mindnet/app/core/ingestion.py

"""
app/core/ingestion.py

Zentraler Service für die Transformation von Markdown-Dateien in Qdrant-Objekte (Notes, Chunks, Edges).
Features:
- Incremental Update (Hashing) für Massenimport.
- Force Smart Edges für Single-File (UI).
- Async Embedding & Chunking.

Version: 2.5.1 (Full Restore + WP-15 Logic)
"""
import os
import logging
import asyncio
import time
from typing import Dict, List, Optional, Tuple, Any

# Core Module Imports
from app.core.parser import (
    read_markdown,
    normalize_frontmatter,
    validate_required_frontmatter,
)
from app.core.note_payload import make_note_payload
# ASYNC CHUNKER (WP-15)
from app.core.chunker import assemble_chunks, get_chunk_config
from app.core.chunk_payload import make_chunk_payloads

# Fallback für Edges Import
try:
    from app.core.derive_edges import build_edges_for_note
except ImportError:
    def build_edges_for_note(*args, **kwargs): return []

from app.core.qdrant import QdrantConfig, get_client, ensure_collections, ensure_payload_indexes
from app.core.qdrant_points import (
    points_for_chunks,
    points_for_note,
    points_for_edges,
    upsert_batch,
)

from app.services.embeddings_client import EmbeddingsClient

logger = logging.getLogger(__name__)

# --- Helper ---
def load_type_registry(custom_path: Optional[str] = None) -> dict:
    import yaml
    path = custom_path or os.getenv("MINDNET_TYPES_FILE", "config/types.yaml")
    if not os.path.exists(path): return {}
    try:
        with open(path, "r", encoding="utf-8") as f: return yaml.safe_load(f) or {}
    except Exception: return {}

def resolve_note_type(requested: Optional[str], reg: dict) -> str:
    types = reg.get("types", {})
    if requested and requested in types: return requested
    return "concept" 

class IngestionService:
    def __init__(self, collection_prefix: str = None):
        env_prefix = os.getenv("COLLECTION_PREFIX", "mindnet")
        self.prefix = collection_prefix or env_prefix
        
        self.cfg = QdrantConfig.from_env()
        self.cfg.prefix = self.prefix 
        self.client = get_client(self.cfg)
        self.dim = self.cfg.dim
        self.registry = load_type_registry()
        self.embedder = EmbeddingsClient()
        
        # Init Checks
        try:
            ensure_collections(self.client, self.prefix, self.dim)
            ensure_payload_indexes(self.client, self.prefix)
        except Exception as e:
            logger.warning(f"DB init warning: {e}")

    async def process_file(
        self, 
        file_path: str, 
        vault_root: str,
        force_replace: bool = False,
        apply: bool = False,
        purge_before: bool = False,
        note_scope_refs: bool = False,
        hash_mode: str = "body",
        hash_source: str = "parsed",
        hash_normalize: str = "canonical",
        force_smart_edges: bool = False  # NEU: Override für UI
    ) -> Dict[str, Any]:
        """
        Verarbeitet eine einzelne Datei (ASYNC).
        Enthält Hashing-Logik für inkrementelle Updates.
        """
        result = {
            "path": file_path,
            "status": "skipped",
            "changed": False,
            "error": None
        }

        # 1. Parse & Validate
        try:
            parsed = read_markdown(file_path)
            if not parsed: return {**result, "error": "Empty/Unreadable"}
            
            fm = normalize_frontmatter(parsed.frontmatter)
            validate_required_frontmatter(fm)
        except Exception as e:
            logger.error(f"Validation failed for {file_path}: {e}")
            return {**result, "error": f"Validation failed: {str(e)}"}

        # 2. Resolve Type
        note_type = resolve_note_type(fm.get("type"), self.registry)
        fm["type"] = note_type
        
        # 3. Build Payload & Hash
        try:
            note_pl = make_note_payload(
                parsed, 
                vault_root=vault_root, 
                file_path=file_path,
                hash_mode=hash_mode,
                hash_normalize=hash_normalize,
                hash_source=hash_source
            )
            if not note_pl.get("fulltext"): 
                note_pl["fulltext"] = getattr(parsed, "body", "") or ""
            
            note_id = note_pl["note_id"]
        except Exception as e:
             return {**result, "error": f"Payload build failed: {str(e)}"}

        # 4. Change Detection (Das Herzstück für Massenimport)
        old_payload = None
        if not force_replace:
            old_payload = self._fetch_note_payload(note_id)
        
        has_old = old_payload is not None
        
        # Hash Vergleich
        key_current = f"{hash_mode}:{hash_source}:{hash_normalize}"
        old_hash = (old_payload or {}).get("hashes", {}).get(key_current)
        new_hash = note_pl.get("hashes", {}).get(key_current)
        
        hash_changed = (old_hash != new_hash)
        
        # Check ob Chunks/Edges in DB fehlen (Reparatur-Modus)
        chunks_missing, edges_missing = self._artifacts_missing(note_id)
        
        should_write = force_replace or (not has_old) or hash_changed or chunks_missing or edges_missing

        if not should_write:
            return {**result, "status": "unchanged", "note_id": note_id}

        if not apply:
            return {**result, "status": "dry-run", "changed": True, "note_id": note_id}

        # 5. Processing (Chunking, Embedding)
        try:
            body_text = getattr(parsed, "body", "") or ""
            
            # --- WP-15 LOGIC ---
            # Config laden und ggf. überschreiben
            chunk_config = get_chunk_config(note_type)
            if force_smart_edges:
                logger.info(f"Ingestion: Forcing Smart Edges for {note_id}")
                chunk_config["enable_smart_edge_allocation"] = True
            
            # Async Chunking
            chunks = await assemble_chunks(fm["id"], body_text, fm["type"], config=chunk_config)
            chunk_pls = make_chunk_payloads(fm, note_pl["path"], chunks, note_text=body_text)
            
            # Embedding
            vecs = []
            if chunk_pls:
                texts = [c.get("window") or c.get("text") or "" for c in chunk_pls]
                try:
                    if hasattr(self.embedder, 'embed_documents'):
                        vecs = await self.embedder.embed_documents(texts)
                    else:
                        for t in texts: vecs.append(await self.embedder.embed_query(t))
                except Exception as e:
                    # Embedding Fehler sind kritisch
                    logger.error(f"Embedding failed: {e}")
                    raise e
            
            # Edges
            try:
                edges = build_edges_for_note(
                    note_id, 
                    chunk_pls, 
                    note_level_references=note_pl.get("references", []),
                    include_note_scope_refs=note_scope_refs
                )
            except TypeError:
                edges = build_edges_for_note(note_id, chunk_pls)

        except Exception as e:
            logger.error(f"Processing failed: {e}", exc_info=True)
            return {**result, "error": f"Processing failed: {str(e)}"}

        # 6. Upsert (Atomic Write recommended, here Batch)
        try:
            if purge_before and has_old:
                self._purge_artifacts(note_id)

            n_name, n_pts = points_for_note(self.prefix, note_pl, None, self.dim)
            upsert_batch(self.client, n_name, n_pts)

            if chunk_pls and vecs:
                c_name, c_pts = points_for_chunks(self.prefix, chunk_pls, vecs)
                upsert_batch(self.client, c_name, c_pts)
            
            if edges:
                e_name, e_pts = points_for_edges(self.prefix, edges)
                upsert_batch(self.client, e_name, e_pts)

            return {
                "path": file_path,
                "status": "success",
                "changed": True,
                "note_id": note_id,
                "chunks_count": len(chunk_pls),
                "edges_count": len(edges)
            }
        except Exception as e:
            logger.error(f"Upsert failed: {e}", exc_info=True)
            return {**result, "error": f"DB Upsert failed: {e}"}

    # --- Interne Qdrant Helper (Wichtig für Change Detection) ---
    
    def _fetch_note_payload(self, note_id: str) -> Optional[dict]:
        from qdrant_client.http import models as rest
        col = f"{self.prefix}_notes"
        try:
            f = rest.Filter(must=[rest.FieldCondition(key="note_id", match=rest.MatchValue(value=note_id))])
            pts, _ = self.client.scroll(collection_name=col, scroll_filter=f, limit=1, with_payload=True)
            return pts[0].payload if pts else None
        except: return None

    def _artifacts_missing(self, note_id: str) -> Tuple[bool, bool]:
        from qdrant_client.http import models as rest
        c_col = f"{self.prefix}_chunks"
        e_col = f"{self.prefix}_edges"
        try:
            f = rest.Filter(must=[rest.FieldCondition(key="note_id", match=rest.MatchValue(value=note_id))])
            c_pts, _ = self.client.scroll(collection_name=c_col, scroll_filter=f, limit=1)
            e_pts, _ = self.client.scroll(collection_name=e_col, scroll_filter=f, limit=1)
            return (not bool(c_pts)), (not bool(e_pts))
        except: return True, True

    def _purge_artifacts(self, note_id: str):
        from qdrant_client.http import models as rest
        f = rest.Filter(must=[rest.FieldCondition(key="note_id", match=rest.MatchValue(value=note_id))])
        selector = rest.FilterSelector(filter=f)
        for suffix in ["chunks", "edges"]:
            try:
                self.client.delete(collection_name=f"{self.prefix}_{suffix}", points_selector=selector)
            except Exception: pass
    
    async def create_from_text(
            self,
            markdown_content: str,
            filename: str,
            vault_root: str,
            folder: str = "00_Inbox" 
        ) -> Dict[str, Any]:
            """
            WP-11 Persistence API Entrypoint.
            Speichert Text und erzwingt sofortige Indizierung mit Smart Edges.
            """
            target_dir = os.path.join(vault_root, folder)
            os.makedirs(target_dir, exist_ok=True)
            
            file_path = os.path.join(target_dir, filename)
            
            try:
                # Robust Write: Ensure Flush
                with open(file_path, "w", encoding="utf-8") as f:
                    f.write(markdown_content)
                    f.flush()
                    os.fsync(f.fileno())
                
                # Kurzer Sleep für OS Filesystem Latenz
                await asyncio.sleep(0.1) 
                
                logger.info(f"Written file to {file_path}")
            except Exception as e:
                return {"status": "error", "error": f"Disk write failed: {str(e)}"}
                
            # Hier aktivieren wir die Smart Edges explizit für den Single-File Import
            return await self.process_file(
                file_path=file_path,
                vault_root=vault_root,
                apply=True,          
                force_replace=True,  
                purge_before=True,
                force_smart_edges=True  # <--- HIER: Intelligence Override
            )