Simple boilerplate code that spins up a webserver to plug their agent into. We call multiple tasks by invoking different pytest commands on folders and once the agent stops or reaches 50 loops (which they will have to define). We handle the deletion of files after a run loop ends. Then we call call the POST request for the next task. Then we will spit out a combined benchmark once all tests run

Agent adds tests by adding to our repo
Agent abstracted from benchmark
Scalable (parallel servers running tests)
Better standardization

Diagrams (out of date, cloud oriented): https://whimsical.com/agbenchmark-5n4hXBq1ZGzBwRsK4TVY7x

Contributing

Make sure you have poetry installed - pip install poetry.
Then poetry install for dependencies
To add requirements poetry add requirement.
To run in venv poetry run python script.py

Feel free to merge with main at will (but also to ask for review) - if you can't send msg in R&D chat for access.

If you push at any point and break things - it'll happen to everyone - fix it asap. Step 1 is to revert main to last working commit

Let people know what beautiful code you write does, document everything well

Share your progress :)

Api

FastAPI with REST, import requests

POST hostname:8080/challenges
{
   "test_name": ""
   "challenge": "memory" - optional
}

Auth:

get preSignedUrl from API

POST preSignedUrl
{
   "artifacts": [{}]
}

Workspace

Kubernetes with AWS3 or GCP

Challenges

Dataset

Manually created, existing challenges within Auto-Gpt, https://osu-nlp-group.github.io/Mind2Web/

Simple challenge creation through a DSL (domain specific language)

Challenge TicTacToeCoding
    Description "The agent should implement a basic tic-tac-toe game in Python."
    Artifacts {
        Code "tictactoe.py"
    }
    Tasks {
        Code "Write a function to initialize the game board."
        Code "Write a function to handle a player's turn."
        Code "Write a function to check for a winning move."
        Test "Write tests for the blog post model, serializer, and view."
        Command "Run Django's test suite to ensure everything is working as expected."
    }
    SuccessCriteria {
        Correctness "The game should correctly alternate between two players."
        Correctness "The game should correctly identify a winning move."
        Efficiency "The game should not use unnecessary computational resources."
        Design "The solution should follow good practices for Django and Django Rest Framework."
    }
EndChallenge

Validators

Designed to handle specific types of output (e.g., text, code, structured data)

Logging

Log different requests coming in - write file, change file, etc. Maybe a db in the future for metrics, logs, etc

Written Challenges

For code, writing we can create a reference text and use metrics like METEOR, BERTScore, BARTScore

Repo

|-- agbenchmark/ **main project directory**
| |-- **init**.py
| |-- server/
| | |-- **init**.py
| | |-- api.py **opens server on host and exposes urls**
| | |-- utils.py
| |-- benchmark/
| | |-- **init**.py
| | |-- benchmark.py **combining scores, metrics, final evaluation**
| | |-- run.py **entry point. sets everything up**
| | |-- challenges/ **challenges across different metrics**
| | | |-- **init**.py
| | | |-- Challenge.py **easy challenge creation through Challenge class. potentially how DSL is defined. may need to inherit challenge class like Adaptability(Challenge)**
| | | |-- utils.py
| | | |-- adaptability.py
| | | |-- basic_abilities.py
| | | |-- code.py
| | | |-- memory.py
| | | |-- retrieval.py
| | | |-- web_navigation.py
| | | |-- writing.py
| |-- workspace/ **workspace related func**
| | |-- **init**.py
| | |-- workspace_manager.py **creation, deletion, preSignedUrl generation**
| | |-- cloud_services/
| | | |-- **init**.py
| | | |-- aws.py **not finalized, but write, read, and del files**
|-- tests/ **test func of agbenchmark**
| |-- **init**.py
| |-- test_api.py
| |-- test_benchmark.py
| |-- test_workspace_manager.py

Later: GitHub Actions integration, OpenAPI?, good versioning and backward compatibility

Languages

JavaScript 68.5%

Python 18.3%

Jupyter Notebook 8.3%

Dart 3.4%

C++ 0.4%

Other 0.8%