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Deploy mindnet to llm-node / deploy (push) Successful in 3s
110 lines
3.9 KiB
Python
110 lines
3.9 KiB
Python
#!/usr/bin/env python3
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from __future__ import annotations
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import argparse, os, glob, json, sys
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from dotenv import load_dotenv
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from qdrant_client import QdrantClient
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from app.core.parser import read_markdown, normalize_frontmatter, validate_required_frontmatter
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from app.core.note_payload import make_note_payload
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from app.core.validate_note import validate_note_payload
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from app.core.chunker import assemble_chunks
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from app.core.chunk_payload import make_chunk_payloads
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from app.core.embed import embed_texts, embed_one
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from app.core.qdrant import QdrantConfig, ensure_collections, get_client
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from app.core.qdrant_points import points_for_chunks, points_for_note, points_for_edges, upsert_batch
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from app.core.edges import deriv_edges_for_note
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def iter_md(root: str, exclude=(" /.obsidian/ ", " /_backup_frontmatter/ ", " /_imported/ ")):
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files = [p for p in glob.glob(os.path.join(root, "**", "*.md"), recursive=True)]
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out = []
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for p in files:
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pn = p.replace("\\","/")
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if any(ex.strip() in pn for ex in ["/.obsidian/", "/_backup_frontmatter/", "/_imported/"]):
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continue
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out.append(p)
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return out
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def main():
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load_dotenv()
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ap = argparse.ArgumentParser()
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ap.add_argument("--vault", required=True, help="Obsidian Vault Pfad (z.B. mindnet/vault)")
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ap.add_argument("--apply", action="store_true", help="Schreibt in Qdrant (sonst Dry-Run)")
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ap.add_argument("--note-id", help="Nur eine Note-ID verarbeiten")
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ap.add_argument("--embed-note", action="store_true", help="Auch Note-Volltext einbetten (optional)")
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args = ap.parse_args()
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# Qdrant
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cfg = QdrantConfig(
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url=os.getenv("QDRANT_URL", "http://127.0.0.1:6333"),
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api_key=os.getenv("QDRANT_API_KEY") or None,
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prefix=os.getenv("COLLECTION_PREFIX", "mindnet"),
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dim=int(os.getenv("VECTOR_DIM","384")),
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)
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client = get_client(cfg)
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ensure_collections(cfg)
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root = os.path.abspath(args.vault)
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files = iter_md(root)
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if not files:
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print("Keine Markdown-Dateien gefunden.", file=sys.stderr); sys.exit(2)
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total_notes = 0
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for path in files:
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parsed = read_markdown(path)
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fm = normalize_frontmatter(parsed.frontmatter)
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try:
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validate_required_frontmatter(fm)
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except Exception:
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continue
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if args.note_id and fm.get("id") != args.note_id:
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continue
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total_notes += 1
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# Note-Payload
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note_pl = make_note_payload(parsed, vault_root=root)
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validate_note_payload(note_pl)
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# Chunks
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chunks = assemble_chunks(fm["id"], parsed.body, fm.get("type", "concept"))
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chunk_pls = make_chunk_payloads(fm, note_pl["path"], chunks)
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# Embeddings (Chunks)
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texts = [c for c in (ch.text for ch in chunks)]
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vectors = embed_texts(texts)
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# Optional: Note-Vektor
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note_vec = None
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if args.embed_note:
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note_vec = embed_one(parsed.body)
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# Kanten
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edges = deriv_edges_for_note(fm, chunk_pls)
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# Dry-Run-Ausgabe
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summary = {
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"note_id": fm["id"],
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"title": fm["title"],
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"chunks": len(chunk_pls),
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"edges": len(edges),
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"path": note_pl["path"]
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}
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print(json.dumps(summary, ensure_ascii=False))
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if args.apply:
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# Notes upsert
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notes_col, note_pts = points_for_note(cfg.prefix, note_pl, note_vec)
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upsert_batch(client, notes_col, note_pts)
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# Chunks upsert
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chunks_col, chunk_pts = points_for_chunks(cfg.prefix, chunk_pls, vectors)
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upsert_batch(client, chunks_col, chunk_pts)
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# Edges upsert
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edges_col, edge_pts = points_for_edges(cfg.prefix, edges)
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upsert_batch(client, edges_col, edge_pts)
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print(f"Done. Processed notes: {total_notes}")
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if __name__ == "__main__":
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main()
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