mirror of
https://github.com/Monadical-SAS/cubbi.git
synced 2025-12-20 12:19:07 +00:00
* feat: migrate container configuration from env vars to YAML config files
- Replace environment variable-based configuration with structured YAML config files
- Add Pydantic models for type-safe configuration management in cubbi_init.py
- Update container.py to generate /cubbi/config.yaml and mount into containers
- Simplify goose plugin to extract provider from default model format
- Remove complex environment variable handling in favor of direct config access
- Maintain backward compatibility while enabling cleaner plugin architecture
* feat: optimize goose plugin to only pass required API key for selected model
- Update goose plugin to set only the API key for the provider of the selected model
- Add selective API key configuration for anthropic, openai, google, and openrouter
- Update README.md with comprehensive automated testing documentation
- Add litellm/gpt-oss:120b to test.sh model matrix (now 5 images × 4 models = 20 tests)
- Include single prompt command syntax for each tool in the documentation
* feat: add comprehensive integration tests with pytest parametrization
- Create tests/test_integration.py with parametrized tests for 5 images × 4 models (20 combinations)
- Add pytest configuration to exclude integration tests by default
- Add integration marker for selective test running
- Include help command tests and image availability tests
- Document test usage in tests/README_integration.md
Integration tests cover:
- goose, aider, claudecode, opencode, crush images
- anthropic/claude-sonnet-4-20250514, openai/gpt-4o, openrouter/openai/gpt-4o, litellm/gpt-oss:120b models
- Proper command syntax for each tool
- Success validation with exit codes and completion markers
Usage:
- pytest (regular tests only)
- pytest -m integration (integration tests only)
- pytest -m integration -k "goose" (specific image)
* feat: update OpenCode plugin with perfect multi-provider configuration
- Add global STANDARD_PROVIDERS constant for maintainability
- Support custom providers (with baseURL) vs standard providers
- Custom providers: include npm package, name, baseURL, apiKey, models
- Standard providers: include only apiKey and empty models
- Use direct API key values from cubbi config instead of env vars
- Only add default model to the provider that matches the default model
- Use @ai-sdk/openai-compatible for OpenAI-compatible providers
- Preserve model names without transformation
- All providers get required empty models{} section per OpenCode spec
This ensures OpenCode can properly recognize and use both native
providers (anthropic, openai, google, openrouter) and custom
providers (litellm, etc.) with correct configuration format.
* refactor: model is now a combination of provider/model
* feat: add separate integration test for Claude Code without model config
Claude Code is Anthropic-specific and doesn't require model selection like other tools.
Created dedicated test that verifies basic functionality without model preselection.
* feat: update Claude Code and Crush plugins to use new config system
- Claude Code plugin now uses cubbi_config.providers to get Anthropic API key
- Crush plugin updated to use cubbi_config.providers for provider configuration
- Both plugins maintain backwards compatibility with environment variables
- Consistent plugin structure across all cubbi images
* feat: add environments_to_forward support for images
- Add environments_to_forward field to ImageConfig and Image models
- Update container creation logic to forward specified environment variables from host
- Add environments_to_forward to claudecode cubbi_image.yaml to ensure Anthropic API key is always available
- Claude Code now gets required environment variables regardless of model selection
- This ensures Claude Code works properly even when other models are specified
Fixes the issue where Claude Code couldn't access Anthropic API key when using different model configurations.
* refactor: remove unused environment field from cubbi_image.yaml files
The 'environment' field was loaded but never processed at runtime.
Only 'environments_to_forward' is actually used to pass environment
variables from host to container.
Cleaned up configuration files by removing:
- 72 lines from aider/cubbi_image.yaml
- 42 lines from claudecode/cubbi_image.yaml
- 28 lines from crush/cubbi_image.yaml
- 16 lines from goose/cubbi_image.yaml
- Empty environment: [] from opencode/cubbi_image.yaml
This makes the configuration files cleaner and only contains
fields that are actually used by the system.
* feat: implement environment variable forwarding for aider
Updates aider to automatically receive all relevant environment variables
from the host, similar to how opencode works.
Changes:
- Added environments_to_forward field to aider/cubbi_image.yaml with
comprehensive list of API keys, configuration, and proxy variables
- Updated aider_plugin.py to use cubbi_config system for provider/model setup
- Environment variables now forwarded automatically during container creation
- Maintains backward compatibility with legacy environment variables
Environment variables forwarded:
- API Keys: OPENAI_API_KEY, ANTHROPIC_API_KEY, DEEPSEEK_API_KEY, etc.
- Configuration: AIDER_MODEL, GIT_* variables, HTTP_PROXY, etc.
- Timezone: TZ for proper log timestamps
Tested: All aider tests pass, environment variables confirmed forwarded.
* refactor: remove unused volumes and init fields from cubbi_image.yaml files
Both 'volumes' and 'init' fields were loaded but never processed at runtime.
These were incomplete implementations that didn't affect container behavior.
Removed from all 5 images:
- volumes: List with mountPath: /app (incomplete, missing host paths)
- init: pre_command and command fields (unused during container creation)
The cubbi_image.yaml files now only contain fields that are actually used:
- Basic metadata (name, description, version, maintainer, image)
- persistent_configs (working functionality)
- environments_to_forward (working functionality where present)
This makes the configuration files cleaner and eliminates confusion
about what functionality is actually implemented.
* refactor: remove unused ImageInit and VolumeMount models
These models were only referenced in the Image model definition but
never used at runtime since we removed all init: and volumes: fields
from cubbi_image.yaml files.
Removed:
- VolumeMount class (mountPath, description fields)
- ImageInit class (pre_command, command fields)
- init: Optional[ImageInit] field from Image model
- volumes: List[VolumeMount] field from Image model
The Image model now only contains fields that are actually used:
- Basic metadata (name, description, version, maintainer, image)
- environment (loaded but unused - kept for future cleanup)
- persistent_configs (working functionality)
- environments_to_forward (working functionality)
This makes the data model cleaner and eliminates dead code.
* feat: add interactive configuration command
Adds `cubbi configure` command for interactive setup of LLM providers
and models through a user-friendly questionnaire interface.
New features:
- Interactive provider configuration (OpenAI, Anthropic, OpenRouter, etc.)
- API key management with environment variable references
- Model selection with provider/model format validation
- Default settings configuration (image, ports, volumes, etc.)
- Added questionary dependency for interactive prompts
Changes:
- Added cubbi/configure.py with full interactive configuration logic
- Added configure command to cubbi/cli.py
- Updated uv.lock with questionary and prompt-toolkit dependencies
Usage: `cubbi configure`
* refactor: update integration tests for current functionality
Updates integration tests to reflect current cubbi functionality:
test_integration.py:
- Simplified image list (removed crush temporarily)
- Updated model list with current supported models
- Removed outdated help command tests that were timing out
- Simplified claudecode test to basic functionality test
- Updated command templates for current tool versions
test_integration_docker.py:
- Cleaned up container management tests
- Fixed formatting and improved readability
- Updated assertion formatting for better error messages
These changes align the tests with the current state of the codebase
and remove tests that were causing timeouts or failures.
* fix: fix temporary file chmod
266 lines
9.7 KiB
Python
266 lines
9.7 KiB
Python
#!/usr/bin/env python3
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import os
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from pathlib import Path
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from cubbi_init import ToolPlugin, cubbi_config
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from ruamel.yaml import YAML
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class GoosePlugin(ToolPlugin):
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@property
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def tool_name(self) -> str:
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return "goose"
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def _get_user_ids(self) -> tuple[int, int]:
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return cubbi_config.user.uid, cubbi_config.user.gid
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def _set_ownership(self, path: Path) -> None:
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user_id, group_id = self._get_user_ids()
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try:
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os.chown(path, user_id, group_id)
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except OSError as e:
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self.status.log(f"Failed to set ownership for {path}: {e}", "WARNING")
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def _get_user_config_path(self) -> Path:
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return Path("/home/cubbi/.config/goose")
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def _ensure_user_config_dir(self) -> Path:
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config_dir = self._get_user_config_path()
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# Create the full directory path
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try:
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config_dir.mkdir(parents=True, exist_ok=True)
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except FileExistsError:
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# Directory already exists, which is fine
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pass
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except OSError as e:
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self.status.log(
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f"Failed to create config directory {config_dir}: {e}", "ERROR"
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)
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return config_dir
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# Set ownership for the directories
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config_parent = config_dir.parent
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if config_parent.exists():
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self._set_ownership(config_parent)
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if config_dir.exists():
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self._set_ownership(config_dir)
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return config_dir
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def _write_env_vars_to_profile(self, env_vars: dict) -> None:
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"""Write environment variables to shell profile for interactive sessions"""
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try:
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# Write to cubbi user's bash profile
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profile_path = Path("/home/cubbi/.bashrc")
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# Create cubbi env section marker
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env_section_start = "# CUBBI GOOSE ENVIRONMENT VARIABLES"
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env_section_end = "# END CUBBI GOOSE ENVIRONMENT VARIABLES"
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# Read existing profile or create empty
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if profile_path.exists():
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with open(profile_path, "r") as f:
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lines = f.readlines()
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else:
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lines = []
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# Remove existing cubbi env section
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new_lines = []
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skip_section = False
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for line in lines:
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if env_section_start in line:
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skip_section = True
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elif env_section_end in line:
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skip_section = False
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continue
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elif not skip_section:
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new_lines.append(line)
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# Add new env vars section
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if env_vars:
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new_lines.append(f"\n{env_section_start}\n")
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for key, value in env_vars.items():
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new_lines.append(f'export {key}="{value}"\n')
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new_lines.append(f"{env_section_end}\n")
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# Write updated profile
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profile_path.parent.mkdir(parents=True, exist_ok=True)
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with open(profile_path, "w") as f:
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f.writelines(new_lines)
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# Set ownership
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self._set_ownership(profile_path)
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self.status.log(
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f"Updated shell profile with {len(env_vars)} environment variables"
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)
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except Exception as e:
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self.status.log(
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f"Failed to write environment variables to profile: {e}", "ERROR"
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)
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def initialize(self) -> bool:
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self._ensure_user_config_dir()
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return self.setup_tool_configuration()
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def setup_tool_configuration(self) -> bool:
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# Ensure directory exists before writing
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config_dir = self._ensure_user_config_dir()
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if not config_dir.exists():
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self.status.log(
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f"Config directory {config_dir} does not exist and could not be created",
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"ERROR",
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)
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return False
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config_file = config_dir / "config.yaml"
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yaml = YAML(typ="safe")
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# Load or initialize configuration
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if config_file.exists():
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with config_file.open("r") as f:
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config_data = yaml.load(f) or {}
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else:
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config_data = {}
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if "extensions" not in config_data:
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config_data["extensions"] = {}
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# Add default developer extension
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config_data["extensions"]["developer"] = {
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"enabled": True,
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"name": "developer",
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"timeout": 300,
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"type": "builtin",
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}
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# Configure Goose with the default model
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provider_config = cubbi_config.get_provider_for_default_model()
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if provider_config and cubbi_config.defaults.model:
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_, model_name = cubbi_config.defaults.model.split("/", 1)
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# Set Goose model and provider
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config_data["GOOSE_MODEL"] = model_name
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config_data["GOOSE_PROVIDER"] = provider_config.type
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# Set ONLY the specific API key for the selected provider
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# Set both in current process AND in shell environment file
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env_vars_to_set = {}
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if provider_config.type == "anthropic" and provider_config.api_key:
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env_vars_to_set["ANTHROPIC_API_KEY"] = provider_config.api_key
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self.status.log("Set Anthropic API key for goose")
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elif provider_config.type == "openai" and provider_config.api_key:
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# For OpenAI-compatible providers (including litellm), goose expects OPENAI_API_KEY
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env_vars_to_set["OPENAI_API_KEY"] = provider_config.api_key
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self.status.log("Set OpenAI API key for goose")
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# Set base URL for OpenAI-compatible providers in both env and config
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if provider_config.base_url:
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env_vars_to_set["OPENAI_BASE_URL"] = provider_config.base_url
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config_data["OPENAI_HOST"] = provider_config.base_url
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self.status.log(
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f"Set OPENAI_BASE_URL and OPENAI_HOST to {provider_config.base_url}"
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)
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elif provider_config.type == "google" and provider_config.api_key:
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env_vars_to_set["GOOGLE_API_KEY"] = provider_config.api_key
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self.status.log("Set Google API key for goose")
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elif provider_config.type == "openrouter" and provider_config.api_key:
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env_vars_to_set["OPENROUTER_API_KEY"] = provider_config.api_key
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self.status.log("Set OpenRouter API key for goose")
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# Set environment variables for current process (for --run commands)
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for key, value in env_vars_to_set.items():
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os.environ[key] = value
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# Write environment variables to shell profile for interactive sessions
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self._write_env_vars_to_profile(env_vars_to_set)
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self.status.log(
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f"Configured Goose: model={model_name}, provider={provider_config.type}"
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)
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else:
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self.status.log("No default model or provider configured", "WARNING")
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try:
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with config_file.open("w") as f:
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yaml.dump(config_data, f)
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# Set ownership of the config file to cubbi user
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self._set_ownership(config_file)
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self.status.log(f"Updated Goose configuration at {config_file}")
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return True
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except Exception as e:
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self.status.log(f"Failed to write Goose configuration: {e}", "ERROR")
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return False
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def integrate_mcp_servers(self) -> bool:
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if not cubbi_config.mcps:
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self.status.log("No MCP servers to integrate")
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return True
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# Ensure directory exists before writing
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config_dir = self._ensure_user_config_dir()
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if not config_dir.exists():
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self.status.log(
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f"Config directory {config_dir} does not exist and could not be created",
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"ERROR",
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)
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return False
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config_file = config_dir / "config.yaml"
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yaml = YAML(typ="safe")
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if config_file.exists():
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with config_file.open("r") as f:
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config_data = yaml.load(f) or {}
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else:
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config_data = {"extensions": {}}
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if "extensions" not in config_data:
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config_data["extensions"] = {}
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for mcp in cubbi_config.mcps:
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if mcp.type == "remote":
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if mcp.name and mcp.url:
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self.status.log(
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f"Adding remote MCP extension: {mcp.name} - {mcp.url}"
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)
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config_data["extensions"][mcp.name] = {
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"enabled": True,
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"name": mcp.name,
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"timeout": 60,
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"type": "sse",
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"uri": mcp.url,
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"envs": {},
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}
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elif mcp.type in ["docker", "proxy"]:
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if mcp.name and mcp.host:
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mcp_port = mcp.port or 8080
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mcp_url = f"http://{mcp.host}:{mcp_port}/sse"
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self.status.log(f"Adding MCP extension: {mcp.name} - {mcp_url}")
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config_data["extensions"][mcp.name] = {
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"enabled": True,
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"name": mcp.name,
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"timeout": 60,
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"type": "sse",
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"uri": mcp_url,
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"envs": {},
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}
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try:
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with config_file.open("w") as f:
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yaml.dump(config_data, f)
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# Set ownership of the config file to cubbi user
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self._set_ownership(config_file)
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return True
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except Exception as e:
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self.status.log(f"Failed to integrate MCP servers: {e}", "ERROR")
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return False
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