o.r(n),o.d(n,{assets:()=>d,contentTitle:()=>r,default:()=>u,frontMatter:()=>i,metadata:()=>l,toc:()=>c});var t=o(4848),s=o(8453);const i={},r="Notes for Windows and WSL Users",l={id:"usage/troubleshooting/windows",title:"Notes for Windows and WSL Users",description:"OpenDevin only supports Windows via WSL.",source:"@site/modules/usage/troubleshooting/windows.md",sourceDirName:"usage/troubleshooting",slug:"/usage/troubleshooting/windows",permalink:"/OpenDevin/modules/usage/troubleshooting/windows",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{},sidebar:"docsSidebar",previous:{title:"\ud83d\udea7 Troubleshooting",permalink:"/OpenDevin/modules/usage/troubleshooting/"},next:{title:"\ud83d\udcda Misc",permalink:"/OpenDevin/modules/usage/about"}},d={},c=[{value:"Troubleshooting",id:"troubleshooting",level:2},{value:"Failed to create opendevin user",id:"failed-to-create-opendevin-user",level:3},{value:"Poetry Installation",id:"poetry-installation",level:3},{value:"NoneType object has no attribute 'request'",id:"nonetype-object-has-no-attribute-request",level:3}];function a(e){const n={a:"a",code:"code",h1:"h1",h2:"h2",h3:"h3",li:"li",p:"p",pre:"pre",ul:"ul",...(0,s.R)(),...e.components};return(0,t.jsxs)(t.Fragment,{children:[(0,t.jsx)(n.h1,{id:"notes-for-windows-and-wsl-users",children:"Notes for Windows and WSL Users"}),"\n",(0,t.jsxs)(n.p,{children:["OpenDevin only supports Windows via ",(0,t.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install",children:"WSL"}),".\nPlease be sure to run all commands inside your WSL terminal."]}),"\n",(0,t.jsx)(n.h2,{id:"troubleshooting",children:"Troubleshooting"}),"\n",(0,t.jsx)(n.h3,{id:"failed-to-create-opendevin-user",children:"Failed to create opendevin user"}),"\n",(0,t.jsxs)(n.p,{children:["If you encounter the following error during setup: ",(0,t.jsx)(n.code,{children:"Exception: Failed to create opendevin user in sandbox: b'useradd: UID 0 is not unique\\n'"}),"\nYou can resolve it by running:\n",(0,t.jsx)(n.code,{children:" export SANDBOX_USER_ID=1000 "})]}),"\n",(0,t.jsx)(n.h3,{id:"poetry-installation",children:"Poetry Installation"}),"\n",(0,t.jsxs)(n.p,{children:["If you face issues running Poetry even after installing it during the build process, you may need to add its binary path to your environment:\n",(0,t.jsx)(n.code,{children:' export PATH="$HOME/.local/bin:$PATH" '})]}),"\n",(0,t.jsx)(n.h3,{id:"nonetype-object-has-no-attribute-request",children:"NoneType object has no attribute 'request'"}),"\n",(0,t.jsxs)(n.p,{children:["If you experiencing issues related to networking, such as ",(0,t.jsx)(n.code,{children:"NoneType object has no attribute 'request'"})," when executing ",(0,t.jsx)(n.code,{children:"make run"}),", you may need to configure your WSL2 networking settings. Follow these steps:"]}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:["Open or create the ",(0,t.jsx)(n.code,{children:".wslconfig"})," file located at ",(0,t.jsx)(n.code,{children:"C:\\Users\\%username%\\.wslconfig"})," on your Windows host machine."]}),"\n",(0,t.jsxs)(n.li,{children:["Add the following configuration to the ",(0,t.jsx)(n.code,{children:".wslconfig"})," file:"]}),"\n"]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{children:"[wsl2]\nnetworkingMode=mirrored\nlocalhostForwarding=true\n"})}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:["Save the ",(0,t.jsx)(n.code,{children:".wslconfig"})," file."]}),"\n",(0,t.jsxs)(n.li,{children:["Restart WSL2 completely by exiting any running WSL2 instances and executing the command ",(0,t.jsx)(n.code,{children:"wsl --shutdown"})," in your command prompt or terminal."]}),"\n",(0,t.jsxs)(n.li,{children:["After restarting WSL, attempt to execute ",(0,t.jsx)(n.code,{children:"make run"})," again. The networking issue should be resolved."]}),"\n"]})]})}function u(e={}){const{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,t.jsx)(n,{...e,children:(0,t.jsx)(a,{...e})}):a(e)}},8453:(e,n,o)=>{o.d(n,{R:()=>r,x:()=>l});var t=o(6540);const s={},i=t.createContext(s);function r(e){const n=t.useContext(i);return t.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function l(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(s):e.components||s:r(e.components),t.createElement(i.Provider,{value:n},e.children)}}}]);
|
||||
@@ -0,0 +1 @@
|
||||
"use strict";(self.webpackChunkdocs=self.webpackChunkdocs||[]).push([[5632],{190:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>c,contentTitle:()=>i,default:()=>u,frontMatter:()=>r,metadata:()=>a,toc:()=>p});var o=t(4848),s=t(8453);const r={sidebar_label:"run",title:"opendevin.observation.run"},i=void 0,a={id:"python/opendevin/observation/run",title:"opendevin.observation.run",description:"CmdOutputObservation Objects",source:"@site/modules/python/opendevin/observation/run.md",sourceDirName:"python/opendevin/observation",slug:"/python/opendevin/observation/run",permalink:"/OpenDevin/modules/python/opendevin/observation/run",draft:!1,unlisted:!1,tags:[],version:"current",frontMatter:{sidebar_label:"run",title:"opendevin.observation.run"},sidebar:"apiSidebar",previous:{title:"recall",permalink:"/OpenDevin/modules/python/opendevin/observation/recall"},next:{title:"process",permalink:"/OpenDevin/modules/python/opendevin/sandbox/docker/process"}},c={},p=[{value:"CmdOutputObservation Objects",id:"cmdoutputobservation-objects",level:2}];function d(e){const n={code:"code",h2:"h2",p:"p",pre:"pre",...(0,s.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(n.h2,{id:"cmdoutputobservation-objects",children:"CmdOutputObservation Objects"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-python",children:"@dataclass\nclass CmdOutputObservation(Observation)\n"})}),"\n",(0,o.jsx)(n.p,{children:"This data class represents the output of a command."})]})}function u(e={}){const{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(d,{...e})}):d(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>i,x:()=>a});var o=t(6540);const s={},r=o.createContext(s);function i(e){const n=o.useContext(r);return o.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function a(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(s):e.components||s:i(e.components),o.createElement(r.Provider,{value:n},e.children)}}}]);
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user