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2 Commits

Author SHA1 Message Date
openhands
c7e00bd101 Fix TypeScript errors and run build 2025-01-08 18:21:24 +00:00
openhands
45ba481fdf Move GitHub API calls from frontend to backend 2025-01-08 18:01:03 +00:00
341 changed files with 6612 additions and 15567 deletions

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@@ -56,7 +56,7 @@ jobs:
docker-images: false
swap-storage: true
- name: Set up QEMU
uses: docker/setup-qemu-action@v3.3.0
uses: docker/setup-qemu-action@v3.2.0
with:
image: tonistiigi/binfmt:latest
- name: Login to GHCR
@@ -119,7 +119,7 @@ jobs:
docker-images: false
swap-storage: true
- name: Set up QEMU
uses: docker/setup-qemu-action@v3.3.0
uses: docker/setup-qemu-action@v3.2.0
with:
image: tonistiigi/binfmt:latest
- name: Login to GHCR

View File

@@ -56,7 +56,6 @@ jobs:
LLM_MODEL: "litellm_proxy/claude-3-5-haiku-20241022"
LLM_API_KEY: ${{ secrets.LLM_API_KEY }}
LLM_BASE_URL: ${{ secrets.LLM_BASE_URL }}
MAX_ITERATIONS: 10
run: |
echo "[llm.eval]" > config.toml
echo "model = \"$LLM_MODEL\"" >> config.toml
@@ -71,7 +70,7 @@ jobs:
env:
SANDBOX_FORCE_REBUILD_RUNTIME: True
run: |
poetry run ./evaluation/integration_tests/scripts/run_infer.sh llm.eval HEAD CodeActAgent '' 10 $N_PROCESSES '' 'haiku_run'
poetry run ./evaluation/integration_tests/scripts/run_infer.sh llm.eval HEAD CodeActAgent '' $N_PROCESSES '' 'haiku_run'
# get integration tests report
REPORT_FILE_HAIKU=$(find evaluation/evaluation_outputs/outputs/integration_tests/CodeActAgent/*haiku*_maxiter_10_N* -name "report.md" -type f | head -n 1)
@@ -89,7 +88,6 @@ jobs:
LLM_MODEL: "litellm_proxy/deepseek-chat"
LLM_API_KEY: ${{ secrets.LLM_API_KEY }}
LLM_BASE_URL: ${{ secrets.LLM_BASE_URL }}
MAX_ITERATIONS: 10
run: |
echo "[llm.eval]" > config.toml
echo "model = \"$LLM_MODEL\"" >> config.toml
@@ -101,7 +99,7 @@ jobs:
env:
SANDBOX_FORCE_REBUILD_RUNTIME: True
run: |
poetry run ./evaluation/integration_tests/scripts/run_infer.sh llm.eval HEAD CodeActAgent '' 10 $N_PROCESSES '' 'deepseek_run'
poetry run ./evaluation/integration_tests/scripts/run_infer.sh llm.eval HEAD CodeActAgent '' $N_PROCESSES '' 'deepseek_run'
# get integration tests report
REPORT_FILE_DEEPSEEK=$(find evaluation/evaluation_outputs/outputs/integration_tests/CodeActAgent/deepseek*_maxiter_10_N* -name "report.md" -type f | head -n 1)
@@ -111,104 +109,11 @@ jobs:
echo >> $GITHUB_ENV
echo "EOF" >> $GITHUB_ENV
# -------------------------------------------------------------
# Run DelegatorAgent tests for Haiku, limited to t01 and t02
- name: Wait a little bit (again)
run: sleep 5
- name: Configure config.toml for testing DelegatorAgent (Haiku)
env:
LLM_MODEL: "litellm_proxy/claude-3-5-haiku-20241022"
LLM_API_KEY: ${{ secrets.LLM_API_KEY }}
LLM_BASE_URL: ${{ secrets.LLM_BASE_URL }}
MAX_ITERATIONS: 30
run: |
echo "[llm.eval]" > config.toml
echo "model = \"$LLM_MODEL\"" >> config.toml
echo "api_key = \"$LLM_API_KEY\"" >> config.toml
echo "base_url = \"$LLM_BASE_URL\"" >> config.toml
echo "temperature = 0.0" >> config.toml
- name: Run integration test evaluation for DelegatorAgent (Haiku)
env:
SANDBOX_FORCE_REBUILD_RUNTIME: True
run: |
poetry run ./evaluation/integration_tests/scripts/run_infer.sh llm.eval HEAD DelegatorAgent '' 30 $N_PROCESSES "t01_fix_simple_typo,t02_add_bash_hello" 'delegator_haiku_run'
# Find and export the delegator test results
REPORT_FILE_DELEGATOR_HAIKU=$(find evaluation/evaluation_outputs/outputs/integration_tests/DelegatorAgent/*haiku*_maxiter_30_N* -name "report.md" -type f | head -n 1)
echo "REPORT_FILE_DELEGATOR_HAIKU: $REPORT_FILE_DELEGATOR_HAIKU"
echo "INTEGRATION_TEST_REPORT_DELEGATOR_HAIKU<<EOF" >> $GITHUB_ENV
cat $REPORT_FILE_DELEGATOR_HAIKU >> $GITHUB_ENV
echo >> $GITHUB_ENV
echo "EOF" >> $GITHUB_ENV
# -------------------------------------------------------------
# Run DelegatorAgent tests for DeepSeek, limited to t01 and t02
- name: Wait a little bit (again)
run: sleep 5
- name: Configure config.toml for testing DelegatorAgent (DeepSeek)
env:
LLM_MODEL: "litellm_proxy/deepseek-chat"
LLM_API_KEY: ${{ secrets.LLM_API_KEY }}
LLM_BASE_URL: ${{ secrets.LLM_BASE_URL }}
MAX_ITERATIONS: 30
run: |
echo "[llm.eval]" > config.toml
echo "model = \"$LLM_MODEL\"" >> config.toml
echo "api_key = \"$LLM_API_KEY\"" >> config.toml
echo "base_url = \"$LLM_BASE_URL\"" >> config.toml
echo "temperature = 0.0" >> config.toml
- name: Run integration test evaluation for DelegatorAgent (DeepSeek)
env:
SANDBOX_FORCE_REBUILD_RUNTIME: True
run: |
poetry run ./evaluation/integration_tests/scripts/run_infer.sh llm.eval HEAD DelegatorAgent '' 30 $N_PROCESSES "t01_fix_simple_typo,t02_add_bash_hello" 'delegator_deepseek_run'
# Find and export the delegator test results
REPORT_FILE_DELEGATOR_DEEPSEEK=$(find evaluation/evaluation_outputs/outputs/integration_tests/DelegatorAgent/deepseek*_maxiter_30_N* -name "report.md" -type f | head -n 1)
echo "REPORT_FILE_DELEGATOR_DEEPSEEK: $REPORT_FILE_DELEGATOR_DEEPSEEK"
echo "INTEGRATION_TEST_REPORT_DELEGATOR_DEEPSEEK<<EOF" >> $GITHUB_ENV
cat $REPORT_FILE_DELEGATOR_DEEPSEEK >> $GITHUB_ENV
echo >> $GITHUB_ENV
echo "EOF" >> $GITHUB_ENV
# -------------------------------------------------------------
# Run VisualBrowsingAgent tests for DeepSeek, limited to t05 and t06
- name: Wait a little bit (again)
run: sleep 5
- name: Configure config.toml for testing VisualBrowsingAgent (DeepSeek)
env:
LLM_MODEL: "litellm_proxy/deepseek-chat"
LLM_API_KEY: ${{ secrets.LLM_API_KEY }}
LLM_BASE_URL: ${{ secrets.LLM_BASE_URL }}
MAX_ITERATIONS: 15
run: |
echo "[llm.eval]" > config.toml
echo "model = \"$LLM_MODEL\"" >> config.toml
echo "api_key = \"$LLM_API_KEY\"" >> config.toml
echo "base_url = \"$LLM_BASE_URL\"" >> config.toml
echo "temperature = 0.0" >> config.toml
- name: Run integration test evaluation for VisualBrowsingAgent (DeepSeek)
env:
SANDBOX_FORCE_REBUILD_RUNTIME: True
run: |
poetry run ./evaluation/integration_tests/scripts/run_infer.sh llm.eval HEAD VisualBrowsingAgent '' 15 $N_PROCESSES "t05_simple_browsing,t06_github_pr_browsing.py" 'visualbrowsing_deepseek_run'
# Find and export the visual browsing agent test results
REPORT_FILE_VISUALBROWSING_DEEPSEEK=$(find evaluation/evaluation_outputs/outputs/integration_tests/VisualBrowsingAgent/deepseek*_maxiter_15_N* -name "report.md" -type f | head -n 1)
echo "REPORT_FILE_VISUALBROWSING_DEEPSEEK: $REPORT_FILE_VISUALBROWSING_DEEPSEEK"
echo "INTEGRATION_TEST_REPORT_VISUALBROWSING_DEEPSEEK<<EOF" >> $GITHUB_ENV
cat $REPORT_FILE_VISUALBROWSING_DEEPSEEK >> $GITHUB_ENV
echo >> $GITHUB_ENV
echo "EOF" >> $GITHUB_ENV
- name: Create archive of evaluation outputs
run: |
TIMESTAMP=$(date +'%y-%m-%d-%H-%M')
cd evaluation/evaluation_outputs/outputs # Change to the outputs directory
tar -czvf ../../../integration_tests_${TIMESTAMP}.tar.gz integration_tests/CodeActAgent/* integration_tests/DelegatorAgent/* integration_tests/VisualBrowsingAgent/* # Only include the actual result directories
tar -czvf ../../../integration_tests_${TIMESTAMP}.tar.gz integration_tests/CodeActAgent/* # Only include the actual result directories
- name: Upload evaluation results as artifact
uses: actions/upload-artifact@v4
@@ -249,14 +154,5 @@ jobs:
**Integration Tests Report (DeepSeek)**
DeepSeek LLM Test Results:
${{ env.INTEGRATION_TEST_REPORT_DEEPSEEK }}
---
**Integration Tests Report Delegator (Haiku)**
${{ env.INTEGRATION_TEST_REPORT_DELEGATOR_HAIKU }}
---
**Integration Tests Report Delegator (DeepSeek)**
${{ env.INTEGRATION_TEST_REPORT_DELEGATOR_DEEPSEEK }}
---
**Integration Tests Report VisualBrowsing (DeepSeek)**
${{ env.INTEGRATION_TEST_REPORT_VISUALBROWSING_DEEPSEEK }}
---
Download testing outputs (includes both Haiku and DeepSeek results): [Download](${{ steps.upload_results_artifact.outputs.artifact-url }})

View File

@@ -84,10 +84,6 @@ jobs:
run: |
python -m pip index versions openhands-ai > openhands_versions.txt
OPENHANDS_VERSION=$(head -n 1 openhands_versions.txt | awk '{print $2}' | tr -d '()')
# Ensure requirements.txt ends with newline before appending
if [ -f requirements.txt ] && [ -s requirements.txt ]; then
sed -i -e '$a\' requirements.txt
fi
echo "openhands-ai==${OPENHANDS_VERSION}" >> requirements.txt
cat requirements.txt
@@ -188,7 +184,6 @@ jobs:
});
- name: Install OpenHands
id: install_openhands
uses: actions/github-script@v7
env:
COMMENT_BODY: ${{ github.event.comment.body || '' }}
@@ -201,6 +196,7 @@ jobs:
const reviewBody = process.env.REVIEW_BODY.trim();
const labelName = process.env.LABEL_NAME.trim();
const eventName = process.env.EVENT_NAME.trim();
// Check conditions
const isExperimentalLabel = labelName === "fix-me-experimental";
const isIssueCommentExperimental =
@@ -209,9 +205,6 @@ jobs:
const isReviewCommentExperimental =
eventName === "pull_request_review" && reviewBody.includes("@openhands-agent-exp");
// Set output variable
core.setOutput('isExperimental', isExperimentalLabel || isIssueCommentExperimental || isReviewCommentExperimental);
// Perform package installation
if (isExperimentalLabel || isIssueCommentExperimental || isReviewCommentExperimental) {
console.log("Installing experimental OpenHands...");
@@ -237,8 +230,7 @@ jobs:
--issue-number ${{ env.ISSUE_NUMBER }} \
--issue-type ${{ env.ISSUE_TYPE }} \
--max-iterations ${{ env.MAX_ITERATIONS }} \
--comment-id ${{ env.COMMENT_ID }} \
--is-experimental ${{ steps.install_openhands.outputs.isExperimental }}
--comment-id ${{ env.COMMENT_ID }}
- name: Check resolution result
id: check_result

1
.gitignore vendored
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@@ -176,7 +176,6 @@ evaluation/gorilla/data
evaluation/toolqa/data
evaluation/scienceagentbench/benchmark
evaluation/commit0_bench/repos
evaluation/visualcodebench/
# openhands resolver
output/

View File

@@ -113,20 +113,6 @@ individual, or aggression toward or disparagement of classes of individuals.
**Consequence**: A permanent ban from any sort of public interaction within the
community.
### Slack and Discord Etiquettes
These Slack and Discord etiquette guidelines are designed to foster an inclusive, respectful, and productive environment for all community members. By following these best practices, we ensure effective communication and collaboration while minimizing disruptions. Lets work together to build a supportive and welcoming community!
- Communicate respectfully and professionally, avoiding sarcasm or harsh language, and remember that tone can be difficult to interpret in text.
- Use threads for specific discussions to keep channels organized and easier to follow.
- Tag others only when their input is critical or urgent, and use @here, @channel or @everyone sparingly to minimize disruptions.
- Be patient, as open-source contributors and maintainers often have other commitments and may need time to respond.
- Post questions or discussions in the most relevant channel (e.g., for [slack - #general](https://app.slack.com/client/T06P212QSEA/C06P5NCGSFP) for general topics, [slack - #questions](https://openhands-ai.slack.com/archives/C06U8UTKSAD) for queries/questions, [discord - #general](https://discord.com/channels/1222935860639563850/1222935861386018885)).
- When asking for help or raising issues, include necessary details like links, screenshots, or clear explanations to provide context.
- Keep discussions in public channels whenever possible to allow others to benefit from the conversation, unless the matter is sensitive or private.
- Always adhere to [our standards](https://github.com/All-Hands-AI/OpenHands/blob/main/CODE_OF_CONDUCT.md#our-standards) to ensure a welcoming and collaborative environment.
- If you choose to mute a channel, consider setting up alerts for topics that still interest you to stay engaged. For Slack, Go to Settings → Notifications → My Keywords to add specific keywords that will notify you when mentioned. For example, if you're here for discussions about LLMs, mute the channel if its too busy, but set notifications to alert you only when “LLMs” appears in messages. Also for Discord, go to the channel notifications and choose the option that best describes your need.
## Attribution
This Code of Conduct is adapted from the [Contributor Covenant][homepage],

View File

@@ -5,7 +5,7 @@ Otherwise, you can clone the OpenHands project directly.
## Start the Server for Development
### 1. Requirements
* Linux, Mac OS, or [WSL on Windows](https://learn.microsoft.com/en-us/windows/wsl/install) [Ubuntu >= 22.04]
* Linux, Mac OS, or [WSL on Windows](https://learn.microsoft.com/en-us/windows/wsl/install) [Ubuntu <= 22.04]
* [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/) = 3.12
* [NodeJS](https://nodejs.org/en/download/package-manager) >= 20.x
@@ -100,7 +100,7 @@ poetry run pytest ./tests/unit/test_*.py
To reduce build time (e.g., if no changes were made to the client-runtime component), you can use an existing Docker container image by
setting the SANDBOX_RUNTIME_CONTAINER_IMAGE environment variable to the desired Docker image.
Example: `export SANDBOX_RUNTIME_CONTAINER_IMAGE=ghcr.io/all-hands-ai/runtime:0.21-nikolaik`
Example: `export SANDBOX_RUNTIME_CONTAINER_IMAGE=ghcr.io/all-hands-ai/runtime:0.19-nikolaik`
## Develop inside Docker container

View File

@@ -39,21 +39,21 @@ Learn more at [docs.all-hands.dev](https://docs.all-hands.dev), or jump to the [
## ⚡ Quick Start
The easiest way to run OpenHands is in Docker.
See the [Running OpenHands](https://docs.all-hands.dev/modules/usage/installation) guide for
See the [Installation](https://docs.all-hands.dev/modules/usage/installation) guide for
system requirements and more information.
```bash
docker pull docker.all-hands.dev/all-hands-ai/runtime:0.21-nikolaik
docker pull docker.all-hands.dev/all-hands-ai/runtime:0.19-nikolaik
docker run -it --rm --pull=always \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.21-nikolaik \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.19-nikolaik \
-e LOG_ALL_EVENTS=true \
-v /var/run/docker.sock:/var/run/docker.sock \
-v ~/.openhands-state:/.openhands-state \
-p 3000:3000 \
--add-host host.docker.internal:host-gateway \
--name openhands-app \
docker.all-hands.dev/all-hands-ai/openhands:0.21
docker.all-hands.dev/all-hands-ai/openhands:0.19
```
You'll find OpenHands running at [http://localhost:3000](http://localhost:3000)!
@@ -69,7 +69,7 @@ run OpenHands in a scriptable [headless mode](https://docs.all-hands.dev/modules
interact with it via a [friendly CLI](https://docs.all-hands.dev/modules/usage/how-to/cli-mode),
or run it on tagged issues with [a github action](https://docs.all-hands.dev/modules/usage/how-to/github-action).
Visit [Running OpenHands](https://docs.all-hands.dev/modules/usage/installation) for more information and setup instructions.
Visit [Installation](https://docs.all-hands.dev/modules/usage/installation) for more information and setup instructions.
> [!CAUTION]
> OpenHands is meant to be run by a single user on their local workstation.

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@@ -1,4 +1,4 @@
#
services:
openhands:
build:
@@ -7,8 +7,8 @@ services:
image: openhands:latest
container_name: openhands-app-${DATE:-}
environment:
- SANDBOX_RUNTIME_CONTAINER_IMAGE=${SANDBOX_RUNTIME_CONTAINER_IMAGE:-docker.all-hands.dev/all-hands-ai/runtime:0.21-nikolaik}
#- SANDBOX_USER_ID=${SANDBOX_USER_ID:-1234} # enable this only if you want a specific non-root sandbox user but you will have to manually adjust permissions of openhands-state for this user
- SANDBOX_RUNTIME_CONTAINER_IMAGE=${SANDBOX_RUNTIME_CONTAINER_IMAGE:-ghcr.io/all-hands-ai/runtime:0.19-nikolaik}
- SANDBOX_USER_ID=${SANDBOX_USER_ID:-1234}
- WORKSPACE_MOUNT_PATH=${WORKSPACE_BASE:-$PWD/workspace}
ports:
- "3000:3000"
@@ -16,7 +16,6 @@ services:
- "host.docker.internal:host-gateway"
volumes:
- /var/run/docker.sock:/var/run/docker.sock
- ~/.openhands-state:/.openhands-state
- ${WORKSPACE_BASE:-$PWD/workspace}:/opt/workspace_base
pull_policy: build
stdin_open: true

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@@ -23,9 +23,6 @@ workspace_base = "./workspace"
# Cache directory path
#cache_dir = "/tmp/cache"
# Reasoning effort for o1 models (low, medium, high, or not set)
#reasoning_effort = "medium"
# Debugging enabled
#debug = false
@@ -37,12 +34,7 @@ workspace_base = "./workspace"
# Path to store trajectories, can be a folder or a file
# If it's a folder, the session id will be used as the file name
#save_trajectory_path="./trajectories"
# Path to replay a trajectory, must be a file path
# If provided, trajectory will be loaded and replayed before the
# agent responds to any user instruction
#replay_trajectory_path = ""
#trajectories_path="./trajectories"
# File store path
#file_store_path = "/tmp/file_store"
@@ -75,7 +67,7 @@ workspace_base = "./workspace"
#run_as_openhands = true
# Runtime environment
#runtime = "docker"
#runtime = "eventstream"
# Name of the default agent
#default_agent = "CodeActAgent"
@@ -228,8 +220,8 @@ codeact_enable_jupyter = true
# LLM config group to use
#llm_config = 'your-llm-config-group'
# Whether to use prompt extension (e.g., microagent, repo/runtime info) at all
#enable_prompt_extensions = true
# Whether to use microagents at all
#use_microagents = true
# List of microagents to disable
#disabled_microagents = []

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@@ -11,7 +11,7 @@ services:
- BACKEND_HOST=${BACKEND_HOST:-"0.0.0.0"}
- SANDBOX_API_HOSTNAME=host.docker.internal
#
- SANDBOX_RUNTIME_CONTAINER_IMAGE=${SANDBOX_RUNTIME_CONTAINER_IMAGE:-ghcr.io/all-hands-ai/runtime:0.21-nikolaik}
- SANDBOX_RUNTIME_CONTAINER_IMAGE=${SANDBOX_RUNTIME_CONTAINER_IMAGE:-ghcr.io/all-hands-ai/runtime:0.19-nikolaik}
- SANDBOX_USER_ID=${SANDBOX_USER_ID:-1234}
- WORKSPACE_MOUNT_PATH=${WORKSPACE_BASE:-$PWD/workspace}
ports:

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@@ -1,3 +1,5 @@
# Options de configuration
Ce guide détaille toutes les options de configuration disponibles pour OpenHands, vous aidant à personnaliser son comportement et à l'intégrer avec d'autres services.
@@ -92,7 +94,7 @@ Les options de configuration de base sont définies dans la section `[core]` du
- Description : Désactiver la couleur dans la sortie du terminal
**Trajectoires**
- `save_trajectory_path`
- `trajectories_path`
- Type : `str`
- Valeur par défaut : `"./trajectories"`
- Description : Chemin pour stocker les trajectoires (peut être un dossier ou un fichier). Si c'est un dossier, les trajectoires seront enregistrées dans un fichier nommé avec l'ID de session et l'extension .json, dans ce dossier.
@@ -182,10 +184,6 @@ Les options de configuration LLM (Large Language Model) sont définies dans la s
Pour les utiliser avec la commande docker, passez `-e LLM_<option>`. Exemple : `-e LLM_NUM_RETRIES`.
:::note
Pour les configurations de développement, vous pouvez également définir des configurations LLM personnalisées. Voir [Configurations LLM personnalisées](./llms/custom-llm-configs) pour plus de détails.
:::
**Informations d'identification AWS**
- `aws_access_key_id`
- Type : `str`
@@ -370,26 +368,4 @@ Les options de configuration de l'agent sont définies dans les sections `[agent
- `codeact_enable_llm_editor`
- Type : `bool`
- Valeur par défaut : `false`
- Description : Si l'éditeur LLM est activé dans l'espace d'action (fonctionne uniquement avec l'appel de fonction)
**Utilisation du micro-agent**
- `enable_prompt_extensions`
- Type : `bool`
- Valeur par défaut : `true`
- Description : Indique si l'utilisation des micro-agents est activée ou non
- `disabled_microagents`
- Type : `list of str`
- Valeur par défaut : `None`
- Description : Liste des micro-agents à désactiver
### Exécution
- `timeout`
- Type : `int`
- Valeur par défaut : `120`
- Description : Délai d'expiration du bac à sable, en secondes
- `user_id`
- Type : `int`
- Valeur par défaut : `1000`
- Description : ID de l'utilisateur du bac à sable
- Description : Si l'éditeur LLM est activé dans l'espace d'action (foncti

View File

@@ -52,7 +52,7 @@ LLM_API_KEY="sk_test_12345"
```bash
docker run -it \
--pull=always \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.21-nikolaik \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.19-nikolaik \
-e SANDBOX_USER_ID=$(id -u) \
-e WORKSPACE_MOUNT_PATH=$WORKSPACE_BASE \
-e LLM_API_KEY=$LLM_API_KEY \
@@ -61,7 +61,7 @@ docker run -it \
-v /var/run/docker.sock:/var/run/docker.sock \
--add-host host.docker.internal:host-gateway \
--name openhands-app-$(date +%Y%m%d%H%M%S) \
docker.all-hands.dev/all-hands-ai/openhands:0.21 \
docker.all-hands.dev/all-hands-ai/openhands:0.19 \
python -m openhands.core.cli
```

View File

@@ -46,7 +46,7 @@ LLM_API_KEY="sk_test_12345"
```bash
docker run -it \
--pull=always \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.21-nikolaik \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.19-nikolaik \
-e SANDBOX_USER_ID=$(id -u) \
-e WORKSPACE_MOUNT_PATH=$WORKSPACE_BASE \
-e LLM_API_KEY=$LLM_API_KEY \
@@ -56,6 +56,6 @@ docker run -it \
-v /var/run/docker.sock:/var/run/docker.sock \
--add-host host.docker.internal:host-gateway \
--name openhands-app-$(date +%Y%m%d%H%M%S) \
docker.all-hands.dev/all-hands-ai/openhands:0.21 \
docker.all-hands.dev/all-hands-ai/openhands:0.19 \
python -m openhands.core.main -t "write a bash script that prints hi" --no-auto-continue
```

View File

@@ -13,16 +13,16 @@
La façon la plus simple d'exécuter OpenHands est avec Docker.
```bash
docker pull docker.all-hands.dev/all-hands-ai/runtime:0.21-nikolaik
docker pull docker.all-hands.dev/all-hands-ai/runtime:0.19-nikolaik
docker run -it --rm --pull=always \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.21-nikolaik \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.19-nikolaik \
-e LOG_ALL_EVENTS=true \
-v /var/run/docker.sock:/var/run/docker.sock \
-p 3000:3000 \
--add-host host.docker.internal:host-gateway \
--name openhands-app \
docker.all-hands.dev/all-hands-ai/openhands:0.21
docker.all-hands.dev/all-hands-ai/openhands:0.19
```
Vous pouvez également exécuter OpenHands en mode [headless scriptable](https://docs.all-hands.dev/modules/usage/how-to/headless-mode), en tant que [CLI interactive](https://docs.all-hands.dev/modules/usage/how-to/cli-mode), ou en utilisant l'[Action GitHub OpenHands](https://docs.all-hands.dev/modules/usage/how-to/github-action).

View File

@@ -1,106 +0,0 @@
# Configurations LLM personnalisées
OpenHands permet de définir plusieurs configurations LLM nommées dans votre fichier `config.toml`. Cette fonctionnalité vous permet d'utiliser différentes configurations LLM pour différents usages, comme utiliser un modèle moins coûteux pour les tâches qui ne nécessitent pas de réponses de haute qualité, ou utiliser différents modèles avec différents paramètres pour des agents spécifiques.
## Comment ça fonctionne
Les configurations LLM nommées sont définies dans le fichier `config.toml` en utilisant des sections qui commencent par `llm.`. Par exemple :
```toml
# Configuration LLM par défaut
[llm]
model = "gpt-4"
api_key = "votre-clé-api"
temperature = 0.0
# Configuration LLM personnalisée pour un modèle moins coûteux
[llm.gpt3]
model = "gpt-3.5-turbo"
api_key = "votre-clé-api"
temperature = 0.2
# Une autre configuration personnalisée avec des paramètres différents
[llm.haute-creativite]
model = "gpt-4"
api_key = "votre-clé-api"
temperature = 0.8
top_p = 0.9
```
Chaque configuration nommée hérite de tous les paramètres de la section `[llm]` par défaut et peut remplacer n'importe lequel de ces paramètres. Vous pouvez définir autant de configurations personnalisées que nécessaire.
## Utilisation des configurations personnalisées
### Avec les agents
Vous pouvez spécifier quelle configuration LLM un agent doit utiliser en définissant le paramètre `llm_config` dans la section de configuration de l'agent :
```toml
[agent.RepoExplorerAgent]
# Utiliser la configuration GPT-3 moins coûteuse pour cet agent
llm_config = 'gpt3'
[agent.CodeWriterAgent]
# Utiliser la configuration haute créativité pour cet agent
llm_config = 'haute-creativite'
```
### Options de configuration
Chaque configuration LLM nommée prend en charge toutes les mêmes options que la configuration LLM par défaut. Celles-ci incluent :
- Sélection du modèle (`model`)
- Configuration de l'API (`api_key`, `base_url`, etc.)
- Paramètres du modèle (`temperature`, `top_p`, etc.)
- Paramètres de nouvelle tentative (`num_retries`, `retry_multiplier`, etc.)
- Limites de jetons (`max_input_tokens`, `max_output_tokens`)
- Et toutes les autres options de configuration LLM
Pour une liste complète des options disponibles, consultez la section Configuration LLM dans la documentation des [Options de configuration](../configuration-options).
## Cas d'utilisation
Les configurations LLM personnalisées sont particulièrement utiles dans plusieurs scénarios :
- **Optimisation des coûts** : Utiliser des modèles moins coûteux pour les tâches qui ne nécessitent pas de réponses de haute qualité, comme l'exploration de dépôt ou les opérations simples sur les fichiers.
- **Réglage spécifique aux tâches** : Configurer différentes valeurs de température et de top_p pour les tâches qui nécessitent différents niveaux de créativité ou de déterminisme.
- **Différents fournisseurs** : Utiliser différents fournisseurs LLM ou points d'accès API pour différentes tâches.
- **Tests et développement** : Basculer facilement entre différentes configurations de modèles pendant le développement et les tests.
## Exemple : Optimisation des coûts
Un exemple pratique d'utilisation des configurations LLM personnalisées pour optimiser les coûts :
```toml
# Configuration par défaut utilisant GPT-4 pour des réponses de haute qualité
[llm]
model = "gpt-4"
api_key = "votre-clé-api"
temperature = 0.0
# Configuration moins coûteuse pour l'exploration de dépôt
[llm.repo-explorer]
model = "gpt-3.5-turbo"
temperature = 0.2
# Configuration pour la génération de code
[llm.code-gen]
model = "gpt-4"
temperature = 0.0
max_output_tokens = 2000
[agent.RepoExplorerAgent]
llm_config = 'repo-explorer'
[agent.CodeWriterAgent]
llm_config = 'code-gen'
```
Dans cet exemple :
- L'exploration de dépôt utilise un modèle moins coûteux car il s'agit principalement de comprendre et de naviguer dans le code
- La génération de code utilise GPT-4 avec une limite de jetons plus élevée pour générer des blocs de code plus importants
- La configuration par défaut reste disponible pour les autres tâches
:::note
Les configurations LLM personnalisées ne sont disponibles que lors de l'utilisation d'OpenHands en mode développement, via `main.py` ou `cli.py`. Lors de l'exécution via `docker run`, veuillez utiliser les options de configuration standard.
:::

View File

@@ -13,7 +13,7 @@ C'est le Runtime par défaut qui est utilisé lorsque vous démarrez OpenHands.
```
docker run # ...
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.21-nikolaik \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.19-nikolaik \
-v /var/run/docker.sock:/var/run/docker.sock \
# ...
```

View File

@@ -91,7 +91,7 @@
- 描述: 禁用终端输出中的颜色
**轨迹**
- `save_trajectory_path`
- `trajectories_path`
- 类型: `str`
- 默认值: `"./trajectories"`
- 描述: 存储轨迹的路径(可以是文件夹或文件)。如果是文件夹,轨迹将保存在该文件夹中以会话 ID 命名的 .json 文件中。
@@ -373,7 +373,7 @@ Agent 配置选项在 `config.toml` 文件的 `[agent]` 和 `[agent.<agent_name>
- 描述: 是否在 action space 中启用 Jupyter
**Microagent 使用**
- `enable_prompt_extensions`
- `use_microagents`
- 类型: `bool`
- 默认值: `true`
- 描述: 是否使用 microagents

View File

@@ -50,7 +50,7 @@ LLM_API_KEY="sk_test_12345"
```bash
docker run -it \
--pull=always \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.21-nikolaik \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.19-nikolaik \
-e SANDBOX_USER_ID=$(id -u) \
-e WORKSPACE_MOUNT_PATH=$WORKSPACE_BASE \
-e LLM_API_KEY=$LLM_API_KEY \
@@ -59,7 +59,7 @@ docker run -it \
-v /var/run/docker.sock:/var/run/docker.sock \
--add-host host.docker.internal:host-gateway \
--name openhands-app-$(date +%Y%m%d%H%M%S) \
docker.all-hands.dev/all-hands-ai/openhands:0.21 \
docker.all-hands.dev/all-hands-ai/openhands:0.19 \
python -m openhands.core.cli
```

View File

@@ -47,7 +47,7 @@ LLM_API_KEY="sk_test_12345"
```bash
docker run -it \
--pull=always \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.21-nikolaik \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.19-nikolaik \
-e SANDBOX_USER_ID=$(id -u) \
-e WORKSPACE_MOUNT_PATH=$WORKSPACE_BASE \
-e LLM_API_KEY=$LLM_API_KEY \
@@ -57,6 +57,6 @@ docker run -it \
-v /var/run/docker.sock:/var/run/docker.sock \
--add-host host.docker.internal:host-gateway \
--name openhands-app-$(date +%Y%m%d%H%M%S) \
docker.all-hands.dev/all-hands-ai/openhands:0.21 \
docker.all-hands.dev/all-hands-ai/openhands:0.19 \
python -m openhands.core.main -t "write a bash script that prints hi" --no-auto-continue
```

View File

@@ -11,16 +11,16 @@
在 Docker 中运行 OpenHands 是最简单的方式。
```bash
docker pull docker.all-hands.dev/all-hands-ai/runtime:0.21-nikolaik
docker pull docker.all-hands.dev/all-hands-ai/runtime:0.19-nikolaik
docker run -it --rm --pull=always \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.21-nikolaik \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.19-nikolaik \
-e LOG_ALL_EVENTS=true \
-v /var/run/docker.sock:/var/run/docker.sock \
-p 3000:3000 \
--add-host host.docker.internal:host-gateway \
--name openhands-app \
docker.all-hands.dev/all-hands-ai/openhands:0.21
docker.all-hands.dev/all-hands-ai/openhands:0.19
```
你也可以在可脚本化的[无头模式](https://docs.all-hands.dev/modules/usage/how-to/headless-mode)下运行 OpenHands作为[交互式 CLI](https://docs.all-hands.dev/modules/usage/how-to/cli-mode),或使用 [OpenHands GitHub Action](https://docs.all-hands.dev/modules/usage/how-to/github-action)。

View File

@@ -11,7 +11,7 @@
```
docker run # ...
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.21-nikolaik \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.19-nikolaik \
-v /var/run/docker.sock:/var/run/docker.sock \
# ...
```

View File

@@ -7,11 +7,53 @@ If you are running in [GUI Mode](https://docs.all-hands.dev/modules/usage/how-to
take precedence.
:::
---
# Table of Contents
- [Core Configuration](#core-configuration)
- [API Keys](#api-keys)
- [Workspace](#workspace)
- [Debugging and Logging](#debugging-and-logging)
- [Session Management](#session-management)
- [Trajectories](#trajectories)
- [File Store](#file-store)
- [Task Management](#task-management)
- [Sandbox Configuration](#sandbox-configuration)
- [Miscellaneous](#miscellaneous)
- [LLM Configuration](#llm-configuration)
- [AWS Credentials](#aws-credentials)
- [API Configuration](#api-configuration)
- [Custom LLM Provider](#custom-llm-provider)
- [Embeddings](#embeddings)
- [Message Handling](#message-handling)
- [Model Selection](#model-selection)
- [Retrying](#retrying)
- [Advanced Options](#advanced-options)
- [Agent Configuration](#agent-configuration)
- [Microagent Configuration](#microagent-configuration)
- [Memory Configuration](#memory-configuration)
- [LLM Configuration](#llm-configuration-2)
- [ActionSpace Configuration](#actionspace-configuration)
- [Microagent Usage](#microagent-usage)
- [Sandbox Configuration](#sandbox-configuration)
- [Execution](#execution)
- [Container Image](#container-image)
- [Networking](#networking)
- [Linting and Plugins](#linting-and-plugins)
- [Dependencies and Environment](#dependencies-and-environment)
- [Evaluation](#evaluation)
- [Security Configuration](#security-configuration)
- [Confirmation Mode](#confirmation-mode)
- [Security Analyzer](#security-analyzer)
---
## Core Configuration
The core configuration options are defined in the `[core]` section of the `config.toml` file.
### API Keys
**API Keys**
- `e2b_api_key`
- Type: `str`
- Default: `""`
@@ -27,7 +69,7 @@ The core configuration options are defined in the `[core]` section of the `confi
- Default: `""`
- Description: API token secret for Modal
### Workspace
**Workspace**
- `workspace_base`
- Type: `str`
- Default: `"./workspace"`
@@ -38,7 +80,7 @@ The core configuration options are defined in the `[core]` section of the `confi
- Default: `"/tmp/cache"`
- Description: Cache directory path
### Debugging and Logging
**Debugging and Logging**
- `debug`
- Type: `bool`
- Default: `false`
@@ -49,18 +91,13 @@ The core configuration options are defined in the `[core]` section of the `confi
- Default: `false`
- Description: Disable color in terminal output
### Trajectories
- `save_trajectory_path`
**Trajectories**
- `trajectories_path`
- Type: `str`
- Default: `"./trajectories"`
- Description: Path to store trajectories (can be a folder or a file). If it's a folder, the trajectories will be saved in a file named with the session id name and .json extension, in that folder.
- `replay_trajectory_path`
- Type: `str`
- Default: `""`
- Description: Path to load a trajectory and replay. If given, must be a path to the trajectory file in JSON format. The actions in the trajectory file would be replayed first before any user instruction is executed.
### File Store
**File Store**
- `file_store_path`
- Type: `str`
- Default: `"/tmp/file_store"`
@@ -91,7 +128,7 @@ The core configuration options are defined in the `[core]` section of the `confi
- Default: `[".*"]`
- Description: List of allowed file extensions for uploads
### Task Management
**Task Management**
- `max_budget_per_task`
- Type: `float`
- Default: `0.0`
@@ -102,7 +139,7 @@ The core configuration options are defined in the `[core]` section of the `confi
- Default: `100`
- Description: Maximum number of iterations
### Sandbox Configuration
**Sandbox Configuration**
- `workspace_mount_path_in_sandbox`
- Type: `str`
- Default: `"/workspace"`
@@ -118,7 +155,7 @@ The core configuration options are defined in the `[core]` section of the `confi
- Default: `""`
- Description: Path to rewrite the workspace mount path to. You can usually ignore this, it refers to special cases of running inside another container.
### Miscellaneous
**Miscellaneous**
- `run_as_openhands`
- Type: `bool`
- Default: `true`
@@ -145,10 +182,6 @@ The LLM (Large Language Model) configuration options are defined in the `[llm]`
To use these with the docker command, pass in `-e LLM_<option>`. Example: `-e LLM_NUM_RETRIES`.
:::note
For development setups, you can also define custom named LLM configurations. See [Custom LLM Configurations](./llms/custom-llm-configs) for details.
:::
**AWS Credentials**
- `aws_access_key_id`
- Type: `str`
@@ -165,7 +198,7 @@ For development setups, you can also define custom named LLM configurations. See
- Default: `""`
- Description: AWS secret access key
### API Configuration
**API Configuration**
- `api_key`
- Type: `str`
- Default: `None`
@@ -191,13 +224,13 @@ For development setups, you can also define custom named LLM configurations. See
- Default: `0.0`
- Description: Cost per output token
### Custom LLM Provider
**Custom LLM Provider**
- `custom_llm_provider`
- Type: `str`
- Default: `""`
- Description: Custom LLM provider
### Embeddings
**Embeddings**
- `embedding_base_url`
- Type: `str`
- Default: `""`
@@ -213,7 +246,7 @@ For development setups, you can also define custom named LLM configurations. See
- Default: `"local"`
- Description: Embedding model to use
### Message Handling
**Message Handling**
- `max_message_chars`
- Type: `int`
- Default: `30000`
@@ -229,13 +262,13 @@ For development setups, you can also define custom named LLM configurations. See
- Default: `0`
- Description: Maximum number of output tokens
### Model Selection
**Model Selection**
- `model`
- Type: `str`
- Default: `"claude-3-5-sonnet-20241022"`
- Description: Model to use
### Retrying
**Retrying**
- `num_retries`
- Type: `int`
- Default: `8`
@@ -256,7 +289,7 @@ For development setups, you can also define custom named LLM configurations. See
- Default: `2.0`
- Description: Multiplier for exponential backoff calculation
### Advanced Options
**Advanced Options**
- `drop_params`
- Type: `bool`
- Default: `false`
@@ -296,13 +329,13 @@ For development setups, you can also define custom named LLM configurations. See
The agent configuration options are defined in the `[agent]` and `[agent.<agent_name>]` sections of the `config.toml` file.
### Microagent Configuration
**Microagent Configuration**
- `micro_agent_name`
- Type: `str`
- Default: `""`
- Description: Name of the micro agent to use for this agent
### Memory Configuration
**Memory Configuration**
- `memory_enabled`
- Type: `bool`
- Default: `false`
@@ -313,13 +346,13 @@ The agent configuration options are defined in the `[agent]` and `[agent.<agent_
- Default: `3`
- Description: The maximum number of threads indexing at the same time for embeddings
### LLM Configuration
**LLM Configuration**
- `llm_config`
- Type: `str`
- Default: `'your-llm-config-group'`
- Description: The name of the LLM config to use
### ActionSpace Configuration
**ActionSpace Configuration**
- `function_calling`
- Type: `bool`
- Default: `true`
@@ -340,8 +373,8 @@ The agent configuration options are defined in the `[agent]` and `[agent.<agent_
- Default: `false`
- Description: Whether Jupyter is enabled in the action space
### Microagent Usage
- `enable_prompt_extensions`
**Microagent Usage**
- `use_microagents`
- Type: `bool`
- Default: `true`
- Description: Whether to use microagents at all
@@ -357,7 +390,7 @@ The sandbox configuration options are defined in the `[sandbox]` section of the
To use these with the docker command, pass in `-e SANDBOX_<option>`. Example: `-e SANDBOX_TIMEOUT`.
### Execution
**Execution**
- `timeout`
- Type: `int`
- Default: `120`
@@ -368,19 +401,19 @@ To use these with the docker command, pass in `-e SANDBOX_<option>`. Example: `-
- Default: `1000`
- Description: Sandbox user ID
### Container Image
**Container Image**
- `base_container_image`
- Type: `str`
- Default: `"nikolaik/python-nodejs:python3.12-nodejs22"`
- Description: Container image to use for the sandbox
### Networking
**Networking**
- `use_host_network`
- Type: `bool`
- Default: `false`
- Description: Use host network
### Linting and Plugins
**Linting and Plugins**
- `enable_auto_lint`
- Type: `bool`
- Default: `false`
@@ -391,7 +424,7 @@ To use these with the docker command, pass in `-e SANDBOX_<option>`. Example: `-
- Default: `true`
- Description: Whether to initialize plugins
### Dependencies and Environment
**Dependencies and Environment**
- `runtime_extra_deps`
- Type: `str`
- Default: `""`
@@ -402,7 +435,7 @@ To use these with the docker command, pass in `-e SANDBOX_<option>`. Example: `-
- Default: `{}`
- Description: Environment variables to set at the launch of the runtime
### Evaluation
**Evaluation**
- `browsergym_eval_env`
- Type: `str`
- Default: `""`
@@ -414,13 +447,13 @@ The security configuration options are defined in the `[security]` section of th
To use these with the docker command, pass in `-e SECURITY_<option>`. Example: `-e SECURITY_CONFIRMATION_MODE`.
### Confirmation Mode
**Confirmation Mode**
- `confirmation_mode`
- Type: `bool`
- Default: `false`
- Description: Enable confirmation mode
### Security Analyzer
**Security Analyzer**
- `security_analyzer`
- Type: `str`
- Default: `""`

View File

@@ -1,6 +1,6 @@
# Getting Started with OpenHands
So you've [run OpenHands](./installation) and have
So you've [installed OpenHands](./installation) and have
[set up your LLM](./installation#setup). Now what?
OpenHands can help you tackle a wide variety of engineering tasks. But the technology

View File

@@ -35,7 +35,7 @@ To run OpenHands in CLI mode with Docker:
```bash
docker run -it \
--pull=always \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.21-nikolaik \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.19-nikolaik \
-e SANDBOX_USER_ID=$(id -u) \
-e WORKSPACE_MOUNT_PATH=$WORKSPACE_BASE \
-e LLM_API_KEY=$LLM_API_KEY \
@@ -45,7 +45,7 @@ docker run -it \
-v ~/.openhands-state:/.openhands-state \
--add-host host.docker.internal:host-gateway \
--name openhands-app-$(date +%Y%m%d%H%M%S) \
docker.all-hands.dev/all-hands-ai/openhands:0.21 \
docker.all-hands.dev/all-hands-ai/openhands:0.19 \
python -m openhands.core.cli
```
@@ -58,7 +58,7 @@ Here are some examples of CLI commands and their expected outputs:
### Example 1: Simple Task
```bash
>> Write a Python script that prints "Hello, World!"
How can I help? >> Write a Python script that prints "Hello, World!"
```
Expected Output:
@@ -72,7 +72,7 @@ Expected Output:
### Example 2: Bash Command
```bash
>> Create a directory named "test_dir"
How can I help? >> Create a directory named "test_dir"
```
Expected Output:
@@ -86,7 +86,7 @@ Expected Output:
### Example 3: Error Handling
```bash
>> Delete a non-existent file
How can I help? >> Delete a non-existent file
```
Expected Output:

View File

@@ -18,21 +18,15 @@ If you choose the first option, you can skip the `Create Your Docker Image` sect
To create a custom Docker image, it must be Debian based.
For example, if you want OpenHands to have `ruby` installed, you could create a `Dockerfile` with the following content:
For example, if you want OpenHands to have `ruby` installed, create a `Dockerfile` with the following content:
```dockerfile
FROM nikolaik/python-nodejs:python3.12-nodejs22
FROM debian:latest
# Install required packages
RUN apt-get update && apt-get install -y ruby
```
Or you could use a Ruby-specific base image:
```dockerfile
FROM ruby:latest
```
Save this file in a folder. Then, build your Docker image (e.g., named custom-image) by navigating to the folder in
the terminal and running::
```bash
@@ -61,28 +55,6 @@ This can be an image youve already pulled or one youve built:
sandbox_base_container_image="custom-image"
```
### Additional Configuration Options
The `config.toml` file supports several other options for customizing your sandbox:
```toml
[core]
# Install additional dependencies when the runtime is built
# Can contain any valid shell commands
# If you need the path to the Python interpreter in any of these commands, you can use the $OH_INTERPRETER_PATH variable
runtime_extra_deps = """
pip install numpy pandas
apt-get update && apt-get install -y ffmpeg
"""
# Set environment variables for the runtime
# Useful for configuration that needs to be available at runtime
runtime_startup_env_vars = { DATABASE_URL = "postgresql://user:pass@localhost/db" }
# Specify platform for multi-architecture builds (e.g., "linux/amd64" or "linux/arm64")
platform = "linux/amd64"
```
### Run
Run OpenHands by running ```make run``` in the top level directory.

View File

@@ -76,18 +76,18 @@ When using OpenHands in online mode, the GitHub OAuth flow:
Common issues and solutions:
- **Token Not Recognized**:
1. **Token Not Recognized**:
- Ensure the token is properly saved in settings.
- Check that the token hasn't expired.
- Verify the token has the required scopes.
- Try regenerating the token.
- **Organization Access Denied**:
2. **Organization Access Denied**:
- Check if SSO is required but not enabled.
- Verify organization membership.
- Contact organization admin if token policies are blocking access.
- **Verifying Token Works**:
3. **Verifying Token Works**:
- The app will show a green checkmark if the token is valid.
- Try accessing a repository to confirm permissions.
- Check the browser console for any error messages.

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@@ -32,7 +32,7 @@ To run OpenHands in Headless mode with Docker:
```bash
docker run -it \
--pull=always \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.21-nikolaik \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.19-nikolaik \
-e SANDBOX_USER_ID=$(id -u) \
-e WORKSPACE_MOUNT_PATH=$WORKSPACE_BASE \
-e LLM_API_KEY=$LLM_API_KEY \
@@ -43,7 +43,7 @@ docker run -it \
-v ~/.openhands-state:/.openhands-state \
--add-host host.docker.internal:host-gateway \
--name openhands-app-$(date +%Y%m%d%H%M%S) \
docker.all-hands.dev/all-hands-ai/openhands:0.21 \
docker.all-hands.dev/all-hands-ai/openhands:0.19 \
python -m openhands.core.main -t "write a bash script that prints hi"
```

View File

@@ -0,0 +1,16 @@
# Persisting Session Data
Using the standard Development Workflow, the session data is stored in memory. Currently, if OpenHands' service is restarted,
previous sessions become invalid (a new secret is generated) and thus not recoverable.
## How to Persist Session Data
### Development Workflow
In the `config.toml` file, specify the following:
```
[core]
...
file_store="local"
file_store_path="/absolute/path/to/openhands/cache/directory"
jwt_secret="secretpass"
```

View File

@@ -1,66 +1,27 @@
# Running OpenHands
# Installation
## System Requirements
- MacOS with [Docker Desktop support](https://docs.docker.com/desktop/setup/install/mac-install/#system-requirements)
- Linux
- Windows with [WSL](https://learn.microsoft.com/en-us/windows/wsl/install) and [Docker Desktop support](https://docs.docker.com/desktop/setup/install/windows-install/#system-requirements)
- Docker version 26.0.0+ or Docker Desktop 4.31.0+.
- You must be using Linux or Mac OS.
- If you are on Windows, you must use [WSL](https://learn.microsoft.com/en-us/windows/wsl/install).
## Prerequisites
<details>
<summary>MacOS</summary>
### Docker Desktop
1. [Install Docker Desktop on Mac](https://docs.docker.com/desktop/setup/install/mac-install).
2. Open Docker Desktop, go to `Settings > Advanced` and ensure `Allow the default Docker socket to be used` is enabled.
</details>
<details>
<summary>Linux</summary>
:::note
Tested with Ubuntu 22.04.
:::
### Docker Desktop
1. [Install Docker Desktop on Linux](https://docs.docker.com/desktop/setup/install/linux/).
</details>
<details>
<summary>Windows</summary>
### WSL
1. [Install WSL](https://learn.microsoft.com/en-us/windows/wsl/install).
2. Run `wsl --version` in powershell and confirm `Default Version: 2`.
### Docker Desktop
1. [Install Docker Desktop on Windows](https://docs.docker.com/desktop/setup/install/windows-install).
2. Open Docker Desktop, go to `Settings` and confirm the following:
- General: `Use the WSL 2 based engine` is enabled.
- Resources > WSL Integration: `Enable integration with my default WSL distro` is enabled.
</details>
## Start the App
## Start the app
The easiest way to run OpenHands is in Docker.
```bash
docker pull docker.all-hands.dev/all-hands-ai/runtime:0.21-nikolaik
docker pull docker.all-hands.dev/all-hands-ai/runtime:0.19-nikolaik
docker run -it --rm --pull=always \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.21-nikolaik \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.19-nikolaik \
-e LOG_ALL_EVENTS=true \
-v /var/run/docker.sock:/var/run/docker.sock \
-v ~/.openhands-state:/.openhands-state \
-p 3000:3000 \
--add-host host.docker.internal:host-gateway \
--name openhands-app \
docker.all-hands.dev/all-hands-ai/openhands:0.21
docker.all-hands.dev/all-hands-ai/openhands:0.19
```
You'll find OpenHands running at http://localhost:3000!

View File

@@ -1,136 +0,0 @@
# Custom LLM Configurations
OpenHands supports defining multiple named LLM configurations in your `config.toml` file. This feature allows you to use different LLM configurations for different purposes, such as using a cheaper model for tasks that don't require high-quality responses, or using different models with different parameters for specific agents.
## How It Works
Named LLM configurations are defined in the `config.toml` file using sections that start with `llm.`. For example:
```toml
# Default LLM configuration
[llm]
model = "gpt-4"
api_key = "your-api-key"
temperature = 0.0
# Custom LLM configuration for a cheaper model
[llm.gpt3]
model = "gpt-3.5-turbo"
api_key = "your-api-key"
temperature = 0.2
# Another custom configuration with different parameters
[llm.high-creativity]
model = "gpt-4"
api_key = "your-api-key"
temperature = 0.8
top_p = 0.9
```
Each named configuration inherits all settings from the default `[llm]` section and can override any of those settings. You can define as many custom configurations as needed.
## Using Custom Configurations
### With Agents
You can specify which LLM configuration an agent should use by setting the `llm_config` parameter in the agent's configuration section:
```toml
[agent.RepoExplorerAgent]
# Use the cheaper GPT-3 configuration for this agent
llm_config = 'gpt3'
[agent.CodeWriterAgent]
# Use the high creativity configuration for this agent
llm_config = 'high-creativity'
```
### Configuration Options
Each named LLM configuration supports all the same options as the default LLM configuration. These include:
- Model selection (`model`)
- API configuration (`api_key`, `base_url`, etc.)
- Model parameters (`temperature`, `top_p`, etc.)
- Retry settings (`num_retries`, `retry_multiplier`, etc.)
- Token limits (`max_input_tokens`, `max_output_tokens`)
- And all other LLM configuration options
For a complete list of available options, see the LLM Configuration section in the [Configuration Options](../configuration-options) documentation.
## Use Cases
Custom LLM configurations are particularly useful in several scenarios:
- **Cost Optimization**: Use cheaper models for tasks that don't require high-quality responses, like repository exploration or simple file operations.
- **Task-Specific Tuning**: Configure different temperature and top_p values for tasks that require different levels of creativity or determinism.
- **Different Providers**: Use different LLM providers or API endpoints for different tasks.
- **Testing and Development**: Easily switch between different model configurations during development and testing.
## Example: Cost Optimization
A practical example of using custom LLM configurations to optimize costs:
```toml
# Default configuration using GPT-4 for high-quality responses
[llm]
model = "gpt-4"
api_key = "your-api-key"
temperature = 0.0
# Cheaper configuration for repository exploration
[llm.repo-explorer]
model = "gpt-3.5-turbo"
temperature = 0.2
# Configuration for code generation
[llm.code-gen]
model = "gpt-4"
temperature = 0.0
max_output_tokens = 2000
[agent.RepoExplorerAgent]
llm_config = 'repo-explorer'
[agent.CodeWriterAgent]
llm_config = 'code-gen'
```
In this example:
- Repository exploration uses a cheaper model since it mainly involves understanding and navigating code
- Code generation uses GPT-4 with a higher token limit for generating larger code blocks
- The default configuration remains available for other tasks
# Custom Configurations with Reserved Names
OpenHands can use custom LLM configurations named with reserved names, for specific use cases. If you specify the model and other settings under the reserved names, then OpenHands will load and them for a specific purpose. As of now, one such configuration is implemented: draft editor.
## Draft Editor Configuration
The `draft_editor` configuration is a group of settings you can provide, to specify the model to use for preliminary drafting of code edits, for any tasks that involve editing and refining code. You need to provide it under the section `[llm.draft_editor]`.
For example, you can define in `config.toml` a draft editor like this:
```toml
[llm.draft_editor]
model = "gpt-4"
temperature = 0.2
top_p = 0.95
presence_penalty = 0.0
frequency_penalty = 0.0
```
This configuration:
- Uses GPT-4 for high-quality edits and suggestions
- Sets a low temperature (0.2) to maintain consistency while allowing some flexibility
- Uses a high top_p value (0.95) to consider a wide range of token options
- Disables presence and frequency penalties to maintain focus on the specific edits needed
Use this configuration when you want to let an LLM draft edits before making them. In general, it may be useful to:
- Review and suggest code improvements
- Refine existing content while maintaining its core meaning
- Make precise, focused changes to code or text
:::note
Custom LLM configurations are only available when using OpenHands in development mode, via `main.py` or `cli.py`. When running via `docker run`, please use the standard configuration options.
:::

View File

@@ -5,14 +5,23 @@ OpenHands can connect to any LLM supported by LiteLLM. However, it requires a po
## Model Recommendations
Based on our evaluations of language models for coding tasks (using the SWE-bench dataset), we can provide some
recommendations for model selection. Our latest benchmarking results can be found in [this spreadsheet](https://docs.google.com/spreadsheets/d/1wOUdFCMyY6Nt0AIqF705KN4JKOWgeI4wUGUP60krXXs/edit?gid=0).
recommendations for model selection. Some analyses can be found in [this blog article comparing LLMs](https://www.all-hands.dev/blog/evaluation-of-llms-as-coding-agents-on-swe-bench-at-30x-speed) and
[this blog article with some more recent results](https://www.all-hands.dev/blog/openhands-codeact-21-an-open-state-of-the-art-software-development-agent).
When choosing a model, consider both the quality of outputs and the associated costs. Here's a summary of the findings:
- Claude 3.5 Sonnet is the best by a fair amount, achieving a 53% resolve rate on SWE-Bench Verified with the default agent in OpenHands.
- GPT-4o lags behind, and o1-mini actually performed somewhat worse than GPT-4o. We went in and analyzed the results a little, and briefly it seemed like o1 was sometimes "overthinking" things, performing extra environment configuration tasks when it could just go ahead and finish the task.
- Finally, the strongest open models were Llama 3.1 405 B and deepseek-v2.5, and they performed reasonably, even besting some of the closed models.
Please refer to the [full article](https://www.all-hands.dev/blog/evaluation-of-llms-as-coding-agents-on-swe-bench-at-30x-speed) for more details.
Based on these findings and community feedback, the following models have been verified to work reasonably well with OpenHands:
- anthropic/claude-3-5-sonnet-20241022 (recommended)
- anthropic/claude-3-5-haiku-20241022
- deepseek/deepseek-chat
- gpt-4o
- claude-3-5-sonnet (recommended)
- gpt-4 / gpt-4o
- llama-3.1-405b
- deepseek-v2.5
:::warning
OpenHands will issue many prompts to the LLM you configure. Most of these LLMs cost money, so be sure to set spending

View File

@@ -1,36 +0,0 @@
# Microagents Overview
Microagents are specialized prompts that enhance OpenHands with domain-specific knowledge, repository-specific context
and task-specific workflows. They help by providing expert guidance, automating common tasks, and ensuring
consistent practices across projects.
## Microagent Types
Currently OpenHands supports the following types of microagents:
* [Repository Microagents](./microagents-repo): Repository-specific context and guidelines for OpenHands.
* [Public Microagents](./microagents-public): General guidelines triggered by keywords for all OpenHands users.
When OpenHands works with a repository, it:
1. Loads repository-specific instructions from `.openhands/microagents/` if present in the repository.
2. Loads general guidelines triggered by keywords in conversations.
See current [Public Microagents](https://github.com/All-Hands-AI/OpenHands/tree/main/microagents/knowledge).
## Microagent Format
All microagents use markdown files with YAML frontmatter that have special instructions to help OpenHands accomplish
tasks:
```
---
name: <Name of the microagent>
type: <MicroAgent type>
version: <MicroAgent version>
agent: <The agent type (Typically CodeActAgent)>
triggers:
- <Optional keywords triggering the microagent. If triggers are removed, it will always be included>
---
<Markdown with any special guidelines, instructions, and prompts that OpenHands should follow.
Check out the specific documentation for each microagent on best practices for more information.>
```

View File

@@ -1,21 +1,31 @@
# Public Microagents
# Public Micro-Agents
OpenHands uses specialized micro-agents to handle specific tasks and contexts efficiently. These micro-agents are small,
focused components that provide specialized behavior and knowledge for particular scenarios.
## Overview
Public microagents are specialized guidelines triggered by keywords for all OpenHands users.
They are defined in markdown files under the
Public micro-agents are defined in markdown files under the
[`microagents/knowledge/`](https://github.com/All-Hands-AI/OpenHands/tree/main/microagents/knowledge) directory.
Each micro-agent is configured with:
Public microagents:
- A unique name.
- The agent type (typically CodeActAgent).
- Trigger keywords that activate the agent.
- Specific instructions and capabilities.
### Integration
Public micro-agents are automatically integrated into OpenHands' workflow. They:
- Monitor incoming commands for their trigger words.
- Activate when relevant triggers are detected.
- Apply their specialized knowledge and capabilities.
- Follow their specific guidelines and restrictions.
## Current Public Microagents
## Available Public Micro-Agents
For more information about specific microagents, refer to their individual documentation files in
the [`microagents/knowledge/`](https://github.com/All-Hands-AI/OpenHands/tree/main/microagents/knowledge/) directory.
For more information about specific micro-agents, refer to their individual documentation files in
the [`micro-agents`](https://github.com/All-Hands-AI/OpenHands/tree/main/microagents) directory.
### GitHub Agent
**File**: `github.md`
@@ -56,54 +66,105 @@ Usage Example:
yes | npm install package-name
```
## Contributing a Public Microagent
### Custom Public Micro-Agents
You can create your own public microagents by adding new markdown files to the
[`microagents/knowledge/`](https://github.com/All-Hands-AI/OpenHands/tree/main/microagents/knowledge/) directory.
You can create your own public micro-agents by adding new markdown files to the `microagents/knowledge/` directory.
Each file should follow this structure:
### Public Microagents Best Practices
```markdown
---
name: agent_name
agent: CodeActAgent
triggers:
- trigger_word1
- trigger_word2
---
- **Clear Scope**: Keep the microagent focused on a specific domain or task.
Instructions and capabilities for the micro-agent...
```
## Working With Public Micro-Agents
When working with public micro-agents:
- **Use Appropriate Triggers**: Ensure your commands include the relevant trigger words to activate the correct micro-agent.
- **Follow Agent Guidelines**: Each agent has specific instructions and limitations. Respect these for optimal results.
- **API-First Approach**: When available, use API endpoints rather than web interfaces.
- **Automation Friendly**: Design commands that work well in non-interactive environments.
## Contributing a Public Micro-Agent
Best practices for creating public micro-agents:
- **Clear Scope**: Keep the micro-agent focused on a specific domain or task.
- **Explicit Instructions**: Provide clear, unambiguous guidelines.
- **Useful Examples**: Include practical examples of common use cases.
- **Safety First**: Include necessary warnings and constraints.
- **Integration Awareness**: Consider how the microagent interacts with other components.
- **Integration Awareness**: Consider how the micro-agent interacts with other components.
### Steps to Contribute a Public Microagent
To contribute a new micro-agent to OpenHands:
#### 1. Plan the Public Microagent
### 1. Plan the Public Micro-Agent
Before creating a public microagent, consider:
Before creating a public micro-agent, consider:
- What specific problem or use case will it address?
- What unique capabilities or knowledge should it have?
- What trigger words make sense for activating it?
- What constraints or guidelines should it follow?
#### 2. Create File
### 2. File Structure
Create a new markdown file in [`microagents/knowledge/`](https://github.com/All-Hands-AI/OpenHands/tree/main/microagents/knowledge/)
with a descriptive name (e.g., `docker.md` for a Docker-focused agent).
Create a new markdown file in `microagents/knowledge/` with a descriptive name (e.g., `docker.md` for a Docker-focused agent).
Update the file with the required frontmatter [according to the required format](./microagents-overview#microagent-format)
and the required specialized guidelines while following the [best practices above](#public-microagents-best-practices).
### 3. Required Components
#### 3. Testing the Public Microagent
The micro-agent file must include:
- **Front Matter**: YAML metadata at the start of the file:
```markdown
---
name: your_agent_name
agent: CodeActAgent
triggers:
- trigger_word1
- trigger_word2
---
```
- **Instructions**: Clear, specific guidelines for the agent's behavior:
```markdown
You are responsible for [specific task/domain].
Key responsibilities:
1. [Responsibility 1]
2. [Responsibility 2]
Guidelines:
- [Guideline 1]
- [Guideline 2]
Examples of usage:
[Example 1]
[Example 2]
```
### 4. Testing the Public Micro-Agent
Before submitting:
- Test the agent with various prompts.
- Verify trigger words activate the agent correctly.
- Ensure instructions are clear and comprehensive.
- Check for potential conflicts with existing agents.
#### 4. Submission Process
### 5. Submission Process
Submit a pull request with:
- The new microagent file.
- The new micro-agent file.
- Updated documentation if needed.
- Description of the agent's purpose and capabilities.
### Example Public Microagent Implementation
### Example Public Micro-Agent Implementation
Here's a template for a new microagent:
Here's a template for a new micro-agent:
```markdown
---
@@ -149,5 +210,5 @@ Remember to:
- Optimize for build time and image size
```
See the [current public micro-agents](https://github.com/All-Hands-AI/OpenHands/tree/main/microagents/knowledge) for
more examples.
Remember that micro-agents are a powerful way to extend OpenHands' capabilities in specific domains. Well-designed
agents can significantly improve the system's ability to handle specialized tasks.

View File

@@ -1,51 +1,25 @@
# Repository Microagents
## Overview
# Repository Micro-Agents
OpenHands can be customized to work more effectively with specific repositories by providing repository-specific context
and guidelines. This section explains how to optimize OpenHands for your project.
## Creating a Repository Micro-Agent
## Repository Configuration
You can customize OpenHands' behavior for your repository by creating a `.openhands/microagents/` directory in your repository's root.
At minimum it should contain the file
At minimum, it should contain the file
`.openhands/microagents/repo.md`, which includes instructions that will
be given to the agent every time it works with this repository.
### Repository Microagents Best Practices
- **Keep Instructions Updated**: Regularly update your `.openhands/microagents/` directory as your project evolves.
- **Be Specific**: Include specific paths, patterns, and requirements unique to your project.
- **Document Dependencies**: List all tools and dependencies required for development.
- **Include Examples**: Provide examples of good code patterns from your project.
- **Specify Conventions**: Document naming conventions, file organization, and code style preferences.
### Steps to Create a Repository Microagent
#### 1. Plan the Repository Microagent
When creating a repository-specific micro-agent, we suggest including the following information:
We suggest including the following information:
- **Repository Overview**: A brief description of your project's purpose and architecture.
- **Directory Structure**: Key directories and their purposes.
- **Development Guidelines**: Project-specific coding standards and practices.
- **Testing Requirements**: How to run tests and what types of tests are required.
- **Setup Instructions**: Steps needed to build and run the project.
#### 2. Create File
Create a file in your repository under `.openhands/microagents/` (Example: `.openhands/microagents/repo.md`)
Update the file with the required frontmatter [according to the required format](./microagents-overview#microagent-format)
and the required specialized guidelines for your repository.
### Example Repository Microagent
### Example Repository Configuration
Example `.openhands/microagents/repo.md` file:
```
---
name: repo
type: repo
agent: CodeActAgent
---
Repository: MyProject
Description: A web application for task management
@@ -63,6 +37,30 @@ Guidelines:
- Follow ESLint configuration
- Write tests for all new features
- Use TypeScript for new code
If adding a new component in src/components, always add appropriate unit tests in tests/components/.
```
### Customizing Prompts
You may also add customized prompts to the `.openhands/microagents/repo.md` file when working with a repository.
These could:
- **Reference Project Standards**: Mention specific coding standards or patterns used in your project.
- **Include Context**: Reference relevant documentation or existing implementations.
- **Specify Testing Requirements**: Include project-specific testing requirements in your prompts.
Example customized prompt:
```
Add a new task completion feature to src/components/TaskList.tsx following our existing component patterns.
Include unit tests in tests/components/ and update the documentation in docs/features/.
The component should use our shared styling from src/styles/components.
```
### Best Practices for Repository Customization
- **Keep Instructions Updated**: Regularly update your `.openhands/microagents/` directory as your project evolves.
- **Be Specific**: Include specific paths, patterns, and requirements unique to your project.
- **Document Dependencies**: List all tools and dependencies required for development.
- **Include Examples**: Provide examples of good code patterns from your project.
- **Specify Conventions**: Document naming conventions, file organization, and code style preferences.
By customizing OpenHands for your repository, you'll get more accurate and consistent results that align with your project's standards and requirements.

View File

@@ -16,7 +16,7 @@ some flags being passed to `docker run` that make this possible:
```
docker run # ...
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.21-nikolaik \
-e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.19-nikolaik \
-v /var/run/docker.sock:/var/run/docker.sock \
# ...
```

View File

@@ -5,7 +5,7 @@ const sidebars: SidebarsConfig = {
docsSidebar: [
{
type: 'doc',
label: 'Running OpenHands',
label: 'Installation',
id: 'usage/installation',
},
{
@@ -24,23 +24,18 @@ const sidebars: SidebarsConfig = {
},
{
type: 'category',
label: 'Microagents',
label: 'Micro-Agents',
items: [
{
type: 'doc',
label: 'Overview',
id: 'usage/prompting/microagents-overview',
label: 'Public',
id: 'usage/prompting/microagents-public',
},
{
type: 'doc',
label: 'Repository',
id: 'usage/prompting/microagents-repo',
},
{
type: 'doc',
label: 'Public',
id: 'usage/prompting/microagents-public',
},
],
}
],
@@ -137,6 +132,11 @@ const sidebars: SidebarsConfig = {
label: 'Custom Sandbox',
id: 'usage/how-to/custom-sandbox-guide',
},
{
type: 'doc',
label: 'Persist Session Data',
id: 'usage/how-to/persist-session-data',
},
],
},
{

View File

@@ -76,7 +76,7 @@ def get_config(
)
config.set_llm_config(metadata.llm_config)
agent_config = config.get_agent_config(metadata.agent_class)
agent_config.enable_prompt_extensions = False
agent_config.use_microagents = False
return config

View File

@@ -60,7 +60,7 @@ def get_config(
)
config.set_llm_config(metadata.llm_config)
agent_config = config.get_agent_config(metadata.agent_class)
agent_config.enable_prompt_extensions = False
agent_config.use_microagents = False
return config

View File

@@ -68,7 +68,7 @@ def get_config(
)
config.set_llm_config(metadata.llm_config)
agent_config = config.get_agent_config(metadata.agent_class)
agent_config.enable_prompt_extensions = False
agent_config.use_microagents = False
# copy 'draft_editor' config if exists
config_copy = copy.deepcopy(config)

View File

@@ -74,7 +74,7 @@ def get_config(
)
config.set_llm_config(metadata.llm_config)
agent_config = config.get_agent_config(metadata.agent_class)
agent_config.enable_prompt_extensions = False
agent_config.use_microagents = False
return config

View File

@@ -87,7 +87,7 @@ def get_config(
)
config.set_llm_config(metadata.llm_config)
agent_config = config.get_agent_config(metadata.agent_class)
agent_config.enable_prompt_extensions = False
agent_config.use_microagents = False
return config

View File

@@ -51,7 +51,7 @@ def get_config(
)
config.set_llm_config(metadata.llm_config)
agent_config = config.get_agent_config(metadata.agent_class)
agent_config.enable_prompt_extensions = False
agent_config.use_microagents = False
return config

View File

@@ -171,7 +171,7 @@ def initialize_runtime(
action = CmdRunAction(
command=f'git clone -b commit0_combined https://github.com/{instance["repo"]}.git'
)
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -181,7 +181,7 @@ def initialize_runtime(
)
action = CmdRunAction(command=f'cd /workspace/{workspace_dir_name}')
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -191,7 +191,7 @@ def initialize_runtime(
)
action = CmdRunAction(command='git checkout -b openhands')
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -201,7 +201,7 @@ def initialize_runtime(
# Install commit0
action = CmdRunAction(command='/root/.cargo/bin/uv pip install commit0')
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
# logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -231,7 +231,7 @@ def complete_runtime(
workspace_dir_name = _get_commit0_workspace_dir_name(instance)
action = CmdRunAction(command='git add .')
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -241,7 +241,7 @@ def complete_runtime(
)
action = CmdRunAction(command='git commit -m "openhands edits"')
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -258,7 +258,7 @@ def complete_runtime(
action = CmdRunAction(
command=f"git diff {instance['base_commit']} HEAD -- . ':(exclude)spec.pdf.bz2'"
)
action.set_hard_timeout(600 + 100 * n_retries)
action.timeout = 600 + 100 * n_retries
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
# logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -282,7 +282,7 @@ def complete_runtime(
action = CmdRunAction(
command=f"{instance['test']['test_cmd']} --json-report --json-report-file=report.json --continue-on-collection-errors {test_dir} > test_output.txt 2>&1"
)
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -292,7 +292,7 @@ def complete_runtime(
)
# Read test output
action = CmdRunAction(command='cat test_output.txt')
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
# logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -305,7 +305,7 @@ def complete_runtime(
# Save pytest exit code
action = CmdRunAction(command='echo $?')
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
# logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -318,7 +318,7 @@ def complete_runtime(
# Read the test report
action = CmdRunAction(command='cat report.json')
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
# logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -330,7 +330,7 @@ def complete_runtime(
repo_name = instance['repo'].split('/')[1]
repo_name = repo_name.replace('.', '-')
action = CmdRunAction(command=f'commit0 get-tests {repo_name}')
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
# logger.info(obs, extra={'msg_type': 'OBSERVATION'})

View File

@@ -78,7 +78,7 @@ def get_config(
)
config.set_llm_config(metadata.llm_config)
agent_config = config.get_agent_config(metadata.agent_class)
agent_config.enable_prompt_extensions = False
agent_config.use_microagents = False
agent_config = AgentConfig(
function_calling=False,
codeact_enable_jupyter=True,

View File

@@ -63,7 +63,7 @@ def get_config(
)
config.set_llm_config(metadata.llm_config)
agent_config = config.get_agent_config(metadata.agent_class)
agent_config.enable_prompt_extensions = False
agent_config.use_microagents = False
return config

View File

@@ -56,7 +56,7 @@ def get_config(
)
config.set_llm_config(metadata.llm_config)
agent_config = config.get_agent_config(metadata.agent_class)
agent_config.enable_prompt_extensions = False
agent_config.use_microagents = False
return config

View File

@@ -77,7 +77,7 @@ def get_config(
)
config.set_llm_config(metadata.llm_config)
agent_config = config.get_agent_config(metadata.agent_class)
agent_config.enable_prompt_extensions = False
agent_config.use_microagents = False
return config

View File

@@ -98,7 +98,7 @@ def get_config(
)
config.set_llm_config(metadata.llm_config)
agent_config = config.get_agent_config(metadata.agent_class)
agent_config.enable_prompt_extensions = False
agent_config.use_microagents = False
return config

View File

@@ -62,7 +62,7 @@ def get_config(
)
config.set_llm_config(metadata.llm_config)
agent_config = config.get_agent_config(metadata.agent_class)
agent_config.enable_prompt_extensions = False
agent_config.use_microagents = False
return config

View File

@@ -8,9 +8,6 @@ Please follow instruction [here](../../README.md#setup) to setup your local deve
## Test if your environment works
Follow the instructions here https://miniwob.farama.org/content/getting_started/ & https://miniwob.farama.org/content/viewing/
to set up MiniWoB server in your local environment at http://localhost:8080/miniwob/
Access with browser the above MiniWoB URLs and see if they load correctly.
## Run Evaluation

View File

@@ -120,7 +120,7 @@ def get_config(
)
config.set_llm_config(metadata.llm_config)
agent_config = config.get_agent_config(metadata.agent_class)
agent_config.enable_prompt_extensions = False
agent_config.use_microagents = False
return config

View File

@@ -93,7 +93,7 @@ def get_config(
)
config.set_llm_config(metadata.llm_config)
agent_config = config.get_agent_config(metadata.agent_class)
agent_config.enable_prompt_extensions = False
agent_config.use_microagents = False
return config

View File

@@ -1,4 +1,3 @@
import json
import os
import tempfile
import time
@@ -12,11 +11,7 @@ from swebench.harness.run_evaluation import (
)
from swebench.harness.test_spec import SWEbenchInstance, TestSpec, make_test_spec
from swebench.harness.utils import load_swebench_dataset
from tqdm import tqdm
from evaluation.benchmarks.swe_bench.resource.mapping import (
get_instance_resource_factor,
)
from evaluation.benchmarks.swe_bench.run_infer import get_instance_docker_image
from evaluation.utils.shared import (
EvalMetadata,
@@ -71,7 +66,7 @@ def process_git_patch(patch):
return patch
def get_config(metadata: EvalMetadata, instance: pd.Series) -> AppConfig:
def get_config(instance: pd.Series) -> AppConfig:
# We use a different instance image for the each instance of swe-bench eval
base_container_image = get_instance_docker_image(instance['instance_id'])
logger.info(
@@ -86,14 +81,10 @@ def get_config(metadata: EvalMetadata, instance: pd.Series) -> AppConfig:
base_container_image=base_container_image,
use_host_network=False,
# large enough timeout, since some testcases take very long to run
timeout=600,
timeout=1800,
api_key=os.environ.get('ALLHANDS_API_KEY', None),
remote_runtime_api_url=os.environ.get('SANDBOX_REMOTE_RUNTIME_API_URL'),
remote_runtime_init_timeout=3600,
remote_runtime_resource_factor=get_instance_resource_factor(
dataset_name=metadata.dataset,
instance_id=instance['instance_id'],
),
),
# do not mount workspace
workspace_base=None,
@@ -132,7 +123,7 @@ def process_instance(
else:
logger.info(f'Starting evaluation for instance {instance.instance_id}.')
config = get_config(metadata, instance)
config = get_config(instance)
instance_id = instance.instance_id
model_patch = instance['model_patch']
test_spec: TestSpec = instance['test_spec']
@@ -160,52 +151,52 @@ def process_instance(
if runtime_failure_count > 0:
config.sandbox.remote_runtime_resource_factor = min(
config.sandbox.remote_runtime_resource_factor * (2**runtime_failure_count),
8,
4, # hardcode maximum resource factor to 4
)
logger.warning(
f'This is the {runtime_failure_count + 1}th attempt for instance {instance.instance_id}, setting resource factor to {config.sandbox.remote_runtime_resource_factor}'
f'This is the second attempt for instance {instance.instance_id}, setting resource factor to {config.sandbox.remote_runtime_resource_factor}'
)
runtime = create_runtime(config)
call_async_from_sync(runtime.connect)
# Get patch and save it to /tmp/patch.diff
with tempfile.TemporaryDirectory() as temp_dir:
# Patch file
patch_file_path = os.path.join(temp_dir, 'patch.diff')
with open(patch_file_path, 'w') as f:
f.write(model_patch)
runtime.copy_to(patch_file_path, '/tmp')
# Eval script
eval_script_path = os.path.join(temp_dir, 'eval.sh')
with open(eval_script_path, 'w') as f:
f.write(test_spec.eval_script)
runtime.copy_to(eval_script_path, '/tmp')
# Set +x
action = CmdRunAction(command='chmod +x /tmp/eval.sh')
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
assert obs.exit_code == 0
# Apply patch
exec_command = (
'cd /testbed && '
"(git apply -v /tmp/patch.diff && echo 'APPLY_PATCH_PASS' || "
"(echo 'Failed to apply patch with git apply, trying with patch command...' && "
"(patch --batch --fuzz=5 -p1 -i /tmp/patch.diff && echo 'APPLY_PATCH_PASS' || "
"echo 'APPLY_PATCH_FAIL')))"
)
action = CmdRunAction(command=exec_command)
action.timeout = 600
obs = runtime.run_action(action)
assert isinstance(obs, CmdOutputObservation)
apply_patch_output = obs.content
assert isinstance(apply_patch_output, str)
instance['test_result']['apply_patch_output'] = apply_patch_output
try:
runtime = create_runtime(config)
call_async_from_sync(runtime.connect)
# Get patch and save it to /tmp/patch.diff
with tempfile.TemporaryDirectory() as temp_dir:
# Patch file
patch_file_path = os.path.join(temp_dir, 'patch.diff')
with open(patch_file_path, 'w') as f:
f.write(model_patch)
runtime.copy_to(patch_file_path, '/tmp')
# Eval script
eval_script_path = os.path.join(temp_dir, 'eval.sh')
with open(eval_script_path, 'w') as f:
f.write(test_spec.eval_script)
runtime.copy_to(eval_script_path, '/tmp')
# Set +x
action = CmdRunAction(command='chmod +x /tmp/eval.sh')
action.set_hard_timeout(600)
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
assert obs.exit_code == 0
# Apply patch
exec_command = (
'cd /testbed && '
"(git apply -v /tmp/patch.diff && echo 'APPLY_PATCH_PASS' || "
"(echo 'Failed to apply patch with git apply, trying with patch command...' && "
"(patch --batch --fuzz=5 -p1 -i /tmp/patch.diff && echo 'APPLY_PATCH_PASS' || "
"echo 'APPLY_PATCH_FAIL')))"
)
action = CmdRunAction(command=exec_command)
action.set_hard_timeout(600)
obs = runtime.run_action(action)
assert isinstance(obs, CmdOutputObservation)
apply_patch_output = obs.content
assert isinstance(apply_patch_output, str)
instance['test_result']['apply_patch_output'] = apply_patch_output
if 'APPLY_PATCH_FAIL' in apply_patch_output:
logger.info(f'[{instance_id}] {APPLY_PATCH_FAIL}:\n{apply_patch_output}')
instance['test_result']['report']['failed_apply_patch'] = True
@@ -221,7 +212,7 @@ def process_instance(
# Run eval script in background and save output to log file
log_file = '/tmp/eval_output.log'
action = CmdRunAction(command=f'/tmp/eval.sh > {log_file} 2>&1 & echo $!')
action.set_hard_timeout(300) # Short timeout just to get the process ID
action.timeout = 60 # Short timeout just to get the process ID
obs = runtime.run_action(action)
if isinstance(obs, CmdOutputObservation) and obs.exit_code == 0:
@@ -244,7 +235,7 @@ def process_instance(
check_action = CmdRunAction(
command=f'ps -p {pid} > /dev/null; echo $?'
)
check_action.set_hard_timeout(300)
check_action.timeout = 60
check_obs = runtime.run_action(check_action)
if (
isinstance(check_obs, CmdOutputObservation)
@@ -261,7 +252,7 @@ def process_instance(
# Read the log file
cat_action = CmdRunAction(command=f'cat {log_file}')
cat_action.set_hard_timeout(300)
cat_action.timeout = 300
cat_obs = runtime.run_action(cat_action)
# Grade answer
@@ -361,14 +352,7 @@ if __name__ == '__main__':
# Load predictions
assert args.input_file.endswith('.jsonl'), 'Input file must be a jsonl file.'
required_fields = ['instance_id', 'model_patch', 'test_result']
with open(args.input_file) as f:
predictions = pd.DataFrame.from_records(
[
{k: v for k, v in json.loads(line).items() if k in required_fields}
for line in tqdm(f, desc='Loading predictions')
]
)
predictions = pd.read_json(args.input_file, lines=True)
assert (
'instance_id' in predictions.columns
), 'Input file must contain instance_id column.'

View File

@@ -1,38 +0,0 @@
"""Mapping instance_id to resource_factor.
Different instances may have different resource requirements.
e.g., some instances may require more memory/CPU to run inference.
This file tracks the resource requirements of different instances.
"""
import json
import os
from openhands.core.logger import openhands_logger as logger
CUR_DIR = os.path.dirname(os.path.abspath(__file__))
DEFAULT_RUNTIME_RESOURCE_FACTOR = int(
os.environ.get('DEFAULT_RUNTIME_RESOURCE_FACTOR', 1)
)
# dataset to resource mapping
_global_resource_mapping: dict[str, dict[str, float]] = {}
def get_resource_mapping(dataset_name: str) -> dict[str, float]:
if dataset_name not in _global_resource_mapping:
file_path = os.path.join(CUR_DIR, f'{dataset_name}.json')
if not os.path.exists(file_path):
logger.warning(f'Resource mapping for {dataset_name} not found.')
return None
with open(file_path, 'r') as f:
_global_resource_mapping[dataset_name] = json.load(f)
logger.info(f'Loaded resource mapping for {dataset_name}')
return _global_resource_mapping[dataset_name]
def get_instance_resource_factor(dataset_name: str, instance_id: str) -> int:
resource_mapping = get_resource_mapping(dataset_name)
if resource_mapping is None:
return DEFAULT_RUNTIME_RESOURCE_FACTOR
return int(resource_mapping.get(instance_id, DEFAULT_RUNTIME_RESOURCE_FACTOR))

View File

@@ -1 +0,0 @@
{"pydata__xarray-6721": 8, "pytest-dev__pytest-7236": 8, "matplotlib__matplotlib-24627": 4, "django__django-15561": 4, "django__django-15098": 4, "django__django-14771": 4, "sympy__sympy-21612": 4, "sympy__sympy-15345": 4, "psf__requests-5414": 4, "astropy__astropy-14508": 2, "django__django-11451": 2, "django__django-11477": 2, "django__django-10880": 2, "django__django-11163": 2, "django__django-11815": 2, "astropy__astropy-14369": 2, "django__django-10097": 2, "django__django-10554": 2, "django__django-12304": 2, "django__django-12325": 2, "django__django-11551": 2, "django__django-11734": 2, "django__django-13109": 2, "django__django-13089": 2, "django__django-13343": 2, "django__django-13363": 2, "django__django-13809": 2, "django__django-13810": 2, "django__django-13786": 2, "django__django-13807": 2, "django__django-14493": 2, "django__django-11820": 2, "django__django-11951": 2, "django__django-11964": 2, "astropy__astropy-14309": 2, "astropy__astropy-14365": 2, "astropy__astropy-12907": 2, "astropy__astropy-14182": 2, "django__django-15161": 2, "django__django-15128": 2, "django__django-14999": 2, "django__django-14915": 2, "django__django-14752": 2, "django__django-14765": 2, "django__django-14089": 2, "django__django-15252": 2, "django__django-15380": 2, "django__django-15382": 2, "django__django-15499": 2, "django__django-15467": 2, "django__django-15280": 2, "django__django-15315": 2, "django__django-15277": 2, "django__django-15268": 2, "django__django-15629": 2, "django__django-15695": 2, "django__django-15732": 2, "django__django-15863": 2, "django__django-16082": 2, "django__django-16145": 2, "django__django-16256": 2, "django__django-16429": 2, "django__django-16454": 2, "django__django-16493": 2, "matplotlib__matplotlib-13989": 2, "matplotlib__matplotlib-20488": 2, "django__django-15503": 2, "django__django-15525": 2, "django__django-15375": 2, "django__django-15278": 2, "matplotlib__matplotlib-21568": 2, "matplotlib__matplotlib-20859": 2, "matplotlib__matplotlib-20826": 2, "matplotlib__matplotlib-20676": 2, "matplotlib__matplotlib-23412": 2, "matplotlib__matplotlib-22719": 2, "matplotlib__matplotlib-23299": 2, "matplotlib__matplotlib-22865": 2, "matplotlib__matplotlib-24149": 2, "matplotlib__matplotlib-24177": 2, "matplotlib__matplotlib-24570": 2, "matplotlib__matplotlib-24637": 2, "matplotlib__matplotlib-24970": 2, "matplotlib__matplotlib-23476": 2, "matplotlib__matplotlib-24026": 2, "matplotlib__matplotlib-23314": 2, "matplotlib__matplotlib-25332": 2, "matplotlib__matplotlib-25311": 2, "matplotlib__matplotlib-25122": 2, "matplotlib__matplotlib-25479": 2, "matplotlib__matplotlib-26342": 2, "psf__requests-2317": 2, "matplotlib__matplotlib-25960": 2, "matplotlib__matplotlib-25775": 2, "pydata__xarray-4356": 2, "pydata__xarray-4075": 2, "pydata__xarray-6461": 2, "pydata__xarray-4687": 2, "pydata__xarray-6599": 2, "pylint-dev__pylint-4661": 2, "django__django-15554": 2, "django__django-15563": 2, "pytest-dev__pytest-5262": 2, "pytest-dev__pytest-10081": 2, "scikit-learn__scikit-learn-12973": 2, "scikit-learn__scikit-learn-13124": 2, "scikit-learn__scikit-learn-13779": 2, "scikit-learn__scikit-learn-14141": 2, "scikit-learn__scikit-learn-13439": 2, "scikit-learn__scikit-learn-13496": 2, "scikit-learn__scikit-learn-15100": 2, "scikit-learn__scikit-learn-25102": 2, "scikit-learn__scikit-learn-25232": 2, "scikit-learn__scikit-learn-25747": 2, "scikit-learn__scikit-learn-26323": 2, "scikit-learn__scikit-learn-9288": 2, "scikit-learn__scikit-learn-14496": 2, "scikit-learn__scikit-learn-14629": 2, "sphinx-doc__sphinx-8265": 2, "sphinx-doc__sphinx-8548": 2, "sphinx-doc__sphinx-8593": 2, "sphinx-doc__sphinx-8595": 2, "sphinx-doc__sphinx-8621": 2, "sphinx-doc__sphinx-8638": 2, "sphinx-doc__sphinx-9229": 2, "sphinx-doc__sphinx-9281": 2, "sphinx-doc__sphinx-9461": 2, "sphinx-doc__sphinx-9591": 2, "sphinx-doc__sphinx-9658": 2, "sphinx-doc__sphinx-9673": 2, "sympy__sympy-12096": 2, "sympy__sympy-12481": 2, "sphinx-doc__sphinx-10323": 2, "sphinx-doc__sphinx-7590": 2, "sympy__sympy-13877": 2, "sympy__sympy-12489": 2, "sympy__sympy-15809": 2, "sympy__sympy-14711": 2, "sympy__sympy-16597": 2, "sympy__sympy-16766": 2, "sympy__sympy-16792": 2, "sympy__sympy-15875": 2, "sympy__sympy-17655": 2, "sympy__sympy-18189": 2, "sympy__sympy-18763": 2, "sympy__sympy-19040": 2, "sympy__sympy-19495": 2, "sympy__sympy-19637": 2, "sympy__sympy-19783": 2, "sympy__sympy-17630": 2, "sympy__sympy-20428": 2, "sympy__sympy-20590": 2, "sympy__sympy-20801": 2, "sympy__sympy-21379": 2, "sympy__sympy-21847": 2, "sympy__sympy-22456": 2, "sympy__sympy-22714": 2, "sympy__sympy-22914": 2, "sympy__sympy-23262": 2, "sympy__sympy-23413": 2, "sympy__sympy-23534": 2, "sympy__sympy-24066": 2, "sympy__sympy-24213": 2, "sympy__sympy-24443": 2, "sympy__sympy-24562": 2, "sympy__sympy-24661": 2}

View File

@@ -9,9 +9,6 @@ import toml
from datasets import load_dataset
import openhands.agenthub
from evaluation.benchmarks.swe_bench.resource.mapping import (
get_instance_resource_factor,
)
from evaluation.utils.shared import (
EvalException,
EvalMetadata,
@@ -44,10 +41,9 @@ from openhands.utils.async_utils import call_async_from_sync
from openhands.utils.shutdown_listener import sleep_if_should_continue
USE_HINT_TEXT = os.environ.get('USE_HINT_TEXT', 'false').lower() == 'true'
USE_INSTANCE_IMAGE = os.environ.get('USE_INSTANCE_IMAGE', 'true').lower() == 'true'
USE_INSTANCE_IMAGE = os.environ.get('USE_INSTANCE_IMAGE', 'false').lower() == 'true'
RUN_WITH_BROWSING = os.environ.get('RUN_WITH_BROWSING', 'false').lower() == 'true'
AGENT_CLS_TO_FAKE_USER_RESPONSE_FN = {
'CodeActAgent': codeact_user_response,
}
@@ -139,10 +135,6 @@ def get_config(
remote_runtime_api_url=os.environ.get('SANDBOX_REMOTE_RUNTIME_API_URL'),
keep_runtime_alive=False,
remote_runtime_init_timeout=3600,
remote_runtime_resource_factor=get_instance_resource_factor(
dataset_name=metadata.dataset,
instance_id=instance['instance_id'],
),
),
# do not mount workspace
workspace_base=None,
@@ -158,7 +150,6 @@ def get_config(
codeact_enable_browsing=RUN_WITH_BROWSING,
codeact_enable_llm_editor=False,
condenser=metadata.condenser_config,
enable_prompt_extensions=False,
)
config.set_agent_config(agent_config)
return config
@@ -182,7 +173,7 @@ def initialize_runtime(
action = CmdRunAction(
command=f"""echo 'export SWE_INSTANCE_ID={instance['instance_id']}' >> ~/.bashrc && echo 'export PIP_CACHE_DIR=~/.cache/pip' >> ~/.bashrc && echo "alias git='git --no-pager'" >> ~/.bashrc"""
)
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -191,7 +182,7 @@ def initialize_runtime(
)
action = CmdRunAction(command="""export USER=$(whoami); echo USER=${USER} """)
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -203,7 +194,7 @@ def initialize_runtime(
# inject the instance info
action = CmdRunAction(command='mkdir -p /swe_util/eval_data/instances')
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -232,14 +223,14 @@ def initialize_runtime(
'/swe_util/',
)
action = CmdRunAction(command='cat ~/.bashrc')
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
assert_and_raise(obs.exit_code == 0, f'Failed to cat ~/.bashrc: {str(obs)}')
action = CmdRunAction(command='source ~/.bashrc')
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -248,7 +239,7 @@ def initialize_runtime(
assert_and_raise(obs.exit_code == 0, f'Failed to source ~/.bashrc: {str(obs)}')
action = CmdRunAction(command='source /swe_util/instance_swe_entry.sh')
action.set_hard_timeout(600)
action.timeout = 3600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -258,7 +249,7 @@ def initialize_runtime(
)
else:
action = CmdRunAction(command='source /swe_util/swe_entry.sh')
action.set_hard_timeout(1800)
action.timeout = 1800
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -268,7 +259,7 @@ def initialize_runtime(
)
action = CmdRunAction(command=f'cd /workspace/{workspace_dir_name}')
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -278,7 +269,7 @@ def initialize_runtime(
)
action = CmdRunAction(command='git reset --hard')
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -287,14 +278,14 @@ def initialize_runtime(
action = CmdRunAction(
command='for remote_name in $(git remote); do git remote remove "${remote_name}"; done'
)
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
assert_and_raise(obs.exit_code == 0, f'Failed to remove git remotes: {str(obs)}')
action = CmdRunAction(command='which python')
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -325,7 +316,7 @@ def complete_runtime(
workspace_dir_name = _get_swebench_workspace_dir_name(instance)
action = CmdRunAction(command=f'cd /workspace/{workspace_dir_name}')
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -335,7 +326,7 @@ def complete_runtime(
)
action = CmdRunAction(command='git config --global core.pager ""')
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -345,7 +336,7 @@ def complete_runtime(
)
action = CmdRunAction(command='git add -A')
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -360,7 +351,7 @@ def complete_runtime(
action = CmdRunAction(
command=f'git diff --no-color --cached {instance["base_commit"]}'
)
action.set_hard_timeout(max(300 + 100 * n_retries, 600))
action.timeout = 600 + 100 * n_retries
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -408,7 +399,7 @@ def process_instance(
8,
)
logger.warning(
f'This is the {runtime_failure_count + 1}th attempt for instance {instance.instance_id}, setting resource factor to {config.sandbox.remote_runtime_resource_factor}'
f'This is the second attempt for instance {instance.instance_id}, setting resource factor to {config.sandbox.remote_runtime_resource_factor}'
)
runtime = create_runtime(config)
call_async_from_sync(runtime.connect)
@@ -488,10 +479,6 @@ def filter_dataset(dataset: pd.DataFrame, filter_column: str) -> pd.DataFrame:
subset = dataset[dataset[filter_column].isin(selected_ids)]
logger.info(f'Retained {subset.shape[0]} tasks after filtering')
return subset
skip_ids = os.environ.get('SKIP_IDS', '').split(',')
if len(skip_ids) > 0:
logger.info(f'Filtering {len(skip_ids)} tasks from "SKIP_IDS"...')
return dataset[~dataset[filter_column].isin(skip_ids)]
return dataset
@@ -514,10 +501,8 @@ if __name__ == '__main__':
# NOTE: It is preferable to load datasets from huggingface datasets and perform post-processing
# so we don't need to manage file uploading to OpenHands's repo
dataset = load_dataset(args.dataset, split=args.split)
logger.info(f'Loaded dataset {args.dataset} with split {args.split}')
swe_bench_tests = filter_dataset(dataset.to_pandas(), 'instance_id')
logger.info(
f'Loaded dataset {args.dataset} with split {args.split}: {len(swe_bench_tests)} tasks'
)
llm_config = None
if args.llm_config:
@@ -546,7 +531,6 @@ if __name__ == '__main__':
)
output_file = os.path.join(metadata.eval_output_dir, 'output.jsonl')
print(f'### OUTPUT FILE: {output_file} ###')
instances = prepare_dataset(swe_bench_tests, output_file, args.eval_n_limit)
if len(instances) > 0 and not isinstance(

View File

@@ -1,69 +0,0 @@
import argparse
import gzip
import json
import os
from glob import glob
from tqdm import tqdm
tqdm.pandas()
# Load trajectories for resolved instances
def load_completions(output_dir: str, instance_id: str):
glob_path = os.path.join(output_dir, 'llm_completions', instance_id, '*.json')
files = sorted(glob(glob_path)) # this is ascending order
# pick the last file (last turn)
try:
file_path = files[-1]
except IndexError:
# print(f'No files found for instance {instance_id}: files={files}')
return None
with open(file_path, 'r') as f:
result = json.load(f)
# create messages
messages = result['messages']
messages.append(result['response']['choices'][0]['message'])
tools = result['kwargs']['tools']
return {
'messages': messages,
'tools': tools,
}
parser = argparse.ArgumentParser()
parser.add_argument('jsonl_path', type=str)
args = parser.parse_args()
output_dir = os.path.dirname(args.jsonl_path)
output_path = os.path.join(output_dir, 'output.with_completions.jsonl.gz')
# Check if output would be different from input
needs_update = False
with open(args.jsonl_path, 'r') as f_in:
for line in tqdm(f_in, desc='Checking for changes'):
data = json.loads(line)
new_completions = load_completions(output_dir, data['instance_id'])
current_completions = data.get('raw_completions')
if current_completions != new_completions:
needs_update = True
break
if not needs_update:
print('No updates required. Skipping file update.')
exit(0)
if os.path.exists(output_path):
print(f'Output file already exists at {output_path}, overwriting? (y/n)')
if input() != 'y':
print('Exiting...')
exit(0)
# Process line by line
with open(args.jsonl_path, 'r') as f_in, gzip.open(output_path, 'wt') as f_out:
for line in tqdm(f_in):
data = json.loads(line)
data['raw_completions'] = load_completions(output_dir, data['instance_id'])
f_out.write(json.dumps(data) + '\n')
print(f'Saved compressed output to {output_path}')

View File

@@ -22,8 +22,7 @@ def convert_row_to_swebench_format(row):
elif 'test_result' in row and 'git_patch' in row['test_result']:
model_patch = row['test_result']['git_patch']
else:
print(f'WARNING: Row {row} does not have a git_patch')
model_patch = ''
raise ValueError(f'Row {row} does not have a git_patch')
return {
'instance_id': row['instance_id'],

View File

@@ -3,7 +3,7 @@ import json
import os
from collections import defaultdict
from tqdm import tqdm
import pandas as pd
parser = argparse.ArgumentParser()
parser.add_argument('input_file', type=str)
@@ -11,7 +11,8 @@ args = parser.parse_args()
dirname = os.path.dirname(args.input_file)
# Initialize counters and data structures
df = pd.read_json(args.input_file, lines=True)
instance_id_to_status = defaultdict(
lambda: {
'empty_generation': False,
@@ -22,7 +23,15 @@ instance_id_to_status = defaultdict(
}
)
# Process official report if it exists
# Apply the status to the dataframe
def apply_report(row):
instance_id = row['instance_id']
if instance_id in instance_id_to_status:
return dict(instance_id_to_status[instance_id])
return row.get('report', {})
swebench_official_report_json = os.path.join(dirname, 'report.json')
openhands_remote_report_jsonl = args.input_file.replace(
'.jsonl', '.swebench_eval.jsonl'
@@ -81,159 +90,113 @@ if os.path.exists(swebench_official_report_json):
f'- [{instance_id}](./eval_outputs/{instance_id}/run_instance.log)\n'
)
df['report'] = df.apply(apply_report, axis=1)
with open(output_md_filepath, 'w') as f:
f.write(output_md)
elif os.path.exists(openhands_remote_report_jsonl):
output_md_filepath = args.input_file.replace('.jsonl', '.swebench_eval.md')
# First pass: Read eval report and count instances
instance_ids = set()
eval_instance_ids = set()
df_eval = pd.read_json(openhands_remote_report_jsonl, lines=True, orient='records')
# Count instances in original file
n_instances = 0
with open(args.input_file, 'r') as f:
for line in tqdm(f, desc='Counting instances in original file'):
data = json.loads(line)
instance_ids.add(data['instance_id'])
n_instances += 1
print(f'Total instances in original file: {n_instances}')
assert len(df['instance_id'].unique()) == len(
df
), 'There are duplicate instance ids in the original output which is not allowed'
assert len(df_eval['instance_id'].unique()) == len(
df_eval
), 'There are duplicate instance ids in the eval report which is not allowed'
# Process eval report
n_eval_instances = 0
with open(openhands_remote_report_jsonl, 'r') as f:
for line in tqdm(f, desc='Processing eval report'):
data = json.loads(line)
instance_id = data['instance_id']
eval_instance_ids.add(instance_id)
n_eval_instances += 1
instance_id_to_status[instance_id] = data['test_result']['report']
print(f'Total instances in eval report: {n_eval_instances}')
for _, row in df_eval.iterrows():
instance_id_to_status[row['instance_id']] = row['test_result']['report']
df['report'] = df.apply(apply_report, axis=1)
# Verify no duplicates
assert (
len(instance_ids) == n_instances
), 'Duplicate instance ids found in original output'
assert (
len(eval_instance_ids) == n_eval_instances
), 'Duplicate instance ids found in eval report'
report_is_dict = df['report'].apply(lambda x: isinstance(x, dict))
if not report_is_dict.all():
print(df[~report_is_dict])
raise ValueError(f'Report is not a dict, but a {type(row["report"])}')
# Initialize counters
stats = {'total': len(instance_ids), 'resolved': 0, 'empty_patch': 0, 'error': 0}
# Collect instance IDs by category
resolved_ids = []
unresolved_ids = []
error_ids = []
empty_patch_ids = []
timeout_ids = []
# Process original file and categorize instances
with open(args.input_file, 'r') as f:
for line in f:
data = json.loads(line)
instance_id = data['instance_id']
report = instance_id_to_status[instance_id]
if report.get('resolved', False):
stats['resolved'] += 1
resolved_ids.append(instance_id)
else:
unresolved_ids.append(instance_id)
if report.get('empty_generation', False):
stats['empty_patch'] += 1
empty_patch_ids.append(instance_id)
if report.get('error_eval', False):
stats['error'] += 1
error_ids.append(instance_id)
if report.get('test_timeout', False):
timeout_ids.append(instance_id)
# Generate markdown report
def _instance_id_to_log_path(instance_id):
path = f"{args.input_file.replace('.jsonl', '.swebench_eval.logs')}/instance_{instance_id}.log"
return os.path.relpath(path, start=dirname)
# ... rest of markdown generation code remains the same ...
_n_instances = len(df)
_n_resolved = len(df[df['report'].apply(lambda x: x.get('resolved', False))])
_n_unresolved = _n_instances - _n_resolved
_n_empty_patch = len(
df[df['report'].apply(lambda x: x.get('empty_generation', False))]
)
_n_error = len(df[df['report'].apply(lambda x: x.get('error_eval', False))])
output_md = (
'# SWE-bench Report\n'
'This folder contains the evaluation results of the SWE-bench using the [official evaluation docker containerization](https://github.com/princeton-nlp/SWE-bench/blob/main/docs/20240627_docker/README.md#choosing-the-right-cache_level).\n\n'
'## Summary\n'
f'- submitted instances: {stats["total"]}\n'
f'- empty patch instances: {stats["empty_patch"]}\n'
f'- resolved instances: {stats["resolved"]}\n'
f'- unresolved instances: {len(unresolved_ids)}\n'
f'- error instances: {stats["error"]}\n'
f'- submitted instances: {_n_instances}\n'
f'- empty patch instances: {_n_empty_patch}\n'
f'- resolved instances: {_n_resolved}\n'
f'- unresolved instances: {_n_unresolved}\n'
f'- error instances: {_n_error}\n'
)
def _instance_id_to_log_path(instance_id):
path = f"{args.input_file.replace('.jsonl', '.swebench_eval.logs')}/instance_{instance_id}.log"
# make it relative path
path = os.path.relpath(path, start=dirname)
return path
output_md += '\n## Resolved Instances\n'
# instance_id to status
for instance_id in resolved_ids:
for instance_id in sorted(
df[df['report'].apply(lambda x: x.get('resolved', False))][
'instance_id'
].unique()
):
instance_id_to_status[instance_id]['resolved'] = True
output_md += f'- [{instance_id}]({_instance_id_to_log_path(instance_id)})\n'
output_md += '\n## Unresolved Instances\n'
for instance_id in unresolved_ids:
for instance_id in sorted(
df[~df['report'].apply(lambda x: x.get('resolved', False))][
'instance_id'
].unique()
):
output_md += f'- [{instance_id}]({_instance_id_to_log_path(instance_id)})\n'
output_md += '\n## Error Instances\n'
for instance_id in error_ids:
for instance_id in sorted(
df[df['report'].apply(lambda x: x.get('error_eval', False))][
'instance_id'
].unique()
):
instance_id_to_status[instance_id]['error_eval'] = True
output_md += f'- [{instance_id}]({_instance_id_to_log_path(instance_id)})\n'
output_md += '\n## Empty Patch Instances\n'
for instance_id in empty_patch_ids:
for instance_id in sorted(
df[df['report'].apply(lambda x: x.get('empty_generation', False))][
'instance_id'
].unique()
):
instance_id_to_status[instance_id]['empty_generation'] = True
output_md += f'- [{instance_id}]({_instance_id_to_log_path(instance_id)})\n'
output_md += '\n## Incomplete Instances\n'
for instance_id in timeout_ids:
for instance_id in sorted(
df[df['report'].apply(lambda x: x.get('test_timeout', False))][
'instance_id'
].unique()
):
output_md += f'- [{instance_id}]({_instance_id_to_log_path(instance_id)})\n'
with open(output_md_filepath, 'w') as f:
f.write(output_md)
else:
print(
f'No report file found: Both {swebench_official_report_json} and {openhands_remote_report_jsonl} do not exist.'
)
exit()
# Before backup and update, check if any changes would be made
needs_update = False
with open(args.input_file, 'r') as infile:
for line in tqdm(infile, desc='Checking for changes'):
data = json.loads(line)
instance_id = data['instance_id']
if instance_id in instance_id_to_status:
current_report = data.get('report', {})
new_report = instance_id_to_status[instance_id]
if current_report != new_report:
needs_update = True
break
if not needs_update:
print('No updates detected. Skipping file update.')
exit()
# Backup and update the original file row by row
if os.path.exists(args.input_file + '.bak'):
conf = input('Existing backup file found. Do you want to overwrite it? (y/n)')
if conf != 'y':
exit()
os.remove(args.input_file + '.bak')
# backup the original file
os.rename(args.input_file, args.input_file + '.bak')
# Process and write file row by row
with open(args.input_file + '.bak', 'r') as infile, open(
args.input_file, 'w'
) as outfile:
for line in tqdm(infile, desc='Updating output file'):
data = json.loads(line)
instance_id = data['instance_id']
if instance_id in instance_id_to_status:
data['report'] = instance_id_to_status[instance_id]
outfile.write(json.dumps(data) + '\n')
df.to_json(args.input_file, orient='records', lines=True)

View File

@@ -108,14 +108,7 @@ if [ -z "$N_RUNS" ]; then
echo "N_RUNS not specified, use default $N_RUNS"
fi
# Skip runs if the run number is in the SKIP_RUNS list
# read from env variable SKIP_RUNS as a comma separated list of run numbers
SKIP_RUNS=(${SKIP_RUNS//,/ })
for i in $(seq 1 $N_RUNS); do
if [[ " ${SKIP_RUNS[@]} " =~ " $i " ]]; then
echo "Skipping run $i"
continue
fi
current_eval_note="$EVAL_NOTE-run_$i"
echo "EVAL_NOTE: $current_eval_note"
run_eval $current_eval_note

View File

@@ -262,7 +262,7 @@ def pre_login(
instruction = action.to_instruction()
browser_action = BrowseInteractiveAction(browser_actions=instruction)
browser_action.set_hard_timeout(10000)
browser_action.timeout = 10000
logger.info(browser_action, extra={'msg_type': 'ACTION'})
obs: BrowserOutputObservation = runtime.run_action(browser_action)
logger.debug(obs, extra={'msg_type': 'OBSERVATION'})

View File

@@ -39,7 +39,7 @@ def get_config(
run_as_openhands=False,
max_budget_per_task=4,
max_iterations=100,
save_trajectory_path=os.path.join(
trajectories_path=os.path.join(
mount_path_on_host, f'traj_{task_short_name}.json'
),
sandbox=SandboxConfig(
@@ -80,13 +80,13 @@ def load_dependencies(runtime: Runtime) -> List[str]:
def init_task_env(runtime: Runtime, hostname: str, env_llm_config: LLMConfig):
command = (
f'SERVER_HOSTNAME={hostname} '
f'LITELLM_API_KEY={env_llm_config.api_key.get_secret_value() if env_llm_config.api_key else None} '
f'LITELLM_API_KEY={env_llm_config.api_key} '
f'LITELLM_BASE_URL={env_llm_config.base_url} '
f'LITELLM_MODEL={env_llm_config.model} '
'bash /utils/init.sh'
)
action = CmdRunAction(command=command)
action.set_hard_timeout(900)
action.timeout = 900
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
@@ -165,14 +165,14 @@ def run_evaluator(
runtime: Runtime, env_llm_config: LLMConfig, trajectory_path: str, result_path: str
):
command = (
f'LITELLM_API_KEY={env_llm_config.api_key.get_secret_value() if env_llm_config.api_key else None} '
f'LITELLM_API_KEY={env_llm_config.api_key} '
f'LITELLM_BASE_URL={env_llm_config.base_url} '
f'LITELLM_MODEL={env_llm_config.model} '
f"DECRYPTION_KEY='theagentcompany is all you need' " # Hardcoded Key
f'python_default /utils/eval.py --trajectory_path {trajectory_path} --result_path {result_path}'
)
action = CmdRunAction(command=command)
action.set_hard_timeout(600)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})

View File

@@ -57,7 +57,7 @@ def get_config(
)
config.set_llm_config(metadata.llm_config)
agent_config = config.get_agent_config(metadata.agent_class)
agent_config.enable_prompt_extensions = False
agent_config.use_microagents = False
return config

View File

@@ -1,674 +0,0 @@
from collections import Counter
from copy import deepcopy
from difflib import SequenceMatcher
from io import BytesIO
from bs4 import BeautifulSoup, Comment, NavigableString, Tag
import cv2
import numpy as np
import torch
from colormath.color_conversions import convert_color
from colormath.color_diff import delta_e_cie2000
from colormath.color_objects import LabColor, sRGBColor
from PIL import Image, ImageChops, ImageColor
from scipy.optimize import linear_sum_assignment
from transformers import CLIPModel, CLIPProcessor
from openhands.core.logger import openhands_logger as logger
def calculate_similarity(block1, block2):
"""Calculate text similarity between two blocks using SequenceMatcher."""
text_similarity = SequenceMatcher(None, block1['text'], block2['text']).ratio()
return text_similarity
def adjust_cost_for_context(cost_matrix, consecutive_bonus=1.0, window_size=20):
"""Adjust cost matrix by considering context similarity."""
if window_size <= 0:
return cost_matrix
n, m = cost_matrix.shape
adjusted_cost_matrix = np.copy(cost_matrix)
for i in range(n):
for j in range(m):
if adjusted_cost_matrix[i][j] >= -0.5:
continue
nearby_matrix = cost_matrix[
max(0, i - window_size) : min(n, i + window_size + 1),
max(0, j - window_size) : min(m, j + window_size + 1),
]
flattened_array = nearby_matrix.flatten()
sorted_array = np.sort(flattened_array)[::-1]
sorted_array = np.delete(
sorted_array, np.where(sorted_array == cost_matrix[i, j])[0][0]
)
top_k_elements = sorted_array[-window_size * 2 :]
bonus = consecutive_bonus * np.sum(top_k_elements)
adjusted_cost_matrix[i][j] += bonus
return adjusted_cost_matrix
def create_cost_matrix(A, B):
"""Create cost matrix for block matching."""
n = len(A)
m = len(B)
cost_matrix = np.zeros((n, m))
for i in range(n):
for j in range(m):
cost_matrix[i, j] = -calculate_similarity(A[i], B[j])
return cost_matrix
def calculate_distance_max_1d(x1, y1, x2, y2):
"""Calculate maximum 1D distance between points."""
return max(abs(x2 - x1), abs(y2 - y1))
def calculate_ratio(h1, h2):
"""Calculate ratio between two heights."""
return max(h1, h2) / min(h1, h2)
def rgb_to_lab(rgb):
"""Convert RGB color to Lab color space."""
rgb_color = sRGBColor(rgb[0], rgb[1], rgb[2], is_upscaled=True)
lab_color = convert_color(rgb_color, LabColor)
return lab_color
def color_similarity_ciede2000(rgb1, rgb2):
"""Calculate color similarity using CIEDE2000 formula."""
lab1 = rgb_to_lab(rgb1)
lab2 = rgb_to_lab(rgb2)
delta_e = delta_e_cie2000(lab1, lab2)
similarity = max(0, 1 - (delta_e / 100))
return similarity
def merge_blocks_wo_check(block1, block2):
"""Merge two blocks without additional checks."""
merged_text = block1['text'] + ' ' + block2['text']
x_min = min(block1['bbox'][0], block2['bbox'][0])
y_min = min(block1['bbox'][1], block2['bbox'][1])
x_max = max(
block1['bbox'][0] + block1['bbox'][2], block2['bbox'][0] + block2['bbox'][2]
)
y_max = max(
block1['bbox'][1] + block1['bbox'][3], block2['bbox'][1] + block2['bbox'][3]
)
merged_bbox = (x_min, y_min, x_max - x_min, y_max - y_min)
merged_color = tuple(
(color1 + color2) // 2
for color1, color2 in zip(block1['color'], block2['color'])
)
return {'text': merged_text, 'bbox': merged_bbox, 'color': merged_color}
def find_maximum_matching(A, B, consecutive_bonus, window_size):
"""Find maximum matching between two sets of blocks."""
cost_matrix = create_cost_matrix(A, B)
cost_matrix = adjust_cost_for_context(cost_matrix, consecutive_bonus, window_size)
row_ind, col_ind = linear_sum_assignment(cost_matrix)
current_cost = cost_matrix[row_ind, col_ind].tolist()
return list(zip(row_ind, col_ind)), current_cost, cost_matrix
def remove_indices(lst, indices):
"""Remove indices from list in reverse order."""
for index in sorted(indices, reverse=True):
if index < len(lst):
lst.pop(index)
return lst
def merge_blocks_by_list(blocks, merge_list):
"""Merge blocks according to merge list."""
pop_list = []
while merge_list:
i = merge_list[0][0]
j = merge_list[0][1]
blocks[i] = merge_blocks_wo_check(blocks[i], blocks[j])
pop_list.append(j)
merge_list.pop(0)
if merge_list:
new_merge_list = []
for k in range(len(merge_list)):
if (
merge_list[k][0] != i
and merge_list[k][1] != i
and merge_list[k][0] != j
and merge_list[k][1] != j
):
new_merge_list.append(merge_list[k])
merge_list = new_merge_list
remove_indices(blocks, pop_list)
return blocks
def difference_of_means(list1, list2):
"""Calculate difference of means between two lists."""
counter1 = Counter(list1)
counter2 = Counter(list2)
for element in set(list1) & set(list2):
common_count = min(counter1[element], counter2[element])
counter1[element] -= common_count
counter2[element] -= common_count
unique_list1 = [item for item in counter1.elements()]
unique_list2 = [item for item in counter2.elements()]
mean_list1 = sum(unique_list1) / len(unique_list1) if unique_list1 else 0
mean_list2 = sum(unique_list2) / len(unique_list2) if unique_list2 else 0
if mean_list1 - mean_list2 > 0:
if min(unique_list1) > min(unique_list2):
return mean_list1 - mean_list2
return 0.0
return mean_list1 - mean_list2
def find_possible_merge(A, B, consecutive_bonus, window_size, debug=False):
"""Find possible merges between blocks."""
merge_bonus = 0.0
merge_windows = 1
def sortFn(value):
return value[2]
while True:
A_changed = False
B_changed = False
matching, current_cost, cost_matrix = find_maximum_matching(
A, B, merge_bonus, merge_windows
)
if len(A) >= 2:
merge_list = []
for i in range(len(A) - 1):
new_A = deepcopy(A)
new_A[i] = merge_blocks_wo_check(new_A[i], new_A[i + 1])
new_A.pop(i + 1)
updated_matching, updated_cost, _ = find_maximum_matching(
new_A, B, merge_bonus, merge_windows
)
diff = difference_of_means(current_cost, updated_cost)
if diff > 0.05:
merge_list.append([i, i + 1, diff])
merge_list.sort(key=sortFn, reverse=True)
if merge_list:
A_changed = True
A = merge_blocks_by_list(A, merge_list)
matching, current_cost, cost_matrix = find_maximum_matching(
A, B, merge_bonus, merge_windows
)
if len(B) >= 2:
merge_list = []
for i in range(len(B) - 1):
new_B = deepcopy(B)
new_B[i] = merge_blocks_wo_check(new_B[i], new_B[i + 1])
new_B.pop(i + 1)
updated_matching, updated_cost, _ = find_maximum_matching(
A, new_B, merge_bonus, merge_windows
)
diff = difference_of_means(current_cost, updated_cost)
if diff > 0.05:
merge_list.append([i, i + 1, diff])
merge_list.sort(key=sortFn, reverse=True)
if merge_list:
B_changed = True
B = merge_blocks_by_list(B, merge_list)
matching, current_cost, cost_matrix = find_maximum_matching(
A, B, merge_bonus, merge_windows
)
if not A_changed and not B_changed:
break
matching, _, _ = find_maximum_matching(A, B, consecutive_bonus, window_size)
return A, B, matching
def merge_blocks_by_bbox(blocks):
"""Merge blocks with same bounding box."""
merged_blocks = {}
for block in blocks:
bbox = tuple(block['bbox'])
if bbox in merged_blocks:
existing_block = merged_blocks[bbox]
existing_block['text'] += ' ' + block['text']
existing_block['color'] = [
(ec + c) / 2 for ec, c in zip(existing_block['color'], block['color'])
]
else:
merged_blocks[bbox] = block
return list(merged_blocks.values())
def mask_bounding_boxes_with_inpainting(image, bounding_boxes):
"""Mask bounding boxes in image using inpainting."""
image_cv = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
mask = np.zeros(image_cv.shape[:2], dtype=np.uint8)
height, width = image_cv.shape[:2]
for bbox in bounding_boxes:
x_ratio, y_ratio, w_ratio, h_ratio = bbox
x = int(x_ratio * width)
y = int(y_ratio * height)
w = int(w_ratio * width)
h = int(h_ratio * height)
mask[y : y + h, x : x + w] = 255
inpainted_image = cv2.inpaint(image_cv, mask, 3, cv2.INPAINT_TELEA)
return Image.fromarray(cv2.cvtColor(inpainted_image, cv2.COLOR_BGR2RGB))
def rescale_and_mask(image, blocks):
"""Rescale image and mask blocks."""
if blocks:
image = mask_bounding_boxes_with_inpainting(image, blocks)
width, height = image.size
if width < height:
new_size = (width, width)
else:
new_size = (height, height)
return image.resize(new_size, Image.LANCZOS)
def calculate_clip_similarity(image1, image2, blocks1, blocks2):
"""Calculate CLIP similarity between two images."""
model = CLIPModel.from_pretrained('openai/clip-vit-base-patch32')
processor = CLIPProcessor.from_pretrained('openai/clip-vit-base-patch32')
device = 'cuda' if torch.cuda.is_available() else 'cpu'
model = model.to(device)
# Mask and preprocess images
image1_masked = rescale_and_mask(image1, [block['bbox'] for block in blocks1])
image2_masked = rescale_and_mask(image2, [block['bbox'] for block in blocks2])
inputs = processor(
images=[image1_masked, image2_masked], return_tensors='pt', padding=True
)
inputs = {k: v.to(device) for k, v in inputs.items()}
# Calculate features and similarity
with torch.no_grad():
image_features = model.get_image_features(**inputs)
image_features1 = image_features[0].unsqueeze(0)
image_features2 = image_features[1].unsqueeze(0)
image_features1 /= image_features1.norm(dim=-1, keepdim=True)
image_features2 /= image_features2.norm(dim=-1, keepdim=True)
similarity = (image_features1 @ image_features2.T).item()
return similarity
def rgb_to_hex(rgb):
"""Convert an RGB tuple to hexadecimal format."""
return '{:02X}{:02X}{:02X}'.format(*rgb)
class ColorPool:
def __init__(self, offset=0):
color_values = list(range(10, 251, 16))
color_list = [((r + offset) % 256, (g + offset) % 256, (b + offset) % 256)
for r in color_values for g in color_values for b in color_values]
self.color_pool = [rgb_to_hex(color) for color in color_list]
def pop_color(self):
if self.color_pool:
return self.color_pool.pop()
else:
raise NotImplementedError
def process_html_str(html_str, offset=0):
"""Process HTML string to assign unique colors to text elements."""
soup = BeautifulSoup(html_str, 'html.parser')
def update_style(element, property_name, value):
important_value = f"{value} !important"
styles = element.attrs.get('style', '').split(';')
updated_styles = [s for s in styles if not s.strip().startswith(property_name) and len(s.strip()) > 0]
updated_styles.append(f"{property_name}: {important_value}")
element['style'] = '; '.join(updated_styles).strip()
# Set background color of all elements to transparent white
for element in soup.find_all(True):
update_style(element, 'background-color', 'rgba(255, 255, 255, 0.0)')
color_pool = ColorPool(offset)
text_tags = ['p', 'h1', 'h2', 'h3', 'h4', 'h5', 'h6', 'div', 'span', 'a', 'b', 'li',
'table', 'td', 'th', 'button', 'footer', 'header', 'figcaption']
for tag in soup.find_all(text_tags):
color = f"#{color_pool.pop_color()}"
update_style(tag, 'color', color)
update_style(tag, 'opacity', '1.0')
return str(soup)
def similar(n1, n2):
"""Check if two numbers are similar within a threshold."""
return abs(n1 - n2) <= 8
def find_different_pixels(image1, image2):
"""Find pixels that differ between two images."""
if image1.size != image2.size:
logger.warning("Images are not the same size")
return None
image1 = image1.convert('RGB')
image2 = image2.convert('RGB')
pixels1 = image1.load()
pixels2 = image2.load()
different_pixels = []
for x in range(image1.size[0]):
for y in range(image1.size[1]):
r1, g1, b1 = pixels1[x, y]
r2, g2, b2 = pixels2[x, y]
if similar((r1 + 50) % 256, r2) and similar((g1 + 50) % 256, g2) and similar((b1 + 50) % 256, b2):
different_pixels.append((y, x))
return np.stack(different_pixels) if different_pixels else None
def extract_text_with_color(html_str):
"""Extract text and color information from HTML string."""
def get_color(tag):
if 'style' in tag.attrs:
styles = tag['style'].split(';')
color_style = [s for s in styles if 'color' in s and 'background-color' not in s]
if color_style:
color = color_style[-1].split(':')[1].strip().replace(" !important", "")
if color[0] == "#":
return color
else:
try:
if color.startswith('rgb'):
color = tuple(map(int, color[4:-1].split(',')))
else:
color = ImageColor.getrgb(color)
return '#{:02x}{:02x}{:02x}'.format(*color)
except ValueError:
logger.warning(f"Unable to identify or convert color: {color}")
return None
return None
def extract_text_recursive(element, parent_color='#000000'):
if isinstance(element, Comment):
return None
elif isinstance(element, NavigableString):
text = element.strip()
return (text, parent_color) if text else None
elif isinstance(element, Tag):
current_color = get_color(element) or parent_color
children_texts = filter(None, [extract_text_recursive(child, current_color)
for child in element.children])
return list(children_texts)
soup = BeautifulSoup(html_str, 'html.parser')
body = soup.body
return extract_text_recursive(body) if body else []
def flatten_tree(tree):
"""Flatten a nested tree structure into a list."""
flat_list = []
def flatten(node):
if isinstance(node, list):
for item in node:
flatten(item)
else:
flat_list.append(node)
flatten(tree)
return flat_list
def get_blocks_from_image_diff_pixels(image, html_text_color_tree, different_pixels):
"""Extract text blocks from image using color differences."""
image_cv = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
x_w = image_cv.shape[0]
y_w = image_cv.shape[1]
def hex_to_bgr(hex_color):
hex_color = hex_color.lstrip('#')
rgb = tuple(int(hex_color[i:i+2], 16) for i in (0, 2, 4))
return rgb[::-1]
def get_intersect(arr1, arr2):
arr1_reshaped = arr1.view([('', arr1.dtype)] * arr1.shape[1])
arr2_reshaped = arr2.view([('', arr2.dtype)] * arr2.shape[1])
common_rows = np.intersect1d(arr1_reshaped, arr2_reshaped)
return common_rows.view(arr1.dtype).reshape(-1, arr1.shape[1])
blocks = []
for item in html_text_color_tree:
try:
color = np.array(hex_to_bgr(item[1]), dtype="uint8")
except:
continue
lower = color - 4
upper = color + 4
mask = cv2.inRange(image_cv, lower, upper)
coords = np.column_stack(np.where(mask > 0))
coords = get_intersect(coords, different_pixels)
if coords.size == 0:
continue
x_min, y_min = np.min(coords, axis=0)
x_max, y_max = np.max(coords, axis=0)
# Get average color from original image
color_coords = coords.copy()
color_coords = color_coords[color_coords[:, 0] <= x_max]
color_coords = color_coords[color_coords[:, 1] <= y_max]
colors = [image_cv[x, y] for x, y in color_coords]
avg_color = tuple(map(int, np.mean(colors, axis=0)))[::-1] # Convert BGR to RGB
blocks.append({
'text': item[0].lower(),
'bbox': (y_min / y_w, x_min / x_w, (y_max - y_min + 1) / y_w, (x_max - x_min + 1) / x_w),
'color': avg_color
})
return blocks
def get_blocks_from_html(html_str, image1):
"""Extract text blocks from HTML and image."""
# Process HTML with two different color offsets
html_str_1 = process_html_str(html_str, offset=0)
html_str_2 = process_html_str(html_str, offset=50)
# Render both HTML versions to images
# TODO: Screenshot html_str_2
filter_color = (255, 0, 0)
image2 = Image.new("RGB", image1.size, filter_color)
# Find pixels that differ between the two rendered images
different_pixels = find_different_pixels(image1, image2)
if different_pixels is None:
logger.warning("Unable to get pixels with different colors")
return []
# Extract text and color information from HTML
html_text_color_tree = flatten_tree(extract_text_with_color(html_str_1))
try:
blocks = get_blocks_from_image_diff_pixels(image1, html_text_color_tree, different_pixels)
except Exception as e:
logger.warning(f"Unable to get blocks: {e}")
return []
return blocks
def evaluate(task, generated_img):
"""Evaluate generated image against reference image using multiple metrics."""
# Load reference image
post_image = task['post_image']
# Extract blocks from HTML and images
post_blocks = get_blocks_from_html(task['post_html'], post_image)
gen_blocks = get_blocks_from_html(task['gen_html'], generated_img)
print("block details", post_blocks, gen_blocks)
if not post_blocks or not gen_blocks:
# Fallback to basic CLIP and pixel comparison if no blocks available
clip_score = calculate_clip_similarity(post_image, generated_img, [], [])
logger.info(f'CLIP similarity score: {clip_score}')
# Pixel comparison
diff = ImageChops.difference(generated_img, post_image)
pixel_match = not diff.getbbox()
logger.info(
f"Pixel difference analysis: {'No difference' if pixel_match else 'Differences found'}"
)
return clip_score > 0.95 or pixel_match
# Merge blocks with same bounding boxes
post_blocks = merge_blocks_by_bbox(post_blocks)
gen_blocks = merge_blocks_by_bbox(gen_blocks)
# Find optimal block matching
consecutive_bonus, window_size = 0.1, 1
gen_blocks_m, post_blocks_m, matching = find_possible_merge(
gen_blocks, deepcopy(post_blocks), consecutive_bonus, window_size
)
# Filter matches with low similarity
filtered_matching = []
for i, j in matching:
text_similarity = calculate_similarity(gen_blocks_m[i], post_blocks_m[j])
if text_similarity >= 0.5:
filtered_matching.append([i, j, text_similarity])
matching = filtered_matching
if not matching:
logger.warning('No matching blocks found')
clip_score = calculate_clip_similarity(
post_image, generated_img, gen_blocks, post_blocks
)
return clip_score > 0.95
# Calculate metrics for matched blocks
indices1 = [item[0] for item in matching]
indices2 = [item[1] for item in matching]
# Calculate unmatched areas
unmatched_area_1 = sum(
block['bbox'][2] * block['bbox'][3]
for i, block in enumerate(gen_blocks_m)
if i not in indices1
)
unmatched_area_2 = sum(
block['bbox'][2] * block['bbox'][3]
for j, block in enumerate(post_blocks_m)
if j not in indices2
)
total_unmatched_area = unmatched_area_1 + unmatched_area_2
# Calculate metrics for matched blocks
matched_areas = []
text_scores = []
position_scores = []
color_scores = []
for i, j, text_similarity in matching:
# Area
block_area = (
gen_blocks_m[i]['bbox'][2] * gen_blocks_m[i]['bbox'][3]
+ post_blocks_m[j]['bbox'][2] * post_blocks_m[j]['bbox'][3]
)
matched_areas.append(block_area)
# Position similarity
position_similarity = 1 - calculate_distance_max_1d(
gen_blocks_m[i]['bbox'][0] + gen_blocks_m[i]['bbox'][2] / 2,
gen_blocks_m[i]['bbox'][1] + gen_blocks_m[i]['bbox'][3] / 2,
post_blocks_m[j]['bbox'][0] + post_blocks_m[j]['bbox'][2] / 2,
post_blocks_m[j]['bbox'][1] + post_blocks_m[j]['bbox'][3] / 2,
)
# Color similarity
color_similarity = color_similarity_ciede2000(
gen_blocks_m[i]['color'], post_blocks_m[j]['color']
)
text_scores.append(text_similarity)
position_scores.append(position_similarity)
color_scores.append(color_similarity)
# Calculate final scores
total_area = sum(matched_areas) + total_unmatched_area
size_score = sum(matched_areas) / total_area if total_area > 0 else 0
text_score = np.mean(text_scores) if text_scores else 0
position_score = np.mean(position_scores) if position_scores else 0
color_score = np.mean(color_scores) if color_scores else 0
clip_score = calculate_clip_similarity(
post_image, generated_img, gen_blocks, post_blocks
)
# Combine scores with equal weights
final_score = 0.2 * (
size_score + text_score + position_score + color_score + clip_score
)
logger.info('Evaluation scores:')
logger.info(f'- Size score: {size_score:.3f}')
logger.info(f'- Text score: {text_score:.3f}')
logger.info(f'- Position score: {position_score:.3f}')
logger.info(f'- Color score: {color_score:.3f}')
logger.info(f'- CLIP score: {clip_score:.3f}')
logger.info(f'- Final score: {final_score:.3f}')
return final_score > 0.8 # Consider it a match if final score > 80%
def png_to_bytes(png):
buffer = BytesIO()
png.save(buffer, format='PNG')
image_bytes = buffer.getvalue()
return image_bytes
def bytes_to_image(image_bytes):
"""Convert bytes to a Pillow Image object."""
return Image.open(BytesIO(image_bytes))
if __name__ == '__main__':
first_image = Image.open('./evaluation/visualcodebench/data/1/post.png')
image = Image.open('./evaluation/visualcodebench/data/1/prev.png')
html_file = open('./evaluation/visualcodebench/data/1/post/index.html', 'r')
first_html = html_file.read()
html_file.close()
html_file = open('./evaluation/visualcodebench/data/1/prev/index.html', 'r')
gen_html = html_file.read()
html_file.close()
sample = {'post_image': first_image, "post_html": first_html, "gen_html": gen_html}
evaluate(sample, image)

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@@ -1,97 +0,0 @@
import base64
import os
from io import BytesIO
import pandas as pd
from huggingface_hub import snapshot_download
from PIL import PngImagePlugin
from tqdm import tqdm
from openhands.core.logger import openhands_logger as logger
REPO_DOWNLOAD_DIR = (
'./evaluation/visualcodebench/' # Directory to store the downloaded repository
)
def download_repository():
"""
Download the entire repository from Hugging Face Hub.
This function clones the repository into REPO_DOWNLOAD_DIR.
"""
repo_id = 'rvmalhot/VisualCodeBench'
try:
logger.info(f"Downloading repository '{repo_id}'...")
snapshot_download(
repo_id=repo_id,
local_dir=REPO_DOWNLOAD_DIR,
repo_type='dataset',
ignore_patterns=None, # Download all files
)
logger.info(f"Repository downloaded to '{REPO_DOWNLOAD_DIR}'.")
except Exception as e:
logger.error(f"Error downloading repository '{repo_id}': {e}")
raise e
def format_task_dict(example):
instance_id = example['id']
prev_remote_path = os.path.join(REPO_DOWNLOAD_DIR, f'data/{instance_id}/prev')
post_remote_path = os.path.join(REPO_DOWNLOAD_DIR, f'data/{instance_id}/post')
# Check if 'prev' and 'post' directories exist
prev_exists = os.path.exists(prev_remote_path)
post_exists = os.path.exists(post_remote_path)
if prev_exists and post_exists:
skip = False
else:
skip = True
task = {
'instance_id': instance_id,
'prev_image': example['prev_image'],
'post_image': example['post_image'],
'changes': example['changes'],
'prev_code_files': example['prev_code_files'],
'post_code_files': example['post_code_files'],
'skip': skip,
}
return task
def prepare_visualcodebench(dataset):
logger.info('Processing dataset')
dataset_processed = []
for example in tqdm(dataset['train']):
formatted_example = format_task_dict(example)
if formatted_example['skip']:
continue
del formatted_example['skip']
dataset_processed.append(formatted_example)
return pd.DataFrame(dataset_processed)
def pil_image_to_base64(image: PngImagePlugin.PngImageFile) -> str:
"""
Converts a PIL image to a Base64-encoded string.
Parameters:
- image (PngImagePlugin.PngImageFile): The PIL image to convert.
Returns:
- str: The Base64-encoded string of the image.
"""
if not isinstance(image, PngImagePlugin.PngImageFile):
raise ValueError(
'The provided image is not a PIL.PngImagePlugin.PngImageFile instance.'
)
buffered = BytesIO()
image.save(buffered, format='PNG')
img_bytes = buffered.getvalue()
img_base64 = base64.b64encode(img_bytes).decode('utf-8')
base64_with_prefix = f'data:image/png;base64,{img_base64}'
return [base64_with_prefix]

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@@ -1,247 +0,0 @@
# FILE: run_infer.py
import asyncio
import os
import shutil
import tempfile
from functools import partial
import pandas as pd
from datasets import load_dataset
# from evaluation.benchmarks.visualcodebench.eval import capture_screenshot
from evaluation.benchmarks.visualcodebench.prepare import (
REPO_DOWNLOAD_DIR,
download_repository,
pil_image_to_base64,
prepare_visualcodebench,
)
from evaluation.utils.shared import (
EvalMetadata,
assert_and_raise,
codeact_user_response,
make_metadata,
prepare_dataset,
reset_logger_for_multiprocessing,
run_evaluation,
)
from openhands.controller.state.state import State
from openhands.core.config import (
AppConfig,
SandboxConfig,
get_llm_config_arg,
)
from openhands.core.config.utils import parse_arguments
from openhands.core.logger import openhands_logger as logger # Import OpenHands logger
from openhands.core.main import create_runtime, run_controller
from openhands.events.action.commands import CmdRunAction
from openhands.events.action.message import MessageAction
from openhands.events.observation.commands import CmdOutputObservation
from openhands.runtime.base import Runtime
from openhands.utils.async_utils import call_async_from_sync
# Define workspace and output directories
WORKSPACE_DIR = './workspace'
FAKE_RESPONSES = {
'CodeActAgent': partial(codeact_user_response, encapsulate_solution=True),
}
def get_config(
metadata: EvalMetadata,
) -> AppConfig:
config = AppConfig(
default_agent=metadata.agent_class,
run_as_openhands=False,
runtime='eventstream',
max_iterations=metadata.max_iterations,
sandbox=SandboxConfig(
base_container_image='python:3.12-bookworm',
enable_auto_lint=True,
use_host_network=False,
),
# do not mount workspace
workspace_base=None,
workspace_mount_path=None,
)
config.set_llm_config(metadata.llm_config)
return config
def initialize_runtime(
runtime: Runtime,
instance: pd.Series, # this argument is not required
):
"""Initialize the runtime for the agent.
This function is called before the runtime is used to run the agent.
"""
logger.info('-' * 30)
logger.info('BEGIN Runtime Initialization Fn')
logger.info('-' * 30)
workspace_dir_name = instance['instance_id']
obs: CmdOutputObservation
action = CmdRunAction(command='mkdir -p /workspace/{workspace_dir_name}')
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
assert_and_raise(
obs.exit_code == 0,
f'Failed to create /workspace/{workspace_dir_name}: {str(obs)}',
)
file_path = REPO_DOWNLOAD_DIR + f'data/{workspace_dir_name}/prev/index.html'
runtime.copy_to(file_path, f'/workspace/{workspace_dir_name}')
logger.info(f'Copied code file for instance {workspace_dir_name}')
action = CmdRunAction(command=f'cd /workspace/{workspace_dir_name}')
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
assert_and_raise(
obs.exit_code == 0,
f'Failed to cd to /workspace/{workspace_dir_name}: {str(obs)}',
)
logger.info('-' * 30)
logger.info('END Runtime Initialization Fn')
logger.info('-' * 30)
def complete_runtime(
runtime: Runtime,
instance: pd.Series, # this argument is not required, but it is used to get the workspace_dir_name
) -> str:
# TODO: extract edited HTML file from agent workspace
# temp_zip = runtime.copy_from(f'/workspace/{instance.instance_id}')
# file_name = f'/workspace/{instance.instance_id}/index.html'
# with zipfile.ZipFile(temp_zip, 'r') as zip_ref:
# if file_name in zip_ref.namelist():
# with zip_ref.open(file_name) as file:
# file_content = file.read().decode('utf-8') # Decode bytes to string
# else:
# raise FileNotFoundError(f"'{file_name}' not found in the ZIP archive.")
with tempfile.TemporaryDirectory() as tmpdir:
src_folder = REPO_DOWNLOAD_DIR + f'data/{instance.instance_id}/post/'
shutil.copytree(src_folder, tmpdir, dirs_exist_ok=True)
# image = capture_screenshot(tmpdir)
# if image is not None:
# shutil.copy(os.path.join(tmpdir, 'final_screenshot.png'), REPO_DOWNLOAD_DIR)
def process_instance(
instance: pd.Series, metadata: EvalMetadata, reset_logger: bool = True
):
config = get_config(metadata)
# Setup the logger properly, so you can run multi-processing to parallelize the evaluation
if reset_logger:
log_dir = os.path.join(metadata.eval_output_dir, 'infer_logs')
reset_logger_for_multiprocessing(logger, instance.instance_id, log_dir)
else:
logger.info(f'Starting evaluation for instance {instance.instance_id}.')
# =============================================
# build instruction
# =============================================
# Prepare instruction
instruction = (
f"Modify the HTML/CSS according to the following instruction:\n\n"
f"{instance['changes']}\n\n"
)
instruction += (
'IMPORTANT: You should ONLY interact with the environment provided '
'to you AND NEVER ASK FOR HUMAN HELP.\n'
)
# =============================================
# create sandbox and run the agent
# =============================================
runtime: Runtime = create_runtime(config)
call_async_from_sync(runtime.connect)
try:
initialize_runtime(runtime, instance=instance)
image_urls = pil_image_to_base64(instance['prev_image'])
action = MessageAction(content=instruction, image_urls=image_urls)
state: State | None = asyncio.run(
run_controller(
config=config,
initial_user_action=action,
runtime=runtime,
fake_user_response_fn=FAKE_RESPONSES[metadata.agent_class],
)
)
if state is None:
raise ValueError('State should not be None.')
# =============================================
# result evaluation
# =============================================
return_val = complete_runtime(runtime, instance)
logger.info(f'Return value {return_val}')
finally:
runtime.close()
# TODO: return EVAL output
def main():
"""Main function to run the evaluation."""
# args = parse_args()
args = parse_arguments()
logger.info(f"\n{'='*80}\nStarting VisualCodeBench Evaluation\n{'='*80}")
logger.info(f'Agent: {args.agent_cls}')
logger.info(f'Model: {args.llm_config}')
logger.info(f'Max iterations: {args.max_iterations}')
logger.info(f'Eval limit: {args.eval_n_limit}')
logger.info(f'Num workers: {args.eval_num_workers}\n')
logger.info(f'Eval output: {args.eval_output_dir}\n')
# Step 1: Download the entire repository once
logger.info('Downloading repository...')
download_repository()
# Step 2: Load Dataset
logger.info('Loading dataset...')
dataset = load_dataset(REPO_DOWNLOAD_DIR)
# Step 3: Prepare dataset
llm_config = get_llm_config_arg(args.llm_config)
if llm_config is None:
logger.error(f'Could not find LLM config: {args.llm_config}')
raise ValueError(f'Could not find LLM config: {args.llm_config}')
metadata = make_metadata(
llm_config,
'VisualCodeBench',
args.agent_cls,
args.max_iterations,
args.eval_note,
'evaluation/output/',
)
output_file = os.path.join(metadata.eval_output_dir, 'output.jsonl')
dataset = prepare_visualcodebench(dataset)
instances = prepare_dataset(dataset, output_file, eval_n_limit=args.eval_n_limit)
# Step 4: Run eval
run_evaluation(
instances, metadata, output_file, args.eval_num_workers, process_instance
)
if __name__ == '__main__':
main()

View File

@@ -1,46 +0,0 @@
#!/bin/bash
set -eo pipefail
source "evaluation/utils/version_control.sh"
# Check if required arguments are provided
if [ "$#" -lt 4 ]; then
echo "Usage: $0 [model_config] [commit_hash] [agent_cls] [eval_limit] [num_workers]"
echo "Example: $0 llm.eval_gpt_4o_mini HEAD CodeActAgent 5 1"
exit 1
fi
MODEL_CONFIG=$1
COMMIT_HASH=$2
AGENT_CLS=$3
EVAL_LIMIT=$4
NUM_WORKERS=${5:-1} # Default to 1 worker if not specified
# Checkout the specified commit
checkout_eval_branch
if [ -z "$AGENT" ]; then
echo "Agent not specified, use default CodeActAgent"
AGENT="CodeActAgent"
fi
get_openhands_version
echo "AGENT: $AGENT"
echo "OPENHANDS_VERSION: $OPENHANDS_VERSION"
echo "MODEL_CONFIG: $MODEL_CONFIG"
COMMAND="export PYTHONPATH=evaluation/benchmarks/visualcodebench:\$PYTHONPATH && poetry run python evaluation/benchmarks/visualcodebench/run_infer.py \
--agent-cls $AGENT \
--llm-config $MODEL_CONFIG \
--max-iterations 5 \
--eval-num-workers $NUM_WORKERS \
--eval-note $OPENHANDS_VERSION" \
if [ -n "$EVAL_LIMIT" ]; then
echo "EVAL_LIMIT: $EVAL_LIMIT"
COMMAND="$COMMAND --eval-n-limit $EVAL_LIMIT"
fi
# Run the command
eval $COMMAND

View File

@@ -1,167 +0,0 @@
import http
import os
import socket
import socketserver
import threading
import time
from io import BytesIO
import requests
from PIL import Image, ImageChops
from playwright.sync_api import sync_playwright
from openhands.core.logger import openhands_logger as logger
def get_free_port():
"""Find a free port to run the HTTP server."""
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
s.bind(('', 0))
return s.getsockname()[1]
def start_http_server(tmpdir):
port = get_free_port()
class CustomHTTPRequestHandler(http.server.SimpleHTTPRequestHandler):
def translate_path(self, path):
# Serve files from the specified directory instead of the current working directory
path = super().translate_path(path)
relative_path = os.path.relpath(path, os.getcwd())
return os.path.join(tmpdir, relative_path)
handler = CustomHTTPRequestHandler
server = socketserver.TCPServer(('', port), handler)
return server, port
def capture_screenshot(tmpdir):
server, port = start_http_server(tmpdir)
server_thread = threading.Thread(target=server.serve_forever)
server_thread.daemon = True
server_thread.start()
time.sleep(10)
image = None
try:
server_url = f'http://localhost:{port}/'
if not is_server_reachable(server_url):
raise RuntimeError(f'Server not reachable at {server_url}')
screenshot_path = os.path.join(tmpdir, 'final_screenshot.png')
capture_screenshot_playwright(server_url, screenshot_path)
image = Image.open(screenshot_path)
image.load()
finally:
# Shut down the server and clean up
server.shutdown()
server.server_close()
return image
def is_server_reachable(url):
"""
Check if the local server is reachable.
"""
try:
response = requests.get(url, timeout=5) # Set a 5-second timeout
if response.status_code == 200:
logger.info(f'Server is reachable at {url}')
return True
else:
logger.warning(
f'Server responded with status code {response.status_code} at {url}'
)
return False
except requests.ConnectionError as e:
logger.error(f'Failed to connect to server at {url}: {e}')
return False
def capture_screenshot_playwright(url, screenshot_path):
"""Capture a screenshot of the given URL using Playwright."""
try:
with sync_playwright() as p:
logger.info('Launching browser...')
browser = p.chromium.launch(timeout=10000) # 10 seconds for browser launch
logger.info('Creating a new page...')
page = browser.new_page()
logger.info(f'Navigating to URL: {url}')
try:
page.goto(url, timeout=60 * 1000) # Set timeout to 5 seconds
logger.info('Page navigation completed.')
except Exception as e:
logger.warning(f'Page navigation timed out. {e}. Continuing...')
logger.info('Waiting for network to be idle...')
try:
page.wait_for_load_state(
'networkidle', timeout=60 * 1000
) # Set timeout to 5 seconds
logger.info('Page load state reached.')
except Exception as e:
logger.warning(f'Page load state timed out. {e}. Continuing...')
logger.info('Capturing screenshot...')
page.screenshot(
path=screenshot_path, full_page=True
) # Capture full page screenshot
logger.info(f'Screenshot saved to {screenshot_path}')
browser.close()
return True
except Exception as e:
logger.error(f'Error capturing screenshot with Playwright: {e}')
return False
def evaluate(task, screenshot_path):
"""Compare generated screenshot with post_image using CLIP score."""
try:
import torch
from transformers import CLIPModel, CLIPProcessor
# Load CLIP model and processor
model = CLIPModel.from_pretrained('openai/clip-vit-base-patch32')
processor = CLIPProcessor.from_pretrained('openai/clip-vit-base-patch32')
# Load images
post_image = Image.open(BytesIO(task['post_image']))
generated_img = Image.open(screenshot_path)
# Process images
inputs = processor(
images=[post_image, generated_img], return_tensors='pt', padding=True
)
# Get image features
image_features = model.get_image_features(**inputs)
# Calculate cosine similarity
similarity = torch.nn.functional.cosine_similarity(
image_features[0].unsqueeze(0), image_features[1].unsqueeze(0)
).item()
logger.info(f'CLIP similarity score: {similarity}')
return similarity > 0.95 # Consider it a match if similarity > 95%
except Exception as e:
logger.error(f'Error in CLIP evaluation: {e}')
# Fallback to pixel comparison if CLIP fails
try:
post_image = Image.open(BytesIO(task['post_image']))
generated_img = Image.open(screenshot_path)
# Compare images directly without converting to bytes
diff = ImageChops.difference(generated_img, post_image)
logger.info(
f"Pixel difference analysis: {'No difference' if not diff.getbbox() else 'Differences found'}"
)
return not diff.getbbox()
except Exception as ex:
logger.error(f'Error in fallback evaluation: {ex}')
return False

View File

@@ -1,50 +0,0 @@
# VisualWebArena Evaluation with OpenHands Browsing Agents
This folder contains evaluation for [VisualWebArena](https://github.com/web-arena-x/visualwebarena) benchmark, powered by [BrowserGym](https://github.com/ServiceNow/BrowserGym) for easy evaluation of how well an agent capable of browsing can perform on realistic web browsing tasks.
## Setup Environment and LLM Configuration
Please follow instruction [here](../../README.md#setup) to setup your local development environment and LLM.
## Setup VisualWebArena Environment
VisualWebArena requires you to set up websites containing pre-populated content that is accessible via URL to the machine running the OpenHands agents.
Follow [this document](https://github.com/web-arena-x/visualwebarena/blob/main/environment_docker/README.md) to set up your own VisualWebArena environment through local servers or AWS EC2 instances.
Take note of the base URL (`$VISUALWEBARENA_BASE_URL`) of the machine where the environment is installed.
## Test if your environment works
Access with browser the above VisualWebArena website URLs and see if they load correctly.
If you cannot access the website, make sure the firewall allows public access of the aforementioned ports on your server
Check the network security policy if you are using an AWS machine.
Follow the VisualWebArena environment setup guide carefully, and make sure the URL fields are populated with the correct base URL of your server.
## Run Evaluation
```bash
export VISUALWEBARENA_BASE_URL=<YOUR_SERVER_URL_HERE>
export OPENAI_API_KEY="yourkey" # this OpenAI API key is required for some visualWebArena validators that utilize LLMs
export OPENAI_BASE_URL="https://api.openai.com/v1/" # base URL for OpenAI model used for VisualWebArena evaluation
bash evaluation/benchmarks/visualwebarena/scripts/run_infer.sh llm.claude HEAD VisualBrowsingAgent
```
Results will be in `evaluation/evaluation_outputs/outputs/visualwebarena/`
To calculate the success rate, run:
```sh
poetry run python evaluation/benchmarks/visualwebarena/get_success_rate.py evaluation/evaluation_outputs/outputs/visualwebarena/SOME_AGENT/EXP_NAME/output.jsonl
```
## Submit your evaluation results
You can start your own fork of [our huggingface evaluation outputs](https://huggingface.co/spaces/OpenHands/evaluation) and submit a PR of your evaluation results following the guide [here](https://huggingface.co/docs/hub/en/repositories-pull-requests-discussions#pull-requests-and-discussions).
## VisualBrowsingAgent V1.0 result
Tested on VisualBrowsingAgent V1.0
VisualWebArena, 910 tasks (high cost, single run due to fixed task), max step 15. Resolve rates are:
- GPT4o: 26.15%
- Claude-3.5 Sonnet: 25.27%

View File

@@ -1,40 +0,0 @@
import argparse
import json
import browsergym.visualwebarena # noqa F401 register visualwebarena tasks as gym environments
import gymnasium as gym
parser = argparse.ArgumentParser(description='Calculate average reward.')
parser.add_argument('output_path', type=str, help='path to output.jsonl')
args = parser.parse_args()
if __name__ == '__main__':
env_ids = [
id
for id in gym.envs.registry.keys()
if id.startswith('browsergym/visualwebarena')
]
total_num = len(env_ids)
print('Total number of tasks: ', total_num)
total_reward = 0
total_cost = 0
actual_num = 0
with open(args.output_path, 'r') as f:
for line in f:
data = json.loads(line)
actual_num += 1
total_cost += data['metrics']['accumulated_cost']
reward = data['test_result']['reward']
if reward >= 0:
total_reward += data['test_result']['reward']
else:
actual_num -= 1
avg_reward = total_reward / total_num
print('Total reward: ', total_reward)
print('Success Rate: ', avg_reward)
avg_cost = total_cost / actual_num
print('Avg Cost: ', avg_cost)
print('Total Cost: ', total_cost)
print('Actual number of tasks finished: ', actual_num)

View File

@@ -1,254 +0,0 @@
import asyncio
import json
import os
from typing import Any
import browsergym.visualwebarena # noqa F401 register visualwebarena tasks as gym environments
import gymnasium as gym
import pandas as pd
from evaluation.utils.shared import (
EvalMetadata,
EvalOutput,
compatibility_for_eval_history_pairs,
make_metadata,
prepare_dataset,
reset_logger_for_multiprocessing,
run_evaluation,
update_llm_config_for_completions_logging,
)
from openhands.controller.state.state import State
from openhands.core.config import (
AppConfig,
SandboxConfig,
get_llm_config_arg,
parse_arguments,
)
from openhands.core.logger import openhands_logger as logger
from openhands.core.main import create_runtime, run_controller
from openhands.events.action import (
BrowseInteractiveAction,
CmdRunAction,
MessageAction,
)
from openhands.events.observation import CmdOutputObservation
from openhands.runtime.base import Runtime
from openhands.runtime.browser.browser_env import (
BROWSER_EVAL_GET_GOAL_ACTION,
BROWSER_EVAL_GET_REWARDS_ACTION,
)
from openhands.utils.async_utils import call_async_from_sync
SUPPORTED_AGENT_CLS = {'VisualBrowsingAgent'}
AGENT_CLS_TO_FAKE_USER_RESPONSE_FN = {
'VisualBrowsingAgent': 'Continue the task. IMPORTANT: do not talk to the user until you have finished the task',
}
def get_config(
metadata: EvalMetadata,
env_id: str,
) -> AppConfig:
base_url = os.environ.get('VISUALWEBARENA_BASE_URL', None)
openai_api_key = os.environ.get('OPENAI_API_KEY', None)
openai_base_url = os.environ.get('OPENAI_BASE_URL', None)
assert base_url is not None, 'VISUALWEBARENA_BASE_URL must be set'
assert openai_api_key is not None, 'OPENAI_API_KEY must be set'
assert openai_base_url is not None, 'OPENAI_BASE_URL must be set'
config = AppConfig(
default_agent=metadata.agent_class,
run_as_openhands=False,
runtime='docker',
max_iterations=metadata.max_iterations,
sandbox=SandboxConfig(
base_container_image='python:3.12-bookworm',
enable_auto_lint=True,
use_host_network=False,
browsergym_eval_env=env_id,
runtime_startup_env_vars={
'BASE_URL': base_url,
'OPENAI_API_KEY': openai_api_key,
'OPENAI_BASE_URL': openai_base_url,
'VWA_CLASSIFIEDS': f'{base_url}:9980',
'VWA_CLASSIFIEDS_RESET_TOKEN': '4b61655535e7ed388f0d40a93600254c',
'VWA_SHOPPING': f'{base_url}:7770',
'VWA_SHOPPING_ADMIN': f'{base_url}:7780/admin',
'VWA_REDDIT': f'{base_url}:9999',
'VWA_GITLAB': f'{base_url}:8023',
'VWA_WIKIPEDIA': f'{base_url}:8888',
'VWA_HOMEPAGE': f'{base_url}:4399',
},
timeout=300,
),
# do not mount workspace
workspace_base=None,
workspace_mount_path=None,
attach_to_existing=True,
)
config.set_llm_config(
update_llm_config_for_completions_logging(
metadata.llm_config,
metadata.eval_output_dir,
env_id,
)
)
return config
def initialize_runtime(
runtime: Runtime,
) -> tuple[str, list]:
"""Initialize the runtime for the agent.
This function is called before the runtime is used to run the agent.
"""
logger.info(f"{'-' * 50} BEGIN Runtime Initialization Fn {'-' * 50}")
obs: CmdOutputObservation
# Set instance id
action = CmdRunAction(command='mkdir -p /workspace')
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
assert obs.exit_code == 0
action = BrowseInteractiveAction(browser_actions=BROWSER_EVAL_GET_GOAL_ACTION)
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
goal = obs.content
goal_image_urls = []
if hasattr(obs, 'goal_image_urls'):
goal_image_urls = obs.goal_image_urls
logger.info(f"{'-' * 50} END Runtime Initialization Fn {'-' * 50}")
return goal, goal_image_urls
def complete_runtime(
runtime: Runtime,
) -> dict[str, Any]:
"""Complete the runtime for the agent.
This function is called before the runtime is used to run the agent.
If you need to do something in the sandbox to get the correctness metric after
the agent has run, modify this function.
"""
logger.info(f"{'-' * 50} BEGIN Runtime Completion Fn {'-' * 50}")
obs: CmdOutputObservation
action = BrowseInteractiveAction(browser_actions=BROWSER_EVAL_GET_REWARDS_ACTION)
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
logger.info(f"{'-' * 50} END Runtime Completion Fn {'-' * 50}")
return {
'rewards': json.loads(obs.content),
}
def process_instance(
instance: pd.Series,
metadata: EvalMetadata,
reset_logger: bool = True,
):
env_id = instance.instance_id
config = get_config(metadata, env_id)
# Setup the logger properly, so you can run multi-processing to parallelize the evaluation
if reset_logger:
log_dir = os.path.join(metadata.eval_output_dir, 'infer_logs')
reset_logger_for_multiprocessing(logger, env_id, log_dir)
else:
logger.info(f'Starting evaluation for instance {env_id}.')
runtime = create_runtime(config)
call_async_from_sync(runtime.connect)
task_str, goal_image_urls = initialize_runtime(runtime)
initial_user_action = MessageAction(content=task_str, image_urls=goal_image_urls)
state: State | None = asyncio.run(
run_controller(
config=config,
initial_user_action=initial_user_action,
runtime=runtime,
)
)
# ======= Attempt to evaluate the agent's environment impact =======
# If you are working on some simpler benchmark that only evaluates the final model output (e.g., in a MessageAction)
# You can simply get the LAST `MessageAction` from the returned `state.history` and parse it for evaluation.
if state is None:
raise ValueError('State should not be None.')
metrics = state.metrics.get() if state.metrics else None
# Instruction obtained from the first message from the USER
instruction = ''
for event in state.history:
if isinstance(event, MessageAction):
instruction = event.content
break
try:
return_val = complete_runtime(runtime)
logger.info(f'Return value from complete_runtime: {return_val}')
reward = max(return_val['rewards'])
except Exception:
reward = -1.0 # kept -1 to identify instances for which evaluation failed.
# history is now available as a stream of events, rather than list of pairs of (Action, Observation)
# for compatibility with the existing output format, we can remake the pairs here
# remove when it becomes unnecessary
histories = compatibility_for_eval_history_pairs(state.history)
# Save the output
output = EvalOutput(
instance_id=env_id,
instruction=instruction,
metadata=metadata,
history=histories,
metrics=metrics,
error=state.last_error if state and state.last_error else None,
test_result={
'reward': reward,
},
)
runtime.close()
return output
if __name__ == '__main__':
args = parse_arguments()
dataset = pd.DataFrame(
{
'instance_id': [
id
for id in gym.envs.registry.keys()
if id.startswith('browsergym/visualwebarena')
]
}
)
llm_config = None
if args.llm_config:
llm_config = get_llm_config_arg(args.llm_config)
if llm_config is None:
raise ValueError(f'Could not find LLM config: --llm_config {args.llm_config}')
metadata = make_metadata(
llm_config,
'visualwebarena',
args.agent_cls,
args.max_iterations,
args.eval_note,
args.eval_output_dir,
)
output_file = os.path.join(metadata.eval_output_dir, 'output.jsonl')
instances = prepare_dataset(dataset, output_file, args.eval_n_limit)
run_evaluation(
instances,
metadata,
output_file,
args.eval_num_workers,
process_instance,
)

View File

@@ -1,48 +0,0 @@
#!/bin/bash
set -eo pipefail
source "evaluation/utils/version_control.sh"
# configure browsing agent
export USE_NAV="true"
export USE_CONCISE_ANSWER="true"
MODEL_CONFIG=$1
COMMIT_HASH=$2
AGENT=$3
EVAL_LIMIT=$4
NUM_WORKERS=$5
if [ -z "$NUM_WORKERS" ]; then
NUM_WORKERS=1
echo "Number of workers not specified, use default $NUM_WORKERS"
fi
checkout_eval_branch
if [ -z "$AGENT" ]; then
echo "Agent not specified, use default VisualBrowsingAgent"
AGENT="VisualBrowsingAgent"
fi
get_openhands_version
echo "AGENT: $AGENT"
echo "AGENT_VERSION: $OPENHANDS_VERSION"
echo "MODEL_CONFIG: $MODEL_CONFIG"
EVAL_NOTE="${OPENHANDS_VERSION}"
COMMAND="poetry run python evaluation/benchmarks/visualwebarena/run_infer.py \
--agent-cls $AGENT \
--llm-config $MODEL_CONFIG \
--max-iterations 15 \
--eval-num-workers $NUM_WORKERS \
--eval-note $EVAL_NOTE"
if [ -n "$EVAL_LIMIT" ]; then
echo "EVAL_LIMIT: $EVAL_LIMIT"
COMMAND="$COMMAND --eval-n-limit $EVAL_LIMIT"
fi
# Run the command
eval $COMMAND

View File

@@ -78,7 +78,7 @@ def get_config(
)
config.set_llm_config(metadata.llm_config)
agent_config = config.get_agent_config(metadata.agent_class)
agent_config.enable_prompt_extensions = False
agent_config.use_microagents = False
return config

View File

@@ -8,15 +8,13 @@ from evaluation.integration_tests.tests.base import BaseIntegrationTest, TestRes
from evaluation.utils.shared import (
EvalMetadata,
EvalOutput,
codeact_user_response,
make_metadata,
prepare_dataset,
reset_logger_for_multiprocessing,
run_evaluation,
update_llm_config_for_completions_logging,
)
from evaluation.utils.shared import (
codeact_user_response as fake_user_response,
)
from openhands.controller.state.state import State
from openhands.core.config import (
AgentConfig,
@@ -33,9 +31,7 @@ from openhands.runtime.base import Runtime
from openhands.utils.async_utils import call_async_from_sync
FAKE_RESPONSES = {
'CodeActAgent': fake_user_response,
'DelegatorAgent': fake_user_response,
'VisualBrowsingAgent': fake_user_response,
'CodeActAgent': codeact_user_response,
}
@@ -223,7 +219,7 @@ if __name__ == '__main__':
df = pd.read_json(output_file, lines=True, orient='records')
# record success and reason
# record success and reason for failure for the final report
df['success'] = df['test_result'].apply(lambda x: x['success'])
df['reason'] = df['test_result'].apply(lambda x: x['reason'])
logger.info('-' * 100)
@@ -238,27 +234,15 @@ if __name__ == '__main__':
logger.info('-' * 100)
# record cost for each instance, with 3 decimal places
# we sum up all the "costs" from the metrics array
df['cost'] = df['metrics'].apply(
lambda m: round(sum(c['cost'] for c in m['costs']), 3)
if m and 'costs' in m
else 0.0
)
# capture the top-level error if present, per instance
df['error_message'] = df.get('error', None)
df['cost'] = df['metrics'].apply(lambda x: round(x['accumulated_cost'], 3))
logger.info(f'Total cost: USD {df["cost"].sum():.2f}')
report_file = os.path.join(metadata.eval_output_dir, 'report.md')
with open(report_file, 'w') as f:
f.write(
f'Success rate: {df["success"].mean():.2%}'
f' ({df["success"].sum()}/{len(df)})\n'
f'Success rate: {df["success"].mean():.2%} ({df["success"].sum()}/{len(df)})\n'
)
f.write(f'\nTotal cost: USD {df["cost"].sum():.2f}\n')
f.write(
df[
['instance_id', 'success', 'reason', 'cost', 'error_message']
].to_markdown(index=False)
df[['instance_id', 'success', 'reason', 'cost']].to_markdown(index=False)
)

View File

@@ -7,9 +7,8 @@ MODEL_CONFIG=$1
COMMIT_HASH=$2
AGENT=$3
EVAL_LIMIT=$4
MAX_ITERATIONS=$5
NUM_WORKERS=$6
EVAL_IDS=$7
NUM_WORKERS=$5
EVAL_IDS=$6
if [ -z "$NUM_WORKERS" ]; then
NUM_WORKERS=1
@@ -44,7 +43,7 @@ fi
COMMAND="poetry run python evaluation/integration_tests/run_infer.py \
--agent-cls $AGENT \
--llm-config $MODEL_CONFIG \
--max-iterations ${MAX_ITERATIONS:-10} \
--max-iterations 10 \
--eval-num-workers $NUM_WORKERS \
--eval-note $EVAL_NOTE"

View File

@@ -1,73 +0,0 @@
import hashlib
from evaluation.integration_tests.tests.base import BaseIntegrationTest, TestResult
from openhands.events.action import (
AgentFinishAction,
FileWriteAction,
MessageAction,
)
from openhands.events.event import Event
from openhands.events.observation import AgentDelegateObservation
from openhands.runtime.base import Runtime
class Test(BaseIntegrationTest):
INSTRUCTION = 'Execute the python script /workspace/python_script.py with input "John" and "25" and tell me the secret number.'
SECRET_NUMBER = int(hashlib.sha256(str(25).encode()).hexdigest()[:8], 16) % 1000
@classmethod
def initialize_runtime(cls, runtime: Runtime) -> None:
from openhands.core.logger import openhands_logger as logger
action = FileWriteAction(
path='/workspace/python_script.py',
content=(
'name = input("Enter your name: "); age = input("Enter your age: "); '
'import hashlib; secret = int(hashlib.sha256(str(age).encode()).hexdigest()[:8], 16) % 1000; '
'print(f"Hello {name}, you are {age} years old. Tell you a secret number: {secret}")'
),
)
logger.info(action, extra={'msg_type': 'ACTION'})
observation = runtime.run_action(action)
logger.info(observation, extra={'msg_type': 'OBSERVATION'})
@classmethod
def verify_result(cls, runtime: Runtime, histories: list[Event]) -> TestResult:
from openhands.core.logger import openhands_logger as logger
# check if the license information is in any message
message_actions = [
event
for event in histories
if isinstance(
event, (MessageAction, AgentFinishAction, AgentDelegateObservation)
)
]
logger.info(f'Total message-like events: {len(message_actions)}')
for event in message_actions:
try:
if isinstance(event, AgentDelegateObservation):
content = event.content
elif isinstance(event, AgentFinishAction):
content = event.outputs.get('content', '')
if event.thought:
content += f'\n\n{event.thought}'
elif isinstance(event, MessageAction):
content = event.content
else:
logger.warning(f'Unexpected event type: {type(event)}')
continue
if str(cls.SECRET_NUMBER) in content:
return TestResult(success=True)
except Exception as e:
logger.error(f'Error processing event: {e}')
logger.debug(
f'Total messages: {len(message_actions)}. Messages: {message_actions}'
)
return TestResult(
success=False,
reason=f'The answer is not found in any message. Total messages: {len(message_actions)}.',
)

View File

@@ -52,6 +52,30 @@ class EvalMetadata(BaseModel):
details: dict[str, Any] | None = None
condenser_config: CondenserConfig | None = None
def model_dump(self, *args, **kwargs):
dumped_dict = super().model_dump(*args, **kwargs)
# avoid leaking sensitive information
dumped_dict['llm_config'] = self.llm_config.to_safe_dict()
if hasattr(self.condenser_config, 'llm_config'):
dumped_dict['condenser_config']['llm_config'] = (
self.condenser_config.llm_config.to_safe_dict()
)
return dumped_dict
def model_dump_json(self, *args, **kwargs):
dumped = super().model_dump_json(*args, **kwargs)
dumped_dict = json.loads(dumped)
# avoid leaking sensitive information
dumped_dict['llm_config'] = self.llm_config.to_safe_dict()
if hasattr(self.condenser_config, 'llm_config'):
dumped_dict['condenser_config']['llm_config'] = (
self.condenser_config.llm_config.to_safe_dict()
)
logger.debug(f'Dumped metadata: {dumped_dict}')
return json.dumps(dumped_dict)
class EvalOutput(BaseModel):
# NOTE: User-specified
@@ -74,6 +98,23 @@ class EvalOutput(BaseModel):
# Optionally save the input test instance
instance: dict[str, Any] | None = None
def model_dump(self, *args, **kwargs):
dumped_dict = super().model_dump(*args, **kwargs)
# Remove None values
dumped_dict = {k: v for k, v in dumped_dict.items() if v is not None}
# Apply custom serialization for metadata (to avoid leaking sensitive information)
if self.metadata is not None:
dumped_dict['metadata'] = self.metadata.model_dump()
return dumped_dict
def model_dump_json(self, *args, **kwargs):
dumped = super().model_dump_json(*args, **kwargs)
dumped_dict = json.loads(dumped)
# Apply custom serialization for metadata (to avoid leaking sensitive information)
if 'metadata' in dumped_dict:
dumped_dict['metadata'] = json.loads(self.metadata.model_dump_json())
return json.dumps(dumped_dict)
class EvalException(Exception):
pass
@@ -273,7 +314,7 @@ def update_progress(
logger.info(
f'Finished evaluation for instance {result.instance_id}: {str(result.test_result)[:300]}...\n'
)
output_fp.write(result.model_dump_json() + '\n')
output_fp.write(json.dumps(result.model_dump()) + '\n')
output_fp.flush()
@@ -330,6 +371,7 @@ def _process_instance_wrapper(
error = str(e)
stacktrace = traceback.format_exc()
if attempt == max_retries:
logger.exception(e)
msg = (
'-' * 10
+ '\n'
@@ -353,15 +395,19 @@ def _process_instance_wrapper(
+ '-' * 10
+ '\n'
)
# e is likely an EvalException, so we can't directly infer it from type
# but rather check if it's a fatal error
# But it can also be AgentRuntime**Error (e.g., swe_bench/eval_infer.py)
_error_str = type(e).__name__ + ': ' + str(e)
if is_fatal_runtime_error(_error_str):
if isinstance(
e,
(
AgentRuntimeDisconnectedError,
AgentRuntimeUnavailableError,
AgentRuntimeNotFoundError,
),
):
runtime_failure_count += 1
msg += f'Runtime disconnected error detected for instance {instance.instance_id}, runtime failure count: {runtime_failure_count}'
msg += '\n' + '-' * 10 + '\n'
logger.error(msg)
if use_mp:
print(msg) # use print to directly print to console
time.sleep(5)
@@ -518,7 +564,6 @@ def is_fatal_evaluation_error(error: str | None) -> bool:
AgentRuntimeNotReadyError,
AgentRuntimeDisconnectedError,
AgentRuntimeNotFoundError,
ConnectionError,
]
if any(exception.__name__ in error for exception in FATAL_EXCEPTIONS):
@@ -528,24 +573,6 @@ def is_fatal_evaluation_error(error: str | None) -> bool:
return False
def is_fatal_runtime_error(error: str | None) -> bool:
if not error:
return False
FATAL_RUNTIME_ERRORS = [
AgentRuntimeTimeoutError,
AgentRuntimeUnavailableError,
AgentRuntimeDisconnectedError,
AgentRuntimeNotFoundError,
]
if any(exception.__name__ in error for exception in FATAL_RUNTIME_ERRORS):
logger.error(f'Fatal runtime error detected: {error}')
return True
return False
def get_metrics(state: State) -> dict[str, Any]:
"""Extract metrics from the state."""
metrics = state.metrics.get() if state.metrics else {}

View File

@@ -0,0 +1,47 @@
import { describe, expect, it, vi } from "vitest";
import { retrieveLatestGitHubCommit } from "../../src/api/github";
describe("retrieveLatestGitHubCommit", () => {
const { openHandsGetMock } = vi.hoisted(() => ({
openHandsGetMock: vi.fn(),
}));
vi.mock("../../src/api/open-hands-axios", () => ({
openHands: {
get: openHandsGetMock,
},
}));
it("should return the latest commit when repository has commits", async () => {
const mockCommit = {
sha: "123abc",
commit: {
message: "Initial commit",
},
};
openHandsGetMock.mockResolvedValueOnce({
data: [mockCommit],
});
const result = await retrieveLatestGitHubCommit("user/repo");
expect(result).toEqual(mockCommit);
});
it("should return null when repository is empty", async () => {
const error = new Error("Repository is empty");
(error as any).response = { status: 409 };
openHandsGetMock.mockRejectedValueOnce(error);
const result = await retrieveLatestGitHubCommit("user/empty-repo");
expect(result).toBeNull();
});
it("should throw error for other error cases", async () => {
const error = new Error("Network error");
(error as any).response = { status: 500 };
openHandsGetMock.mockRejectedValueOnce(error);
await expect(retrieveLatestGitHubCommit("user/repo")).rejects.toThrow();
});
});

View File

@@ -1,10 +1,11 @@
import { describe, it, expect, afterEach, vi } from "vitest";
import * as router from "react-router";
// Mock useParams before importing components
vi.mock("react-router", async () => {
const actual = await vi.importActual("react-router");
return {
...(actual as object),
...actual as object,
useParams: () => ({ conversationId: "test-conversation-id" }),
};
});
@@ -13,7 +14,7 @@ vi.mock("react-router", async () => {
vi.mock("react-i18next", async () => {
const actual = await vi.importActual("react-i18next");
return {
...(actual as object),
...actual as object,
useTranslation: () => ({
t: (key: string) => key,
i18n: {
@@ -27,6 +28,7 @@ import { screen } from "@testing-library/react";
import { renderWithProviders } from "../../test-utils";
import { BrowserPanel } from "#/components/features/browser/browser";
describe("Browser", () => {
afterEach(() => {
vi.clearAllMocks();
@@ -37,12 +39,13 @@ describe("Browser", () => {
browser: {
url: "https://example.com",
screenshotSrc: "",
updateCount: 0,
},
},
});
// i18n empty message key
expect(screen.getByText("BROWSER$NO_PAGE_LOADED")).toBeInTheDocument();
expect(screen.getByText("BROWSER$EMPTY_MESSAGE")).toBeInTheDocument();
});
it("renders the url and a screenshot", () => {
@@ -52,6 +55,7 @@ describe("Browser", () => {
url: "https://example.com",
screenshotSrc:
"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mN0uGvyHwAFCAJS091fQwAAAABJRU5ErkJggg==",
updateCount: 0,
},
},
});

View File

@@ -84,10 +84,12 @@ describe("ChatInput", () => {
expect(onSubmitMock).not.toHaveBeenCalled();
});
it("should render a placeholder with translation key", () => {
render(<ChatInput onSubmit={onSubmitMock} />);
it("should render a placeholder", () => {
render(
<ChatInput placeholder="Enter your message" onSubmit={onSubmitMock} />,
);
const textarea = screen.getByPlaceholderText("SUGGESTIONS$WHAT_TO_BUILD");
const textarea = screen.getByPlaceholderText("Enter your message");
expect(textarea).toBeInTheDocument();
});

View File

@@ -2,42 +2,36 @@ import { describe, expect, it } from "vitest";
import { screen } from "@testing-library/react";
import { renderWithProviders } from "test-utils";
import { ExpandableMessage } from "#/components/features/chat/expandable-message";
import { vi } from "vitest";
import { vi } from 'vitest';
vi.mock("react-i18next", async () => {
const actual = await vi.importActual("react-i18next");
vi.mock('react-i18next', async () => {
const actual = await vi.importActual('react-i18next');
return {
...actual,
useTranslation: () => ({
t: (key: string) => key,
t: (key:string) => key,
i18n: {
changeLanguage: () => new Promise(() => {}),
language: "en",
language: 'en',
exists: () => true,
},
}),
};
}
});
describe("ExpandableMessage", () => {
it("should render with neutral border for non-action messages", () => {
renderWithProviders(<ExpandableMessage message="Hello" type="thought" />);
const element = screen.getByText("Hello");
const container = element.closest(
"div.flex.gap-2.items-center.justify-start",
);
const container = element.closest("div.flex.gap-2.items-center.justify-start");
expect(container).toHaveClass("border-neutral-300");
expect(screen.queryByTestId("status-icon")).not.toBeInTheDocument();
});
it("should render with neutral border for error messages", () => {
renderWithProviders(
<ExpandableMessage message="Error occurred" type="error" />,
);
renderWithProviders(<ExpandableMessage message="Error occurred" type="error" />);
const element = screen.getByText("Error occurred");
const container = element.closest(
"div.flex.gap-2.items-center.justify-start",
);
const container = element.closest("div.flex.gap-2.items-center.justify-start");
expect(container).toHaveClass("border-danger");
expect(screen.queryByTestId("status-icon")).not.toBeInTheDocument();
});
@@ -49,12 +43,10 @@ describe("ExpandableMessage", () => {
message="Command executed successfully"
type="action"
success={true}
/>,
/>
);
const element = screen.getByText("OBSERVATION_MESSAGE$RUN");
const container = element.closest(
"div.flex.gap-2.items-center.justify-start",
);
const container = element.closest("div.flex.gap-2.items-center.justify-start");
expect(container).toHaveClass("border-neutral-300");
const icon = screen.getByTestId("status-icon");
expect(icon).toHaveClass("fill-success");
@@ -67,12 +59,10 @@ describe("ExpandableMessage", () => {
message="Command failed"
type="action"
success={false}
/>,
/>
);
const element = screen.getByText("OBSERVATION_MESSAGE$RUN");
const container = element.closest(
"div.flex.gap-2.items-center.justify-start",
);
const container = element.closest("div.flex.gap-2.items-center.justify-start");
expect(container).toHaveClass("border-neutral-300");
const icon = screen.getByTestId("status-icon");
expect(icon).toHaveClass("fill-danger");
@@ -84,12 +74,10 @@ describe("ExpandableMessage", () => {
id="OBSERVATION_MESSAGE$RUN"
message="Running command"
type="action"
/>,
/>
);
const element = screen.getByText("OBSERVATION_MESSAGE$RUN");
const container = element.closest(
"div.flex.gap-2.items-center.justify-start",
);
const container = element.closest("div.flex.gap-2.items-center.justify-start");
expect(container).toHaveClass("border-neutral-300");
expect(screen.queryByTestId("status-icon")).not.toBeInTheDocument();
});

View File

@@ -5,10 +5,7 @@ import { ContextMenuListItem } from "#/components/features/context-menu/context-
describe("ContextMenuListItem", () => {
it("should render the component with the children", () => {
const onClickMock = vi.fn();
render(
<ContextMenuListItem onClick={onClickMock}>Test</ContextMenuListItem>,
);
render(<ContextMenuListItem onClick={vi.fn}>Test</ContextMenuListItem>);
expect(screen.getByTestId("context-menu-list-item")).toBeInTheDocument();
expect(screen.getByText("Test")).toBeInTheDocument();

View File

@@ -9,7 +9,6 @@ describe("ConversationCard", () => {
const onClick = vi.fn();
const onDelete = vi.fn();
const onChangeTitle = vi.fn();
const onDownloadWorkspace = vi.fn();
afterEach(() => {
vi.clearAllMocks();
@@ -19,8 +18,8 @@ describe("ConversationCard", () => {
render(
<ConversationCard
onDelete={onDelete}
onClick={onClick}
onChangeTitle={onChangeTitle}
isActive
title="Conversation 1"
selectedRepository={null}
lastUpdatedAt="2021-10-01T12:00:00Z"
@@ -39,8 +38,8 @@ describe("ConversationCard", () => {
const { rerender } = render(
<ConversationCard
onDelete={onDelete}
onClick={onClick}
onChangeTitle={onChangeTitle}
isActive
title="Conversation 1"
selectedRepository={null}
lastUpdatedAt="2021-10-01T12:00:00Z"
@@ -54,8 +53,8 @@ describe("ConversationCard", () => {
rerender(
<ConversationCard
onDelete={onDelete}
onClick={onClick}
onChangeTitle={onChangeTitle}
isActive
title="Conversation 1"
selectedRepository="org/selectedRepository"
lastUpdatedAt="2021-10-01T12:00:00Z"
@@ -65,13 +64,32 @@ describe("ConversationCard", () => {
screen.getByTestId("conversation-card-selected-repository");
});
it("should call onClick when the card is clicked", async () => {
const user = userEvent.setup();
render(
<ConversationCard
onDelete={onDelete}
onClick={onClick}
onChangeTitle={onChangeTitle}
title="Conversation 1"
selectedRepository={null}
lastUpdatedAt="2021-10-01T12:00:00Z"
/>,
);
const card = screen.getByTestId("conversation-card");
await user.click(card);
expect(onClick).toHaveBeenCalled();
});
it("should toggle a context menu when clicking the ellipsis button", async () => {
const user = userEvent.setup();
render(
<ConversationCard
onDelete={onDelete}
onClick={onClick}
onChangeTitle={onChangeTitle}
isActive
title="Conversation 1"
selectedRepository={null}
lastUpdatedAt="2021-10-01T12:00:00Z"
@@ -94,8 +112,8 @@ describe("ConversationCard", () => {
const user = userEvent.setup();
render(
<ConversationCard
onClick={onClick}
onDelete={onDelete}
isActive
onChangeTitle={onChangeTitle}
title="Conversation 1"
selectedRepository={null}
@@ -118,8 +136,8 @@ describe("ConversationCard", () => {
const user = userEvent.setup();
render(
<ConversationCard
onClick={onClick}
onDelete={onDelete}
isActive
onChangeTitle={onChangeTitle}
title="Conversation 1"
selectedRepository="org/selectedRepository"
@@ -139,8 +157,8 @@ describe("ConversationCard", () => {
const user = userEvent.setup();
render(
<ConversationCard
onClick={onClick}
onDelete={onDelete}
isActive
title="Conversation 1"
selectedRepository={null}
lastUpdatedAt="2021-10-01T12:00:00Z"
@@ -171,8 +189,8 @@ describe("ConversationCard", () => {
const user = userEvent.setup();
render(
<ConversationCard
onClick={onClick}
onDelete={onDelete}
isActive
onChangeTitle={onChangeTitle}
title="Conversation 1"
selectedRepository={null}
@@ -195,8 +213,8 @@ describe("ConversationCard", () => {
const user = userEvent.setup();
render(
<ConversationCard
onClick={onClick}
onDelete={onDelete}
isActive
onChangeTitle={onChangeTitle}
title="Conversation 1"
selectedRepository={null}
@@ -214,8 +232,8 @@ describe("ConversationCard", () => {
const user = userEvent.setup();
render(
<ConversationCard
onClick={onClick}
onDelete={onDelete}
isActive
onChangeTitle={onChangeTitle}
title="Conversation 1"
selectedRepository={null}
@@ -234,126 +252,12 @@ describe("ConversationCard", () => {
expect(onClick).not.toHaveBeenCalled();
});
it("should call onDownloadWorkspace when the download button is clicked", async () => {
const user = userEvent.setup();
render(
<ConversationCard
onClick={onClick}
onDelete={onDelete}
onChangeTitle={onChangeTitle}
onDownloadWorkspace={onDownloadWorkspace}
title="Conversation 1"
selectedRepository={null}
lastUpdatedAt="2021-10-01T12:00:00Z"
/>,
);
const ellipsisButton = screen.getByTestId("ellipsis-button");
await user.click(ellipsisButton);
const menu = screen.getByTestId("context-menu");
const downloadButton = within(menu).getByTestId("download-button");
await user.click(downloadButton);
expect(onDownloadWorkspace).toHaveBeenCalled();
});
it("should not display the edit or delete options if the handler is not provided", async () => {
const user = userEvent.setup();
const { rerender } = render(
<ConversationCard
onClick={onClick}
onChangeTitle={onChangeTitle}
title="Conversation 1"
selectedRepository={null}
lastUpdatedAt="2021-10-01T12:00:00Z"
/>,
);
const ellipsisButton = screen.getByTestId("ellipsis-button");
await user.click(ellipsisButton);
expect(screen.queryByTestId("edit-button")).toBeInTheDocument();
expect(screen.queryByTestId("delete-button")).not.toBeInTheDocument();
// toggle to hide the context menu
await user.click(ellipsisButton);
rerender(
<ConversationCard
onClick={onClick}
onDelete={onDelete}
title="Conversation 1"
selectedRepository={null}
lastUpdatedAt="2021-10-01T12:00:00Z"
/>,
);
await user.click(ellipsisButton);
expect(screen.queryByTestId("edit-button")).not.toBeInTheDocument();
expect(screen.queryByTestId("delete-button")).toBeInTheDocument();
});
it("should not render the ellipsis button if there are no actions", () => {
const { rerender } = render(
<ConversationCard
onClick={onClick}
onDelete={onDelete}
onChangeTitle={onChangeTitle}
onDownloadWorkspace={onDownloadWorkspace}
title="Conversation 1"
selectedRepository={null}
lastUpdatedAt="2021-10-01T12:00:00Z"
/>,
);
expect(screen.getByTestId("ellipsis-button")).toBeInTheDocument();
rerender(
<ConversationCard
onClick={onClick}
onDelete={onDelete}
onDownloadWorkspace={onDownloadWorkspace}
title="Conversation 1"
selectedRepository={null}
lastUpdatedAt="2021-10-01T12:00:00Z"
/>,
);
expect(screen.getByTestId("ellipsis-button")).toBeInTheDocument();
rerender(
<ConversationCard
onClick={onClick}
onDownloadWorkspace={onDownloadWorkspace}
title="Conversation 1"
selectedRepository={null}
lastUpdatedAt="2021-10-01T12:00:00Z"
/>,
);
expect(screen.queryByTestId("ellipsis-button")).toBeInTheDocument();
rerender(
<ConversationCard
onClick={onClick}
title="Conversation 1"
selectedRepository={null}
lastUpdatedAt="2021-10-01T12:00:00Z"
/>,
);
expect(screen.queryByTestId("ellipsis-button")).not.toBeInTheDocument();
});
describe("state indicator", () => {
it("should render the 'STOPPED' indicator by default", () => {
render(
<ConversationCard
onClick={onClick}
onDelete={onDelete}
isActive
onChangeTitle={onChangeTitle}
title="Conversation 1"
selectedRepository={null}
@@ -367,8 +271,8 @@ describe("ConversationCard", () => {
it("should render the other indicators when provided", () => {
render(
<ConversationCard
onClick={onClick}
onDelete={onDelete}
isActive
onChangeTitle={onChangeTitle}
title="Conversation 1"
selectedRepository={null}

View File

@@ -1,4 +1,4 @@
import { render, screen, waitFor, within } from "@testing-library/react";
import { render, screen, within } from "@testing-library/react";
import { beforeAll, beforeEach, describe, expect, it, vi } from "vitest";
import {
QueryClientProvider,
@@ -6,25 +6,16 @@ import {
QueryClientConfig,
} from "@tanstack/react-query";
import userEvent from "@testing-library/user-event";
import { createRoutesStub } from "react-router";
import React from "react";
import { ConversationPanel } from "#/components/features/conversation-panel/conversation-panel";
import OpenHands from "#/api/open-hands";
import { AuthProvider } from "#/context/auth-context";
import { clickOnEditButton } from "./utils";
import { queryClientConfig } from "#/query-client-config";
describe("ConversationPanel", () => {
const onCloseMock = vi.fn();
const RouterStub = createRoutesStub([
{
Component: () => <ConversationPanel onClose={onCloseMock} />,
path: "/",
},
]);
const renderConversationPanel = (config?: QueryClientConfig) =>
render(<RouterStub />, {
render(<ConversationPanel onClose={onCloseMock} />, {
wrapper: ({ children }) => (
<AuthProvider>
<QueryClientProvider client={new QueryClient(config)}>
@@ -73,7 +64,7 @@ describe("ConversationPanel", () => {
renderConversationPanel();
const emptyState = await screen.findByText("CONVERSATION$NO_CONVERSATIONS");
const emptyState = await screen.findByText("No conversations found");
expect(emptyState).toBeInTheDocument();
});
@@ -233,47 +224,4 @@ describe("ConversationPanel", () => {
expect(onCloseMock).toHaveBeenCalledOnce();
});
it("should refetch data on rerenders", async () => {
// We need to simulate the toggling of the component to test the refetching
function PanelWithToggle() {
const [isOpen, setIsOpen] = React.useState(true);
return (
<>
<button type="button" onClick={() => setIsOpen((prev) => !prev)}>
Toggle
</button>
{isOpen && <ConversationPanel onClose={onCloseMock} />}
</>
);
}
const MyRouterStub = createRoutesStub([
{
Component: PanelWithToggle,
path: "/",
},
]);
const getUserConversationsSpy = vi.spyOn(OpenHands, "getUserConversations");
render(<MyRouterStub />, {
wrapper: ({ children }) => (
<AuthProvider>
<QueryClientProvider client={new QueryClient(queryClientConfig)}>
{children}
</QueryClientProvider>
</AuthProvider>
),
});
await waitFor(() => expect(getUserConversationsSpy).toHaveBeenCalledOnce());
const button = screen.getByText("Toggle");
await userEvent.click(button);
await userEvent.click(button);
await waitFor(() =>
expect(getUserConversationsSpy).toHaveBeenCalledTimes(2),
);
});
});

View File

@@ -3,6 +3,7 @@ import { describe, expect, it, vi } from "vitest";
import { renderWithProviders } from "test-utils";
import { GitHubRepositorySelector } from "#/components/features/github/github-repo-selector";
import OpenHands from "#/api/open-hands";
import * as GitHubAPI from "#/api/github";
describe("GitHubRepositorySelector", () => {
const onInputChangeMock = vi.fn();
@@ -19,7 +20,7 @@ describe("GitHubRepositorySelector", () => {
);
expect(
screen.getByPlaceholderText("LANDING$SELECT_REPO"),
screen.getByPlaceholderText("Select a GitHub project"),
).toBeInTheDocument();
});
@@ -59,8 +60,8 @@ describe("GitHubRepositorySelector", () => {
];
const searchPublicRepositoriesSpy = vi.spyOn(
OpenHands,
"searchGitHubRepositories",
GitHubAPI,
"searchPublicRepositories",
);
searchPublicRepositoriesSpy.mockResolvedValue(mockSearchedRepos);

View File

@@ -1,15 +1,10 @@
import { screen, within } from "@testing-library/react";
import { screen } from "@testing-library/react";
import userEvent from "@testing-library/user-event";
import { afterEach, describe, expect, it, vi } from "vitest";
import { describe, expect, it } from "vitest";
import { renderWithProviders } from "test-utils";
import { createRoutesStub } from "react-router";
import { Sidebar } from "#/components/features/sidebar/sidebar";
import { MULTI_CONVERSATION_UI } from "#/utils/feature-flags";
import OpenHands from "#/api/open-hands";
import { MOCK_USER_PREFERENCES } from "#/mocks/handlers";
// These tests will now fail because the conversation panel is rendered through a portal
// and technically not a child of the Sidebar component.
const renderSidebar = () => {
const RouterStub = createRoutesStub([
@@ -48,132 +43,4 @@ describe("Sidebar", () => {
).not.toBeInTheDocument();
},
);
describe("Settings", () => {
const getSettingsSpy = vi.spyOn(OpenHands, "getSettings");
const saveSettingsSpy = vi.spyOn(OpenHands, "saveSettings");
afterEach(() => {
vi.clearAllMocks();
});
it("should fetch settings data on mount", () => {
renderSidebar();
expect(getSettingsSpy).toHaveBeenCalledOnce();
});
it("should send all settings data when saving AI configuration", async () => {
const user = userEvent.setup();
renderSidebar();
const settingsButton = screen.getByTestId("settings-button");
await user.click(settingsButton);
const settingsModal = screen.getByTestId("ai-config-modal");
const saveButton = within(settingsModal).getByTestId(
"save-settings-button",
);
await user.click(saveButton);
expect(saveSettingsSpy).toHaveBeenCalledWith({
...MOCK_USER_PREFERENCES.settings,
// the actual values are falsey (null or "") but we're checking for undefined
llm_api_key: undefined,
llm_base_url: undefined,
security_analyzer: undefined,
});
});
it("should send all settings data when saving account settings", async () => {
const user = userEvent.setup();
renderSidebar();
const userAvatar = screen.getByTestId("user-avatar");
await user.click(userAvatar);
const menu = screen.getByTestId("account-settings-context-menu");
const accountSettingsButton = within(menu).getByTestId(
"account-settings-button",
);
await user.click(accountSettingsButton);
const accountSettingsModal = screen.getByTestId("account-settings-form");
const saveButton =
within(accountSettingsModal).getByTestId("save-settings");
await user.click(saveButton);
expect(saveSettingsSpy).toHaveBeenCalledWith({
...MOCK_USER_PREFERENCES.settings,
llm_api_key: undefined, // null or undefined
});
});
it("should not reset AI configuration when saving account settings", async () => {
const user = userEvent.setup();
renderSidebar();
const userAvatar = screen.getByTestId("user-avatar");
await user.click(userAvatar);
const menu = screen.getByTestId("account-settings-context-menu");
const accountSettingsButton = within(menu).getByTestId(
"account-settings-button",
);
await user.click(accountSettingsButton);
const accountSettingsModal = screen.getByTestId("account-settings-form");
const languageInput =
within(accountSettingsModal).getByLabelText(/language/i);
await user.click(languageInput);
const norskOption = screen.getByText(/norsk/i);
await user.click(norskOption);
const tokenInput =
within(accountSettingsModal).getByLabelText(/GITHUB\$TOKEN_LABEL/i);
await user.type(tokenInput, "new-token");
const saveButton =
within(accountSettingsModal).getByTestId("save-settings");
await user.click(saveButton);
expect(saveSettingsSpy).toHaveBeenCalledWith({
...MOCK_USER_PREFERENCES.settings,
language: "no",
llm_api_key: undefined, // null or undefined
});
});
it("should not send the api key if its SET", async () => {
const user = userEvent.setup();
renderSidebar();
const settingsButton = screen.getByTestId("settings-button");
await user.click(settingsButton);
const settingsModal = screen.getByTestId("ai-config-modal");
// Click the advanced options switch to show the API key input
const advancedOptionsSwitch = within(settingsModal).getByTestId(
"advanced-option-switch",
);
await user.click(advancedOptionsSwitch);
const apiKeyInput = within(settingsModal).getByLabelText(/API\$KEY/i);
await user.type(apiKeyInput, "**********");
const saveButton = within(settingsModal).getByTestId(
"save-settings-button",
);
await user.click(saveButton);
expect(saveSettingsSpy).toHaveBeenCalledWith({
...MOCK_USER_PREFERENCES.settings,
llm_api_key: undefined,
llm_base_url: "",
security_analyzer: undefined,
});
});
});
});

View File

@@ -1,13 +1,12 @@
import { render, screen, within } from "@testing-library/react";
import userEvent from "@testing-library/user-event";
import { afterEach, describe, expect, it, vi } from "vitest";
import { TrajectoryActions } from "#/components/features/trajectory/trajectory-actions";
import { FeedbackActions } from "#/components/features/feedback/feedback-actions";
describe("TrajectoryActions", () => {
describe("FeedbackActions", () => {
const user = userEvent.setup();
const onPositiveFeedback = vi.fn();
const onNegativeFeedback = vi.fn();
const onExportTrajectory = vi.fn();
afterEach(() => {
vi.clearAllMocks();
@@ -15,10 +14,9 @@ describe("TrajectoryActions", () => {
it("should render correctly", () => {
render(
<TrajectoryActions
<FeedbackActions
onPositiveFeedback={onPositiveFeedback}
onNegativeFeedback={onNegativeFeedback}
onExportTrajectory={onExportTrajectory}
/>,
);
@@ -29,10 +27,9 @@ describe("TrajectoryActions", () => {
it("should call onPositiveFeedback when positive feedback is clicked", async () => {
render(
<TrajectoryActions
<FeedbackActions
onPositiveFeedback={onPositiveFeedback}
onNegativeFeedback={onNegativeFeedback}
onExportTrajectory={onExportTrajectory}
/>,
);
@@ -44,10 +41,9 @@ describe("TrajectoryActions", () => {
it("should call onNegativeFeedback when negative feedback is clicked", async () => {
render(
<TrajectoryActions
<FeedbackActions
onPositiveFeedback={onPositiveFeedback}
onNegativeFeedback={onNegativeFeedback}
onExportTrajectory={onExportTrajectory}
/>,
);
@@ -56,19 +52,4 @@ describe("TrajectoryActions", () => {
expect(onNegativeFeedback).toHaveBeenCalled();
});
it("should call onExportTrajectory when negative feedback is clicked", async () => {
render(
<TrajectoryActions
onPositiveFeedback={onPositiveFeedback}
onNegativeFeedback={onNegativeFeedback}
onExportTrajectory={onExportTrajectory}
/>,
);
const exportButton = screen.getByTestId("export-trajectory");
await user.click(exportButton);
expect(onExportTrajectory).toHaveBeenCalled();
});
});

View File

@@ -1,10 +1,11 @@
import { afterEach, describe, expect, it, vi } from "vitest";
import { afterEach, beforeEach, describe, expect, it, vi } from "vitest";
import * as router from "react-router";
// Mock useParams before importing components
vi.mock("react-router", async () => {
const actual = await vi.importActual("react-router");
return {
...(actual as object),
...actual as object,
useParams: () => ({ conversationId: "test-conversation-id" }),
};
});
@@ -13,7 +14,6 @@ import { screen } from "@testing-library/react";
import userEvent from "@testing-library/user-event";
import { renderWithProviders } from "test-utils";
import { FeedbackForm } from "#/components/features/feedback/feedback-form";
import { I18nKey } from "#/i18n/declaration";
describe("FeedbackForm", () => {
const user = userEvent.setup();
@@ -28,20 +28,20 @@ describe("FeedbackForm", () => {
<FeedbackForm polarity="positive" onClose={onCloseMock} />,
);
screen.getByLabelText(I18nKey.FEEDBACK$EMAIL_LABEL);
screen.getByLabelText(I18nKey.FEEDBACK$PRIVATE_LABEL);
screen.getByLabelText(I18nKey.FEEDBACK$PUBLIC_LABEL);
screen.getByLabelText("Email");
screen.getByLabelText("Private");
screen.getByLabelText("Public");
screen.getByRole("button", { name: I18nKey.FEEDBACK$CONTRIBUTE_LABEL });
screen.getByRole("button", { name: I18nKey.FEEDBACK$CANCEL_LABEL });
screen.getByRole("button", { name: "Submit" });
screen.getByRole("button", { name: "Cancel" });
});
it("should switch between private and public permissions", async () => {
renderWithProviders(
<FeedbackForm polarity="positive" onClose={onCloseMock} />,
);
const privateRadio = screen.getByLabelText(I18nKey.FEEDBACK$PRIVATE_LABEL);
const publicRadio = screen.getByLabelText(I18nKey.FEEDBACK$PUBLIC_LABEL);
const privateRadio = screen.getByLabelText("Private");
const publicRadio = screen.getByLabelText("Public");
expect(privateRadio).toBeChecked(); // private is the default value
expect(publicRadio).not.toBeChecked();
@@ -59,9 +59,7 @@ describe("FeedbackForm", () => {
renderWithProviders(
<FeedbackForm polarity="positive" onClose={onCloseMock} />,
);
await user.click(
screen.getByRole("button", { name: I18nKey.FEEDBACK$CANCEL_LABEL }),
);
await user.click(screen.getByRole("button", { name: "Cancel" }));
expect(onCloseMock).toHaveBeenCalled();
});

View File

@@ -157,7 +157,7 @@ describe("InteractiveChatBox", () => {
expect(onChange).not.toHaveBeenCalledWith("");
// Submit the message with image
const submitButton = screen.getByRole("button", { name: "BUTTON$SEND" });
const submitButton = screen.getByRole("button", { name: "Send" });
await user.click(submitButton);
// Verify onSubmit was called with the message and image

View File

@@ -1,190 +0,0 @@
import { render, screen } from "@testing-library/react";
import { test, expect, describe, vi } from "vitest";
import { useTranslation } from "react-i18next";
import translations from "../../src/i18n/translation.json";
import { UserAvatar } from "../../src/components/features/sidebar/user-avatar";
vi.mock("@nextui-org/react", () => ({
Tooltip: ({ content, children }: { content: string; children: React.ReactNode }) => (
<div>
{children}
<div>{content}</div>
</div>
),
}));
const supportedLanguages = ['en', 'ja', 'zh-CN', 'zh-TW', 'ko-KR', 'de', 'no', 'it', 'pt', 'es', 'ar', 'fr', 'tr'];
// Helper function to check if a translation exists for all supported languages
function checkTranslationExists(key: string) {
const missingTranslations: string[] = [];
const translationEntry = (translations as Record<string, Record<string, string>>)[key];
if (!translationEntry) {
throw new Error(`Translation key "${key}" does not exist in translation.json`);
}
for (const lang of supportedLanguages) {
if (!translationEntry[lang]) {
missingTranslations.push(lang);
}
}
return missingTranslations;
}
// Helper function to find duplicate translation keys
function findDuplicateKeys(obj: Record<string, any>) {
const seen = new Set<string>();
const duplicates = new Set<string>();
// Only check top-level keys as these are our translation keys
for (const key in obj) {
if (seen.has(key)) {
duplicates.add(key);
} else {
seen.add(key);
}
}
return Array.from(duplicates);
}
vi.mock("react-i18next", () => ({
useTranslation: () => ({
t: (key: string) => {
const translationEntry = (translations as Record<string, Record<string, string>>)[key];
return translationEntry?.ja || key;
},
}),
}));
describe("Landing page translations", () => {
test("should render Japanese translations correctly", () => {
// Mock a simple component that uses the translations
const TestComponent = () => {
const { t } = useTranslation();
return (
<div>
<UserAvatar onClick={() => {}} />
<div data-testid="main-content">
<h1>{t("LANDING$TITLE")}</h1>
<button>{t("VSCODE$OPEN")}</button>
<button>{t("SUGGESTIONS$INCREASE_TEST_COVERAGE")}</button>
<button>{t("SUGGESTIONS$AUTO_MERGE_PRS")}</button>
<button>{t("SUGGESTIONS$FIX_README")}</button>
<button>{t("SUGGESTIONS$CLEAN_DEPENDENCIES")}</button>
</div>
<div data-testid="tabs">
<span>{t("WORKSPACE$TERMINAL_TAB_LABEL")}</span>
<span>{t("WORKSPACE$BROWSER_TAB_LABEL")}</span>
<span>{t("WORKSPACE$JUPYTER_TAB_LABEL")}</span>
<span>{t("WORKSPACE$CODE_EDITOR_TAB_LABEL")}</span>
</div>
<div data-testid="workspace-label">{t("WORKSPACE$TITLE")}</div>
<button data-testid="new-project">{t("PROJECT$NEW_PROJECT")}</button>
<div data-testid="status">
<span>{t("TERMINAL$WAITING_FOR_CLIENT")}</span>
<span>{t("STATUS$CONNECTED")}</span>
<span>{t("STATUS$CONNECTED_TO_SERVER")}</span>
</div>
<div data-testid="time">
<span>{`5 ${t("TIME$MINUTES_AGO")}`}</span>
<span>{`2 ${t("TIME$HOURS_AGO")}`}</span>
<span>{`3 ${t("TIME$DAYS_AGO")}`}</span>
</div>
</div>
);
};
render(<TestComponent />);
// Check main content translations
expect(screen.getByText("開発を始めましょう!")).toBeInTheDocument();
expect(screen.getByText("VS Codeで開く")).toBeInTheDocument();
expect(screen.getByText("テストカバレッジを向上させる")).toBeInTheDocument();
expect(screen.getByText("Dependabot PRを自動マージ")).toBeInTheDocument();
expect(screen.getByText("READMEを改善")).toBeInTheDocument();
expect(screen.getByText("依存関係を整理")).toBeInTheDocument();
// Check user avatar tooltip
const userAvatar = screen.getByTestId("user-avatar");
userAvatar.focus();
expect(screen.getByText("アカウント設定")).toBeInTheDocument();
// Check tab labels
const tabs = screen.getByTestId("tabs");
expect(tabs).toHaveTextContent("ターミナル");
expect(tabs).toHaveTextContent("ブラウザ");
expect(tabs).toHaveTextContent("Jupyter");
expect(tabs).toHaveTextContent("コードエディタ");
// Check workspace label and new project button
expect(screen.getByTestId("workspace-label")).toHaveTextContent("ワークスペース");
expect(screen.getByTestId("new-project")).toHaveTextContent("新規プロジェクト");
// Check status messages
const status = screen.getByTestId("status");
expect(status).toHaveTextContent("クライアントの準備を待機中");
expect(status).toHaveTextContent("接続済み");
expect(status).toHaveTextContent("サーバーに接続済み");
// Check account settings menu
expect(screen.getByText("アカウント設定")).toBeInTheDocument();
// Check time-related translations
const time = screen.getByTestId("time");
expect(time).toHaveTextContent("5 分前");
expect(time).toHaveTextContent("2 時間前");
expect(time).toHaveTextContent("3 日前");
});
test("all translation keys should have translations for all supported languages", () => {
// Test all translation keys used in the component
const translationKeys = [
"LANDING$TITLE",
"VSCODE$OPEN",
"SUGGESTIONS$INCREASE_TEST_COVERAGE",
"SUGGESTIONS$AUTO_MERGE_PRS",
"SUGGESTIONS$FIX_README",
"SUGGESTIONS$CLEAN_DEPENDENCIES",
"WORKSPACE$TERMINAL_TAB_LABEL",
"WORKSPACE$BROWSER_TAB_LABEL",
"WORKSPACE$JUPYTER_TAB_LABEL",
"WORKSPACE$CODE_EDITOR_TAB_LABEL",
"WORKSPACE$TITLE",
"PROJECT$NEW_PROJECT",
"TERMINAL$WAITING_FOR_CLIENT",
"STATUS$CONNECTED",
"STATUS$CONNECTED_TO_SERVER",
"TIME$MINUTES_AGO",
"TIME$HOURS_AGO",
"TIME$DAYS_AGO"
];
// Check all keys and collect missing translations
const missingTranslationsMap = new Map<string, string[]>();
translationKeys.forEach(key => {
const missing = checkTranslationExists(key);
if (missing.length > 0) {
missingTranslationsMap.set(key, missing);
}
});
// If any translations are missing, throw an error with all missing translations
if (missingTranslationsMap.size > 0) {
const errorMessage = Array.from(missingTranslationsMap.entries())
.map(([key, langs]) => `\n- "${key}" is missing translations for: ${langs.join(', ')}`)
.join('');
throw new Error(`Missing translations:${errorMessage}`);
}
});
test("translation file should not have duplicate keys", () => {
const duplicates = findDuplicateKeys(translations);
if (duplicates.length > 0) {
throw new Error(`Found duplicate translation keys: ${duplicates.join(', ')}`);
}
});
});

View File

@@ -4,21 +4,13 @@ import { describe, it, vi, expect } from "vitest";
import { BaseModal } from "#/components/shared/modals/base-modal/base-modal";
describe("BaseModal", () => {
const onOpenChangeMock = vi.fn();
it("should render if the modal is open", () => {
const { rerender } = render(
<BaseModal
isOpen={false}
onOpenChange={onOpenChangeMock}
title="Settings"
/>,
<BaseModal isOpen={false} onOpenChange={vi.fn} title="Settings" />,
);
expect(screen.queryByText("Settings")).not.toBeInTheDocument();
rerender(
<BaseModal title="Settings" onOpenChange={onOpenChangeMock} isOpen />,
);
rerender(<BaseModal title="Settings" onOpenChange={vi.fn} isOpen />);
expect(screen.getByText("Settings")).toBeInTheDocument();
});
@@ -26,7 +18,7 @@ describe("BaseModal", () => {
render(
<BaseModal
isOpen
onOpenChange={onOpenChangeMock}
onOpenChange={vi.fn}
title="Settings"
subtitle="Subtitle"
/>,
@@ -51,7 +43,7 @@ describe("BaseModal", () => {
render(
<BaseModal
isOpen
onOpenChange={onOpenChangeMock}
onOpenChange={vi.fn}
title="Settings"
actions={[primaryAction, secondaryAction]}
/>,
@@ -68,6 +60,7 @@ describe("BaseModal", () => {
});
it("should close the modal after an action is performed", async () => {
const onOpenChangeMock = vi.fn();
render(
<BaseModal
isOpen
@@ -89,7 +82,7 @@ describe("BaseModal", () => {
it("should render children", () => {
render(
<BaseModal isOpen onOpenChange={onOpenChangeMock} title="Settings">
<BaseModal isOpen onOpenChange={vi.fn} title="Settings">
<div>Children</div>
</BaseModal>,
);
@@ -100,7 +93,7 @@ describe("BaseModal", () => {
const { rerender } = render(
<BaseModal
isOpen
onOpenChange={onOpenChangeMock}
onOpenChange={vi.fn}
title="Settings"
actions={[
{
@@ -117,7 +110,7 @@ describe("BaseModal", () => {
rerender(
<BaseModal
isOpen
onOpenChange={onOpenChangeMock}
onOpenChange={vi.fn}
title="Settings"
actions={[
{
@@ -133,6 +126,7 @@ describe("BaseModal", () => {
});
it.skip("should not close if the backdrop or escape key is pressed", () => {
const onOpenChangeMock = vi.fn();
render(
<BaseModal
isOpen

View File

@@ -1,23 +1,7 @@
import { describe, it, expect, vi } from "vitest";
import { describe, it, expect } from "vitest";
import { render, screen } from "@testing-library/react";
import userEvent from "@testing-library/user-event";
import { ModelSelector } from "#/components/shared/modals/settings/model-selector";
import { I18nKey } from "#/i18n/declaration";
// Mock react-i18next
vi.mock("react-i18next", () => ({
useTranslation: () => ({
t: (key: string) => {
const translations: { [key: string]: string } = {
LLM$PROVIDER: "LLM Provider",
LLM$MODEL: "LLM Model",
LLM$SELECT_PROVIDER_PLACEHOLDER: "Select a provider",
LLM$SELECT_MODEL_PLACEHOLDER: "Select a model",
};
return translations[key] || key;
},
}),
}));
describe("ModelSelector", () => {
const models = {

View File

@@ -1,22 +1,13 @@
import { screen, fireEvent } from "@testing-library/react";
import { describe, it, expect, vi, afterEach } from "vitest";
import { describe, it, expect, vi } from "vitest";
import { renderWithProviders } from "test-utils";
import { createRoutesStub } from "react-router";
import userEvent from "@testing-library/user-event";
import { DEFAULT_SETTINGS } from "#/services/settings";
import { SettingsForm } from "#/components/shared/modals/settings/settings-form";
import OpenHands from "#/api/open-hands";
describe("SettingsForm", () => {
const getConfigSpy = vi.spyOn(OpenHands, "getConfig");
const saveSettingsSpy = vi.spyOn(OpenHands, "saveSettings");
const onCloseMock = vi.fn();
afterEach(() => {
vi.clearAllMocks();
});
getConfigSpy.mockResolvedValue({
APP_MODE: "saas",
GITHUB_CLIENT_ID: "123",
@@ -28,10 +19,10 @@ describe("SettingsForm", () => {
Component: () => (
<SettingsForm
settings={DEFAULT_SETTINGS}
models={["anthropic/claude-3-5-sonnet-20241022", "model2"]}
agents={["CodeActAgent", "agent2"]}
securityAnalyzers={["analyzer1", "analyzer2"]}
onClose={onCloseMock}
models={[]}
agents={[]}
securityAnalyzers={[]}
onClose={() => {}}
/>
),
path: "/",
@@ -44,33 +35,11 @@ describe("SettingsForm", () => {
});
it("should show runtime size selector when advanced options are enabled", async () => {
const user = userEvent.setup();
renderWithProviders(<RouterStub />);
const toggleAdvancedMode = screen.getByTestId("advanced-option-switch");
await user.click(toggleAdvancedMode);
await screen.findByTestId("runtime-size");
});
it("should not submit the form if required fields are empty", async () => {
const user = userEvent.setup();
renderWithProviders(<RouterStub />);
expect(screen.queryByTestId("custom-model-input")).not.toBeInTheDocument();
const toggleAdvancedMode = screen.getByTestId("advanced-option-switch");
await user.click(toggleAdvancedMode);
const customModelInput = screen.getByTestId("custom-model-input");
expect(customModelInput).toBeInTheDocument();
await user.clear(customModelInput);
const saveButton = screen.getByTestId("save-settings-button");
await user.click(saveButton);
expect(saveSettingsSpy).not.toHaveBeenCalled();
expect(onCloseMock).not.toHaveBeenCalled();
const advancedSwitch = screen.getByRole("switch", {
name: "SETTINGS_FORM$ADVANCED_OPTIONS_LABEL",
});
fireEvent.click(advancedSwitch);
await screen.findByText("SETTINGS_FORM$RUNTIME_SIZE_LABEL");
});
});

View File

@@ -2,20 +2,6 @@ import { render, screen } from "@testing-library/react";
import userEvent from "@testing-library/user-event";
import { afterEach, describe, expect, it, vi } from "vitest";
import { SuggestionItem } from "#/components/features/suggestions/suggestion-item";
import { I18nKey } from "#/i18n/declaration";
vi.mock("react-i18next", () => ({
useTranslation: () => ({
t: (key: string) => {
const translations: Record<string, string> = {
"SUGGESTIONS$TODO_APP": "ToDoリストアプリを開発する",
"LANDING$BUILD_APP_BUTTON": "プルリクエストを表示するアプリを開発する",
"SUGGESTIONS$HACKER_NEWS": "Hacker Newsのトップ記事を表示するbashスクリプトを作成する",
};
return translations[key] || key;
},
}),
}));
describe("SuggestionItem", () => {
const suggestionItem = { label: "suggestion1", value: "a long text value" };
@@ -32,19 +18,6 @@ describe("SuggestionItem", () => {
expect(screen.getByText(/suggestion1/i)).toBeInTheDocument();
});
it("should render a translated suggestion when using I18nKey", async () => {
const translatedSuggestion = {
label: I18nKey.SUGGESTIONS$TODO_APP,
value: "todo app value",
};
const { container } = render(<SuggestionItem suggestion={translatedSuggestion} onClick={onClick} />);
console.log('Rendered HTML:', container.innerHTML);
expect(screen.getByText("ToDoリストアプリを開発する")).toBeInTheDocument();
});
it("should call onClick when clicking a suggestion", async () => {
const user = userEvent.setup();
render(<SuggestionItem suggestion={suggestionItem} onClick={onClick} />);

View File

@@ -14,7 +14,7 @@ describe("UserAvatar", () => {
render(<UserAvatar onClick={onClickMock} />);
expect(screen.getByTestId("user-avatar")).toBeInTheDocument();
expect(
screen.getByLabelText("USER$AVATAR_PLACEHOLDER"),
screen.getByLabelText("user avatar placeholder"),
).toBeInTheDocument();
});
@@ -38,7 +38,7 @@ describe("UserAvatar", () => {
expect(screen.getByAltText("user avatar")).toBeInTheDocument();
expect(
screen.queryByLabelText("USER$AVATAR_PLACEHOLDER"),
screen.queryByLabelText("user avatar placeholder"),
).not.toBeInTheDocument();
});
@@ -46,13 +46,13 @@ describe("UserAvatar", () => {
const { rerender } = render(<UserAvatar onClick={onClickMock} />);
expect(screen.queryByTestId("loading-spinner")).not.toBeInTheDocument();
expect(
screen.getByLabelText("USER$AVATAR_PLACEHOLDER"),
screen.getByLabelText("user avatar placeholder"),
).toBeInTheDocument();
rerender(<UserAvatar onClick={onClickMock} isLoading />);
expect(screen.getByTestId("loading-spinner")).toBeInTheDocument();
expect(
screen.queryByLabelText("USER$AVATAR_PLACEHOLDER"),
screen.queryByLabelText("user avatar placeholder"),
).not.toBeInTheDocument();
rerender(

View File

@@ -27,17 +27,4 @@ describe("Propagate error message", () => {
type: 'error'
});
});
it("should display error including translation id when present", () => {
const message = "We have a problem!"
const addErrorMessageSpy = vi.spyOn(ChatSlice, "addErrorMessage")
updateStatusWhenErrorMessagePresent({message, data: {msg_id: '..id..'}})
expect(addErrorMessageSpy).toHaveBeenCalledWith({
message,
id: '..id..',
status_update: true,
type: 'error'
});
});
});

View File

@@ -1,76 +0,0 @@
import { describe, expect, it } from 'vitest';
import fs from 'fs';
import path from 'path';
describe('translation.json', () => {
it('should not have duplicate translation keys', () => {
// Read the translation.json file
const translationPath = path.join(__dirname, '../../src/i18n/translation.json');
const translationContent = fs.readFileSync(translationPath, 'utf-8');
// First, let's check for exact string matches of key definitions
const keyRegex = /"([^"]+)": {/g;
const matches = translationContent.matchAll(keyRegex);
const keyOccurrences = new Map<string, number>();
const duplicateKeys: string[] = [];
for (const match of matches) {
const key = match[1];
const count = (keyOccurrences.get(key) || 0) + 1;
keyOccurrences.set(key, count);
if (count > 1) {
duplicateKeys.push(key);
}
}
// Remove duplicates from duplicateKeys array
const uniqueDuplicates = [...new Set(duplicateKeys)];
// If there are duplicates, create a helpful error message
if (uniqueDuplicates.length > 0) {
const errorMessage = `Found duplicate translation keys:\n${uniqueDuplicates
.map((key) => ` - "${key}" appears ${keyOccurrences.get(key)} times`)
.join('\n')}`;
throw new Error(errorMessage);
}
// Expect no duplicates (this will pass if we reach here)
expect(uniqueDuplicates).toHaveLength(0);
});
it('should have consistent translations for each key', () => {
// Read the translation.json file
const translationPath = path.join(__dirname, '../../src/i18n/translation.json');
const translationContent = fs.readFileSync(translationPath, 'utf-8');
const translations = JSON.parse(translationContent);
// Create a map to store English translations for each key
const englishTranslations = new Map<string, string>();
const inconsistentKeys: string[] = [];
// Check each key's English translation
Object.entries(translations).forEach(([key, value]: [string, any]) => {
if (typeof value === 'object' && value.en !== undefined) {
const currentEn = value.en.toLowerCase();
const existingEn = englishTranslations.get(key)?.toLowerCase();
if (existingEn !== undefined && existingEn !== currentEn) {
inconsistentKeys.push(key);
} else {
englishTranslations.set(key, value.en);
}
}
});
// If there are inconsistencies, create a helpful error message
if (inconsistentKeys.length > 0) {
const errorMessage = `Found inconsistent translations for keys:\n${inconsistentKeys
.map((key) => ` - "${key}" has multiple different English translations`)
.join('\n')}`;
throw new Error(errorMessage);
}
// Expect no inconsistencies
expect(inconsistentKeys).toHaveLength(0);
});
});

View File

@@ -1,20 +0,0 @@
import { screen } from '@testing-library/react';
import { describe, expect, it } from 'vitest';
import i18n from '../../src/i18n';
import { AccountSettingsContextMenu } from '../../src/components/features/context-menu/account-settings-context-menu';
import { renderWithProviders } from '../../test-utils';
describe('Translations', () => {
it('should render translated text', () => {
i18n.changeLanguage('en');
renderWithProviders(
<AccountSettingsContextMenu
onClickAccountSettings={() => {}}
onLogout={() => {}}
onClose={() => {}}
isLoggedIn={true}
/>
);
expect(screen.getByTestId('account-settings-context-menu')).toBeInTheDocument();
});
});

View File

@@ -1,20 +1,20 @@
import { describe, it, expect } from "vitest";
import store from "../src/store";
import {
setInitialPrompt,
clearInitialPrompt,
setInitialQuery,
clearInitialQuery,
} from "../src/state/initial-query-slice";
describe("Initial Query Behavior", () => {
it("should clear initial query when clearInitialPrompt is dispatched", () => {
it("should clear initial query when clearInitialQuery is dispatched", () => {
// Set up initial query in the store
store.dispatch(setInitialPrompt("test query"));
expect(store.getState().initialQuery.initialPrompt).toBe("test query");
store.dispatch(setInitialQuery("test query"));
expect(store.getState().initialQuery.initialQuery).toBe("test query");
// Clear the initial query
store.dispatch(clearInitialPrompt());
store.dispatch(clearInitialQuery());
// Verify initial query is cleared
expect(store.getState().initialQuery.initialPrompt).toBeNull();
expect(store.getState().initialQuery.initialQuery).toBeNull();
});
});

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