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Squashed commit of the following: commit7d6476d329Author: Reinier van der Leer <pwuts@agpt.co> Date: Tue Jan 9 18:10:45 2024 +0100 refactor(benchmark/challenge): Set up structure to support more challenge providers - Move `Challenge`, `ChallengeData`, `load_challenges` to `challenges/builtin.py` and rename to `BuiltinChallenge`, `BuiltinChallengeSpec`, `load_builtin_challenges` - Create `BaseChallenge` to serve as interface and base class for different challenge implementations - Create `ChallengeInfo` model to serve as universal challenge info object - Create `get_challenge_from_source_uri` function in `challenges/__init__.py` - Replace `ChallengeData` by `ChallengeInfo` everywhere except in `BuiltinChallenge` - Add strong typing to `task_informations` store in app.py - Use `call.duration` in `finalize_test_report` and remove `timer` fixture - Update docstring on `challenges/__init__.py:get_unique_categories` - Add docstring to `generate_test.py` commit5df2aa7939Author: Reinier van der Leer <pwuts@agpt.co> Date: Tue Jan 9 16:58:01 2024 +0100 refactor(benchmark): Refactor & rename functions in agent_interface.py and agent_api_interface.py - `copy_artifacts_into_temp_folder` -> `copy_challenge_artifacts_into_workspace` - `copy_agent_artifacts_into_folder` -> `download_agent_artifacts_into_folder` - Reorder parameters of `run_api_agent`, `copy_challenge_artifacts_into_workspace`; use `Path` instead of `str` commit6a256fef4cAuthor: Reinier van der Leer <pwuts@agpt.co> Date: Tue Jan 9 16:02:25 2024 +0100 refactor(benchmark): Refactor & typefix report generation and handling logic - Rename functions in reports.py and ReportManager.py to better reflect what they do - `get_previous_test_results` -> `get_and_update_success_history` - `generate_single_call_report` -> `initialize_test_report` - `finalize_reports` -> `finalize_test_report` - `ReportManager.end_info_report` -> `SessionReportManager.finalize_session_report` - Modify `pytest_runtest_makereport` hook in conftest.py to finalize the report immediately after the challenge finishes running instead of after teardown - Move result processing logic from `initialize_test_report` to `finalize_test_report` in reports.py - Use `Test` and `Report` types from report_types.py where possible instead of untyped dicts: reports.py, utils.py, ReportManager.py - Differentiate `ReportManager` into `SessionReportManager`, `RegressionTestsTracker`, `SuccessRateTracker` - Move filtering of optional challenge categories from challenge.py (`Challenge.skip_optional_categories`) to conftest.py (`pytest_collection_modifyitems`) - Remove unused `scores` fixture in conftest.py commit370d6dbf5dAuthor: Reinier van der Leer <pwuts@agpt.co> Date: Tue Jan 9 15:16:43 2024 +0100 refactor(benchmark): Simplify models in report_types.py - Removed ForbidOptionalMeta and BaseModelBenchmark classes. - Changed model attributes to optional: `Metrics.difficulty`, `Metrics.success`, `Metrics.success_percentage`, `Metrics.run_time`, and `Test.reached_cutoff`. - Added validator to `Metrics` model to require `success` and `run_time` fields if `attempted=True`. - Added default values to all optional model fields. - Removed duplicate imports. - Added condition in process_report.py to prevent null lookups if `metrics.difficulty` is not set.
As a user
pip install auto-gpt-benchmarks- Add boilerplate code to run and kill agent
agbenchmark--category challenge_categoryto run tests in a specific category--mockto only run mock tests if they exists for each test--noregto skip any tests that have passed in the past. When you run without this flag and a previous challenge that passed fails, it will now not be regression tests
- We call boilerplate code for your agent
- Show pass rate of tests, logs, and any other metrics
Contributing
Diagrams: https://whimsical.com/agbenchmark-5n4hXBq1ZGzBwRsK4TVY7x
To run the existing mocks
- clone the repo
auto-gpt-benchmarks pip install poetrypoetry shellpoetry installcp .env_example .envgit submodule update --init --remote --recursiveuvicorn server:app --reloadagbenchmark --mockKeep config the same and watch the logs :)
To run with mini-agi
- Navigate to
auto-gpt-benchmarks/agent/mini-agi pip install -r requirements.txtcp .env_example .env, setPROMPT_USER=falseand add yourOPENAI_API_KEY=. SsetMODEL="gpt-3.5-turbo"if you don't have access togpt-4yet. Also make sure you have Python 3.10^ installed- set
AGENT_NAME=mini-agiin.envfile and where you want yourREPORT_LOCATIONto be - Make sure to follow the commands above, and remove mock flag
agbenchmark
- To add requirements
poetry add requirement.
Feel free to create prs to merge with main at will (but also feel free 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 master to last working commit
Let people know what beautiful code you write does, document everything well
Share your progress :)
Dataset
Manually created, existing challenges within Auto-Gpt, https://osu-nlp-group.github.io/Mind2Web/
How do I add new agents to agbenchmark ?
Example with smol developer.
1- Create a github branch with your agent following the same pattern as this example:
https://github.com/smol-ai/developer/pull/114/files
2- Create the submodule and the github workflow by following the same pattern as this example:
https://github.com/Significant-Gravitas/Auto-GPT-Benchmarks/pull/48/files
How do I run agent in different environments?
To just use as the benchmark for your agent. pip install the package and run agbenchmark
For internal Auto-GPT ci runs, specify the AGENT_NAME you want you use and set the HOME_ENV.
Ex. AGENT_NAME=mini-agi
To develop agent alongside benchmark, you can specify the AGENT_NAME you want you use and add as a submodule to the repo