diff --git a/app/frontend/ui.py b/app/frontend/ui.py
index ac23908..954519e 100644
--- a/app/frontend/ui.py
+++ b/app/frontend/ui.py
@@ -1,42 +1,15 @@
import streamlit as st
-import requests
import uuid
-import os
-import json
-import re
-import yaml
-import unicodedata
-from datetime import datetime
-from pathlib import Path
-from dotenv import load_dotenv
-# --- WP-19 GRAPH IMPORTS ---
+# --- MODULE IMPORTS ---
try:
- from streamlit_agraph import agraph, Node, Edge, Config
- from qdrant_client import QdrantClient, models
-except ImportError:
- st.error("Fehlende Bibliotheken! Bitte installiere: pip install streamlit-agraph qdrant-client")
+ from ui_config import QDRANT_URL, QDRANT_KEY, COLLECTION_PREFIX
+ from ui_graph_service import GraphExplorerService
+ from ui_components import render_sidebar, render_chat_interface, render_manual_editor, render_graph_explorer
+except ImportError as e:
+ st.error(f"Import Error: {e}. Bitte stelle sicher, dass alle UI-Dateien im selben Ordner liegen.")
st.stop()
-# --- CONFIGURATION ---
-load_dotenv()
-API_BASE_URL = os.getenv("MINDNET_API_URL", "http://localhost:8002")
-CHAT_ENDPOINT = f"{API_BASE_URL}/chat"
-FEEDBACK_ENDPOINT = f"{API_BASE_URL}/feedback"
-INGEST_ANALYZE_ENDPOINT = f"{API_BASE_URL}/ingest/analyze"
-INGEST_SAVE_ENDPOINT = f"{API_BASE_URL}/ingest/save"
-HISTORY_FILE = Path("data/logs/search_history.jsonl")
-
-# Qdrant Config (Direct Access for Graph)
-QDRANT_URL = os.getenv("QDRANT_URL", "http://localhost:6333")
-QDRANT_KEY = os.getenv("QDRANT_API_KEY", None)
-if QDRANT_KEY == "": QDRANT_KEY = None
-COLLECTION_PREFIX = os.getenv("COLLECTION_PREFIX", "mindnet")
-
-# Timeout Strategy
-timeout_setting = os.getenv("MINDNET_API_TIMEOUT") or os.getenv("MINDNET_LLM_TIMEOUT")
-API_TIMEOUT = float(timeout_setting) if timeout_setting else 300.0
-
# --- PAGE SETUP ---
st.set_page_config(page_title="mindnet v2.6", page_icon="🧠", layout="wide")
@@ -75,676 +48,11 @@ st.markdown("""
if "messages" not in st.session_state: st.session_state.messages = []
if "user_id" not in st.session_state: st.session_state.user_id = str(uuid.uuid4())
-# --- GRAPH STYLING CONFIG (WP-19) ---
-# Colors based on types.yaml and standard conventions
-GRAPH_COLORS = {
- "project": "#ff9f43", # Orange
- "concept": "#54a0ff", # Blue
- "decision": "#5f27cd", # Purple
- "risk": "#ff6b6b", # Red
- "person": "#1dd1a1", # Green
- "experience": "#feca57",# Yellow
- "value": "#00d2d3", # Cyan
- "goal": "#ff9ff3", # Pink
- "default": "#8395a7" # Grey
-}
-
-# Colors based on edge 'kind'
-EDGE_COLORS = {
- "depends_on": "#ff6b6b", # Red (Blocker)
- "blocks": "#ee5253", # Dark Red
- "caused_by": "#ff9ff3", # Pink
- "related_to": "#c8d6e5", # Light Grey
- "similar_to": "#c8d6e5", # Light Grey
- "next": "#54a0ff", # Blue
- "derived_from": "#ff9ff3",# Pink
- "references": "#bdc3c7", # Grey
- "belongs_to": "#2e86de" # Dark Blue
- "contributes_to": "#1dd1a1"
-}
-
-# --- HELPER FUNCTIONS ---
-
-def slugify(value):
- if not value: return ""
- value = str(value).lower()
- replacements = {'ä': 'ae', 'ö': 'oe', 'ü': 'ue', 'ß': 'ss', '&': 'und', '+': 'und'}
- for k, v in replacements.items():
- value = value.replace(k, v)
-
- value = unicodedata.normalize('NFKD', value).encode('ascii', 'ignore').decode('ascii')
- value = re.sub(r'[^\w\s-]', '', value).strip()
- return re.sub(r'[-\s]+', '-', value)
-
-def normalize_meta_and_body(meta, body):
- ALLOWED_KEYS = {"title", "type", "status", "tags", "id", "created", "updated", "aliases", "lang"}
- clean_meta = {}
- extra_content = []
-
- if "titel" in meta and "title" not in meta:
- meta["title"] = meta.pop("titel")
-
- tag_candidates = ["tags", "emotionale_keywords", "keywords", "schluesselwoerter"]
- all_tags = []
- for key in tag_candidates:
- if key in meta:
- val = meta[key]
- if isinstance(val, list): all_tags.extend(val)
- elif isinstance(val, str): all_tags.extend([t.strip() for t in val.split(",")])
-
- for key, val in meta.items():
- if key in ALLOWED_KEYS:
- clean_meta[key] = val
- elif key in tag_candidates:
- pass
- else:
- if val and isinstance(val, str):
- header = key.replace("_", " ").title()
- extra_content.append(f"## {header}\n{val}\n")
-
- if all_tags:
- clean_tags = []
- for t in all_tags:
- t_clean = str(t).replace("#", "").strip()
- if t_clean: clean_tags.append(t_clean)
- clean_meta["tags"] = list(set(clean_tags))
-
- if extra_content:
- new_section = "\n".join(extra_content)
- final_body = f"{new_section}\n{body}"
- else:
- final_body = body
-
- return clean_meta, final_body
-
-def parse_markdown_draft(full_text):
- clean_text = full_text.strip()
- pattern_block = r"```(?:markdown|md|yaml)?\s*(.*?)\s*```"
- match_block = re.search(pattern_block, clean_text, re.DOTALL | re.IGNORECASE)
- if match_block:
- clean_text = match_block.group(1).strip()
-
- meta = {}
- body = clean_text
- yaml_str = ""
-
- parts = re.split(r"^---+\s*$", clean_text, maxsplit=2, flags=re.MULTILINE)
-
- if len(parts) >= 3:
- yaml_str = parts[1]
- body = parts[2]
- elif clean_text.startswith("---"):
- fallback_match = re.search(r"^---\s*(.*?)(?=\n#)", clean_text, re.DOTALL | re.MULTILINE)
- if fallback_match:
- yaml_str = fallback_match.group(1)
- body = clean_text.replace(f"---{yaml_str}", "", 1).strip()
-
- if yaml_str:
- yaml_str_clean = yaml_str.replace("#", "")
- try:
- parsed = yaml.safe_load(yaml_str_clean)
- if isinstance(parsed, dict):
- meta = parsed
- except Exception as e:
- print(f"YAML Parsing Warning: {e}")
-
- if not meta.get("title"):
- h1_match = re.search(r"^#\s+(.*)$", body, re.MULTILINE)
- if h1_match:
- meta["title"] = h1_match.group(1).strip()
-
- if meta.get("type") == "draft":
- meta["status"] = "draft"
- meta["type"] = "experience"
-
- return normalize_meta_and_body(meta, body)
-
-def build_markdown_doc(meta, body):
- if "id" not in meta or meta["id"] == "generated_on_save":
- raw_title = meta.get('title', 'note')
- clean_slug = slugify(raw_title)[:50] or "note"
- meta["id"] = f"{datetime.now().strftime('%Y%m%d')}-{clean_slug}"
-
- meta["updated"] = datetime.now().strftime("%Y-%m-%d")
-
- ordered_meta = {}
- prio_keys = ["id", "type", "title", "status", "tags"]
- for k in prio_keys:
- if k in meta: ordered_meta[k] = meta.pop(k)
- ordered_meta.update(meta)
-
- try:
- yaml_str = yaml.dump(ordered_meta, default_flow_style=None, sort_keys=False, allow_unicode=True).strip()
- except:
- yaml_str = "error: generating_yaml"
-
- return f"---\n{yaml_str}\n---\n\n{body}"
-
-def load_history_from_logs(limit=10):
- queries = []
- if HISTORY_FILE.exists():
- try:
- with open(HISTORY_FILE, "r", encoding="utf-8") as f:
- lines = f.readlines()
- for line in reversed(lines):
- try:
- entry = json.loads(line)
- q = entry.get("query_text")
- if q and q not in queries:
- queries.append(q)
- if len(queries) >= limit: break
- except: continue
- except: pass
- return queries
-
-# --- WP-19 GRAPH SERVICE (Advanced) ---
-
-class GraphExplorerService:
- def __init__(self, url, api_key=None, prefix="mindnet"):
- self.client = QdrantClient(url=url, api_key=api_key)
- self.prefix = prefix
- self.notes_col = f"{prefix}_notes"
- self.chunks_col = f"{prefix}_chunks"
- self.edges_col = f"{prefix}_edges"
- self._note_cache = {}
-
- def get_ego_graph(self, center_note_id: str):
- nodes_dict = {}
- unique_edges = {}
-
- center_note = self._fetch_note_cached(center_note_id)
- if not center_note: return [], []
- self._add_node_to_dict(nodes_dict, center_note, is_center=True)
-
- center_title = center_note.get("title")
-
- # Chunks laden
- scroll_filter = models.Filter(
- must=[models.FieldCondition(key="note_id", match=models.MatchValue(value=center_note_id))]
- )
- chunks, _ = self.client.scroll(
- collection_name=self.chunks_col, scroll_filter=scroll_filter, limit=100, with_payload=True
- )
- center_chunk_ids = [c.id for c in chunks]
-
- raw_edges = []
-
- # 1. OUTGOING: Source ist einer unserer Chunks
- if center_chunk_ids:
- out_filter = models.Filter(
- must=[models.FieldCondition(key="source_id", match=models.MatchAny(any=center_chunk_ids))]
- )
- res_out, _ = self.client.scroll(
- collection_name=self.edges_col, scroll_filter=out_filter, limit=100, with_payload=True
- )
- raw_edges.extend(res_out)
-
- # 2. INCOMING: Target ist Chunk, Titel oder exakte Note-ID
- # Hinweis: Target mit #Section (z.B. 'note#header') kann via Keyword-Index schwer gefunden werden,
- # wenn wir den Header-Teil nicht kennen.
- must_conditions = []
- if center_chunk_ids:
- must_conditions.append(models.FieldCondition(key="target_id", match=models.MatchAny(any=center_chunk_ids)))
- if center_title:
- must_conditions.append(models.FieldCondition(key="target_id", match=models.MatchValue(value=center_title)))
-
- # NEU: Auch exakte Note-ID als Target prüfen
- must_conditions.append(models.FieldCondition(key="target_id", match=models.MatchValue(value=center_note_id)))
-
- if must_conditions:
- in_filter = models.Filter(should=must_conditions) # 'should' wirkt wie OR
- res_in, _ = self.client.scroll(
- collection_name=self.edges_col, scroll_filter=in_filter, limit=100, with_payload=True
- )
- raw_edges.extend(res_in)
-
- # Verarbeitung
- for record in raw_edges:
- payload = record.payload
-
- src_ref = payload.get("source_id")
- tgt_ref = payload.get("target_id")
- kind = payload.get("kind", "related_to")
- provenance = payload.get("provenance", "explicit")
-
- src_note = self._resolve_note_from_ref(src_ref)
- tgt_note = self._resolve_note_from_ref(tgt_ref)
-
- if src_note and tgt_note:
- src_id = src_note['note_id']
- tgt_id = tgt_note['note_id']
-
- if src_id != tgt_id:
- self._add_node_to_dict(nodes_dict, src_note)
- self._add_node_to_dict(nodes_dict, tgt_note)
-
- key = (src_id, tgt_id)
- existing = unique_edges.get(key)
-
- is_current_explicit = (provenance == "explicit" or provenance == "rule")
- should_update = True
-
- if existing:
- is_existing_explicit = (existing['provenance'] == "explicit" or existing['provenance'] == "rule")
- if is_existing_explicit and not is_current_explicit:
- should_update = False
-
- if should_update:
- unique_edges[key] = {
- "source": src_id, "target": tgt_id, "kind": kind, "provenance": provenance
- }
-
- final_edges = []
- for (src, tgt), data in unique_edges.items():
- kind = data['kind']
- prov = data['provenance']
- color = EDGE_COLORS.get(kind, "#bdc3c7")
- is_smart = (prov != "explicit" and prov != "rule")
-
- final_edges.append(Edge(
- source=src, target=tgt, label=kind, color=color, dashes=is_smart,
- title=f"Provenance: {prov}\nType: {kind}"
- ))
-
- return list(nodes_dict.values()), final_edges
-
- def _fetch_note_cached(self, note_id):
- if note_id in self._note_cache: return self._note_cache[note_id]
- res, _ = self.client.scroll(
- collection_name=self.notes_col,
- scroll_filter=models.Filter(must=[models.FieldCondition(key="note_id", match=models.MatchValue(value=note_id))]),
- limit=1, with_payload=True
- )
- if res:
- self._note_cache[note_id] = res[0].payload
- return res[0].payload
- return None
-
- def _resolve_note_from_ref(self, ref_str):
- if not ref_str: return None
-
- # Fall A: Chunk ID (Format: note_id#cXX)
- if "#" in ref_str:
- # 1. Versuch: Echte Chunk ID in DB suchen
- try:
- res = self.client.retrieve(collection_name=self.chunks_col, ids=[ref_str], with_payload=True)
- if res:
- parent_id = res[0].payload.get("note_id")
- return self._fetch_note_cached(parent_id)
- except: pass
-
- # 2. Versuch (NEU): Es ist ein Link auf eine Section (z.B. "note-id#Header")
- # Wir entfernen den Hash-Teil und suchen die Basis-Notiz
- possible_note_id = ref_str.split("#")[0]
- note_by_id = self._fetch_note_cached(possible_note_id)
- if note_by_id: return note_by_id
-
- # Fall B: Es ist direkt die Note ID
- note_by_id = self._fetch_note_cached(ref_str)
- if note_by_id: return note_by_id
-
- # Fall C: Es ist der Titel (Wikilink)
- res, _ = self.client.scroll(
- collection_name=self.notes_col,
- scroll_filter=models.Filter(must=[models.FieldCondition(key="title", match=models.MatchValue(value=ref_str))]),
- limit=1, with_payload=True
- )
- if res:
- p = res[0].payload
- self._note_cache[p['note_id']] = p
- return p
-
- return None
-
- def _add_node_to_dict(self, node_dict, note_payload, is_center=False):
- nid = note_payload.get("note_id")
- if nid in node_dict: return
- ntype = note_payload.get("type", "default")
- color = GRAPH_COLORS.get(ntype, GRAPH_COLORS["default"])
- size = 35 if is_center else 20
- node_dict[nid] = Node(
- id=nid, label=note_payload.get("title", nid), size=size, color=color, shape="dot",
- title=f"Type: {ntype}\nTags: {note_payload.get('tags')}", font={'color': 'black'}
- )
-
-# Init Graph Service
+# --- SERVICE INIT ---
+# Initialisiert den Graph Service einmalig
graph_service = GraphExplorerService(QDRANT_URL, QDRANT_KEY, COLLECTION_PREFIX)
-# --- API CLIENT ---
-
-def send_chat_message(message: str, top_k: int, explain: bool):
- try:
- response = requests.post(
- CHAT_ENDPOINT,
- json={"message": message, "top_k": top_k, "explain": explain},
- timeout=API_TIMEOUT
- )
- response.raise_for_status()
- return response.json()
- except Exception as e:
- return {"error": str(e)}
-
-def analyze_draft_text(text: str, n_type: str):
- try:
- response = requests.post(INGEST_ANALYZE_ENDPOINT, json={"text": text, "type": n_type}, timeout=15)
- response.raise_for_status()
- return response.json()
- except Exception as e:
- return {"error": str(e)}
-
-def save_draft_to_vault(markdown_content: str, filename: str = None):
- try:
- response = requests.post(INGEST_SAVE_ENDPOINT, json={"markdown_content": markdown_content, "filename": filename}, timeout=API_TIMEOUT)
- response.raise_for_status()
- return response.json()
- except Exception as e:
- return {"error": str(e)}
-
-def submit_feedback(query_id, node_id, score, comment=None):
- try:
- requests.post(FEEDBACK_ENDPOINT, json={"query_id": query_id, "node_id": node_id, "score": score, "comment": comment}, timeout=2)
- st.toast(f"Feedback ({score}) gesendet!")
- except: pass
-
-# --- UI COMPONENTS ---
-
-def render_sidebar():
- with st.sidebar:
- st.title("🧠 mindnet")
- st.caption("v2.6 | WP-19 Graph View")
- mode = st.radio("Modus", ["💬 Chat", "📝 Manueller Editor", "🕸️ Graph Explorer"], index=0)
- st.divider()
- st.subheader("⚙️ Settings")
- top_k = st.slider("Quellen (Top-K)", 1, 10, 5)
- explain = st.toggle("Explanation Layer", True)
- st.divider()
- st.subheader("🕒 Verlauf")
- for q in load_history_from_logs(8):
- if st.button(f"🔎 {q[:25]}...", key=f"hist_{q}", use_container_width=True):
- st.session_state.messages.append({"role": "user", "content": q})
- st.rerun()
- return mode, top_k, explain
-
-def render_draft_editor(msg):
- if "query_id" not in msg or not msg["query_id"]:
- msg["query_id"] = str(uuid.uuid4())
-
- qid = msg["query_id"]
- key_base = f"draft_{qid}"
-
- # State Keys
- data_meta_key = f"{key_base}_data_meta"
- data_sugg_key = f"{key_base}_data_suggestions"
- widget_body_key = f"{key_base}_widget_body"
- data_body_key = f"{key_base}_data_body"
-
- # INIT STATE
- if f"{key_base}_init" not in st.session_state:
- meta, body = parse_markdown_draft(msg["content"])
- if "type" not in meta: meta["type"] = "default"
- if "title" not in meta: meta["title"] = ""
- tags = meta.get("tags", [])
- meta["tags_str"] = ", ".join(tags) if isinstance(tags, list) else str(tags)
-
- st.session_state[data_meta_key] = meta
- st.session_state[data_sugg_key] = []
- st.session_state[data_body_key] = body.strip()
- st.session_state[f"{key_base}_wdg_title"] = meta["title"]
- st.session_state[f"{key_base}_wdg_type"] = meta["type"]
- st.session_state[f"{key_base}_wdg_tags"] = meta["tags_str"]
- st.session_state[f"{key_base}_init"] = True
-
- # RESURRECTION
- if widget_body_key not in st.session_state and data_body_key in st.session_state:
- st.session_state[widget_body_key] = st.session_state[data_body_key]
-
- # CALLBACKS
- def _sync_meta():
- meta = st.session_state[data_meta_key]
- meta["title"] = st.session_state.get(f"{key_base}_wdg_title", "")
- meta["type"] = st.session_state.get(f"{key_base}_wdg_type", "default")
- meta["tags_str"] = st.session_state.get(f"{key_base}_wdg_tags", "")
- st.session_state[data_meta_key] = meta
-
- def _sync_body():
- st.session_state[data_body_key] = st.session_state[widget_body_key]
-
- def _insert_text(text_to_insert):
- current = st.session_state.get(widget_body_key, "")
- new_text = f"{current}\n\n{text_to_insert}"
- st.session_state[widget_body_key] = new_text
- st.session_state[data_body_key] = new_text
-
- def _remove_text(text_to_remove):
- current = st.session_state.get(widget_body_key, "")
- new_text = current.replace(text_to_remove, "").strip()
- st.session_state[widget_body_key] = new_text
- st.session_state[data_body_key] = new_text
-
- # UI LAYOUT
- st.markdown(f'', unsafe_allow_html=True)
- st.markdown("### 📝 Entwurf bearbeiten")
-
- meta_ref = st.session_state[data_meta_key]
- c1, c2 = st.columns([2, 1])
- with c1:
- st.text_input("Titel", key=f"{key_base}_wdg_title", on_change=_sync_meta)
- with c2:
- known_types = ["concept", "project", "decision", "experience", "journal", "value", "goal", "principle", "risk", "belief"]
- curr_type = st.session_state.get(f"{key_base}_wdg_type", meta_ref["type"])
- if curr_type not in known_types: known_types.append(curr_type)
- st.selectbox("Typ", known_types, key=f"{key_base}_wdg_type", on_change=_sync_meta)
-
- st.text_input("Tags", key=f"{key_base}_wdg_tags", on_change=_sync_meta)
-
- tab_edit, tab_intel, tab_view = st.tabs(["✏️ Inhalt", "🧠 Intelligence", "👁️ Vorschau"])
-
- with tab_edit:
- st.text_area("Body", key=widget_body_key, height=500, on_change=_sync_body, label_visibility="collapsed")
-
- with tab_intel:
- st.info("Klicke auf 'Analysieren', um Verknüpfungen für den AKTUELLEN Text zu finden.")
- if st.button("🔍 Analyse starten", key=f"{key_base}_analyze"):
- st.session_state[data_sugg_key] = []
- text_to_analyze = st.session_state.get(widget_body_key, st.session_state.get(data_body_key, ""))
- current_doc_type = st.session_state.get(f"{key_base}_wdg_type", "concept")
-
- with st.spinner("Analysiere..."):
- analysis = analyze_draft_text(text_to_analyze, current_doc_type)
- if "error" in analysis:
- st.error(f"Fehler: {analysis['error']}")
- else:
- suggestions = analysis.get("suggestions", [])
- st.session_state[data_sugg_key] = suggestions
- if not suggestions: st.warning("Keine Vorschläge gefunden.")
- else: st.success(f"{len(suggestions)} Vorschläge gefunden.")
-
- suggestions = st.session_state[data_sugg_key]
- if suggestions:
- current_text_state = st.session_state.get(widget_body_key, "")
- for idx, sugg in enumerate(suggestions):
- link_text = sugg.get('suggested_markdown', '')
- is_inserted = link_text in current_text_state
- bg_color = "#e6fffa" if is_inserted else "#ffffff"
- border = "3px solid #28a745" if is_inserted else "3px solid #1a73e8"
- st.markdown(f"""
-
- {sugg.get('target_title')} ({sugg.get('type')})
- {sugg.get('reason')}
- {link_text}
-
- """, unsafe_allow_html=True)
- if is_inserted:
- st.button("❌ Entfernen", key=f"del_{idx}_{key_base}", on_click=_remove_text, args=(link_text,))
- else:
- st.button("➕ Einfügen", key=f"add_{idx}_{key_base}", on_click=_insert_text, args=(link_text,))
-
- final_tags_str = st.session_state.get(f"{key_base}_wdg_tags", "")
- final_tags = [t.strip() for t in final_tags_str.split(",") if t.strip()]
- final_meta = {
- "id": "generated_on_save",
- "type": st.session_state.get(f"{key_base}_wdg_type", "default"),
- "title": st.session_state.get(f"{key_base}_wdg_title", "").strip(),
- "status": "draft",
- "tags": final_tags
- }
- final_body = st.session_state.get(widget_body_key, st.session_state[data_body_key])
- if not final_meta["title"]:
- h1_match = re.search(r"^#\s+(.*)$", final_body, re.MULTILINE)
- if h1_match: final_meta["title"] = h1_match.group(1).strip()
-
- final_doc = build_markdown_doc(final_meta, final_body)
-
- with tab_view:
- st.markdown('
', unsafe_allow_html=True)
- st.markdown(final_doc)
- st.markdown('
', unsafe_allow_html=True)
-
- st.markdown("---")
- b1, b2 = st.columns([1, 1])
- with b1:
- if st.button("💾 Speichern & Indizieren", type="primary", key=f"{key_base}_save"):
- with st.spinner("Speichere im Vault..."):
- raw_title = final_meta.get("title", "")
- if not raw_title:
- clean_body = re.sub(r"[#*_\[\]()]", "", final_body).strip()
- raw_title = clean_body[:40] if clean_body else "draft"
- safe_title = slugify(raw_title)[:60] or "draft"
- fname = f"{datetime.now().strftime('%Y%m%d')}-{safe_title}.md"
- result = save_draft_to_vault(final_doc, filename=fname)
- if "error" in result: st.error(f"Fehler: {result['error']}")
- else:
- st.success(f"Gespeichert: {result.get('file_path')}")
- st.balloons()
- with b2:
- if st.button("📋 Code anzeigen", key=f"{key_base}_btn_copy"):
- st.code(final_doc, language="markdown")
- st.markdown("
{icon} Intent: {intent} ({src})
', unsafe_allow_html=True)
-
- with st.expander("🐞 Debug Raw Payload", expanded=False):
- st.json(msg)
-
- if intent == "INTERVIEW":
- render_draft_editor(msg)
- else:
- st.markdown(msg["content"])
-
- if "sources" in msg and msg["sources"]:
- for hit in msg["sources"]:
- with st.expander(f"📄 {hit.get('note_id', '?')} ({hit.get('total_score', 0):.2f})"):
- st.markdown(f"_{hit.get('source', {}).get('text', '')[:300]}..._")
- if hit.get('explanation'):
- st.caption(f"Grund: {hit['explanation']['reasons'][0]['message']}")
- def _cb(qid=msg.get("query_id"), nid=hit.get('node_id')):
- val = st.session_state.get(f"fb_src_{qid}_{nid}")
- if val is not None: submit_feedback(qid, nid, val+1)
- st.feedback("faces", key=f"fb_src_{msg.get('query_id')}_{hit.get('node_id')}", on_change=_cb)
-
- if "query_id" in msg:
- qid = msg["query_id"]
- st.feedback("stars", key=f"fb_glob_{qid}", on_change=lambda: submit_feedback(qid, "generated_answer", st.session_state[f"fb_glob_{qid}"]+1))
- else:
- st.markdown(msg["content"])
-
- if prompt := st.chat_input("Frage Mindnet..."):
- st.session_state.messages.append({"role": "user", "content": prompt})
- st.rerun()
-
- if len(st.session_state.messages) > 0 and st.session_state.messages[-1]["role"] == "user":
- with st.chat_message("assistant"):
- with st.spinner("Thinking..."):
- resp = send_chat_message(st.session_state.messages[-1]["content"], top_k, explain)
- if "error" in resp:
- st.error(resp["error"])
- else:
- st.session_state.messages.append({
- "role": "assistant",
- "content": resp.get("answer"),
- "intent": resp.get("intent", "FACT"),
- "intent_source": resp.get("intent_source", "Unknown"),
- "sources": resp.get("sources", []),
- "query_id": resp.get("query_id")
- })
- st.rerun()
-
-def render_manual_editor():
- mock_msg = {
- "content": "---\ntype: concept\ntitle: Neue Notiz\nstatus: draft\ntags: []\n---\n# Titel\n",
- "query_id": "manual_mode_v2"
- }
- render_draft_editor(mock_msg)
-
-def render_graph_explorer():
- st.header("🕸️ Graph Explorer (WP-19)")
-
- col_ctrl, col_graph = st.columns([1, 3])
-
- with col_ctrl:
- st.subheader("Fokus setzen")
- search_term = st.text_input("Suche Notiz (Titel)", placeholder="z.B. Project Alpha")
- selected_note_id = None
-
- if search_term:
- # Suche nach Titel für Autocomplete
- hits, _ = graph_service.client.scroll(
- collection_name=f"{COLLECTION_PREFIX}_notes",
- scroll_filter=models.Filter(
- must=[models.FieldCondition(key="title", match=models.MatchText(text=search_term))]
- ),
- limit=10
- )
- options = {h.payload['title']: h.payload['note_id'] for h in hits}
- if options:
- selected_title = st.selectbox("Wähle Notiz:", list(options.keys()))
- selected_note_id = options[selected_title]
- else:
- st.warning("Keine Notiz gefunden.")
-
- st.markdown("---")
- st.markdown("**Legende:**")
- st.markdown(f"🔴 **Blocker** (Risk/Block)")
- st.markdown(f"🔵 **Konzept/Struktur**")
- st.markdown(f"🟣 **Entscheidung**")
- st.markdown(f"--- **Solid**: Explicit Link")
- st.markdown(f"- - **Dashed**: Smart/AI Link")
-
- with col_graph:
- if selected_note_id:
- with st.spinner(f"Lade Graph für {selected_note_id}..."):
- nodes, edges = graph_service.get_ego_graph(selected_note_id)
-
- if not nodes:
- st.error("Knoten konnte nicht geladen werden.")
- else:
- config = Config(
- width=900,
- height=700,
- directed=True,
- physics=True,
- hierarchical=False,
- nodeHighlightBehavior=True,
- highlightColor="#F7A7A6",
- collapsible=False
- )
- # Rendering the Graph
- st.caption(f"Graph zeigt {len(nodes)} Knoten und {len(edges)} Kanten.")
- return_value = agraph(nodes=nodes, edges=edges, config=config)
-
- if return_value:
- st.info(f"Auswahl: {return_value}")
- else:
- st.info("👈 Bitte wähle links eine Notiz aus, um den Graphen zu starten.")
-
-# --- MAIN ---
+# --- MAIN ROUTING ---
mode, top_k, explain = render_sidebar()
if mode == "💬 Chat":
@@ -752,4 +60,4 @@ if mode == "💬 Chat":
elif mode == "📝 Manueller Editor":
render_manual_editor()
elif mode == "🕸️ Graph Explorer":
- render_graph_explorer()
\ No newline at end of file
+ render_graph_explorer(graph_service)
\ No newline at end of file
diff --git a/app/frontend/ui_api.py b/app/frontend/ui_api.py
new file mode 100644
index 0000000..8057a26
--- /dev/null
+++ b/app/frontend/ui_api.py
@@ -0,0 +1,37 @@
+import requests
+import streamlit as st
+from ui_config import CHAT_ENDPOINT, INGEST_ANALYZE_ENDPOINT, INGEST_SAVE_ENDPOINT, FEEDBACK_ENDPOINT, API_TIMEOUT
+
+def send_chat_message(message: str, top_k: int, explain: bool):
+ try:
+ response = requests.post(
+ CHAT_ENDPOINT,
+ json={"message": message, "top_k": top_k, "explain": explain},
+ timeout=API_TIMEOUT
+ )
+ response.raise_for_status()
+ return response.json()
+ except Exception as e:
+ return {"error": str(e)}
+
+def analyze_draft_text(text: str, n_type: str):
+ try:
+ response = requests.post(INGEST_ANALYZE_ENDPOINT, json={"text": text, "type": n_type}, timeout=15)
+ response.raise_for_status()
+ return response.json()
+ except Exception as e:
+ return {"error": str(e)}
+
+def save_draft_to_vault(markdown_content: str, filename: str = None):
+ try:
+ response = requests.post(INGEST_SAVE_ENDPOINT, json={"markdown_content": markdown_content, "filename": filename}, timeout=API_TIMEOUT)
+ response.raise_for_status()
+ return response.json()
+ except Exception as e:
+ return {"error": str(e)}
+
+def submit_feedback(query_id, node_id, score, comment=None):
+ try:
+ requests.post(FEEDBACK_ENDPOINT, json={"query_id": query_id, "node_id": node_id, "score": score, "comment": comment}, timeout=2)
+ st.toast(f"Feedback ({score}) gesendet!")
+ except: pass
\ No newline at end of file
diff --git a/app/frontend/ui_components.py b/app/frontend/ui_components.py
new file mode 100644
index 0000000..30a9959
--- /dev/null
+++ b/app/frontend/ui_components.py
@@ -0,0 +1,305 @@
+import streamlit as st
+import uuid
+import re
+from datetime import datetime
+from streamlit_agraph import agraph, Config
+from qdrant_client import models
+
+from ui_utils import parse_markdown_draft, build_markdown_doc, load_history_from_logs, slugify
+from ui_api import save_draft_to_vault, analyze_draft_text, send_chat_message, submit_feedback
+from ui_config import HISTORY_FILE, COLLECTION_PREFIX
+
+def render_sidebar():
+ with st.sidebar:
+ st.title("🧠 mindnet")
+ st.caption("v2.6 | WP-19 Graph View")
+ mode = st.radio("Modus", ["💬 Chat", "📝 Manueller Editor", "🕸️ Graph Explorer"], index=0)
+ st.divider()
+ st.subheader("⚙️ Settings")
+ top_k = st.slider("Quellen (Top-K)", 1, 10, 5)
+ explain = st.toggle("Explanation Layer", True)
+ st.divider()
+ st.subheader("🕒 Verlauf")
+ for q in load_history_from_logs(HISTORY_FILE, 8):
+ if st.button(f"🔎 {q[:25]}...", key=f"hist_{q}", use_container_width=True):
+ st.session_state.messages.append({"role": "user", "content": q})
+ st.rerun()
+ return mode, top_k, explain
+
+def render_draft_editor(msg):
+ if "query_id" not in msg or not msg["query_id"]:
+ msg["query_id"] = str(uuid.uuid4())
+
+ qid = msg["query_id"]
+ key_base = f"draft_{qid}"
+
+ # State Keys
+ data_meta_key = f"{key_base}_data_meta"
+ data_sugg_key = f"{key_base}_data_suggestions"
+ widget_body_key = f"{key_base}_widget_body"
+ data_body_key = f"{key_base}_data_body"
+
+ # INIT STATE
+ if f"{key_base}_init" not in st.session_state:
+ meta, body = parse_markdown_draft(msg["content"])
+ if "type" not in meta: meta["type"] = "default"
+ if "title" not in meta: meta["title"] = ""
+ tags = meta.get("tags", [])
+ meta["tags_str"] = ", ".join(tags) if isinstance(tags, list) else str(tags)
+
+ st.session_state[data_meta_key] = meta
+ st.session_state[data_sugg_key] = []
+ st.session_state[data_body_key] = body.strip()
+ st.session_state[f"{key_base}_wdg_title"] = meta["title"]
+ st.session_state[f"{key_base}_wdg_type"] = meta["type"]
+ st.session_state[f"{key_base}_wdg_tags"] = meta["tags_str"]
+ st.session_state[f"{key_base}_init"] = True
+
+ # RESURRECTION
+ if widget_body_key not in st.session_state and data_body_key in st.session_state:
+ st.session_state[widget_body_key] = st.session_state[data_body_key]
+
+ # CALLBACKS
+ def _sync_meta():
+ meta = st.session_state[data_meta_key]
+ meta["title"] = st.session_state.get(f"{key_base}_wdg_title", "")
+ meta["type"] = st.session_state.get(f"{key_base}_wdg_type", "default")
+ meta["tags_str"] = st.session_state.get(f"{key_base}_wdg_tags", "")
+ st.session_state[data_meta_key] = meta
+
+ def _sync_body():
+ st.session_state[data_body_key] = st.session_state[widget_body_key]
+
+ def _insert_text(text_to_insert):
+ current = st.session_state.get(widget_body_key, "")
+ new_text = f"{current}\n\n{text_to_insert}"
+ st.session_state[widget_body_key] = new_text
+ st.session_state[data_body_key] = new_text
+
+ def _remove_text(text_to_remove):
+ current = st.session_state.get(widget_body_key, "")
+ new_text = current.replace(text_to_remove, "").strip()
+ st.session_state[widget_body_key] = new_text
+ st.session_state[data_body_key] = new_text
+
+ # UI LAYOUT
+ st.markdown(f'', unsafe_allow_html=True)
+ st.markdown("### 📝 Entwurf bearbeiten")
+
+ meta_ref = st.session_state[data_meta_key]
+ c1, c2 = st.columns([2, 1])
+ with c1:
+ st.text_input("Titel", key=f"{key_base}_wdg_title", on_change=_sync_meta)
+ with c2:
+ known_types = ["concept", "project", "decision", "experience", "journal", "value", "goal", "principle", "risk", "belief"]
+ curr_type = st.session_state.get(f"{key_base}_wdg_type", meta_ref["type"])
+ if curr_type not in known_types: known_types.append(curr_type)
+ st.selectbox("Typ", known_types, key=f"{key_base}_wdg_type", on_change=_sync_meta)
+
+ st.text_input("Tags", key=f"{key_base}_wdg_tags", on_change=_sync_meta)
+
+ tab_edit, tab_intel, tab_view = st.tabs(["✏️ Inhalt", "🧠 Intelligence", "👁️ Vorschau"])
+
+ with tab_edit:
+ st.text_area("Body", key=widget_body_key, height=500, on_change=_sync_body, label_visibility="collapsed")
+
+ with tab_intel:
+ st.info("Klicke auf 'Analysieren', um Verknüpfungen für den AKTUELLEN Text zu finden.")
+ if st.button("🔍 Analyse starten", key=f"{key_base}_analyze"):
+ st.session_state[data_sugg_key] = []
+ text_to_analyze = st.session_state.get(widget_body_key, st.session_state.get(data_body_key, ""))
+ current_doc_type = st.session_state.get(f"{key_base}_wdg_type", "concept")
+
+ with st.spinner("Analysiere..."):
+ analysis = analyze_draft_text(text_to_analyze, current_doc_type)
+ if "error" in analysis:
+ st.error(f"Fehler: {analysis['error']}")
+ else:
+ suggestions = analysis.get("suggestions", [])
+ st.session_state[data_sugg_key] = suggestions
+ if not suggestions: st.warning("Keine Vorschläge gefunden.")
+ else: st.success(f"{len(suggestions)} Vorschläge gefunden.")
+
+ suggestions = st.session_state[data_sugg_key]
+ if suggestions:
+ current_text_state = st.session_state.get(widget_body_key, "")
+ for idx, sugg in enumerate(suggestions):
+ link_text = sugg.get('suggested_markdown', '')
+ is_inserted = link_text in current_text_state
+ bg_color = "#e6fffa" if is_inserted else "#ffffff"
+ border = "3px solid #28a745" if is_inserted else "3px solid #1a73e8"
+ st.markdown(f"""
+
+ {sugg.get('target_title')} ({sugg.get('type')})
+ {sugg.get('reason')}
+ {link_text}
+
+ """, unsafe_allow_html=True)
+ if is_inserted:
+ st.button("❌ Entfernen", key=f"del_{idx}_{key_base}", on_click=_remove_text, args=(link_text,))
+ else:
+ st.button("➕ Einfügen", key=f"add_{idx}_{key_base}", on_click=_insert_text, args=(link_text,))
+
+ final_tags_str = st.session_state.get(f"{key_base}_wdg_tags", "")
+ final_tags = [t.strip() for t in final_tags_str.split(",") if t.strip()]
+ final_meta = {
+ "id": "generated_on_save",
+ "type": st.session_state.get(f"{key_base}_wdg_type", "default"),
+ "title": st.session_state.get(f"{key_base}_wdg_title", "").strip(),
+ "status": "draft",
+ "tags": final_tags
+ }
+ final_body = st.session_state.get(widget_body_key, st.session_state[data_body_key])
+ if not final_meta["title"]:
+ h1_match = re.search(r"^#\s+(.*)$", final_body, re.MULTILINE)
+ if h1_match: final_meta["title"] = h1_match.group(1).strip()
+
+ final_doc = build_markdown_doc(final_meta, final_body)
+
+ with tab_view:
+ st.markdown('
', unsafe_allow_html=True)
+ st.markdown(final_doc)
+ st.markdown('
', unsafe_allow_html=True)
+
+ st.markdown("---")
+ b1, b2 = st.columns([1, 1])
+ with b1:
+ if st.button("💾 Speichern & Indizieren", type="primary", key=f"{key_base}_save"):
+ with st.spinner("Speichere im Vault..."):
+ raw_title = final_meta.get("title", "")
+ if not raw_title:
+ clean_body = re.sub(r"[#*_\[\]()]", "", final_body).strip()
+ raw_title = clean_body[:40] if clean_body else "draft"
+ safe_title = slugify(raw_title)[:60] or "draft"
+ fname = f"{datetime.now().strftime('%Y%m%d')}-{safe_title}.md"
+ result = save_draft_to_vault(final_doc, filename=fname)
+ if "error" in result: st.error(f"Fehler: {result['error']}")
+ else:
+ st.success(f"Gespeichert: {result.get('file_path')}")
+ st.balloons()
+ with b2:
+ if st.button("📋 Code anzeigen", key=f"{key_base}_btn_copy"):
+ st.code(final_doc, language="markdown")
+ st.markdown("
{icon} Intent: {intent} ({src})
', unsafe_allow_html=True)
+
+ with st.expander("🐞 Debug Raw Payload", expanded=False):
+ st.json(msg)
+
+ if intent == "INTERVIEW":
+ render_draft_editor(msg)
+ else:
+ st.markdown(msg["content"])
+
+ if "sources" in msg and msg["sources"]:
+ for hit in msg["sources"]:
+ with st.expander(f"📄 {hit.get('note_id', '?')} ({hit.get('total_score', 0):.2f})"):
+ st.markdown(f"_{hit.get('source', {}).get('text', '')[:300]}..._")
+ if hit.get('explanation'):
+ st.caption(f"Grund: {hit['explanation']['reasons'][0]['message']}")
+ def _cb(qid=msg.get("query_id"), nid=hit.get('node_id')):
+ val = st.session_state.get(f"fb_src_{qid}_{nid}")
+ if val is not None: submit_feedback(qid, nid, val+1)
+ st.feedback("faces", key=f"fb_src_{msg.get('query_id')}_{hit.get('node_id')}", on_change=_cb)
+
+ if "query_id" in msg:
+ qid = msg["query_id"]
+ st.feedback("stars", key=f"fb_glob_{qid}", on_change=lambda: submit_feedback(qid, "generated_answer", st.session_state[f"fb_glob_{qid}"]+1))
+ else:
+ st.markdown(msg["content"])
+
+ if prompt := st.chat_input("Frage Mindnet..."):
+ st.session_state.messages.append({"role": "user", "content": prompt})
+ st.rerun()
+
+ if len(st.session_state.messages) > 0 and st.session_state.messages[-1]["role"] == "user":
+ with st.chat_message("assistant"):
+ with st.spinner("Thinking..."):
+ resp = send_chat_message(st.session_state.messages[-1]["content"], top_k, explain)
+ if "error" in resp:
+ st.error(resp["error"])
+ else:
+ st.session_state.messages.append({
+ "role": "assistant",
+ "content": resp.get("answer"),
+ "intent": resp.get("intent", "FACT"),
+ "intent_source": resp.get("intent_source", "Unknown"),
+ "sources": resp.get("sources", []),
+ "query_id": resp.get("query_id")
+ })
+ st.rerun()
+
+def render_manual_editor():
+ mock_msg = {
+ "content": "---\ntype: concept\ntitle: Neue Notiz\nstatus: draft\ntags: []\n---\n# Titel\n",
+ "query_id": "manual_mode_v2"
+ }
+ render_draft_editor(mock_msg)
+
+def render_graph_explorer(graph_service):
+ st.header("🕸️ Graph Explorer (WP-19)")
+
+ col_ctrl, col_graph = st.columns([1, 3])
+
+ with col_ctrl:
+ st.subheader("Fokus setzen")
+ search_term = st.text_input("Suche Notiz (Titel)", placeholder="z.B. Project Alpha")
+ selected_note_id = None
+
+ if search_term:
+ hits, _ = graph_service.client.scroll(
+ collection_name=f"{COLLECTION_PREFIX}_notes",
+ scroll_filter=models.Filter(
+ must=[models.FieldCondition(key="title", match=models.MatchText(text=search_term))]
+ ),
+ limit=10
+ )
+ options = {h.payload['title']: h.payload['note_id'] for h in hits}
+ if options:
+ selected_title = st.selectbox("Wähle Notiz:", list(options.keys()))
+ selected_note_id = options[selected_title]
+ else:
+ st.warning("Keine Notiz gefunden.")
+
+ st.markdown("---")
+ st.markdown("**Legende:**")
+ st.markdown(f"🔴 **Blocker** (Risk/Block)")
+ st.markdown(f"🔵 **Konzept/Struktur**")
+ st.markdown(f"🟣 **Entscheidung**")
+ st.markdown(f"🟢 **Beitrag**")
+ st.markdown(f"--- **Solid**: Explicit Link")
+ st.markdown(f"- - **Dashed**: Smart/AI Link")
+
+ with col_graph:
+ if selected_note_id:
+ with st.spinner(f"Lade Graph für {selected_note_id}..."):
+ nodes, edges = graph_service.get_ego_graph(selected_note_id)
+
+ if not nodes:
+ st.error("Knoten konnte nicht geladen werden.")
+ else:
+ config = Config(
+ width=900,
+ height=700,
+ directed=True,
+ physics=True,
+ hierarchical=False,
+ nodeHighlightBehavior=True,
+ highlightColor="#F7A7A6",
+ collapsible=False
+ )
+ st.caption(f"Graph zeigt {len(nodes)} Knoten und {len(edges)} Kanten.")
+ return_value = agraph(nodes=nodes, edges=edges, config=config)
+
+ if return_value:
+ st.info(f"Auswahl: {return_value}")
+ else:
+ st.info("👈 Bitte wähle links eine Notiz aus, um den Graphen zu starten.")
\ No newline at end of file
diff --git a/app/frontend/ui_config.py b/app/frontend/ui_config.py
new file mode 100644
index 0000000..af95cff
--- /dev/null
+++ b/app/frontend/ui_config.py
@@ -0,0 +1,49 @@
+import os
+from dotenv import load_dotenv
+from pathlib import Path
+
+load_dotenv()
+
+# --- API & PORTS ---
+API_BASE_URL = os.getenv("MINDNET_API_URL", "http://localhost:8002")
+CHAT_ENDPOINT = f"{API_BASE_URL}/chat"
+FEEDBACK_ENDPOINT = f"{API_BASE_URL}/feedback"
+INGEST_ANALYZE_ENDPOINT = f"{API_BASE_URL}/ingest/analyze"
+INGEST_SAVE_ENDPOINT = f"{API_BASE_URL}/ingest/save"
+
+# --- QDRANT ---
+QDRANT_URL = os.getenv("QDRANT_URL", "http://localhost:6333")
+QDRANT_KEY = os.getenv("QDRANT_API_KEY", None)
+if QDRANT_KEY == "": QDRANT_KEY = None
+COLLECTION_PREFIX = os.getenv("COLLECTION_PREFIX", "mindnet")
+
+# --- FILES & TIMEOUTS ---
+HISTORY_FILE = Path("data/logs/search_history.jsonl")
+timeout_setting = os.getenv("MINDNET_API_TIMEOUT") or os.getenv("MINDNET_LLM_TIMEOUT")
+API_TIMEOUT = float(timeout_setting) if timeout_setting else 300.0
+
+# --- STYLING CONSTANTS ---
+GRAPH_COLORS = {
+ "project": "#ff9f43", # Orange
+ "concept": "#54a0ff", # Blau
+ "decision": "#5f27cd", # Lila
+ "risk": "#ff6b6b", # Rot
+ "person": "#1dd1a1", # Grün
+ "experience": "#feca57",# Gelb
+ "value": "#00d2d3", # Cyan
+ "goal": "#ff9ff3", # Pink
+ "default": "#8395a7" # Grau
+}
+
+EDGE_COLORS = {
+ "depends_on": "#ff6b6b", # Rot (Blocker)
+ "blocks": "#ee5253", # Dunkelrot
+ "caused_by": "#ff9ff3", # Pink
+ "related_to": "#c8d6e5", # Hellgrau
+ "similar_to": "#c8d6e5", # Hellgrau
+ "next": "#54a0ff", # Blau
+ "derived_from": "#ff9ff3", # Pink
+ "references": "#bdc3c7", # Grau
+ "belongs_to": "#2e86de", # Dunkelblau
+ "contributes_to": "#1dd1a1" # Grün (Neu!)
+}
\ No newline at end of file
diff --git a/app/frontend/ui_praph_service.py b/app/frontend/ui_praph_service.py
new file mode 100644
index 0000000..6af4f18
--- /dev/null
+++ b/app/frontend/ui_praph_service.py
@@ -0,0 +1,181 @@
+from qdrant_client import QdrantClient, models
+from streamlit_agraph import Node, Edge
+from ui_config import GRAPH_COLORS, EDGE_COLORS
+
+class GraphExplorerService:
+ def __init__(self, url, api_key=None, prefix="mindnet"):
+ self.client = QdrantClient(url=url, api_key=api_key)
+ self.prefix = prefix
+ self.notes_col = f"{prefix}_notes"
+ self.chunks_col = f"{prefix}_chunks"
+ self.edges_col = f"{prefix}_edges"
+ self._note_cache = {}
+
+ def get_ego_graph(self, center_note_id: str):
+ nodes_dict = {}
+ unique_edges = {}
+
+ # 1. Center Note laden
+ center_note = self._fetch_note_cached(center_note_id)
+ if not center_note: return [], []
+ self._add_node_to_dict(nodes_dict, center_note, is_center=True)
+
+ center_title = center_note.get("title")
+
+ # 2. Chunks der Center Note finden
+ scroll_filter = models.Filter(
+ must=[models.FieldCondition(key="note_id", match=models.MatchValue(value=center_note_id))]
+ )
+ chunks, _ = self.client.scroll(
+ collection_name=self.chunks_col, scroll_filter=scroll_filter, limit=100, with_payload=True
+ )
+ center_chunk_ids = [c.id for c in chunks]
+
+ raw_edges = []
+
+ # 3. OUTGOING EDGES: Source = einer meiner Chunks
+ if center_chunk_ids:
+ out_filter = models.Filter(
+ must=[models.FieldCondition(key="source_id", match=models.MatchAny(any=center_chunk_ids))]
+ )
+ res_out, _ = self.client.scroll(
+ collection_name=self.edges_col, scroll_filter=out_filter, limit=100, with_payload=True
+ )
+ raw_edges.extend(res_out)
+
+ # 4. INCOMING EDGES: Target = Chunk, Titel oder Note-ID
+ must_conditions = []
+ if center_chunk_ids:
+ must_conditions.append(models.FieldCondition(key="target_id", match=models.MatchAny(any=center_chunk_ids)))
+ if center_title:
+ must_conditions.append(models.FieldCondition(key="target_id", match=models.MatchValue(value=center_title)))
+
+ # FIX: Auch exakte Note-ID als Target prüfen
+ must_conditions.append(models.FieldCondition(key="target_id", match=models.MatchValue(value=center_note_id)))
+
+ if must_conditions:
+ in_filter = models.Filter(should=must_conditions) # 'should' = OR
+ res_in, _ = self.client.scroll(
+ collection_name=self.edges_col, scroll_filter=in_filter, limit=100, with_payload=True
+ )
+ raw_edges.extend(res_in)
+
+ # 5. Verarbeitung & Auflösung
+ for record in raw_edges:
+ payload = record.payload
+
+ src_ref = payload.get("source_id")
+ tgt_ref = payload.get("target_id")
+ kind = payload.get("kind", "related_to")
+ provenance = payload.get("provenance", "explicit")
+
+ src_note = self._resolve_note_from_ref(src_ref)
+ tgt_note = self._resolve_note_from_ref(tgt_ref)
+
+ if src_note and tgt_note:
+ src_id = src_note['note_id']
+ tgt_id = tgt_note['note_id']
+
+ # Keine Self-Loops und valide Verbindung
+ if src_id != tgt_id:
+ self._add_node_to_dict(nodes_dict, src_note)
+ self._add_node_to_dict(nodes_dict, tgt_note)
+
+ key = (src_id, tgt_id)
+ existing = unique_edges.get(key)
+
+ # Deduplizierung: Explizite Kanten überschreiben Smart Edges
+ is_current_explicit = (provenance == "explicit" or provenance == "rule")
+ should_update = True
+
+ if existing:
+ is_existing_explicit = (existing['provenance'] == "explicit" or existing['provenance'] == "rule")
+ if is_existing_explicit and not is_current_explicit:
+ should_update = False
+
+ if should_update:
+ unique_edges[key] = {
+ "source": src_id, "target": tgt_id, "kind": kind, "provenance": provenance
+ }
+
+ # 6. Agraph Objekte bauen
+ final_edges = []
+ for (src, tgt), data in unique_edges.items():
+ kind = data['kind']
+ prov = data['provenance']
+
+ color = EDGE_COLORS.get(kind, "#bdc3c7")
+ is_smart = (prov != "explicit" and prov != "rule")
+
+ final_edges.append(Edge(
+ source=src, target=tgt, label=kind, color=color, dashes=is_smart,
+ title=f"Provenance: {prov}\nType: {kind}"
+ ))
+
+ return list(nodes_dict.values()), final_edges
+
+ def _fetch_note_cached(self, note_id):
+ if note_id in self._note_cache: return self._note_cache[note_id]
+
+ res, _ = self.client.scroll(
+ collection_name=self.notes_col,
+ scroll_filter=models.Filter(must=[models.FieldCondition(key="note_id", match=models.MatchValue(value=note_id))]),
+ limit=1, with_payload=True
+ )
+ if res:
+ self._note_cache[note_id] = res[0].payload
+ return res[0].payload
+ return None
+
+ def _resolve_note_from_ref(self, ref_str):
+ if not ref_str: return None
+
+ # Fall A: Chunk ID (Format: note_id#cXX)
+ if "#" in ref_str:
+ # Versuch 1: Echte Chunk ID in DB
+ try:
+ res = self.client.retrieve(collection_name=self.chunks_col, ids=[ref_str], with_payload=True)
+ if res:
+ parent_id = res[0].payload.get("note_id")
+ return self._fetch_note_cached(parent_id)
+ except: pass
+
+ # Versuch 2: Section Link (note-id#Header) -> Hash abschneiden
+ possible_note_id = ref_str.split("#")[0]
+ note_by_id = self._fetch_note_cached(possible_note_id)
+ if note_by_id: return note_by_id
+
+ # Fall B: Es ist direkt die Note ID
+ note_by_id = self._fetch_note_cached(ref_str)
+ if note_by_id: return note_by_id
+
+ # Fall C: Es ist der Titel (Wikilink)
+ res, _ = self.client.scroll(
+ collection_name=self.notes_col,
+ scroll_filter=models.Filter(must=[models.FieldCondition(key="title", match=models.MatchValue(value=ref_str))]),
+ limit=1, with_payload=True
+ )
+ if res:
+ p = res[0].payload
+ self._note_cache[p['note_id']] = p
+ return p
+
+ return None
+
+ def _add_node_to_dict(self, node_dict, note_payload, is_center=False):
+ nid = note_payload.get("note_id")
+ if nid in node_dict: return
+
+ ntype = note_payload.get("type", "default")
+ color = GRAPH_COLORS.get(ntype, GRAPH_COLORS["default"])
+ size = 35 if is_center else 20
+
+ node_dict[nid] = Node(
+ id=nid,
+ label=note_payload.get("title", nid),
+ size=size,
+ color=color,
+ shape="dot" if not is_center else "diamond",
+ title=f"Type: {ntype}\nTags: {note_payload.get('tags')}",
+ font={'color': 'black'}
+ )
\ No newline at end of file
diff --git a/app/frontend/ui_utils.py b/app/frontend/ui_utils.py
new file mode 100644
index 0000000..3afc6d9
--- /dev/null
+++ b/app/frontend/ui_utils.py
@@ -0,0 +1,137 @@
+import re
+import yaml
+import unicodedata
+import json
+from datetime import datetime
+
+def slugify(value):
+ if not value: return ""
+ value = str(value).lower()
+ replacements = {'ä': 'ae', 'ö': 'oe', 'ü': 'ue', 'ß': 'ss', '&': 'und', '+': 'und'}
+ for k, v in replacements.items():
+ value = value.replace(k, v)
+
+ value = unicodedata.normalize('NFKD', value).encode('ascii', 'ignore').decode('ascii')
+ value = re.sub(r'[^\w\s-]', '', value).strip()
+ return re.sub(r'[-\s]+', '-', value)
+
+def normalize_meta_and_body(meta, body):
+ ALLOWED_KEYS = {"title", "type", "status", "tags", "id", "created", "updated", "aliases", "lang"}
+ clean_meta = {}
+ extra_content = []
+
+ if "titel" in meta and "title" not in meta:
+ meta["title"] = meta.pop("titel")
+
+ tag_candidates = ["tags", "emotionale_keywords", "keywords", "schluesselwoerter"]
+ all_tags = []
+ for key in tag_candidates:
+ if key in meta:
+ val = meta[key]
+ if isinstance(val, list): all_tags.extend(val)
+ elif isinstance(val, str): all_tags.extend([t.strip() for t in val.split(",")])
+
+ for key, val in meta.items():
+ if key in ALLOWED_KEYS:
+ clean_meta[key] = val
+ elif key in tag_candidates:
+ pass
+ else:
+ if val and isinstance(val, str):
+ header = key.replace("_", " ").title()
+ extra_content.append(f"## {header}\n{val}\n")
+
+ if all_tags:
+ clean_tags = []
+ for t in all_tags:
+ t_clean = str(t).replace("#", "").strip()
+ if t_clean: clean_tags.append(t_clean)
+ clean_meta["tags"] = list(set(clean_tags))
+
+ if extra_content:
+ new_section = "\n".join(extra_content)
+ final_body = f"{new_section}\n{body}"
+ else:
+ final_body = body
+
+ return clean_meta, final_body
+
+def parse_markdown_draft(full_text):
+ clean_text = full_text.strip()
+ pattern_block = r"```(?:markdown|md|yaml)?\s*(.*?)\s*```"
+ match_block = re.search(pattern_block, clean_text, re.DOTALL | re.IGNORECASE)
+ if match_block:
+ clean_text = match_block.group(1).strip()
+
+ meta = {}
+ body = clean_text
+ yaml_str = ""
+
+ parts = re.split(r"^---+\s*$", clean_text, maxsplit=2, flags=re.MULTILINE)
+
+ if len(parts) >= 3:
+ yaml_str = parts[1]
+ body = parts[2]
+ elif clean_text.startswith("---"):
+ fallback_match = re.search(r"^---\s*(.*?)(?=\n#)", clean_text, re.DOTALL | re.MULTILINE)
+ if fallback_match:
+ yaml_str = fallback_match.group(1)
+ body = clean_text.replace(f"---{yaml_str}", "", 1).strip()
+
+ if yaml_str:
+ yaml_str_clean = yaml_str.replace("#", "")
+ try:
+ parsed = yaml.safe_load(yaml_str_clean)
+ if isinstance(parsed, dict):
+ meta = parsed
+ except Exception as e:
+ print(f"YAML Parsing Warning: {e}")
+
+ if not meta.get("title"):
+ h1_match = re.search(r"^#\s+(.*)$", body, re.MULTILINE)
+ if h1_match:
+ meta["title"] = h1_match.group(1).strip()
+
+ if meta.get("type") == "draft":
+ meta["status"] = "draft"
+ meta["type"] = "experience"
+
+ return normalize_meta_and_body(meta, body)
+
+def build_markdown_doc(meta, body):
+ if "id" not in meta or meta["id"] == "generated_on_save":
+ raw_title = meta.get('title', 'note')
+ clean_slug = slugify(raw_title)[:50] or "note"
+ meta["id"] = f"{datetime.now().strftime('%Y%m%d')}-{clean_slug}"
+
+ meta["updated"] = datetime.now().strftime("%Y-%m-%d")
+
+ ordered_meta = {}
+ prio_keys = ["id", "type", "title", "status", "tags"]
+ for k in prio_keys:
+ if k in meta: ordered_meta[k] = meta.pop(k)
+ ordered_meta.update(meta)
+
+ try:
+ yaml_str = yaml.dump(ordered_meta, default_flow_style=None, sort_keys=False, allow_unicode=True).strip()
+ except:
+ yaml_str = "error: generating_yaml"
+
+ return f"---\n{yaml_str}\n---\n\n{body}"
+
+def load_history_from_logs(filepath, limit=10):
+ queries = []
+ if filepath.exists():
+ try:
+ with open(filepath, "r", encoding="utf-8") as f:
+ lines = f.readlines()
+ for line in reversed(lines):
+ try:
+ entry = json.loads(line)
+ q = entry.get("query_text")
+ if q and q not in queries:
+ queries.append(q)
+ if len(queries) >= limit: break
+ except: continue
+ except: pass
+ return queries
\ No newline at end of file