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skill-seekers-reference/docs/integrations/MULTI_LLM_SUPPORT.md
yusyus 4f87de6b56 fix: improve MiniMax adaptor from PR #318 review (#319) 
* 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>
2026-03-20 22:12:23 +03:00

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# Multi-LLM Platform Support Guide
Skill Seekers supports multiple LLM platforms through a clean adaptor system. The core scraping and content organization remains universal, while packaging and upload are platform-specific.
## Supported Platforms
| Platform | Status | Format | Upload | Enhancement | API Key Required |
|----------|--------|--------|--------|-------------|------------------|
| **Claude AI** | ✅ Full Support | ZIP + YAML | ✅ Automatic | ✅ Yes | ANTHROPIC_API_KEY |
| **Google Gemini** | ✅ Full Support | tar.gz | ✅ Automatic | ✅ Yes | GOOGLE_API_KEY |
| **OpenAI ChatGPT** | ✅ Full Support | ZIP + Vector Store | ✅ Automatic | ✅ Yes | OPENAI_API_KEY |
| **MiniMax AI** | ✅ Full Support | ZIP | ✅ Validation | ✅ Yes | MINIMAX_API_KEY |
| **Generic Markdown** | ✅ Export Only | ZIP | ❌ Manual | ❌ No | None |
## Quick Start
### Claude AI (Default)
No changes needed! All existing workflows continue to work:
```bash
# Scrape documentation
skill-seekers scrape --config configs/react.json
# Package for Claude (default)
skill-seekers package output/react/
# Upload to Claude
skill-seekers upload react.zip
```
### Google Gemini
```bash
# Install Gemini support
pip install skill-seekers[gemini]
# Set API key
export GOOGLE_API_KEY=AIzaSy...
# Scrape documentation (same as always)
skill-seekers scrape --config configs/react.json
# Package for Gemini
skill-seekers package output/react/ --target gemini
# Upload to Gemini
skill-seekers upload react-gemini.tar.gz --target gemini
# Optional: Enhance with Gemini
skill-seekers enhance output/react/ --target gemini
```
**Output:** `react-gemini.tar.gz` ready for Google AI Studio
### OpenAI ChatGPT
```bash
# Install OpenAI support
pip install skill-seekers[openai]
# Set API key
export OPENAI_API_KEY=sk-proj-...
# Scrape documentation (same as always)
skill-seekers scrape --config configs/react.json
# Package for OpenAI
skill-seekers package output/react/ --target openai
# Upload to OpenAI (creates Assistant + Vector Store)
skill-seekers upload react-openai.zip --target openai
# Optional: Enhance with GPT-4o
skill-seekers enhance output/react/ --target openai
```
**Output:** OpenAI Assistant created with file search enabled
### Generic Markdown (Universal Export)
```bash
# Package as generic markdown (no dependencies)
skill-seekers package output/react/ --target markdown
# Output: react-markdown.zip with:
# - README.md
# - references/*.md
# - DOCUMENTATION.md (combined)
```
**Use case:** Export for any LLM, documentation hosting, or manual distribution
## Installation Options
### Install Core Package Only
```bash
# Default installation (Claude support only)
pip install skill-seekers
```
### Install with Specific Platform Support
```bash
# Google Gemini support
pip install skill-seekers[gemini]
# OpenAI ChatGPT support
pip install skill-seekers[openai]
# MiniMax AI support
pip install skill-seekers[minimax]
# All LLM platforms
pip install skill-seekers[all-llms]
# Development dependencies (includes testing)
pip install skill-seekers[dev]
```
### Install from Source
```bash
git clone https://github.com/yusufkaraaslan/Skill_Seekers.git
cd Skill_Seekers
# Editable install with all platforms
pip install -e .[all-llms]
```
## Platform Comparison
### Format Differences
**Claude AI:**
- Format: ZIP archive
- SKILL.md: YAML frontmatter + markdown
- Structure: `SKILL.md`, `references/`, `scripts/`, `assets/`
- API: Anthropic Skills API
- Enhancement: Claude Sonnet 4
**Google Gemini:**
- Format: tar.gz archive
- SKILL.md → `system_instructions.md` (plain markdown, no frontmatter)
- Structure: `system_instructions.md`, `references/`, `gemini_metadata.json`
- API: Google Files API + grounding
- Enhancement: Gemini 2.0 Flash
**OpenAI ChatGPT:**
- Format: ZIP archive
- SKILL.md → `assistant_instructions.txt` (plain text)
- Structure: `assistant_instructions.txt`, `vector_store_files/`, `openai_metadata.json`
- API: Assistants API + Vector Store
- Enhancement: GPT-4o
**MiniMax AI:**
- Format: ZIP archive
- SKILL.md -> `system_instructions.txt` (plain text, no frontmatter)
- Structure: `system_instructions.txt`, `knowledge_files/`, `minimax_metadata.json`
- API: OpenAI-compatible chat completions
- Enhancement: MiniMax-M2.7
**Generic Markdown:**
- Format: ZIP archive
- Structure: `README.md`, `references/`, `DOCUMENTATION.md` (combined)
- No API integration
- No enhancement support
- Universal compatibility
### API Key Configuration
**Claude AI:**
```bash
export ANTHROPIC_API_KEY=sk-ant-...
```
**Google Gemini:**
```bash
export GOOGLE_API_KEY=AIzaSy...
```
**OpenAI ChatGPT:**
```bash
export OPENAI_API_KEY=sk-proj-...
```
**MiniMax AI:**
```bash
export MINIMAX_API_KEY=your-key
```
## Complete Workflow Examples
### Workflow 1: Claude AI (Default)
```bash
# 1. Scrape
skill-seekers scrape --config configs/react.json
# 2. Enhance (optional but recommended)
skill-seekers enhance output/react/
# 3. Package
skill-seekers package output/react/
# 4. Upload
skill-seekers upload react.zip
# Access at: https://claude.ai/skills
```
### Workflow 2: Google Gemini
```bash
# Setup (one-time)
pip install skill-seekers[gemini]
export GOOGLE_API_KEY=AIzaSy...
# 1. Scrape (universal)
skill-seekers scrape --config configs/react.json
# 2. Enhance for Gemini
skill-seekers enhance output/react/ --target gemini
# 3. Package for Gemini
skill-seekers package output/react/ --target gemini
# 4. Upload to Gemini
skill-seekers upload react-gemini.tar.gz --target gemini
# Access at: https://aistudio.google.com/files/
```
### Workflow 3: OpenAI ChatGPT
```bash
# Setup (one-time)
pip install skill-seekers[openai]
export OPENAI_API_KEY=sk-proj-...
# 1. Scrape (universal)
skill-seekers scrape --config configs/react.json
# 2. Enhance with GPT-4o
skill-seekers enhance output/react/ --target openai
# 3. Package for OpenAI
skill-seekers package output/react/ --target openai
# 4. Upload (creates Assistant + Vector Store)
skill-seekers upload react-openai.zip --target openai
# Access at: https://platform.openai.com/assistants/
```
### Workflow 4: MiniMax AI
```bash
# Setup (one-time)
pip install skill-seekers[minimax]
export MINIMAX_API_KEY=your-key
# 1. Scrape (universal)
skill-seekers scrape --config configs/react.json
# 2. Enhance with MiniMax-M2.7
skill-seekers enhance output/react/ --target minimax
# 3. Package for MiniMax
skill-seekers package output/react/ --target minimax
# 4. Upload to MiniMax (validates with API)
skill-seekers upload react-minimax.zip --target minimax
# Access at: https://platform.minimaxi.com/
```
### Workflow 5: Export to All Platforms
```bash
# Install all platforms
pip install skill-seekers[all-llms]
# Scrape once
skill-seekers scrape --config configs/react.json
# Package for all platforms
skill-seekers package output/react/ --target claude
skill-seekers package output/react/ --target gemini
skill-seekers package output/react/ --target openai
skill-seekers package output/react/ --target minimax
skill-seekers package output/react/ --target markdown
# Result:
# - react.zip (Claude)
# - react-gemini.tar.gz (Gemini)
# - react-openai.zip (OpenAI)
# - react-minimax.zip (MiniMax)
# - react-markdown.zip (Universal)
```
## Advanced Usage
### Custom Enhancement Models
Each platform uses its default enhancement model, but you can customize:
```bash
# Use specific model for enhancement (if supported)
skill-seekers enhance output/react/ --target gemini --model gemini-2.0-flash-exp
skill-seekers enhance output/react/ --target openai --model gpt-4o
```
### Programmatic Usage
```python
from skill_seekers.cli.adaptors import get_adaptor
# Get platform-specific adaptor
gemini = get_adaptor('gemini')
openai = get_adaptor('openai')
claude = get_adaptor('claude')
# Package for specific platform
gemini_package = gemini.package(skill_dir, output_path)
openai_package = openai.package(skill_dir, output_path)
# Upload with API key
result = gemini.upload(gemini_package, api_key)
print(f"Uploaded to: {result['url']}")
```
### Platform Detection
Check which platforms are available:
```python
from skill_seekers.cli.adaptors import list_platforms, is_platform_available
# List all registered platforms
platforms = list_platforms()
print(platforms) # ['claude', 'gemini', 'minimax', 'openai', 'markdown']
# Check if platform is available
if is_platform_available('gemini'):
print("Gemini adaptor is available")
```
## Backward Compatibility
**100% backward compatible** with existing workflows:
- All existing Claude commands work unchanged
- Default behavior remains Claude-focused
- Optional `--target` flag adds multi-platform support
- No breaking changes to existing configs or workflows
## Platform-Specific Guides
For detailed platform-specific instructions, see:
- [Claude AI Integration](CLAUDE_INTEGRATION.md) (default)
- [Google Gemini Integration](GEMINI_INTEGRATION.md)
- [OpenAI ChatGPT Integration](OPENAI_INTEGRATION.md)
- [MiniMax AI Integration](MINIMAX_INTEGRATION.md)
## Troubleshooting
### Missing Dependencies
**Error:** `ModuleNotFoundError: No module named 'google.generativeai'`
**Solution:**
```bash
pip install skill-seekers[gemini]
```
**Error:** `ModuleNotFoundError: No module named 'openai'`
**Solution:**
```bash
pip install skill-seekers[openai]
# or for MiniMax (also uses openai library)
pip install skill-seekers[minimax]
```
### API Key Issues
**Error:** `Invalid API key format`
**Solution:** Check your API key format:
- Claude: `sk-ant-...`
- Gemini: `AIza...`
- OpenAI: `sk-proj-...` or `sk-...`
- MiniMax: Any valid API key string
### Package Format Errors
**Error:** `Not a tar.gz file: react.zip`
**Solution:** Use correct --target flag:
```bash
# Gemini requires tar.gz
skill-seekers package output/react/ --target gemini
# OpenAI and Claude use ZIP
skill-seekers package output/react/ --target openai
```
## FAQ
**Q: Can I use the same scraped data for all platforms?**
A: Yes! The scraping phase is universal. Only packaging and upload are platform-specific.
**Q: Do I need separate API keys for each platform?**
A: Yes, each platform requires its own API key. Set them as environment variables.
**Q: Can I enhance with different models?**
A: Yes, each platform uses its own enhancement model:
- Claude: Claude Sonnet 4
- Gemini: Gemini 2.0 Flash
- OpenAI: GPT-4o
- MiniMax: MiniMax-M2.7
**Q: What if I don't want to upload automatically?**
A: Use the `package` command without `upload`. You'll get the packaged file to upload manually.
**Q: Is the markdown export compatible with all LLMs?**
A: Yes! The generic markdown export creates universal documentation that works with any LLM or documentation system.
**Q: Can I contribute a new platform adaptor?**
A: Absolutely! See the [Contributing Guide](../CONTRIBUTING.md) for how to add new platform adaptors.
## Next Steps
1. Choose your target platform
2. Install optional dependencies if needed
3. Set up API keys
4. Follow the platform-specific workflow
5. Upload and test your skill
For more help, see:
- [Quick Start Guide](../QUICKSTART.md)
- [Troubleshooting Guide](../TROUBLESHOOTING.md)
- [Platform-Specific Guides](.)
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