- 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
* 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.
