Squashed commit of the following:
commit 7d6476d3297860f74c276d571da995d958a8cc1a
Author: 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`
commit 5df2aa7939b45d85a2c2b5de9ac0522330d1502a
Author: 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`
commit 6a256fef4c7950b7ee82fb801e70c83afe6b6f8b
Author: 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
commit 370d6dbf5df75d78e3878877968e8cd309d6d7fb
Author: 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.
- Update `openai` dependency from ^v0.27.10 to ^v1.7.2
- Update poetry.lock
- Update code for changed endpoints and new output types of OpenAI library
- Replace uses of `AssistantChatMessageDict` by `AssistantChatMessage`
- Update `PromptStrategy`, `BaseAgent`, and all of their subclasses accordingly
- Update `OpenAIProvider`, `OpenAICredentials`, azure.yaml.template, .env.template and test_config.py to work with new separate `AzureOpenAI` client
- Remove `_OpenAIRetryHandler` and implement retry mechanism with `tenacity`
- Rewrite pytest fixture `cached_openai_client` (renamed from `patched_api_requestor`) for OpenAI v1 library
* Update `openai` dependency from `^0.27.8` to `^1.7.2`
* Update `litellm` dependency from `^0.1.821` to `^1.17.9`
* Migrate llm.py from OpenAI module-level client to client instance
* Update return types in llm.py for new OpenAI and LiteLLM versions
* Also remove `Exception` as a return type because they are raised, not returned
* Update tutorials/003_crafting_agent_logic.md accordingly
Note: this changes the output types of the functions in `forge.llm`: `chat_completion_request`, `create_embedding_request`, `transcribe_audio`
* docs: Add documentation on how to use Agent Protocol in the template
- Added documentation on how to use Agent Protocol and its settings in the `.env.template` file.
- An explanation is provided for the `AP_SERVER_PORT` and `AP_SERVER_DB_URL` settings.
- This change aims to improve the understanding and usage of Agent Protocol in the project.
* docs: Update usage.md with information about configuring the API port
- Update the documentation for the `serve` mode in `usage.md`
- Add information about configuring the port for the API server using the `AP_SERVER_PORT` environment variable.
---------
Co-authored-by: Reinier van der Leer <pwuts@agpt.co>
When executing `port = os.getenv("PORT", 8000)` if the port is being fetched from a `.env` file it is fetched as a string.
This caused an error: `TypeError: 'str' object cannot be interpreted as an integer`
* refactor(benchmark): Deduplicate configuration loading logic
- Move the configuration loading logic to a separate `load_agbenchmark_config` function in `agbenchmark/config.py` module.
- Replace the duplicate loading logic in `conftest.py`, `generate_test.py`, `ReportManager.py`, `reports.py`, and `__main__.py` with calls to `load_agbenchmark_config` function.
* fix(benchmark): Fix type errors, linting errors, and clean up CLI validation in __main__.py
- Fixed type errors and linting errors in `__main__.py`
- Improved the readability of CLI argument validation by introducing a separate function for it
* refactor(benchmark): Lint and typefix app.py
- Rearranged and cleaned up import statements
- Fixed type errors caused by improper use of `psutil` objects
- Simplified a number of `os.path` usages by converting to `pathlib`
- Use `Task` and `TaskRequestBody` classes from `agent_protocol_client` instead of `.schema`
* refactor(benchmark): Replace `.agent_protocol_client` by `agent-protcol-client`, clean up schema.py
- Remove `agbenchmark.agent_protocol_client` (an offline copy of `agent-protocol-client`).
- Add `agent-protocol-client` as a dependency and change imports to `agent_protocol_client`.
- Fix type annotation on `agent_api_interface.py::upload_artifacts` (`ApiClient` -> `AgentApi`).
- Remove all unused types from schema.py (= most of them).
* refactor(benchmark): Use pathlib in agent_interface.py and agent_api_interface.py
* refactor(benchmark): Improve typing, response validation, and readability in app.py
- Simplified response generation by leveraging type checking and conversion by FastAPI.
- Introduced use of `HTTPException` for error responses.
- Improved naming, formatting, and typing in `app.py::create_evaluation`.
- Updated the docstring on `app.py::create_agent_task`.
- Fixed return type annotations of `create_single_test` and `create_challenge` in generate_test.py.
- Added default values to optional attributes on models in report_types_v2.py.
- Removed unused imports in `generate_test.py`
* refactor(benchmark): Clean up logging and print statements
- Introduced use of the `logging` library for unified logging and better readability.
- Converted most print statements to use `logger.debug`, `logger.warning`, and `logger.error`.
- Improved descriptiveness of log statements.
- Removed unnecessary print statements.
- Added log statements to unspecific and non-verbose `except` blocks.
- Added `--debug` flag, which sets the log level to `DEBUG` and enables a more comprehensive log format.
- Added `.utils.logging` module with `configure_logging` function to easily configure the logging library.
- Converted raw escape sequences in `.utils.challenge` to use `colorama`.
- Renamed `generate_test.py::generate_tests` to `load_challenges`.
* refactor(benchmark): Remove unused server.py and agent_interface.py::run_agent
- Remove unused server.py file
- Remove unused run_agent function from agent_interface.py
* refactor(benchmark): Clean up conftest.py
- Fix and add type annotations
- Rewrite docstrings
- Disable or remove unused code
- Fix definition of arguments and their types in `pytest_addoption`
* refactor(benchmark): Clean up generate_test.py file
- Refactored the `create_single_test` function for clarity and readability
- Removed unused variables
- Made creation of `Challenge` subclasses more straightforward
- Made bare `except` more specific
- Renamed `Challenge.setup_challenge` method to `run_challenge`
- Updated type hints and annotations
- Made minor code/readability improvements in `load_challenges`
- Added a helper function `_add_challenge_to_module` for attaching a Challenge class to the current module
* fix(benchmark): Fix and add type annotations in execute_sub_process.py
* refactor(benchmark): Simplify const determination in agent_interface.py
- Simplify the logic that determines the value of `HELICONE_GRAPHQL_LOGS`
* fix(benchmark): Register category markers to prevent warnings
- Use the `pytest_configure` hook to register the known challenge categories as markers. Otherwise, Pytest will raise "unknown marker" warnings at runtime.
* refactor(benchmark/challenges): Fix indentation in 4_revenue_retrieval_2/data.json
* refactor(benchmark): Update agent_api_interface.py
- Add type annotations to `copy_agent_artifacts_into_temp_folder` function
- Add note about broken endpoint in the `agent_protocol_client` library
- Remove unused variable in `run_api_agent` function
- Improve readability and resolve linting error
* feat(benchmark): Improve and centralize pathfinding
- Search path hierarchy for applicable `agbenchmark_config`, rather than assuming it's in the current folder.
- Create `agbenchmark.utils.path_manager` with `AGBenchmarkPathManager` and exporting a `PATH_MANAGER` const.
- Replace path constants defined in __main__.py with usages of `PATH_MANAGER`.
* feat(benchmark/cli): Clean up and improve CLI
- Updated commands, options, and their descriptions to be more intuitive and consistent
- Moved slow imports into the entrypoints that use them to speed up application startup
- Fixed type hints to match output types of Click options
- Hid deprecated `agbenchmark start` command
- Refactored code to improve readability and maintainability
- Moved main entrypoint into `run` subcommand
- Fixed `version` and `serve` subcommands
- Added `click-default-group` package to allow using `run` implicitly (for backwards compatibility)
- Renamed `--no_dep` to `--no-dep` for consistency
- Fixed string formatting issues in log statements
* refactor(benchmark/config): Move AgentBenchmarkConfig and related functions to config.py
- Move the `AgentBenchmarkConfig` class from `utils/data_types.py` to `config.py`.
- Extract the `calculate_info_test_path` function from `utils/data_types.py` and move it to `config.py` as a private helper function `_calculate_info_test_path`.
- Move `load_agent_benchmark_config()` to `AgentBenchmarkConfig.load()`.
- Changed simple getter methods on `AgentBenchmarkConfig` to calculated properties.
- Update all code references according to the changes mentioned above.
* refactor(benchmark): Fix ReportManager init parameter types and use pathlib
- Fix the type annotation of the `benchmark_start_time` parameter in `ReportManager.__init__`, was mistyped as `str` instead of `datetime`.
- Change the type of the `filename` parameter in the `ReportManager.__init__` method from `str` to `Path`.
- Rename `self.filename` with `self.report_file` in `ReportManager`.
- Change the way the report file is created, opened and saved to use the `Path` object.
* refactor(benchmark): Improve typing surrounding ChallengeData and clean up its implementation
- Use `ChallengeData` objects instead of untyped `dict` in app.py, generate_test.py, reports.py.
- Remove unnecessary methods `serialize`, `get_data`, `get_json_from_path`, `deserialize` from `ChallengeData` class.
- Remove unused methods `challenge_from_datum` and `challenge_from_test_data` from `ChallengeData class.
- Update function signatures and annotations of `create_challenge` and `generate_single_test` functions in generate_test.py.
- Add types to function signatures of `generate_single_call_report` and `finalize_reports` in reports.py.
- Remove unnecessary `challenge_data` parameter (in generate_test.py) and fixture (in conftest.py).
* refactor(benchmark): Clean up generate_test.py, conftest.py and __main__.py
- Cleaned up generate_test.py and conftest.py
- Consolidated challenge creation logic in the `Challenge` class itself, most notably the new `Challenge.from_challenge_spec` method.
- Moved challenge selection logic from generate_test.py to the `pytest_collection_modifyitems` hook in conftest.py.
- Converted methods in the `Challenge` class to class methods where appropriate.
- Improved argument handling in the `run_benchmark` function in `__main__.py`.
* refactor(benchmark/config): Merge AGBenchmarkPathManager into AgentBenchmarkConfig and reduce fragmented/global state
- Merge the functionality of `AGBenchmarkPathManager` into `AgentBenchmarkConfig` to consolidate the configuration management.
- Remove the `.path_manager` module containing `AGBenchmarkPathManager`.
- Pass the `AgentBenchmarkConfig` and its attributes through function arguments to reduce global state and improve code clarity.
* feat(benchmark/serve): Configurable port for `serve` subcommand
- Added `--port` option to `serve` subcommand to allow for specifying the port to run the API on.
- If no `--port` option is provided, the port will default to the value specified in the `PORT` environment variable, or 8080 if not set.
* feat(benchmark/cli): Add `config` subcommand
- Added a new subcommand `config` to the AGBenchmark CLI, to display information about the present AGBenchmark config.
* fix(benchmark): Gracefully handle incompatible challenge spec files in app.py
- Added a check to skip deprecated challenges
- Added logging to allow debugging of the loading process
- Added handling of validation errors when parsing challenge spec files
- Added missing `spec_file` attribute to `ChallengeData`
* refactor(benchmark): Move `run_benchmark` entrypoint to main.py, use it in `/reports` endpoint
- Move `run_benchmark` and `validate_args` from __main__.py to main.py
- Replace agbenchmark subprocess in `app.py:run_single_test` with `run_benchmark`
- Move `get_unique_categories` from __main__.py to challenges/__init__.py
- Move `OPTIONAL_CATEGORIES` from __main__.py to challenge.py
- Reduce operations on updates.json (including `initialize_updates_file`) outside of API
* refactor(benchmark): Remove unused `/updates` endpoint and all related code
- Remove `updates_json_file` attribute from `AgentBenchmarkConfig`
- Remove `get_updates` and `_initialize_updates_file` in app.py
- Remove `append_updates_file` and `create_update_json` functions in agent_api_interface.py
- Remove call to `append_updates_file` in challenge.py
* refactor(benchmark/config): Clean up and update docstrings on `AgentBenchmarkConfig`
- Add and update docstrings
- Change base class from `BaseModel` to `BaseSettings`, allow extras for backwards compatibility
- Make naming of path attributes on `AgentBenchmarkConfig` more consistent
- Remove unused `agent_home_directory` attribute
- Remove unused `workspace` attribute
* fix(benchmark): Restore mechanism to select (optional) categories in agent benchmark config
* fix(benchmark): Update agent-protocol-client to v1.1.0
- Fixes issue with fetching task artifact listings
gitpython was installed as an indirect dependency via agbenchmark. The release builds don't contain agbenchmark and thus also lack the gitpython package, which breaks the image.
- Move `auto-gpt-plugin-template` from dev dependencies to regular dependencies in `pyproject.toml`.
- Fixes#6566 - No module named 'auto_gpt_plugin_template'.
- Add logging to capture errors raised during execution of actions in the Agent
- Move `fmt_kwargs` function from `agent_protocol_server.py` to `logs/utils.py`
- Update the `read_file` function in `file_operations.py` to pass the file's extension to the `decode_textual_file` function.
- Modify the `decode_textual_file` function in `file_operations_utils.py` to accept the file extension as an argument.
- Update the `content` property in the `FileContextItem` class in `context_item.py` to pass the file's extension to the `decode_textual_file` function.
- Update the `test_parsers` function in `test_text_file_parsers.py` to pass the file extension to the `decode_textual_file` function.
- Prevent the Agent from treating `AgentTerminated` like it would any other exception raised by a command.
- The agent should raise AgentTerminated exception to exit the loop.
- Fix the parsing of invalid LLM responses by appending an error message to the prompt and allowing the LLM to fix its mistakes.
- Update the `OpenAIProvider` to handle the self-correction process and limit the number of attempts to fix parsing errors.
- Update the `BaseAgent` to profit from the new pasing and parse-fixing mechanism.
This change ensures that the system can handle and recover from errors in parsing LLM responses.
Hopefully this fixes#1407 once and for all.
- Updated the quick links and user guide URLs in the bulletin
- Released v0.5.0 with cloud-readiness, a new UI, support for the newest Agent Protocol version, and other improvements
See the release notes on Github for more details: https://github.com/Significant-Gravitas/AutoGPT/releases
- Removed unnecessary print_attribute calls in configurators.py and configurator.py files
- Consolidated printing of configuration attributes in main.py for improved readability and reduced log spam in Agent Protocol mode
- Update GCSFileWorkspace.initialize() to handle cases where the bucket doesn't exist and create it if necessary
- Add logging to S3FileWorkspace.initialize() and GCSFileWorkspace.initialize()
- Update GCSFileWorkspace.list() and S3FileWorkspace.list() to correctly handle nested paths and return the relative paths of files
- Fix tests for GCSFileWorkspace and S3FileWorkspace to account for the changes in initialization and listing behavior
- Fix S3FileWorkspace.open_file() to correctly switch between binary and text mode
- Added tests to verify the fixes in workspace initialization and listing behavior
- Fixes#6553 (`web_search` command not working)
- v3.x.x of the duckduckgo-search library no longer works, so updating to v4.0.0 unbreaks the `web_search` command
feat: Add dependencies required to use PostgreSQL
- Added psycopg2-binary version 2.9.9 to the dependencies in pyproject.toml
- Updated the poetry.lock file with the new package information
- Update the signature of `FileWorkspace.open_file` and fix implementations in every workspace backend
- Replace `open()` with `workspace.open_file` in the `read_file` command to use the workspace's file opening functionality
- Fix the parametrization of the `test_text_file_parsers` test to correctly test text file parsers
- Adjusted path processing and use of `agent.workspace` in the file_operations.py module to prevent double path resolution.
- Updated the `is_duplicate_operation` and `log_operation` functions in file_operations.py to use the `make_relative` argument of the `sanitize_path_arg` decorator.
- Refactored the `write_to_file`, `list_folder`, and `list_files` functions in file_operations.py to accept both string and Path objects as the path argument.
- Modified the GCSFileWorkspace and S3FileWorkspace classes in the file_workspace module to ensure that the root path is always an absolute path.
This commit addresses issues with path processing in the file_operations.py module and across different workspace backend implementations. The changes ensure that relative paths are correctly converted to absolute paths where necessary and that the file operations logic functions consistently handle path arguments as strings or Path objects. Additionally, the GCSFileWorkspace and S3FileWorkspace classes now enforce that the root path is always an absolute path.
- Remove X- prefix from X-AutoGPT-UserID, X-AP-TaskID, and X-AP-StepID headers
- Refactor literal references to "ask_user" to `ask_user.__name__` in AgentProtocolServer
- Fix type annotation for `agent_id` in `BaseAgentSettings` class
- Add assertion to ensure `agent_id` is not an empty string in `AgentManager.get_agent_dir()` method
- Change type of `override_name` and `override_role` to be optional in `apply_overrides_to_ai_settings()` function
- Update `AgentProtocolServer` to include `X-AP-TaskID` and `X-AutoGPT-UserID` headers in outgoing requests for Agent Protocol tasks.
- Modify `ModelProvider` and `OpenAIProvider` to allow configuring extra headers to be added to all outgoing requests.
- Fix the type of the `task_id` parameter in `AgentProtocolServer.get_task`
- Update the return type of the `AgentProtocolServer.get_artifact` method to `StreamingResponse`.
- Fix the Content-Disposition header in the response to include quotes around the filename.
- Fixed the persistence issue of additional_input and additional_output in the Step class in `forge.sdk`. The additional_input and additional_output attributes were not typed and initialized properly.
* refactor: Rename FileWorkspace to LocalFileWorkspace and create FileWorkspace abstract class
- Rename `FileWorkspace` to `LocalFileWorkspace` to provide a more descriptive name for the class that represents a file workspace that works with local files.
- Create a new base class `FileWorkspace` to serve as the parent class for `LocalFileWorkspace`. This allows for easier extension and customization of file workspaces in the future.
- Update import statements and references to `FileWorkspace` throughout the codebase to use the new naming conventions.
* feat: Add S3FileWorkspace + tests + test setups for CI and Docker
- Added S3FileWorkspace class to provide an interface for interacting with a file workspace and storing files in an S3 bucket.
- Updated pyproject.toml to include dependencies for boto3 and boto3-stubs.
- Implemented unit tests for S3FileWorkspace.
- Added MinIO service to Docker CI to allow testing S3 features in CI.
- Added autogpt-test service config to docker-compose.yml for local testing with MinIO.
* ci(docker): tee test output instead of capturing
* fix: Improve error handling in S3FileWorkspace.initialize()
- Do not tolerate all `botocore.exceptions.ClientError`s
- Raise the exception anyways if the error is not "NoSuchBucket"
* feat: Add S3 workspace backend support and S3Credentials
- Added support for S3 workspace backend in the Autogpt configuration
- Added a new sub-config `S3Credentials` to store S3 credentials
- Modified the `.env.template` file to include variables related to S3 credentials
- Added a new `s3_credentials` attribute on the `Config` class to store S3 credentials
- Moved the `unmasked` method from `ModelProviderCredentials` to the parent `ProviderCredentials` class to handle unmasking for S3 credentials
* fix(agent/tests): Fix S3FileWorkspace initialization in test_s3_file_workspace.py
- Update the S3FileWorkspace initialization in the test_s3_file_workspace.py file to include the required S3 Credentials.
* refactor: Remove S3Credentials and add get_workspace function
- Remove `S3Credentials` as boto3 will fetch the config from the environment by itself
- Add `get_workspace` function in `autogpt.file_workspace` module
- Update `.env.template` and tests to reflect the changes
* feat(agent/workspace): Make agent workspace backend configurable
- Modified `autogpt.file_workspace.get_workspace` function to either take a workspace `id` or `root_path`.
- Modified `FileWorkspaceMixin` to use the `get_workspace` function to set up the workspace.
- Updated the type hints and imports accordingly.
* feat(agent/workspace): Add GCSFileWorkspace for Google Cloud Storage
- Added support for Google Cloud Storage as a storage backend option in the workspace.
- Created the `GCSFileWorkspace` class to interface with a file workspace stored in a Google Cloud Storage bucket.
- Implemented the `GCSFileWorkspaceConfiguration` class to handle the configuration for Google Cloud Storage workspaces.
- Updated the `get_workspace` function to include the option to use Google Cloud Storage as a workspace backend.
- Added unit tests for the new `GCSFileWorkspace` class.
* fix: Unbreak use of non-local workspaces in AgentProtocolServer
- Modify the `_get_task_agent_file_workspace` method to handle both local and non-local workspaces correctly
