* feat: add MiniMax AI as LLM platform adaptor
Original implementation by octo-patch in PR #318.
This commit includes comprehensive improvements and documentation.
Code Improvements:
- Fix API key validation to properly check JWT format (eyJ prefix)
- Add specific exception handling for timeout and connection errors
- Remove unused variable in upload method
Dependencies:
- Add MiniMax to [all-llms] extra group in pyproject.toml
Tests:
- Remove duplicate setUp method in integration test class
- Add 4 new test methods:
* test_package_excludes_backup_files
* test_upload_success_mocked (with OpenAI mocking)
* test_upload_network_error
* test_upload_connection_error
* test_validate_api_key_jwt_format
- Update test_validate_api_key_valid to use JWT format keys
- Fix test assertions for error message matching
Documentation:
- Create comprehensive MINIMAX_INTEGRATION.md guide (380+ lines)
- Update MULTI_LLM_SUPPORT.md with MiniMax platform entry
- Update 01-installation.md extras table
- Update INTEGRATIONS.md AI platforms table
- Update AGENTS.md adaptor import pattern example
- Fix README.md platform count from 4 to 5
All tests pass (33 passed, 3 skipped)
Lint checks pass
Co-authored-by: octo-patch <octo-patch@users.noreply.github.com>
* fix: improve MiniMax adaptor — typed exceptions, key validation, tests, docs
- Remove invalid "minimax" self-reference from all-llms dependency group
- Use typed OpenAI exceptions (APITimeoutError, APIConnectionError)
instead of string-matching on generic Exception
- Replace incorrect JWT assumption in validate_api_key with length check
- Use DEFAULT_API_ENDPOINT constant instead of hardcoded URLs (3 sites)
- Add Path() cast for output_path before .is_dir() call
- Add sys.modules mock to test_enhance_missing_library
- Add mocked test_enhance_success with backup/content verification
- Update test assertions for new exception types and key validation
- Add MiniMax to __init__.py docstrings (module, get_adaptor, list_platforms)
- Add MiniMax sections to MULTI_LLM_SUPPORT.md (install, format, API key,
workflow example, export-to-all)
Follows up on PR #318 by @octo-patch (feat: add MiniMax AI as LLM platform adaptor).
Co-Authored-By: Octopus <octo-patch@users.noreply.github.com>
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: octo-patch <octo-patch@users.noreply.github.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Add Claude Code Plugin: plugin.json, .mcp.json, 3 slash commands, skill-builder agent skill
- Add GitHub Action: composite action.yml with 6 inputs/2 outputs, comprehensive README
- Add Smithery: publishing guide with namespace yusufkaraaslan/skill-seekers created
- Add render-mcp.yaml for MCP server deployment on Render
- Fix Dockerfile.mcp: --transport flag (nonexistent) → --http, add dynamic PORT support
- Update AGENTS.md to v3.3.0 with corrected test count and expanded CI section
- Allow distribution/claude-plugin/.mcp.json in .gitignore
Auto-detects NVIDIA (CUDA), AMD (ROCm), or CPU-only GPU and installs the
correct PyTorch variant + easyocr + all visual extraction dependencies.
Removes easyocr from video-full pip extras to avoid pulling ~2GB of wrong
CUDA packages on non-NVIDIA systems.
New files:
- video_setup.py (835 lines): GPU detection, PyTorch install, ROCm config,
venv checks, system dep validation, module selection, verification
- test_video_setup.py (60 tests): Full coverage of detection, install, verify
Updated docs: CHANGELOG, AGENTS.md, CLAUDE.md, README.md, CLI_REFERENCE,
FAQ, TROUBLESHOOTING, installation guide, video dependency plan
All 2523 tests passing (15 skipped).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- enhancement_workflow.py: WorkflowEngine class for multi-stage AI
enhancement workflows with preset support (security-focus,
architecture-comprehensive, api-documentation, minimal, default)
- unified_enhancer.py: unified enhancement orchestrator integrating
workflow execution with traditional enhance-level based enhancement
- create_command.py: wire workflow args into the unified create command
- AGENTS.md: update agent capability documentation
- configs/godot_unified.json: add unified Godot documentation config
- ENHANCEMENT_WORKFLOW_SYSTEM.md: documentation for the workflow system
- WORKFLOW_ENHANCEMENT_SEQUENTIAL_EXECUTION.md: docs explaining
sequential execution of workflows followed by AI enhancement
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Major improvements to developer documentation:
CLAUDE.md:
- Add unified `create` command to quick command reference
- New comprehensive section on unified create command architecture
- Auto-detection of source types (web/GitHub/local/PDF/config)
- Progressive disclosure help system (--help-web, --help-github, etc.)
- Universal flags that work across all sources
- -p shortcut for preset selection
- Document enhancement flag consolidation (Phase 1)
- Old: --enhance, --enhance-local, --api-key (3 flags)
- New: --enhance-level 0-3 (1 granular flag)
- Auto-detection of API vs LOCAL mode
- Add "Modifying the Unified Create Command" section
- Three-tier argument system (universal/source-specific/advanced)
- File locations and architecture
- Examples for contributors
- New troubleshooting: "Confused About Command Options"
- Update test counts: 1,765 current (1,852+ in v3.1.0)
- Add v3.1.0 to recent achievements
- Update best practices to prioritize create command
AGENTS.md:
- Update version to 3.0.0
- Add new directories: arguments/, presets/, create_command.py
These changes ensure future Claude instances understand the CLI
refactor work and can effectively contribute to the project.
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
- Comprehensive guide for AI assistants working with the codebase
- Covers project structure, development commands, architecture patterns
- Includes testing guidelines, CI/CD info, and troubleshooting
- Documents all entry points, dependencies, and best practices
