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Deploy mindnet to llm-node / deploy (push) Successful in 3s

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Lars 2025-12-22 05:56:36 +01:00
parent 0c2dc61cb5
commit 74cac7e16c

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import asyncio
import os
import sys
from pathlib import Path
# Pfad-Setup
sys.path.insert(0, os.path.abspath("."))
from app.core.chunker import assemble_chunks, _extract_all_edges_from_md
from app.core.derive_edges import build_edges_for_note
# Mock für Settings, falls nötig
os.environ["MINDNET_LLM_MODEL"] = "phi3:mini"
async def analyze_file(file_path: str):
print(f"\n=== ANALYSE: {file_path} ===")
with open(file_path, "r", encoding="utf-8") as f:
text = f.read()
# 1. Globale Kandidaten (Was sieht der Pre-Scan?)
# Wir simulieren den Aufruf, den der Chunker macht
note_id = Path(file_path).stem
candidates = _extract_all_edges_from_md(text, note_id, "concept")
print(f"\n[1] Globale Kandidaten (Pre-Scan):")
for c in candidates:
print(f" - {c}")
# 2. Chunking (Ohne Smart Edges erstmal, um die physische Integrität zu prüfen)
# Wir nutzen ein Profil, das dem User-Setup entspricht
config = {
"strategy": "sliding_window",
"target": 400,
"max": 600,
"overlap": 50,
"enable_smart_edge_allocation": False # Erstmal aus
}
chunks = await assemble_chunks(note_id, text, "concept", config=config)
print(f"\n[2] Chunk-Struktur & Physische Kanten:")
for i, chunk in enumerate(chunks):
print(f"\n--- Chunk {i} (Section: {chunk.section_path}) ---")
print(f"Snippet: {chunk.text[:50]}...")
# Was findet derive_edges in diesem rohen Chunk?
# Wir simulieren das Payload-Dict, das derive_edges erwartet
chunk_pl = {"text": chunk.text, "window": chunk.window, "chunk_id": chunk.id}
edges = build_edges_for_note(note_id, [chunk_pl])
found_explicitly = [f"{e['kind']}:{e.get('target_id')}" for e in edges if e['rule_id'] in ['callout:edge', 'inline:rel']]
if found_explicitly:
print(f" ✅ Gefundene Explizite Kanten: {found_explicitly}")
else:
print(f" ❌ Keine expliziten Kanten gefunden (trotz Callout im Text?)")
# Check auf Callout im Text
if "> [!edge]" in chunk.text:
print(" HINWEIS: '> [!edge]' String ist im Text vorhanden!")
if __name__ == "__main__":
# Pfad zu deiner problematischen Datei hier anpassen!
target_file = "./vault_master/Dein_Problematisches_File.md"
if len(sys.argv) > 1:
target_file = sys.argv[1]
asyncio.run(analyze_file(target_file))