Initial commit: workspace setup with skills, memory, config

2026-02-10 14:37:49 -06:00
commit d1357c5463
77 changed files with 10822 additions and 0 deletions
--- a/skills/qdrant-memory/scripts/kb_search.py
+++ b/skills/qdrant-memory/scripts/kb_search.py
@@ -0,0 +1,136 @@
+#!/usr/bin/env python3
+"""
+Search kimi_kb (Knowledge Base) - Manual only
+
+Usage:
+    python3 kb_search.py "query"
+    python3 kb_search.py "docker volumes" --domain "Docker"
+    python3 kb_search.py "query" --include-urls
+"""
+
+import json
+import sys
+import urllib.request
+from pathlib import Path
+
+QDRANT_URL = "http://10.0.0.40:6333"
+COLLECTION = "kimi_kb"
+OLLAMA_URL = "http://10.0.0.10:11434/v1"
+
+def get_embedding(text):
+    """Generate embedding using snowflake-arctic-embed2"""
+    data = json.dumps({
+        "model": "snowflake-arctic-embed2",
+        "input": text[:8192]
+    }).encode()
+    
+    req = urllib.request.Request(
+        f"{OLLAMA_URL}/embeddings",
+        data=data,
+        headers={"Content-Type": "application/json"}
+    )
+    
+    try:
+        with urllib.request.urlopen(req, timeout=60) as response:
+            result = json.loads(response.read().decode())
+            return result["data"][0]["embedding"]
+    except Exception as e:
+        print(f"Error generating embedding: {e}", file=sys.stderr)
+        return None
+
+def search_kb(query, domain=None, limit=5):
+    """Search knowledge base"""
+    
+    embedding = get_embedding(query)
+    if embedding is None:
+        return None
+    
+    # Build filter if domain specified
+    filter_clause = {}
+    if domain:
+        filter_clause = {
+            "must": [
+                {"key": "domain", "match": {"value": domain}}
+            ]
+        }
+    
+    search_body = {
+        "vector": embedding,
+        "limit": limit,
+        "with_payload": True,
+        "with_vector": False
+    }
+    
+    if filter_clause:
+        search_body["filter"] = filter_clause
+    
+    data = json.dumps(search_body).encode()
+    req = urllib.request.Request(
+        f"{QDRANT_URL}/collections/{COLLECTION}/points/search",
+        data=data,
+        headers={"Content-Type": "application/json"}
+    )
+    
+    try:
+        with urllib.request.urlopen(req, timeout=30) as response:
+            result = json.loads(response.read().decode())
+            return result.get("result", [])
+    except Exception as e:
+        print(f"Error searching KB: {e}", file=sys.stderr)
+        return None
+
+def format_result(point, idx):
+    """Format a search result for display"""
+    payload = point.get("payload", {})
+    score = point.get("score", 0)
+    
+    output = f"\n[{idx}] {payload.get('title', 'Untitled')} (score: {score:.3f})\n"
+    output += f"    Domain: {payload.get('domain', 'unknown')}\n"
+    
+    if payload.get('url'):
+        output += f"    URL: {payload['url']}\n"
+    if payload.get('source'):
+        output += f"    Source: {payload['source']}\n"
+    
+    text = payload.get('text', '')[:300]
+    if len(payload.get('text', '')) > 300:
+        text += "..."
+    output += f"    Content: {text}\n"
+    
+    return output
+
+def main():
+    import argparse
+    
+    parser = argparse.ArgumentParser(description="Search kimi_kb")
+    parser.add_argument("query", help="Search query")
+    parser.add_argument("--domain", default=None, help="Filter by domain")
+    parser.add_argument("--limit", type=int, default=5, help="Number of results")
+    parser.add_argument("--json", action="store_true", help="Output as JSON")
+    
+    args = parser.parse_args()
+    
+    print(f"🔍 Searching kimi_kb: {args.query}")
+    if args.domain:
+        print(f"   Filter: domain={args.domain}")
+    print()
+    
+    results = search_kb(args.query, args.domain, args.limit)
+    
+    if results is None:
+        print("❌ Search failed", file=sys.stderr)
+        sys.exit(1)
+    
+    if not results:
+        print("No results found in kimi_kb")
+        return
+    
+    if args.json:
+        print(json.dumps(results, indent=2))
+    else:
+        print(f"Found {len(results)} results:\n")
+        for i, point in enumerate(results, 1):
+            print(format_result(point, i))
+
+if __name__ == "__main__":
+    main()