feat: Unified create command + consolidated enhancement flags
This commit includes two major improvements:
## 1. Unified Create Command (v3.0.0 feature)
- Auto-detects source type (web, GitHub, local, PDF, config)
- Three-tier argument organization (universal, source-specific, advanced)
- Routes to existing scrapers (100% backward compatible)
- Progressive disclosure: 15 universal flags in default help
**New files:**
- src/skill_seekers/cli/source_detector.py - Auto-detection logic
- src/skill_seekers/cli/arguments/create.py - Argument definitions
- src/skill_seekers/cli/create_command.py - Main orchestrator
- src/skill_seekers/cli/parsers/create_parser.py - Parser integration
**Tests:**
- tests/test_source_detector.py (35 tests)
- tests/test_create_arguments.py (30 tests)
- tests/test_create_integration_basic.py (10 tests)
## 2. Enhanced Flag Consolidation (Phase 1)
- Consolidated 3 flags (--enhance, --enhance-local, --enhance-level) → 1 flag
- --enhance-level 0-3 with auto-detection of API vs LOCAL mode
- Default: --enhance-level 2 (balanced enhancement)
**Modified files:**
- arguments/{common,create,scrape,github,analyze}.py - Added enhance_level
- {doc_scraper,github_scraper,config_extractor,main}.py - Updated logic
- create_command.py - Uses consolidated flag
**Auto-detection:**
- If ANTHROPIC_API_KEY set → API mode
- Else → LOCAL mode (Claude Code)
## 3. PresetManager Bug Fix
- Fixed module naming conflict (presets.py vs presets/ directory)
- Moved presets.py → presets/manager.py
- Updated __init__.py exports
**Test Results:**
- All 160+ tests passing
- Zero regressions
- 100% backward compatible
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
This commit is contained in:
yusyus
769
CLAUDE.md
769
CLAUDE.md
@@ -4,13 +4,47 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co
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## 🎯 Project Overview
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**Skill Seekers** is a Python tool that converts documentation websites, GitHub repositories, and PDFs into LLM skills. It supports 4 platforms: Claude AI, Google Gemini, OpenAI ChatGPT, and Generic Markdown.
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**Skill Seekers** is the **universal documentation preprocessor** for AI systems. It transforms documentation websites, GitHub repositories, and PDFs into production-ready formats for **16+ platforms**: RAG pipelines (LangChain, LlamaIndex, Haystack), vector databases (Pinecone, Chroma, Weaviate, FAISS, Qdrant), AI coding assistants (Cursor, Windsurf, Cline, Continue.dev), and LLM platforms (Claude, Gemini, OpenAI).
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**Current Version:** v2.9.0
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**Current Version:** v3.0.0
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**Python Version:** 3.10+ required
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**Status:** Production-ready, published on PyPI
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**Website:** https://skillseekersweb.com/ - Browse configs, share, and access documentation
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## 📚 Table of Contents
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- [First Time Here?](#-first-time-here) - Start here!
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- [Quick Commands](#-quick-command-reference-most-used) - Common workflows
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- [Architecture](#️-architecture) - How it works
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- [Development](#️-development-commands) - Building & testing
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- [Testing](#-testing-guidelines) - Test strategy
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- [Debugging](#-debugging-tips) - Troubleshooting
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- [Contributing](#-where-to-make-changes) - How to add features
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## 👋 First Time Here?
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**Complete this 3-minute setup to start contributing:**
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```bash
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# 1. Install package in editable mode (REQUIRED for development)
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pip install -e .
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# 2. Verify installation
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python -c "import skill_seekers; print(skill_seekers.__version__)" # Should print: 3.0.0
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# 3. Run a quick test
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pytest tests/test_scraper_features.py::test_detect_language -v
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# 4. You're ready! Pick a task from the roadmap:
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# https://github.com/users/yusufkaraaslan/projects/2
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```
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**Quick Navigation:**
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- Building/Testing → [Development Commands](#️-development-commands)
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- Architecture → [Core Design Pattern](#️-architecture)
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- Common Issues → [Common Pitfalls](#-common-pitfalls--solutions)
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- Contributing → See `CONTRIBUTING.md`
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## ⚡ Quick Command Reference (Most Used)
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**First time setup:**
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@@ -43,31 +77,97 @@ skill-seekers github --repo facebook/react
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# Local codebase analysis
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skill-seekers analyze --directory . --comprehensive
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# Package for all platforms
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# Package for LLM platforms
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skill-seekers package output/react/ --target claude
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skill-seekers package output/react/ --target gemini
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```
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**RAG Pipeline workflows:**
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```bash
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# LangChain Documents
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skill-seekers package output/react/ --format langchain
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# LlamaIndex TextNodes
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skill-seekers package output/react/ --format llama-index
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# Haystack Documents
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skill-seekers package output/react/ --format haystack
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# ChromaDB direct upload
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skill-seekers package output/react/ --format chroma --upload
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# FAISS export
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skill-seekers package output/react/ --format faiss
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# Weaviate/Qdrant upload (requires API keys)
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skill-seekers package output/react/ --format weaviate --upload
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skill-seekers package output/react/ --format qdrant --upload
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```
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**AI Coding Assistant workflows:**
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```bash
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# Cursor IDE
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skill-seekers package output/react/ --target claude
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cp output/react-claude/SKILL.md .cursorrules
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# Windsurf
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cp output/react-claude/SKILL.md .windsurf/rules/react.md
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# Cline (VS Code)
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cp output/react-claude/SKILL.md .clinerules
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# Continue.dev (universal IDE)
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python examples/continue-dev-universal/context_server.py
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# Configure in ~/.continue/config.json
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```
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**Cloud Storage:**
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```bash
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# Upload to S3
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skill-seekers cloud upload --provider s3 --bucket my-skills output/react.zip
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# Upload to GCS
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skill-seekers cloud upload --provider gcs --bucket my-skills output/react.zip
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# Upload to Azure
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skill-seekers cloud upload --provider azure --container my-skills output/react.zip
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```
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## 🏗️ Architecture
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### Core Design Pattern: Platform Adaptors
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The codebase uses the **Strategy Pattern** with a factory method to support multiple LLM platforms:
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The codebase uses the **Strategy Pattern** with a factory method to support **16 platforms** across 4 categories:
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```
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src/skill_seekers/cli/adaptors/
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├── __init__.py # Factory: get_adaptor(target)
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├── base_adaptor.py # Abstract base class
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├── claude_adaptor.py # Claude AI (ZIP + YAML)
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├── gemini_adaptor.py # Google Gemini (tar.gz)
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├── openai_adaptor.py # OpenAI ChatGPT (ZIP + Vector Store)
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└── markdown_adaptor.py # Generic Markdown (ZIP)
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├── __init__.py # Factory: get_adaptor(target/format)
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├── base.py # Abstract base class
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# LLM Platforms (3)
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├── claude.py # Claude AI (ZIP + YAML)
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├── gemini.py # Google Gemini (tar.gz)
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├── openai.py # OpenAI ChatGPT (ZIP + Vector Store)
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# RAG Frameworks (3)
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├── langchain.py # LangChain Documents
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├── llama_index.py # LlamaIndex TextNodes
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├── haystack.py # Haystack Documents
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# Vector Databases (5)
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├── chroma.py # ChromaDB
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├── faiss_helpers.py # FAISS
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├── qdrant.py # Qdrant
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├── weaviate.py # Weaviate
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# AI Coding Assistants (4 - via Claude format + config files)
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# - Cursor, Windsurf, Cline, Continue.dev
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# Generic (1)
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├── markdown.py # Generic Markdown (ZIP)
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└── streaming_adaptor.py # Streaming data ingest
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```
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**Key Methods:**
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- `package(skill_dir, output_path)` - Platform-specific packaging
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- `upload(package_path, api_key)` - Platform-specific upload
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- `upload(package_path, api_key)` - Platform-specific upload (where applicable)
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- `enhance(skill_dir, mode)` - AI enhancement with platform-specific models
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- `export(skill_dir, format)` - Export to RAG/vector DB formats
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### Data Flow (5 Phases)
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@@ -90,21 +190,23 @@ src/skill_seekers/cli/adaptors/
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5. **Upload Phase** (optional, `upload_skill.py` → adaptor)
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- Upload via platform API
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### File Structure (src/ layout)
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### File Structure (src/ layout) - Key Files Only
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```
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src/skill_seekers/
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├── cli/ # CLI tools
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│ ├── main.py # Git-style CLI dispatcher
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│ ├── doc_scraper.py # Main scraper (~790 lines)
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├── cli/ # All CLI commands
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│ ├── main.py # ⭐ Git-style CLI dispatcher
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│ ├── doc_scraper.py # ⭐ Main scraper (~790 lines)
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│ │ ├── scrape_all() # BFS traversal engine
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│ │ ├── smart_categorize() # Category detection
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│ │ └── build_skill() # SKILL.md generation
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│ ├── github_scraper.py # GitHub repo analysis
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│ ├── pdf_scraper.py # PDF extraction
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│ ├── codebase_scraper.py # ⭐ Local analysis (C2.x+C3.x)
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│ ├── package_skill.py # Platform packaging
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│ ├── unified_scraper.py # Multi-source scraping
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│ ├── codebase_scraper.py # Local codebase analysis (C2.x)
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│ ├── unified_codebase_analyzer.py # Three-stream GitHub+local analyzer
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│ ├── enhance_skill_local.py # AI enhancement (LOCAL mode)
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│ ├── enhance_status.py # Enhancement status monitoring
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│ ├── package_skill.py # Skill packager
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│ ├── upload_skill.py # Upload to platforms
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│ ├── install_skill.py # Complete workflow automation
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│ ├── install_agent.py # Install to AI agent directories
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@@ -117,18 +219,32 @@ src/skill_seekers/
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│ ├── api_reference_builder.py # API documentation builder
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│ ├── dependency_analyzer.py # Dependency graph analysis
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│ ├── signal_flow_analyzer.py # C3.10 Signal flow analysis (Godot)
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│ └── adaptors/ # Platform adaptor architecture
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│ ├── __init__.py
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│ ├── base_adaptor.py
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│ ├── claude_adaptor.py
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│ ├── gemini_adaptor.py
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│ ├── openai_adaptor.py
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│ └── markdown_adaptor.py
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└── mcp/ # MCP server integration
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├── server.py # FastMCP server (stdio + HTTP)
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└── tools/ # 18 MCP tool implementations
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│ ├── pdf_scraper.py # PDF extraction
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│ └── adaptors/ # ⭐ Platform adaptor pattern
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│ ├── __init__.py # Factory: get_adaptor()
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│ ├── base_adaptor.py # Abstract base
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│ ├── claude_adaptor.py # Claude AI
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│ ├── gemini_adaptor.py # Google Gemini
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│ ├── openai_adaptor.py # OpenAI ChatGPT
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│ ├── markdown_adaptor.py # Generic Markdown
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│ ├── langchain.py # LangChain RAG
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│ ├── llama_index.py # LlamaIndex RAG
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│ ├── haystack.py # Haystack RAG
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│ ├── chroma.py # ChromaDB
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│ ├── faiss_helpers.py # FAISS
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│ ├── qdrant.py # Qdrant
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│ ├── weaviate.py # Weaviate
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│ └── streaming_adaptor.py # Streaming data ingest
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└── mcp/ # MCP server (26 tools)
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├── server_fastmcp.py # FastMCP server
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└── tools/ # Tool implementations
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```
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**Most Modified Files (when contributing):**
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- Platform adaptors: `src/skill_seekers/cli/adaptors/{platform}.py`
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- Tests: `tests/test_{feature}.py`
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- Configs: `configs/{framework}.json`
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## 🛠️ Development Commands
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### Setup
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@@ -172,7 +288,7 @@ pytest tests/test_mcp_fastmcp.py -v
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**Test Architecture:**
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- 46 test files covering all features
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- CI Matrix: Ubuntu + macOS, Python 3.10-3.13
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- 700+ tests passing
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- **1,852 tests passing** (up from 700+ in v2.x)
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- Must run `pip install -e .` before tests (src/ layout requirement)
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### Building & Publishing
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@@ -232,6 +348,36 @@ python -m skill_seekers.mcp.server_fastmcp
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python -m skill_seekers.mcp.server_fastmcp --transport http --port 8765
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```
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### New v3.0.0 CLI Commands
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```bash
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# Setup wizard (interactive configuration)
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skill-seekers-setup
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# Cloud storage operations
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skill-seekers cloud upload --provider s3 --bucket my-bucket output/react.zip
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skill-seekers cloud download --provider gcs --bucket my-bucket react.zip
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skill-seekers cloud list --provider azure --container my-container
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# Embedding server (for RAG pipelines)
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skill-seekers embed --port 8080 --model sentence-transformers
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# Sync & incremental updates
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skill-seekers sync --source https://docs.react.dev/ --target output/react/
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skill-seekers update --skill output/react/ --check-changes
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# Quality metrics & benchmarking
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skill-seekers quality --skill output/react/ --report
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skill-seekers benchmark --config configs/react.json --compare-versions
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# Multilingual support
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skill-seekers multilang --detect output/react/
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skill-seekers multilang --translate output/react/ --target zh-CN
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# Streaming data ingest
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skill-seekers stream --source docs/ --target output/streaming/
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```
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## 🔧 Key Implementation Details
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### CLI Architecture (Git-style)
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@@ -547,27 +693,44 @@ export BITBUCKET_TOKEN=...
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# Main unified CLI
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skill-seekers = "skill_seekers.cli.main:main"
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# Individual tool entry points
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skill-seekers-config = "skill_seekers.cli.config_command:main" # NEW: v2.7.0 Configuration wizard
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skill-seekers-resume = "skill_seekers.cli.resume_command:main" # NEW: v2.7.0 Resume interrupted jobs
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# Individual tool entry points (Core)
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skill-seekers-config = "skill_seekers.cli.config_command:main" # v2.7.0 Configuration wizard
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skill-seekers-resume = "skill_seekers.cli.resume_command:main" # v2.7.0 Resume interrupted jobs
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skill-seekers-scrape = "skill_seekers.cli.doc_scraper:main"
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skill-seekers-github = "skill_seekers.cli.github_scraper:main"
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skill-seekers-pdf = "skill_seekers.cli.pdf_scraper:main"
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skill-seekers-unified = "skill_seekers.cli.unified_scraper:main"
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skill-seekers-codebase = "skill_seekers.cli.codebase_scraper:main" # NEW: C2.x
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skill-seekers-codebase = "skill_seekers.cli.codebase_scraper:main" # C2.x Local codebase analysis
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skill-seekers-enhance = "skill_seekers.cli.enhance_skill_local:main"
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skill-seekers-enhance-status = "skill_seekers.cli.enhance_status:main" # NEW: Status monitoring
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skill-seekers-enhance-status = "skill_seekers.cli.enhance_status:main" # Status monitoring
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skill-seekers-package = "skill_seekers.cli.package_skill:main"
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skill-seekers-upload = "skill_seekers.cli.upload_skill:main"
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skill-seekers-estimate = "skill_seekers.cli.estimate_pages:main"
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skill-seekers-install = "skill_seekers.cli.install_skill:main"
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skill-seekers-install-agent = "skill_seekers.cli.install_agent:main"
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skill-seekers-patterns = "skill_seekers.cli.pattern_recognizer:main" # NEW: C3.1
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skill-seekers-how-to-guides = "skill_seekers.cli.how_to_guide_builder:main" # NEW: C3.3
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skill-seekers-patterns = "skill_seekers.cli.pattern_recognizer:main" # C3.1 Pattern detection
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skill-seekers-how-to-guides = "skill_seekers.cli.how_to_guide_builder:main" # C3.3 Guide generation
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|
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# New v3.0.0 Entry Points
|
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skill-seekers-setup = "skill_seekers.cli.setup_wizard:main" # NEW: v3.0.0 Setup wizard
|
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skill-seekers-cloud = "skill_seekers.cli.cloud_storage_cli:main" # NEW: v3.0.0 Cloud storage
|
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skill-seekers-embed = "skill_seekers.embedding.server:main" # NEW: v3.0.0 Embedding server
|
||||
skill-seekers-sync = "skill_seekers.cli.sync_cli:main" # NEW: v3.0.0 Sync & monitoring
|
||||
skill-seekers-benchmark = "skill_seekers.cli.benchmark_cli:main" # NEW: v3.0.0 Benchmarking
|
||||
skill-seekers-stream = "skill_seekers.cli.streaming_ingest:main" # NEW: v3.0.0 Streaming ingest
|
||||
skill-seekers-update = "skill_seekers.cli.incremental_updater:main" # NEW: v3.0.0 Incremental updates
|
||||
skill-seekers-multilang = "skill_seekers.cli.multilang_support:main" # NEW: v3.0.0 Multilingual
|
||||
skill-seekers-quality = "skill_seekers.cli.quality_metrics:main" # NEW: v3.0.0 Quality metrics
|
||||
```
|
||||
|
||||
### Optional Dependencies
|
||||
|
||||
**Project uses PEP 735 `[dependency-groups]` (Python 3.13+)**:
|
||||
- Replaces deprecated `tool.uv.dev-dependencies`
|
||||
- Dev dependencies: `[dependency-groups] dev = [...]` in pyproject.toml
|
||||
- Install with: `pip install -e .` (installs only core deps)
|
||||
- Install dev deps: See CI workflow or manually install pytest, ruff, mypy
|
||||
|
||||
```toml
|
||||
[project.optional-dependencies]
|
||||
gemini = ["google-generativeai>=0.8.0"]
|
||||
@@ -583,8 +746,6 @@ dev = [
|
||||
]
|
||||
```
|
||||
|
||||
**Note:** Project uses PEP 735 `dependency-groups` instead of deprecated `tool.uv.dev-dependencies`.
|
||||
|
||||
## 🚨 Critical Development Notes
|
||||
|
||||
### Must Run Before Tests
|
||||
@@ -601,17 +762,33 @@ pip install -e .
|
||||
|
||||
Per user instructions in `~/.claude/CLAUDE.md`:
|
||||
- "never skipp any test. always make sure all test pass"
|
||||
- All 700+ tests must pass before commits
|
||||
- All 1,852 tests must pass before commits
|
||||
- Run full test suite: `pytest tests/ -v`
|
||||
|
||||
### Platform-Specific Dependencies
|
||||
|
||||
Platform dependencies are optional:
|
||||
Platform dependencies are optional (install only what you need):
|
||||
|
||||
```bash
|
||||
# Install only what you need
|
||||
pip install skill-seekers[gemini] # Gemini support
|
||||
pip install skill-seekers[openai] # OpenAI support
|
||||
pip install skill-seekers[all-llms] # All platforms
|
||||
# Install specific platform support
|
||||
pip install -e ".[gemini]" # Google Gemini
|
||||
pip install -e ".[openai]" # OpenAI ChatGPT
|
||||
pip install -e ".[chroma]" # ChromaDB
|
||||
pip install -e ".[weaviate]" # Weaviate
|
||||
pip install -e ".[s3]" # AWS S3
|
||||
pip install -e ".[gcs]" # Google Cloud Storage
|
||||
pip install -e ".[azure]" # Azure Blob Storage
|
||||
pip install -e ".[mcp]" # MCP integration
|
||||
pip install -e ".[all]" # Everything (16 platforms + cloud + embedding)
|
||||
|
||||
# Or install from PyPI:
|
||||
pip install skill-seekers[gemini] # Google Gemini support
|
||||
pip install skill-seekers[openai] # OpenAI ChatGPT support
|
||||
pip install skill-seekers[all-llms] # All LLM platforms
|
||||
pip install skill-seekers[chroma] # ChromaDB support
|
||||
pip install skill-seekers[weaviate] # Weaviate support
|
||||
pip install skill-seekers[s3] # AWS S3 support
|
||||
pip install skill-seekers[all] # All optional dependencies
|
||||
```
|
||||
|
||||
### AI Enhancement Modes
|
||||
@@ -659,10 +836,13 @@ See `docs/ENHANCEMENT_MODES.md` for detailed documentation.
|
||||
|
||||
### Git Workflow
|
||||
|
||||
**Git Workflow Notes:**
|
||||
- Main branch: `main`
|
||||
- Current branch: `development`
|
||||
- Development branch: `development`
|
||||
- Always create feature branches from `development`
|
||||
- Feature branch naming: `feature/{task-id}-{description}` or `feature/{category}`
|
||||
- Branch naming: `feature/{task-id}-{description}` or `feature/{category}`
|
||||
|
||||
**To see current status:** `git status`
|
||||
|
||||
### CI/CD Pipeline
|
||||
|
||||
@@ -816,7 +996,7 @@ skill-seekers config --test
|
||||
|
||||
## 🔌 MCP Integration
|
||||
|
||||
### MCP Server (18 Tools)
|
||||
### MCP Server (26 Tools)
|
||||
|
||||
**Transport modes:**
|
||||
- stdio: Claude Code, VS Code + Cline
|
||||
@@ -828,21 +1008,33 @@ skill-seekers config --test
|
||||
3. `validate_config` - Validate config structure
|
||||
4. `estimate_pages` - Estimate page count
|
||||
5. `scrape_docs` - Scrape documentation
|
||||
6. `package_skill` - Package to .zip (supports `--target`)
|
||||
6. `package_skill` - Package to format (supports `--format` and `--target`)
|
||||
7. `upload_skill` - Upload to platform (supports `--target`)
|
||||
8. `enhance_skill` - AI enhancement with platform support
|
||||
9. `install_skill` - Complete workflow automation
|
||||
|
||||
**Extended Tools (9):**
|
||||
**Extended Tools (10):**
|
||||
10. `scrape_github` - GitHub repository analysis
|
||||
11. `scrape_pdf` - PDF extraction
|
||||
12. `unified_scrape` - Multi-source scraping
|
||||
13. `merge_sources` - Merge docs + code
|
||||
14. `detect_conflicts` - Find discrepancies
|
||||
15. `split_config` - Split large configs
|
||||
16. `generate_router` - Generate router skills
|
||||
17. `add_config_source` - Register git repos
|
||||
18. `fetch_config` - Fetch configs from git
|
||||
15. `add_config_source` - Register git repos
|
||||
16. `fetch_config` - Fetch configs from git
|
||||
17. `list_config_sources` - List registered sources
|
||||
18. `remove_config_source` - Remove config source
|
||||
19. `split_config` - Split large configs
|
||||
|
||||
**NEW Vector DB Tools (4):**
|
||||
20. `export_to_chroma` - Export to ChromaDB
|
||||
21. `export_to_weaviate` - Export to Weaviate
|
||||
22. `export_to_faiss` - Export to FAISS
|
||||
23. `export_to_qdrant` - Export to Qdrant
|
||||
|
||||
**NEW Cloud Tools (3):**
|
||||
24. `cloud_upload` - Upload to S3/GCS/Azure
|
||||
25. `cloud_download` - Download from cloud storage
|
||||
26. `cloud_list` - List files in cloud storage
|
||||
|
||||
### Starting MCP Server
|
||||
|
||||
@@ -854,6 +1046,336 @@ python -m skill_seekers.mcp.server_fastmcp
|
||||
python -m skill_seekers.mcp.server_fastmcp --transport http --port 8765
|
||||
```
|
||||
|
||||
## 🤖 RAG Framework & Vector Database Integrations (**NEW - v3.0.0**)
|
||||
|
||||
Skill Seekers is now the **universal preprocessor for RAG pipelines**. Export documentation to any RAG framework or vector database with a single command.
|
||||
|
||||
### RAG Frameworks
|
||||
|
||||
**LangChain Documents:**
|
||||
```bash
|
||||
# Export to LangChain Document format
|
||||
skill-seekers package output/django --format langchain
|
||||
|
||||
# Output: output/django-langchain.json
|
||||
# Format: Array of LangChain Document objects
|
||||
# - page_content: Full text content
|
||||
# - metadata: {source, category, type, url}
|
||||
|
||||
# Use in LangChain:
|
||||
from langchain.document_loaders import JSONLoader
|
||||
loader = JSONLoader("output/django-langchain.json")
|
||||
documents = loader.load()
|
||||
```
|
||||
|
||||
**LlamaIndex TextNodes:**
|
||||
```bash
|
||||
# Export to LlamaIndex TextNode format
|
||||
skill-seekers package output/django --format llama-index
|
||||
|
||||
# Output: output/django-llama-index.json
|
||||
# Format: Array of LlamaIndex TextNode objects
|
||||
# - text: Content
|
||||
# - id_: Unique identifier
|
||||
# - metadata: {source, category, type}
|
||||
# - relationships: Document relationships
|
||||
|
||||
# Use in LlamaIndex:
|
||||
from llama_index import StorageContext, load_index_from_storage
|
||||
from llama_index.schema import TextNode
|
||||
nodes = [TextNode.from_dict(n) for n in json.load(open("output/django-llama-index.json"))]
|
||||
```
|
||||
|
||||
**Haystack Documents:**
|
||||
```bash
|
||||
# Export to Haystack Document format
|
||||
skill-seekers package output/django --format haystack
|
||||
|
||||
# Output: output/django-haystack.json
|
||||
# Format: Haystack Document objects for pipelines
|
||||
# Perfect for: Question answering, search, RAG pipelines
|
||||
```
|
||||
|
||||
### Vector Databases
|
||||
|
||||
**ChromaDB (Direct Integration):**
|
||||
```bash
|
||||
# Export and optionally upload to ChromaDB
|
||||
skill-seekers package output/django --format chroma
|
||||
|
||||
# Output: output/django-chroma/ (ChromaDB collection)
|
||||
# With direct upload (requires chromadb running):
|
||||
skill-seekers package output/django --format chroma --upload
|
||||
|
||||
# Configuration via environment:
|
||||
export CHROMA_HOST=localhost
|
||||
export CHROMA_PORT=8000
|
||||
```
|
||||
|
||||
**FAISS (Facebook AI Similarity Search):**
|
||||
```bash
|
||||
# Export to FAISS index format
|
||||
skill-seekers package output/django --format faiss
|
||||
|
||||
# Output:
|
||||
# - output/django-faiss.index (FAISS index)
|
||||
# - output/django-faiss-metadata.json (Document metadata)
|
||||
|
||||
# Use with FAISS:
|
||||
import faiss
|
||||
index = faiss.read_index("output/django-faiss.index")
|
||||
```
|
||||
|
||||
**Weaviate:**
|
||||
```bash
|
||||
# Export and upload to Weaviate
|
||||
skill-seekers package output/django --format weaviate --upload
|
||||
|
||||
# Requires environment variables:
|
||||
export WEAVIATE_URL=http://localhost:8080
|
||||
export WEAVIATE_API_KEY=your-api-key
|
||||
|
||||
# Creates class "DjangoDoc" with schema
|
||||
```
|
||||
|
||||
**Qdrant:**
|
||||
```bash
|
||||
# Export and upload to Qdrant
|
||||
skill-seekers package output/django --format qdrant --upload
|
||||
|
||||
# Requires environment variables:
|
||||
export QDRANT_URL=http://localhost:6333
|
||||
export QDRANT_API_KEY=your-api-key
|
||||
|
||||
# Creates collection "django_docs"
|
||||
```
|
||||
|
||||
**Pinecone (via Markdown):**
|
||||
```bash
|
||||
# Pinecone uses the markdown format
|
||||
skill-seekers package output/django --target markdown
|
||||
|
||||
# Then use Pinecone's Python client for upsert
|
||||
# See: docs/integrations/PINECONE.md
|
||||
```
|
||||
|
||||
### Complete RAG Pipeline Example
|
||||
|
||||
```bash
|
||||
# 1. Scrape documentation
|
||||
skill-seekers scrape --config configs/django.json
|
||||
|
||||
# 2. Export to your RAG stack
|
||||
skill-seekers package output/django --format langchain # For LangChain
|
||||
skill-seekers package output/django --format llama-index # For LlamaIndex
|
||||
skill-seekers package output/django --format chroma --upload # Direct to ChromaDB
|
||||
|
||||
# 3. Use in your application
|
||||
# See examples/:
|
||||
# - examples/langchain-rag-pipeline/
|
||||
# - examples/llama-index-query-engine/
|
||||
# - examples/pinecone-upsert/
|
||||
```
|
||||
|
||||
**Integration Hub:** [docs/integrations/RAG_PIPELINES.md](docs/integrations/RAG_PIPELINES.md)
|
||||
|
||||
## 🛠️ AI Coding Assistant Integrations (**NEW - v3.0.0**)
|
||||
|
||||
Transform any framework documentation into persistent expert context for 4+ AI coding assistants. Your IDE's AI now "knows" your frameworks without manual prompting.
|
||||
|
||||
### Cursor IDE
|
||||
|
||||
**Setup:**
|
||||
```bash
|
||||
# 1. Generate skill
|
||||
skill-seekers scrape --config configs/react.json
|
||||
skill-seekers package output/react/ --target claude
|
||||
|
||||
# 2. Install to Cursor
|
||||
cp output/react-claude/SKILL.md .cursorrules
|
||||
|
||||
# 3. Restart Cursor
|
||||
# AI now has React expertise!
|
||||
```
|
||||
|
||||
**Benefits:**
|
||||
- ✅ AI suggests React-specific patterns
|
||||
- ✅ No manual "use React hooks" prompts needed
|
||||
- ✅ Consistent team patterns
|
||||
- ✅ Works for ANY framework
|
||||
|
||||
**Guide:** [docs/integrations/CURSOR.md](docs/integrations/CURSOR.md)
|
||||
**Example:** [examples/cursor-react-skill/](examples/cursor-react-skill/)
|
||||
|
||||
### Windsurf
|
||||
|
||||
**Setup:**
|
||||
```bash
|
||||
# 1. Generate skill
|
||||
skill-seekers scrape --config configs/django.json
|
||||
skill-seekers package output/django/ --target claude
|
||||
|
||||
# 2. Install to Windsurf
|
||||
mkdir -p .windsurf/rules
|
||||
cp output/django-claude/SKILL.md .windsurf/rules/django.md
|
||||
|
||||
# 3. Restart Windsurf
|
||||
# AI now knows Django patterns!
|
||||
```
|
||||
|
||||
**Benefits:**
|
||||
- ✅ Flow-based coding with framework knowledge
|
||||
- ✅ IDE-native AI assistance
|
||||
- ✅ Persistent context across sessions
|
||||
|
||||
**Guide:** [docs/integrations/WINDSURF.md](docs/integrations/WINDSURF.md)
|
||||
**Example:** [examples/windsurf-fastapi-context/](examples/windsurf-fastapi-context/)
|
||||
|
||||
### Cline (VS Code Extension)
|
||||
|
||||
**Setup:**
|
||||
```bash
|
||||
# 1. Generate skill
|
||||
skill-seekers scrape --config configs/fastapi.json
|
||||
skill-seekers package output/fastapi/ --target claude
|
||||
|
||||
# 2. Install to Cline
|
||||
cp output/fastapi-claude/SKILL.md .clinerules
|
||||
|
||||
# 3. Reload VS Code
|
||||
# Cline now has FastAPI expertise!
|
||||
```
|
||||
|
||||
**Benefits:**
|
||||
- ✅ Agentic code generation in VS Code
|
||||
- ✅ Cursor Composer equivalent for VS Code
|
||||
- ✅ System prompts + MCP integration
|
||||
|
||||
**Guide:** [docs/integrations/CLINE.md](docs/integrations/CLINE.md)
|
||||
**Example:** [examples/cline-django-assistant/](examples/cline-django-assistant/)
|
||||
|
||||
### Continue.dev (Universal IDE)
|
||||
|
||||
**Setup:**
|
||||
```bash
|
||||
# 1. Generate skill
|
||||
skill-seekers scrape --config configs/react.json
|
||||
skill-seekers package output/react/ --target claude
|
||||
|
||||
# 2. Start context server
|
||||
cd examples/continue-dev-universal/
|
||||
python context_server.py --port 8765
|
||||
|
||||
# 3. Configure in ~/.continue/config.json
|
||||
{
|
||||
"contextProviders": [
|
||||
{
|
||||
"name": "http",
|
||||
"params": {
|
||||
"url": "http://localhost:8765/context",
|
||||
"title": "React Documentation"
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
# 4. Works in ALL IDEs!
|
||||
# VS Code, JetBrains, Vim, Emacs...
|
||||
```
|
||||
|
||||
**Benefits:**
|
||||
- ✅ IDE-agnostic (works in VS Code, IntelliJ, Vim, Emacs)
|
||||
- ✅ Custom LLM providers supported
|
||||
- ✅ HTTP-based context serving
|
||||
- ✅ Team consistency across mixed IDE environments
|
||||
|
||||
**Guide:** [docs/integrations/CONTINUE_DEV.md](docs/integrations/CONTINUE_DEV.md)
|
||||
**Example:** [examples/continue-dev-universal/](examples/continue-dev-universal/)
|
||||
|
||||
### Multi-IDE Team Setup
|
||||
|
||||
For teams using different IDEs (VS Code, IntelliJ, Vim):
|
||||
|
||||
```bash
|
||||
# Use Continue.dev as universal context provider
|
||||
skill-seekers scrape --config configs/react.json
|
||||
python context_server.py --host 0.0.0.0 --port 8765
|
||||
|
||||
# ALL team members configure Continue.dev
|
||||
# Result: Identical AI suggestions across all IDEs!
|
||||
```
|
||||
|
||||
**Integration Hub:** [docs/integrations/INTEGRATIONS.md](docs/integrations/INTEGRATIONS.md)
|
||||
|
||||
## ☁️ Cloud Storage Integration (**NEW - v3.0.0**)
|
||||
|
||||
Upload skills directly to cloud storage for team sharing and CI/CD pipelines.
|
||||
|
||||
### Supported Providers
|
||||
|
||||
**AWS S3:**
|
||||
```bash
|
||||
# Upload skill
|
||||
skill-seekers cloud upload --provider s3 --bucket my-skills output/react.zip
|
||||
|
||||
# Download skill
|
||||
skill-seekers cloud download --provider s3 --bucket my-skills react.zip
|
||||
|
||||
# List skills
|
||||
skill-seekers cloud list --provider s3 --bucket my-skills
|
||||
|
||||
# Environment variables:
|
||||
export AWS_ACCESS_KEY_ID=your-key
|
||||
export AWS_SECRET_ACCESS_KEY=your-secret
|
||||
export AWS_REGION=us-east-1
|
||||
```
|
||||
|
||||
**Google Cloud Storage:**
|
||||
```bash
|
||||
# Upload skill
|
||||
skill-seekers cloud upload --provider gcs --bucket my-skills output/react.zip
|
||||
|
||||
# Download skill
|
||||
skill-seekers cloud download --provider gcs --bucket my-skills react.zip
|
||||
|
||||
# List skills
|
||||
skill-seekers cloud list --provider gcs --bucket my-skills
|
||||
|
||||
# Environment variables:
|
||||
export GOOGLE_APPLICATION_CREDENTIALS=/path/to/credentials.json
|
||||
```
|
||||
|
||||
**Azure Blob Storage:**
|
||||
```bash
|
||||
# Upload skill
|
||||
skill-seekers cloud upload --provider azure --container my-skills output/react.zip
|
||||
|
||||
# Download skill
|
||||
skill-seekers cloud download --provider azure --container my-skills react.zip
|
||||
|
||||
# List skills
|
||||
skill-seekers cloud list --provider azure --container my-skills
|
||||
|
||||
# Environment variables:
|
||||
export AZURE_STORAGE_CONNECTION_STRING=your-connection-string
|
||||
```
|
||||
|
||||
### CI/CD Integration
|
||||
|
||||
```yaml
|
||||
# GitHub Actions example
|
||||
- name: Upload skill to S3
|
||||
run: |
|
||||
skill-seekers scrape --config configs/react.json
|
||||
skill-seekers package output/react/
|
||||
skill-seekers cloud upload --provider s3 --bucket ci-skills output/react.zip
|
||||
env:
|
||||
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
|
||||
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
|
||||
```
|
||||
|
||||
**Guide:** [docs/integrations/CLOUD_STORAGE.md](docs/integrations/CLOUD_STORAGE.md)
|
||||
|
||||
## 📋 Common Workflows
|
||||
|
||||
### Adding a New Platform
|
||||
@@ -971,29 +1493,41 @@ This section helps you quickly locate the right files when implementing common c
|
||||
**Files to modify:**
|
||||
1. **Create adaptor:** `src/skill_seekers/cli/adaptors/my_platform_adaptor.py`
|
||||
```python
|
||||
from .base_adaptor import BaseAdaptor
|
||||
from .base import BaseAdaptor
|
||||
|
||||
class MyPlatformAdaptor(BaseAdaptor):
|
||||
def package(self, skill_dir, output_path):
|
||||
def package(self, skill_dir, output_path, **kwargs):
|
||||
# Platform-specific packaging
|
||||
pass
|
||||
|
||||
def upload(self, package_path, api_key):
|
||||
# Platform-specific upload
|
||||
def upload(self, package_path, api_key=None, **kwargs):
|
||||
# Platform-specific upload (optional for some platforms)
|
||||
pass
|
||||
|
||||
def enhance(self, skill_dir, mode):
|
||||
# Platform-specific AI enhancement
|
||||
def export(self, skill_dir, format, **kwargs):
|
||||
# For RAG/vector DB adaptors: export to specific format
|
||||
pass
|
||||
```
|
||||
|
||||
2. **Register in factory:** `src/skill_seekers/cli/adaptors/__init__.py`
|
||||
```python
|
||||
def get_adaptor(target):
|
||||
adaptors = {
|
||||
def get_adaptor(target=None, format=None):
|
||||
# For LLM platforms (--target flag)
|
||||
target_adaptors = {
|
||||
'claude': ClaudeAdaptor,
|
||||
'gemini': GeminiAdaptor,
|
||||
'openai': OpenAIAdaptor,
|
||||
'markdown': MarkdownAdaptor,
|
||||
'myplatform': MyPlatformAdaptor, # ADD THIS
|
||||
}
|
||||
|
||||
# For RAG/vector DBs (--format flag)
|
||||
format_adaptors = {
|
||||
'langchain': LangChainAdaptor,
|
||||
'llama-index': LlamaIndexAdaptor,
|
||||
'chroma': ChromaAdaptor,
|
||||
# ... etc
|
||||
}
|
||||
```
|
||||
|
||||
3. **Add optional dependency:** `pyproject.toml`
|
||||
@@ -1003,8 +1537,14 @@ This section helps you quickly locate the right files when implementing common c
|
||||
```
|
||||
|
||||
4. **Add tests:** `tests/test_adaptors/test_my_platform_adaptor.py`
|
||||
- Test export format
|
||||
- Test upload (if applicable)
|
||||
- Test with real data
|
||||
|
||||
5. **Update README:** Add to platform comparison table
|
||||
5. **Update documentation:**
|
||||
- README.md - Platform comparison table
|
||||
- docs/integrations/MY_PLATFORM.md - Integration guide
|
||||
- examples/my-platform-example/ - Working example
|
||||
|
||||
### Adding a New Config Preset
|
||||
|
||||
@@ -1069,6 +1609,18 @@ This section helps you quickly locate the right files when implementing common c
|
||||
|
||||
4. **Update count:** README.md (currently 18 tools)
|
||||
|
||||
## 📍 Key Files Quick Reference
|
||||
|
||||
| Task | File(s) | What to Modify |
|
||||
|------|---------|----------------|
|
||||
| Add new CLI command | `src/skill_seekers/cli/my_cmd.py`<br>`pyproject.toml` | Create `main()` function<br>Add entry point |
|
||||
| Add platform adaptor | `src/skill_seekers/cli/adaptors/my_platform.py`<br>`adaptors/__init__.py` | Inherit `BaseAdaptor`<br>Register in factory |
|
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| Fix scraping logic | `src/skill_seekers/cli/doc_scraper.py` | `scrape_all()`, `extract_content()` |
|
||||
| Add MCP tool | `src/skill_seekers/mcp/server_fastmcp.py` | Add `@mcp.tool()` function |
|
||||
| Fix tests | `tests/test_{feature}.py` | Add/modify test functions |
|
||||
| Add config preset | `configs/{framework}.json` | Create JSON config |
|
||||
| Update CI | `.github/workflows/tests.yml` | Modify workflow steps |
|
||||
|
||||
## 📚 Key Code Locations
|
||||
|
||||
**Documentation Scraper** (`src/skill_seekers/cli/doc_scraper.py`):
|
||||
@@ -1154,15 +1706,84 @@ This section helps you quickly locate the right files when implementing common c
|
||||
- `--profile` flag to select GitHub profile from config
|
||||
- Config supports `interactive` and `github_profile` keys
|
||||
|
||||
**RAG & Vector Database Adaptors** (NEW: v3.0.0 - `src/skill_seekers/cli/adaptors/`):
|
||||
- `langchain.py` - LangChain Documents export (~250 lines)
|
||||
- Exports to LangChain Document format
|
||||
- Preserves metadata (source, category, type, url)
|
||||
- Smart chunking with overlap
|
||||
- `llama_index.py` - LlamaIndex TextNodes export (~280 lines)
|
||||
- Exports to TextNode format with unique IDs
|
||||
- Relationship mapping between documents
|
||||
- Metadata preservation
|
||||
- `haystack.py` - Haystack Documents export (~230 lines)
|
||||
- Pipeline-ready document format
|
||||
- Supports embeddings and filters
|
||||
- `chroma.py` - ChromaDB integration (~350 lines)
|
||||
- Direct collection creation
|
||||
- Batch upsert with embeddings
|
||||
- Query interface
|
||||
- `weaviate.py` - Weaviate vector search (~320 lines)
|
||||
- Schema creation with auto-detection
|
||||
- Batch import with error handling
|
||||
- `faiss_helpers.py` - FAISS index generation (~280 lines)
|
||||
- Index building with metadata
|
||||
- Search utilities
|
||||
- `qdrant.py` - Qdrant vector database (~300 lines)
|
||||
- Collection management
|
||||
- Payload indexing
|
||||
- `streaming_adaptor.py` - Streaming data ingest (~200 lines)
|
||||
- Real-time data processing
|
||||
- Incremental updates
|
||||
|
||||
**Cloud Storage & Infrastructure** (NEW: v3.0.0 - `src/skill_seekers/cli/`):
|
||||
- `cloud_storage_cli.py` - S3/GCS/Azure upload/download (~450 lines)
|
||||
- Multi-provider abstraction
|
||||
- Parallel uploads for large files
|
||||
- Retry logic with exponential backoff
|
||||
- `embedding_pipeline.py` - Embedding generation for vectors (~320 lines)
|
||||
- Sentence-transformers integration
|
||||
- Batch processing
|
||||
- Multiple embedding models
|
||||
- `sync_cli.py` - Continuous sync & monitoring (~380 lines)
|
||||
- File watching for changes
|
||||
- Automatic re-scraping
|
||||
- Smart diff detection
|
||||
- `incremental_updater.py` - Smart incremental updates (~350 lines)
|
||||
- Change detection algorithms
|
||||
- Partial skill updates
|
||||
- Version tracking
|
||||
- `streaming_ingest.py` - Real-time data streaming (~290 lines)
|
||||
- Stream processing pipelines
|
||||
- WebSocket support
|
||||
- `benchmark_cli.py` - Performance benchmarking (~280 lines)
|
||||
- Scraping performance tests
|
||||
- Comparison reports
|
||||
- CI/CD integration
|
||||
- `quality_metrics.py` - Quality analysis & reporting (~340 lines)
|
||||
- Completeness scoring
|
||||
- Link checking
|
||||
- Content quality metrics
|
||||
- `multilang_support.py` - Internationalization support (~260 lines)
|
||||
- Language detection
|
||||
- Translation integration
|
||||
- Multi-locale skills
|
||||
- `setup_wizard.py` - Interactive setup wizard (~220 lines)
|
||||
- Configuration management
|
||||
- Profile creation
|
||||
- First-time setup
|
||||
|
||||
## 🎯 Project-Specific Best Practices
|
||||
|
||||
1. **Always use platform adaptors** - Never hardcode platform-specific logic
|
||||
2. **Test all platforms** - Changes must work for all 4 platforms
|
||||
3. **Maintain backward compatibility** - Legacy configs must still work
|
||||
2. **Test all platforms** - Changes must work for all 16 platforms (was 4 in v2.x)
|
||||
3. **Maintain backward compatibility** - Legacy configs and v2.x workflows must still work
|
||||
4. **Document API changes** - Update CHANGELOG.md for every release
|
||||
5. **Keep dependencies optional** - Platform-specific deps are optional
|
||||
5. **Keep dependencies optional** - Platform-specific deps are optional (RAG, cloud, etc.)
|
||||
6. **Use src/ layout** - Proper package structure with `pip install -e .`
|
||||
7. **Run tests before commits** - Per user instructions, never skip tests
|
||||
7. **Run tests before commits** - Per user instructions, never skip tests (1,852 tests must pass)
|
||||
8. **RAG-first mindset** - v3.0.0 is the universal preprocessor for AI systems
|
||||
9. **Export format clarity** - Use `--format` for RAG/vector DBs, `--target` for LLM platforms
|
||||
10. **Test with real integrations** - Verify exports work with actual LangChain, ChromaDB, etc.
|
||||
|
||||
## 🐛 Debugging Tips
|
||||
|
||||
@@ -1422,6 +2043,20 @@ The `scripts/` directory contains utility scripts:
|
||||
|
||||
## 🎉 Recent Achievements
|
||||
|
||||
**v3.0.0 (February 10, 2026) - "Universal Intelligence Platform":**
|
||||
- 🚀 **16 Platform Adaptors** - RAG frameworks (LangChain, LlamaIndex, Haystack), vector DBs (Chroma, FAISS, Weaviate, Qdrant), AI coding assistants (Cursor, Windsurf, Cline, Continue.dev), LLM platforms (Claude, Gemini, OpenAI)
|
||||
- 🛠️ **26 MCP Tools** (up from 18) - Complete automation for any AI system
|
||||
- ✅ **1,852 Tests Passing** (up from 700+) - Production-grade reliability
|
||||
- ☁️ **Cloud Storage** - S3, GCS, Azure Blob Storage integration
|
||||
- 🎯 **AI Coding Assistants** - Persistent context for Cursor, Windsurf, Cline, Continue.dev
|
||||
- 📊 **Quality Metrics** - Automated completeness scoring and content analysis
|
||||
- 🌐 **Multilingual Support** - Language detection and translation
|
||||
- 🔄 **Streaming Ingest** - Real-time data processing pipelines
|
||||
- 📈 **Benchmarking Tools** - Performance comparison and CI/CD integration
|
||||
- 🔧 **Setup Wizard** - Interactive first-time configuration
|
||||
- 📦 **12 Example Projects** - Complete working examples for every integration
|
||||
- 📚 **18 Integration Guides** - Comprehensive documentation for all platforms
|
||||
|
||||
**v2.9.0 (February 3, 2026):**
|
||||
- **C3.10: Signal Flow Analysis** - Complete signal flow analysis for Godot projects
|
||||
- Comprehensive Godot 4.x support (GDScript, .tscn, .tres, .gdshader files)
|
||||
@@ -1448,7 +2083,7 @@ The `scripts/` directory contains utility scripts:
|
||||
|
||||
**v2.6.0 (January 14, 2026):**
|
||||
- **C3.x Codebase Analysis Suite Complete** (C3.1-C3.8)
|
||||
- Multi-platform support with platform adaptor architecture
|
||||
- Multi-platform support with platform adaptor architecture (4 platforms)
|
||||
- 18 MCP tools fully functional
|
||||
- 700+ tests passing
|
||||
- Unified multi-source scraping maturity
|
||||
|
||||
Reference in New Issue
Block a user