docs: Add 4 comprehensive vector database examples (Weaviate, Chroma, FAISS, Qdrant)

Created complete working examples for all 4 vector databases with RAG adaptors:

Weaviate Example:
- Comprehensive README with hybrid search guide
- 3 Python scripts (generate, upload, query)
- Sample outputs and query results
- Covers hybrid search, filtering, schema design

Chroma Example:
- Simple, local-first approach
- In-memory and persistent storage options
- Semantic search and metadata filtering
- Comparison with Weaviate

FAISS Example:
- Facebook AI Similarity Search integration
- OpenAI embeddings generation
- Index building and persistence
- Performance-focused for scale

Qdrant Example:
- Advanced filtering capabilities
- Production-ready features
- Complex query patterns
- Rust-based performance

Each example includes:
- Detailed README with setup and troubleshooting
- requirements.txt with dependencies
- 3 working Python scripts
- Sample outputs directory

Total files: 20 (4 examples × 5 files each)
Documentation: 4 comprehensive READMEs (~800 lines total)

Phase 2 of optional enhancements complete.

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

examples/chroma-example/1_generate_skill.py

@@ -0,0 +1,88 @@
+#!/usr/bin/env python3
+"""
+Step 1: Generate Skill for ChromaDB
+
+This script:
+1. Scrapes Vue documentation (limited to 20 pages for demo)
+2. Packages the skill in ChromaDB format
+3. Saves to output/vue-chroma.json
+
+Usage:
+    python 1_generate_skill.py
+"""
+
+import subprocess
+import sys
+from pathlib import Path
+
+def main():
+    print("=" * 60)
+    print("Step 1: Generating Skill for ChromaDB")
+    print("=" * 60)
+
+    # Check if skill-seekers is installed
+    try:
+        result = subprocess.run(
+            ["skill-seekers", "--version"],
+            capture_output=True,
+            text=True
+        )
+        print(f"\n✅ skill-seekers found: {result.stdout.strip()}")
+    except FileNotFoundError:
+        print("\n❌ skill-seekers not found!")
+        print("Install it with: pip install skill-seekers")
+        sys.exit(1)
+
+    # Step 1: Scrape Vue docs (small sample for demo)
+    print("\n📥 Step 1/2: Scraping Vue documentation (20 pages)...")
+    print("This may take 1-2 minutes...\n")
+
+    scrape_result = subprocess.run(
+        [
+            "skill-seekers", "scrape",
+            "--config", "configs/vue.json",
+            "--max-pages", "20",
+        ],
+        capture_output=True,
+        text=True
+    )
+
+    if scrape_result.returncode != 0:
+        print(f"❌ Scraping failed:\n{scrape_result.stderr}")
+        sys.exit(1)
+
+    print("✅ Scraping completed!")
+
+    # Step 2: Package for ChromaDB
+    print("\n📦 Step 2/2: Packaging for ChromaDB...\n")
+
+    package_result = subprocess.run(
+        [
+            "skill-seekers", "package",
+            "output/vue",
+            "--target", "chroma",
+        ],
+        capture_output=True,
+        text=True
+    )
+
+    if package_result.returncode != 0:
+        print(f"❌ Packaging failed:\n{package_result.stderr}")
+        sys.exit(1)
+
+    # Show the output
+    print(package_result.stdout)
+
+    # Check if output file exists
+    output_file = Path("output/vue-chroma.json")
+    if output_file.exists():
+        size_kb = output_file.stat().st_size / 1024
+        print(f"📄 File size: {size_kb:.1f} KB")
+        print(f"📂 Location: {output_file.absolute()}")
+        print("\n✅ Ready for upload! Next step: python 2_upload_to_chroma.py")
+    else:
+        print("❌ Output file not found!")
+        sys.exit(1)
+
+if __name__ == "__main__":
+    main()