- 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
* feat: Refactor config loading and initialization to be modular and decentralized
- Refactored the `ConfigBuilder` class to support modular loading and initialization of the configuration from environment variables.
- Implemented recursive loading and initialization of nested config objects.
- Introduced the `SystemConfiguration` base class to provide common functionality for all system settings.
- Added the `from_env` attribute to the `UserConfigurable` decorator to provide environment variable mappings.
- Updated the `Config` class and its related classes to inherit from `SystemConfiguration` and use the `UserConfigurable` decorator.
- Updated `LoggingConfig` and `TTSConfig` to use the `UserConfigurable` decorator for their fields.
- Modified the implementation of the `build_config_from_env` method in `ConfigBuilder` to utilize the new modular and recursive loading and initialization logic.
- Updated applicable test cases to reflect the changes in the config loading and initialization logic.
This refactor improves the flexibility and maintainability of the configuration loading process by introducing modular and recursive behavior, allowing for easier extension and customization through environment variables.
* refactor: Move OpenAI credentials into `OpenAICredentials` sub-config
- Move OpenAI API key and other OpenAI credentials from the global config to a new sub-config called OpenAICredentials.
- Update the necessary code to use the new OpenAICredentials sub-config instead of the global config when accessing OpenAI credentials.
- (Hopefully) unbreak Azure support.
- Update azure.yaml.template.
- Enable validation of assignment operations on SystemConfiguration and SystemSettings objects.
* feat: Update AutoGPT configuration options and setup instructions
- Added new configuration options for logging and OpenAI usage to .env.template
- Removed deprecated configuration options in config/config.py
- Updated setup instructions in Docker and general setup documentation to include information on using Azure's OpenAI services
* fix: Fix image generation with Dall-E
- Fix issue with image generation with Dall-E API
Additional user context: This commit fixes an issue with image generation using the Dall-E API. The code now correctly retrieves the API key from the agent's legacy configuration.
* refactor(agent/core): Refactor `autogpt.core.configuration.schema` and update docstrings
- Refactor the `schema.py` file in the `autogpt.core.configuration` module.
- Added docstring to `SystemConfiguration.from_env()`
- Updated docstrings for functions `_get_user_config_values`, `_get_non_default_user_config_values`, `_recursive_init_model`, `_recurse_user_config_fields`, and `_recurse_user_config_values`.
- Update the instruction in the prompt strategy to ensure the response is pure JSON.
- Remove unnecessary text and make the instruction clearer.
- Also update the error logging to include the received JSON content.
This commit refactors the code in the `one_shot.py` file and the `utilities.py` file.
- Update the pytest command in the .pre-commit-config.yaml file to use Poetry run instead of directly running pytest in the autogpts/autogpt directory.
- Refactored the `MemoryItem` class in the `autogpt.memory.vector.memory_item` module to improve code organization and readability.
- Split the `MemoryItem` class into two separate classes: `MemoryItem` and `MemoryItemFactory`.
- Modified the `get_embedding` function in the `autogpt.memory.vector.utils` module to accept an `EmbeddingModelProvider` for creating embeddings.
- Updated the usage of the `get_embedding` function in the `MemoryItem` class to pass the `embedding_provider` parameter.
- Updated the imports in the affected modules.
- Modify check_requirements.py to correctly handle optional dependencies
- Skip optional dependencies when iterating through dependence group dependencies in check_requirements.py
- Update autogpt.bat to use `poetry install` instead of `%PYTHON_CMD% -m poetry install`
- Update autogpt.sh to use `poetry install` instead of `$PYTHON_CMD -m poetry install`
- Use `poetry run` to execute the `autogpt` command in both scripts
- Update the reference to the VCR submodule in the autogpt tests
- Previous reference: 1896d8ac12ff1d27b7e9e5db6549abc38b260b40
- New reference: 9996f1d104a1e4f33c1e10aa664d01ea78db2a06
- Updated the `run` script to also check if `$OPENAI_API_KEY` is empty before copying `.env.example` and prompting the user to set API keys.
- Modified the `setup` script to install `--extras benchmark` separately from the initial `poetry install` command.
- Added `POETRY_INSTALLER_PARALLEL=false` flag to prevent conflicts between `forge` and `agbenchmark` during installation.
* Fix all but one flake8 linting errors
* Remove unused imports
* Wrap strings that are too long
* Add basic autogpts/autogpt/.flake8
* Delete planning_agent.py
* Delete default_prompts.py
* Delete _test_json_parser.py
* Refactor the example function call in AgentProfileGeneratorConfiguration from a string to an object
* Rewrite/update docstrings here and there while I'm at it
* Minor change to the description of the `open_file` command
* Use `user-agent` from config in web_selenium.py
* Delete hardcoded ABILITIES from core/planning/templates.py
* Delete duplicate and superseded test from test_image_gen.py
* Fix parameter definitions in mock_commands.py
* Delete code analysis blocks from test_spinner.py, test_url_validation.py
- Modify the test_url_validation_fails_local_path function to remove the specific match parameter and raise the ValueError without any match requirement.
- Update `test_config.py` to check if `config.smart_llm` starts with "gpt-4"
- Delete `test_retry_provider_openai.py` as it is no longer needed
- Update `test_url_validation.py` to properly test local file URLs
- Update `test_web_search.py` to assert against expected parts of output
- Refactor the `run_auto_gpt_server` function to make the Agent Protocol server database URL configurable.
- Use the `os.getenv` method to retrieve the database URL from the environment variable `AP_SERVER_DB_URL`.
- Created a new `LoggingConfig` class to represent the logging configuration in the `Config` class.
- Created a new `LogFormatName` enum to represent the available log formats: 'simple', 'debug', and 'structured_google_cloud'.
- Modified the `configure_logging` function to also accept an unpacked `LoggingConfig` object for arguments.
- Updated the `configure_logging` function to use the appropriate log format based on the log level.
- Added a `StructuredLoggingFormatter` class to handle formatting for structured logs.
- Updated the import statements and usages of `configure_logging` etc. in relevant modules to reflect the changes.
- Updated the `config` fixture in the unit tests to include the new logging configuration attributes.
- Updated the CLI with new parameters for log level and format.
- Reordered the parameters of the CLI.
- Removed memory related parameter from CLI.
- Remove the unused debug argument from the functions `inspect_zip_for_modules`, `initialize_openai_plugins`, `instantiate_openai_plugin_clients`, and `scan_plugins`.
- The debug argument was not being used in these functions and was unnecessary.
