Add RAG ingestion script

ingest_to_rag.py

@@ -0,0 +1,130 @@
+#!/usr/bin/env python3
+"""
+ingest_to_rag.py
+
+Push ask-annie chunks.json into the knowledge-mcp RAG notebook.
+
+Usage:
+  python3 ingest_to_rag.py --chunks out/1020102626/chunks.json \
+    --notebook securetransport-md \
+    --mcporter /path/to/mcporter.json
+"""
+
+import argparse
+import json
+import subprocess
+import sys
+import time
+from pathlib import Path
+
+
+def mcporter_call(config_path, tool, args_dict):
+    """Call an MCP tool via mcporter CLI."""
+    cmd = [
+        "mcporter", "call", tool,
+        "--config", config_path,
+        "--args", json.dumps(args_dict),
+        "--output", "json",
+    ]
+    result = subprocess.run(cmd, capture_output=True, text=True)
+    if result.returncode != 0:
+        raise RuntimeError(f"mcporter error: {result.stderr.strip()}")
+    try:
+        return json.loads(result.stdout)
+    except json.JSONDecodeError:
+        raise RuntimeError(f"mcporter bad output: {result.stdout!r}")
+
+
+def chunk_to_markdown(chunk):
+    """Format a chunk as markdown for ingestion."""
+    lines = [
+        f"# {chunk['title']}",
+        f"",
+        f"**Series:** {chunk['series']}",
+        f"**Video:** [{chunk['video_id']}]({chunk['video_url']}) @ {chunk['timestamp']}",
+        f"**Type:** {'Demo/walkthrough' if chunk['is_demo'] else 'Q&A'}",
+        f"",
+        f"## Summary",
+        f"",
+        chunk['summary'],
+        f"",
+    ]
+    if chunk.get('transcript'):
+        lines += [
+            f"## Transcript",
+            f"",
+            chunk['transcript'],
+            f"",
+        ]
+    return "\n".join(lines)
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Ingest Ask Annie chunks into knowledge-mcp RAG")
+    parser.add_argument("--chunks", required=True, help="Path to chunks.json")
+    parser.add_argument("--notebook", default="securetransport-md", help="knowledge-mcp notebook ID")
+    parser.add_argument("--mcporter", default="/home/node/.openclaw/workspace/config/mcporter.json",
+                        help="Path to mcporter config")
+    parser.add_argument("--dry-run", action="store_true", help="Print what would be ingested, don't send")
+    parser.add_argument("--skip", type=int, default=0, help="Skip first N chunks (resume)")
+    args = parser.parse_args()
+
+    with open(args.chunks) as f:
+        chunks = json.load(f)
+
+    print(f"Loaded {len(chunks)} chunks from {args.chunks}")
+    print(f"Notebook: {args.notebook}")
+    print(f"Dry run: {args.dry_run}")
+    if args.skip:
+        print(f"Skipping first {args.skip} chunks")
+    print()
+
+    success = 0
+    failed = 0
+
+    for i, chunk in enumerate(chunks):
+        if i < args.skip:
+            continue
+
+        content = chunk_to_markdown(chunk)
+        metadata = {
+            "source": "ask-annie",
+            "series": chunk["series"],
+            "video_id": chunk["video_id"],
+            "video_url": chunk["video_url"],
+            "chapter_index": chunk["chapter_index"],
+            "timestamp": chunk["timestamp"],
+            "title": chunk["title"],
+            "is_demo": chunk["is_demo"],
+        }
+
+        print(f"[{i:02d}/{len(chunks)-1}] {chunk['timestamp']} — {chunk['title'][:55]}")
+
+        if args.dry_run:
+            print(f"  Would ingest {len(content)} chars")
+            continue
+
+        try:
+            result = mcporter_call(
+                args.mcporter,
+                "knowledge-mcp.add_source",
+                {
+                    "notebook_id": args.notebook,
+                    "content": content,
+                    "metadata": metadata,
+                }
+            )
+            print(f"  ✅ ok")
+            success += 1
+        except Exception as e:
+            print(f"  ❌ failed: {e}")
+            failed += 1
+
+        # Brief pause to avoid hammering the API
+        time.sleep(0.5)
+
+    print(f"\n=== Done: {success} ingested, {failed} failed ===")
+
+
+if __name__ == "__main__":
+    main()