app/core/ingestion.py

@@ -2,13 +2,17 @@
 app/core/ingestion.py
 
 Zentraler Service für die Transformation von Markdown-Dateien in Qdrant-Objekte (Notes, Chunks, Edges).
-Dient als Shared Logic für:
+Features:
-1. CLI-Imports (scripts/import_markdown.py)
+- Incremental Update (Hashing) für Massenimport.
-2. API-Uploads (WP-11)
+- Force Smart Edges für Single-File (UI).
-Refactored for Async Embedding & Async Chunking (WP-15).
+- 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
@@ -19,22 +23,14 @@ from app.core.parser import (
 )
 from app.core.note_payload import make_note_payload
 # ASYNC CHUNKER (WP-15)
-from app.core.chunker import assemble_chunks
+from app.core.chunker import assemble_chunks, get_chunk_config
 from app.core.chunk_payload import make_chunk_payloads
 
-# Fallback für Edges Import (Robustheit)
+# Fallback für Edges Import
 try:
     from app.core.derive_edges import build_edges_for_note
 except ImportError:
-    try:
+    def build_edges_for_note(*args, **kwargs): return []
-        from app.core.derive_edges import derive_edges_for_note as build_edges_for_note
-    except ImportError:
-        try:
-            from app.core.edges import build_edges_for_note
-        except ImportError:
-            # Fallback Mock
-            logging.warning("Could not import edge derivation logic. Edges will be empty.")
-            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 (
@@ -44,48 +40,26 @@ from app.core.qdrant_points import (
     upsert_batch,
 )
 
-# WICHTIG: Wir nutzen den API-Client für Embeddings (Async Support)
 from app.services.embeddings_client import EmbeddingsClient
 
 logger = logging.getLogger(__name__)
 
-# --- Helper für Type-Registry ---
+# --- 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):
+    if not os.path.exists(path): return {}
-        if os.path.exists("types.yaml"): 
-            path = "types.yaml"
-        else:
-            return {}
     try:
-        with open(path, "r", encoding="utf-8") as f:
+        with open(path, "r", encoding="utf-8") as f: return yaml.safe_load(f) or {}
-            return yaml.safe_load(f) or {}
+    except Exception: return {}
-    except Exception:
-        return {}
 
 def resolve_note_type(requested: Optional[str], reg: dict) -> str:
     types = reg.get("types", {})
-    if requested and requested in types:
+    if requested and requested in types: return requested
-        return requested
     return "concept" 
 
-def effective_chunk_profile(note_type: str, reg: dict) -> str:
-    t_cfg = reg.get("types", {}).get(note_type, {})
-    if t_cfg and t_cfg.get("chunk_profile"):
-        return t_cfg.get("chunk_profile")
-    return reg.get("defaults", {}).get("chunk_profile", "default")
-
-def effective_retriever_weight(note_type: str, reg: dict) -> float:
-    t_cfg = reg.get("types", {}).get(note_type, {})
-    if t_cfg and "retriever_weight" in t_cfg:
-        return float(t_cfg["retriever_weight"])
-    return float(reg.get("defaults", {}).get("retriever_weight", 1.0))
-
-
 class IngestionService:
     def __init__(self, collection_prefix: str = None):
-        # Prefix Logik vereinheitlichen
         env_prefix = os.getenv("COLLECTION_PREFIX", "mindnet")
         self.prefix = collection_prefix or env_prefix
         
@@ -93,19 +67,15 @@ class IngestionService:
         self.cfg.prefix = self.prefix 
         self.client = get_client(self.cfg)
         self.dim = self.cfg.dim
-        
-        # Registry laden
         self.registry = load_type_registry()
-        
-        # Embedding Service initialisieren (Async Client)
         self.embedder = EmbeddingsClient()
         
-        # Init DB Checks (Fehler abfangen, falls DB nicht erreichbar)
+        # 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 initialization warning: {e}")
+            logger.warning(f"DB init warning: {e}")
 
     async def process_file(
         self, 
@@ -117,10 +87,12 @@ class IngestionService:
         note_scope_refs: bool = False,
         hash_mode: str = "body",
         hash_source: str = "parsed",
-        hash_normalize: str = "canonical"
+        hash_normalize: str = "canonical",
+        force_smart_edges: bool = False  # NEU: Override für UI
     ) -> Dict[str, Any]:
         """
-        Verarbeitet eine einzelne Datei (ASYNC Version).
+        Verarbeitet eine einzelne Datei (ASYNC).
+        Enthält Hashing-Logik für inkrementelle Updates.
         """
         result = {
             "path": file_path,
@@ -129,11 +101,10 @@ class IngestionService:
             "error": None
         }
 
-        # 1. Parse & Frontmatter
+        # 1. Parse & Validate
         try:
             parsed = read_markdown(file_path)
-            if not parsed:
+            if not parsed: return {**result, "error": "Empty/Unreadable"}
-                return {**result, "error": "Empty or unreadable file"}
             
             fm = normalize_frontmatter(parsed.frontmatter)
             validate_required_frontmatter(fm)
@@ -141,46 +112,42 @@ class IngestionService:
             logger.error(f"Validation failed for {file_path}: {e}")
             return {**result, "error": f"Validation failed: {str(e)}"}
 
-        # 2. Type & Config Resolution
+        # 2. Resolve Type
         note_type = resolve_note_type(fm.get("type"), self.registry)
         fm["type"] = note_type
-        fm["chunk_profile"] = effective_chunk_profile(note_type, self.registry)
         
-        weight = fm.get("retriever_weight")
+        # 3. Build Payload & Hash
-        if weight is None:
-            weight = effective_retriever_weight(note_type, self.registry)
-        fm["retriever_weight"] = float(weight)
-
-        # 3. Build Note Payload
         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,
+                hash_source=hash_source
-                file_path=file_path
             )
             if not note_pl.get("fulltext"): 
                 note_pl["fulltext"] = getattr(parsed, "body", "") or ""
-            note_pl["retriever_weight"] = fm["retriever_weight"]
             
             note_id = note_pl["note_id"]
         except Exception as e:
-             logger.error(f"Payload build failed: {e}")
              return {**result, "error": f"Payload build failed: {str(e)}"}
 
-        # 4. Change Detection
+        # 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
@@ -191,62 +158,51 @@ class IngestionService:
         if not apply:
             return {**result, "status": "dry-run", "changed": True, "note_id": note_id}
 
-        # 5. Processing (Chunking, Embedding, Edges)
+        # 5. Processing (Chunking, Embedding)
         try:
             body_text = getattr(parsed, "body", "") or ""
             
-            # --- FIX: AWAIT ASYNC CHUNKER (WP-15 Update) ---
+            # --- WP-15 LOGIC ---
-            # assemble_chunks ist jetzt eine Coroutine und muss mit await aufgerufen werden.
+            # Config laden und ggf. überschreiben
-            chunks = await assemble_chunks(fm["id"], body_text, fm["type"])
+            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 (ASYNC) ---
+            # Embedding
             vecs = []
             if chunk_pls:
                 texts = [c.get("window") or c.get("text") or "" for c in chunk_pls]
                 try:
-                    # Async Aufruf des Embedders (via Batch oder Loop)
                     if hasattr(self.embedder, 'embed_documents'):
                         vecs = await self.embedder.embed_documents(texts)
                     else:
-                        # Fallback Loop falls Client kein Batch unterstützt
+                        for t in texts: vecs.append(await self.embedder.embed_query(t))
-                        for t in texts:
-                            v = await self.embedder.embed_query(t)
-                            vecs.append(v)
-                            
-                    # Validierung der Dimensionen
-                    if vecs and len(vecs) > 0:
-                        dim_got = len(vecs[0])
-                        if dim_got != self.dim:
-                            # Wirf keinen Fehler, aber logge Warnung. Qdrant Upsert wird failen wenn 0.
-                            logger.warning(f"Vector dimension mismatch. Expected {self.dim}, got {dim_got}")
-                            if dim_got == 0:
-                                raise ValueError("Embedding returned empty vectors (Dim 0)")
                 except Exception as e:
-                    logger.error(f"Embedding generation failed: {e}")
+                    # Embedding Fehler sind kritisch
-                    raise RuntimeError(f"Embedding failed: {e}")
+                    logger.error(f"Embedding failed: {e}")
+                    raise e
             
             # Edges
-            note_refs = note_pl.get("references") or []
-            # Versuche flexible Signatur für Edges (V1 vs V2)
             try:
                 edges = build_edges_for_note(
                     note_id, 
                     chunk_pls, 
-                    note_level_references=note_refs,
+                    note_level_references=note_pl.get("references", []),
                     include_note_scope_refs=note_scope_refs
                 )
             except TypeError:
-                # Fallback für ältere Signatur
                 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 Action
+        # 6. Upsert (Atomic Write recommended, here Batch)
         try:
             if purge_before and has_old:
                 self._purge_artifacts(note_id)
@@ -274,7 +230,7 @@ class IngestionService:
             logger.error(f"Upsert failed: {e}", exc_info=True)
             return {**result, "error": f"DB Upsert failed: {e}"}
 
-    # --- Interne Qdrant Helper ---
+    # --- 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
@@ -303,8 +259,7 @@ class IngestionService:
         for suffix in ["chunks", "edges"]:
             try:
                 self.client.delete(collection_name=f"{self.prefix}_{suffix}", points_selector=selector)
-            except Exception:
+            except Exception: pass
-                pass
     
     async def create_from_text(
             self,
@@ -315,35 +270,33 @@ class IngestionService:
         ) -> Dict[str, Any]:
             """
             WP-11 Persistence API Entrypoint.
-            Schreibt Text in Vault und indiziert ihn sofort.
+            Speichert Text und erzwingt sofortige Indizierung mit Smart Edges.
             """
-            # 1. Zielordner
             target_dir = os.path.join(vault_root, folder)
-            try:
+            os.makedirs(target_dir, exist_ok=True)
-                os.makedirs(target_dir, exist_ok=True)
-            except Exception as e:
-                return {"status": "error", "error": f"Could not create folder {target_dir}: {e}"}
             
-            # 2. Dateiname
+            file_path = os.path.join(target_dir, filename)
-            safe_filename = os.path.basename(filename)
-            if not safe_filename.endswith(".md"):
-                safe_filename += ".md"
-            file_path = os.path.join(target_dir, safe_filename)
             
-            # 3. Schreiben
             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 at {file_path}: {str(e)}"}
+                return {"status": "error", "error": f"Disk write failed: {str(e)}"}
                 
-            # 4. Indizieren (Async Aufruf!)
+            # Hier aktivieren wir die Smart Edges explizit für den Single-File Import
-            # Wir rufen process_file auf, das jetzt ASYNC ist
             return await self.process_file(
                 file_path=file_path,
                 vault_root=vault_root,
                 apply=True,          
                 force_replace=True,  
-                purge_before=True    
+                purge_before=True,
+                force_smart_edges=True  # <--- HIER: Intelligence Override
             )