aufteilung ui auf mehrere dateien
This commit is contained in:
parent
772a202d6e
commit
19f8d76e21
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@ -1,42 +1,15 @@
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import streamlit as st
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import requests
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import uuid
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import os
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import json
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import re
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import yaml
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import unicodedata
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from datetime import datetime
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from pathlib import Path
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from dotenv import load_dotenv
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# --- WP-19 GRAPH IMPORTS ---
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# --- MODULE IMPORTS ---
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try:
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from streamlit_agraph import agraph, Node, Edge, Config
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from qdrant_client import QdrantClient, models
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except ImportError:
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st.error("Fehlende Bibliotheken! Bitte installiere: pip install streamlit-agraph qdrant-client")
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from ui_config import QDRANT_URL, QDRANT_KEY, COLLECTION_PREFIX
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from ui_graph_service import GraphExplorerService
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from ui_components import render_sidebar, render_chat_interface, render_manual_editor, render_graph_explorer
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except ImportError as e:
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st.error(f"Import Error: {e}. Bitte stelle sicher, dass alle UI-Dateien im selben Ordner liegen.")
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st.stop()
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# --- CONFIGURATION ---
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load_dotenv()
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API_BASE_URL = os.getenv("MINDNET_API_URL", "http://localhost:8002")
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CHAT_ENDPOINT = f"{API_BASE_URL}/chat"
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FEEDBACK_ENDPOINT = f"{API_BASE_URL}/feedback"
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INGEST_ANALYZE_ENDPOINT = f"{API_BASE_URL}/ingest/analyze"
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INGEST_SAVE_ENDPOINT = f"{API_BASE_URL}/ingest/save"
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HISTORY_FILE = Path("data/logs/search_history.jsonl")
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# Qdrant Config (Direct Access for Graph)
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QDRANT_URL = os.getenv("QDRANT_URL", "http://localhost:6333")
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QDRANT_KEY = os.getenv("QDRANT_API_KEY", None)
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if QDRANT_KEY == "": QDRANT_KEY = None
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COLLECTION_PREFIX = os.getenv("COLLECTION_PREFIX", "mindnet")
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# Timeout Strategy
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timeout_setting = os.getenv("MINDNET_API_TIMEOUT") or os.getenv("MINDNET_LLM_TIMEOUT")
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API_TIMEOUT = float(timeout_setting) if timeout_setting else 300.0
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# --- PAGE SETUP ---
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st.set_page_config(page_title="mindnet v2.6", page_icon="🧠", layout="wide")
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@ -75,676 +48,11 @@ st.markdown("""
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if "messages" not in st.session_state: st.session_state.messages = []
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if "user_id" not in st.session_state: st.session_state.user_id = str(uuid.uuid4())
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# --- GRAPH STYLING CONFIG (WP-19) ---
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# Colors based on types.yaml and standard conventions
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GRAPH_COLORS = {
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"project": "#ff9f43", # Orange
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"concept": "#54a0ff", # Blue
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"decision": "#5f27cd", # Purple
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"risk": "#ff6b6b", # Red
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"person": "#1dd1a1", # Green
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"experience": "#feca57",# Yellow
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"value": "#00d2d3", # Cyan
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"goal": "#ff9ff3", # Pink
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"default": "#8395a7" # Grey
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}
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# Colors based on edge 'kind'
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EDGE_COLORS = {
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"depends_on": "#ff6b6b", # Red (Blocker)
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"blocks": "#ee5253", # Dark Red
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"caused_by": "#ff9ff3", # Pink
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"related_to": "#c8d6e5", # Light Grey
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"similar_to": "#c8d6e5", # Light Grey
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"next": "#54a0ff", # Blue
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"derived_from": "#ff9ff3",# Pink
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"references": "#bdc3c7", # Grey
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"belongs_to": "#2e86de" # Dark Blue
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"contributes_to": "#1dd1a1"
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}
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# --- HELPER FUNCTIONS ---
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def slugify(value):
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if not value: return ""
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value = str(value).lower()
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replacements = {'ä': 'ae', 'ö': 'oe', 'ü': 'ue', 'ß': 'ss', '&': 'und', '+': 'und'}
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for k, v in replacements.items():
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value = value.replace(k, v)
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value = unicodedata.normalize('NFKD', value).encode('ascii', 'ignore').decode('ascii')
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value = re.sub(r'[^\w\s-]', '', value).strip()
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return re.sub(r'[-\s]+', '-', value)
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def normalize_meta_and_body(meta, body):
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ALLOWED_KEYS = {"title", "type", "status", "tags", "id", "created", "updated", "aliases", "lang"}
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clean_meta = {}
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extra_content = []
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if "titel" in meta and "title" not in meta:
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meta["title"] = meta.pop("titel")
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tag_candidates = ["tags", "emotionale_keywords", "keywords", "schluesselwoerter"]
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all_tags = []
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for key in tag_candidates:
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if key in meta:
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val = meta[key]
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if isinstance(val, list): all_tags.extend(val)
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elif isinstance(val, str): all_tags.extend([t.strip() for t in val.split(",")])
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for key, val in meta.items():
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if key in ALLOWED_KEYS:
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clean_meta[key] = val
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elif key in tag_candidates:
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pass
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else:
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if val and isinstance(val, str):
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header = key.replace("_", " ").title()
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extra_content.append(f"## {header}\n{val}\n")
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if all_tags:
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clean_tags = []
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for t in all_tags:
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t_clean = str(t).replace("#", "").strip()
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if t_clean: clean_tags.append(t_clean)
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clean_meta["tags"] = list(set(clean_tags))
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if extra_content:
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new_section = "\n".join(extra_content)
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final_body = f"{new_section}\n{body}"
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else:
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final_body = body
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return clean_meta, final_body
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def parse_markdown_draft(full_text):
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clean_text = full_text.strip()
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pattern_block = r"```(?:markdown|md|yaml)?\s*(.*?)\s*```"
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match_block = re.search(pattern_block, clean_text, re.DOTALL | re.IGNORECASE)
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if match_block:
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clean_text = match_block.group(1).strip()
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meta = {}
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body = clean_text
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yaml_str = ""
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parts = re.split(r"^---+\s*$", clean_text, maxsplit=2, flags=re.MULTILINE)
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if len(parts) >= 3:
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yaml_str = parts[1]
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body = parts[2]
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elif clean_text.startswith("---"):
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fallback_match = re.search(r"^---\s*(.*?)(?=\n#)", clean_text, re.DOTALL | re.MULTILINE)
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if fallback_match:
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yaml_str = fallback_match.group(1)
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body = clean_text.replace(f"---{yaml_str}", "", 1).strip()
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if yaml_str:
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yaml_str_clean = yaml_str.replace("#", "")
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try:
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parsed = yaml.safe_load(yaml_str_clean)
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if isinstance(parsed, dict):
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meta = parsed
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except Exception as e:
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print(f"YAML Parsing Warning: {e}")
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if not meta.get("title"):
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h1_match = re.search(r"^#\s+(.*)$", body, re.MULTILINE)
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if h1_match:
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meta["title"] = h1_match.group(1).strip()
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if meta.get("type") == "draft":
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meta["status"] = "draft"
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meta["type"] = "experience"
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return normalize_meta_and_body(meta, body)
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def build_markdown_doc(meta, body):
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if "id" not in meta or meta["id"] == "generated_on_save":
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raw_title = meta.get('title', 'note')
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clean_slug = slugify(raw_title)[:50] or "note"
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meta["id"] = f"{datetime.now().strftime('%Y%m%d')}-{clean_slug}"
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meta["updated"] = datetime.now().strftime("%Y-%m-%d")
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ordered_meta = {}
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prio_keys = ["id", "type", "title", "status", "tags"]
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for k in prio_keys:
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if k in meta: ordered_meta[k] = meta.pop(k)
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ordered_meta.update(meta)
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try:
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yaml_str = yaml.dump(ordered_meta, default_flow_style=None, sort_keys=False, allow_unicode=True).strip()
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except:
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yaml_str = "error: generating_yaml"
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return f"---\n{yaml_str}\n---\n\n{body}"
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def load_history_from_logs(limit=10):
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queries = []
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if HISTORY_FILE.exists():
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try:
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with open(HISTORY_FILE, "r", encoding="utf-8") as f:
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lines = f.readlines()
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for line in reversed(lines):
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try:
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entry = json.loads(line)
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q = entry.get("query_text")
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if q and q not in queries:
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queries.append(q)
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if len(queries) >= limit: break
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except: continue
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except: pass
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return queries
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# --- WP-19 GRAPH SERVICE (Advanced) ---
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class GraphExplorerService:
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def __init__(self, url, api_key=None, prefix="mindnet"):
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self.client = QdrantClient(url=url, api_key=api_key)
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self.prefix = prefix
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self.notes_col = f"{prefix}_notes"
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self.chunks_col = f"{prefix}_chunks"
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self.edges_col = f"{prefix}_edges"
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self._note_cache = {}
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def get_ego_graph(self, center_note_id: str):
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nodes_dict = {}
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unique_edges = {}
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center_note = self._fetch_note_cached(center_note_id)
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if not center_note: return [], []
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self._add_node_to_dict(nodes_dict, center_note, is_center=True)
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center_title = center_note.get("title")
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# Chunks laden
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scroll_filter = models.Filter(
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must=[models.FieldCondition(key="note_id", match=models.MatchValue(value=center_note_id))]
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)
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chunks, _ = self.client.scroll(
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collection_name=self.chunks_col, scroll_filter=scroll_filter, limit=100, with_payload=True
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)
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center_chunk_ids = [c.id for c in chunks]
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raw_edges = []
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# 1. OUTGOING: Source ist einer unserer Chunks
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if center_chunk_ids:
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out_filter = models.Filter(
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must=[models.FieldCondition(key="source_id", match=models.MatchAny(any=center_chunk_ids))]
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)
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res_out, _ = self.client.scroll(
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collection_name=self.edges_col, scroll_filter=out_filter, limit=100, with_payload=True
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)
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raw_edges.extend(res_out)
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# 2. INCOMING: Target ist Chunk, Titel oder exakte Note-ID
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# Hinweis: Target mit #Section (z.B. 'note#header') kann via Keyword-Index schwer gefunden werden,
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# wenn wir den Header-Teil nicht kennen.
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must_conditions = []
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if center_chunk_ids:
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must_conditions.append(models.FieldCondition(key="target_id", match=models.MatchAny(any=center_chunk_ids)))
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if center_title:
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must_conditions.append(models.FieldCondition(key="target_id", match=models.MatchValue(value=center_title)))
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# NEU: Auch exakte Note-ID als Target prüfen
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must_conditions.append(models.FieldCondition(key="target_id", match=models.MatchValue(value=center_note_id)))
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if must_conditions:
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in_filter = models.Filter(should=must_conditions) # 'should' wirkt wie OR
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res_in, _ = self.client.scroll(
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collection_name=self.edges_col, scroll_filter=in_filter, limit=100, with_payload=True
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)
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raw_edges.extend(res_in)
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# Verarbeitung
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for record in raw_edges:
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payload = record.payload
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src_ref = payload.get("source_id")
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tgt_ref = payload.get("target_id")
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kind = payload.get("kind", "related_to")
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provenance = payload.get("provenance", "explicit")
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src_note = self._resolve_note_from_ref(src_ref)
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tgt_note = self._resolve_note_from_ref(tgt_ref)
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if src_note and tgt_note:
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src_id = src_note['note_id']
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tgt_id = tgt_note['note_id']
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if src_id != tgt_id:
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self._add_node_to_dict(nodes_dict, src_note)
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self._add_node_to_dict(nodes_dict, tgt_note)
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key = (src_id, tgt_id)
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existing = unique_edges.get(key)
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is_current_explicit = (provenance == "explicit" or provenance == "rule")
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should_update = True
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if existing:
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is_existing_explicit = (existing['provenance'] == "explicit" or existing['provenance'] == "rule")
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if is_existing_explicit and not is_current_explicit:
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should_update = False
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if should_update:
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unique_edges[key] = {
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"source": src_id, "target": tgt_id, "kind": kind, "provenance": provenance
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}
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final_edges = []
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for (src, tgt), data in unique_edges.items():
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kind = data['kind']
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prov = data['provenance']
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color = EDGE_COLORS.get(kind, "#bdc3c7")
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is_smart = (prov != "explicit" and prov != "rule")
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final_edges.append(Edge(
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source=src, target=tgt, label=kind, color=color, dashes=is_smart,
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title=f"Provenance: {prov}\nType: {kind}"
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))
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return list(nodes_dict.values()), final_edges
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def _fetch_note_cached(self, note_id):
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if note_id in self._note_cache: return self._note_cache[note_id]
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res, _ = self.client.scroll(
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collection_name=self.notes_col,
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scroll_filter=models.Filter(must=[models.FieldCondition(key="note_id", match=models.MatchValue(value=note_id))]),
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limit=1, with_payload=True
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)
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if res:
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self._note_cache[note_id] = res[0].payload
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return res[0].payload
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return None
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def _resolve_note_from_ref(self, ref_str):
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if not ref_str: return None
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# Fall A: Chunk ID (Format: note_id#cXX)
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if "#" in ref_str:
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# 1. Versuch: Echte Chunk ID in DB suchen
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try:
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res = self.client.retrieve(collection_name=self.chunks_col, ids=[ref_str], with_payload=True)
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if res:
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parent_id = res[0].payload.get("note_id")
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return self._fetch_note_cached(parent_id)
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except: pass
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# 2. Versuch (NEU): Es ist ein Link auf eine Section (z.B. "note-id#Header")
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# Wir entfernen den Hash-Teil und suchen die Basis-Notiz
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possible_note_id = ref_str.split("#")[0]
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note_by_id = self._fetch_note_cached(possible_note_id)
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if note_by_id: return note_by_id
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# Fall B: Es ist direkt die Note ID
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note_by_id = self._fetch_note_cached(ref_str)
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if note_by_id: return note_by_id
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# Fall C: Es ist der Titel (Wikilink)
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res, _ = self.client.scroll(
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collection_name=self.notes_col,
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scroll_filter=models.Filter(must=[models.FieldCondition(key="title", match=models.MatchValue(value=ref_str))]),
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limit=1, with_payload=True
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)
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if res:
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p = res[0].payload
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self._note_cache[p['note_id']] = p
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return p
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return None
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def _add_node_to_dict(self, node_dict, note_payload, is_center=False):
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nid = note_payload.get("note_id")
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if nid in node_dict: return
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ntype = note_payload.get("type", "default")
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color = GRAPH_COLORS.get(ntype, GRAPH_COLORS["default"])
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size = 35 if is_center else 20
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node_dict[nid] = Node(
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id=nid, label=note_payload.get("title", nid), size=size, color=color, shape="dot",
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title=f"Type: {ntype}\nTags: {note_payload.get('tags')}", font={'color': 'black'}
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)
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# Init Graph Service
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# --- SERVICE INIT ---
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# Initialisiert den Graph Service einmalig
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graph_service = GraphExplorerService(QDRANT_URL, QDRANT_KEY, COLLECTION_PREFIX)
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# --- API CLIENT ---
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def send_chat_message(message: str, top_k: int, explain: bool):
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try:
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response = requests.post(
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CHAT_ENDPOINT,
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json={"message": message, "top_k": top_k, "explain": explain},
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timeout=API_TIMEOUT
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)
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response.raise_for_status()
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return response.json()
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except Exception as e:
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return {"error": str(e)}
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def analyze_draft_text(text: str, n_type: str):
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try:
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response = requests.post(INGEST_ANALYZE_ENDPOINT, json={"text": text, "type": n_type}, timeout=15)
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response.raise_for_status()
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return response.json()
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except Exception as e:
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return {"error": str(e)}
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def save_draft_to_vault(markdown_content: str, filename: str = None):
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try:
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response = requests.post(INGEST_SAVE_ENDPOINT, json={"markdown_content": markdown_content, "filename": filename}, timeout=API_TIMEOUT)
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response.raise_for_status()
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return response.json()
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except Exception as e:
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return {"error": str(e)}
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def submit_feedback(query_id, node_id, score, comment=None):
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try:
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requests.post(FEEDBACK_ENDPOINT, json={"query_id": query_id, "node_id": node_id, "score": score, "comment": comment}, timeout=2)
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st.toast(f"Feedback ({score}) gesendet!")
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except: pass
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||||
# --- 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'<div class="draft-box">', 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"""
|
||||
<div style="border-left: {border}; background-color: {bg_color}; padding: 10px; margin-bottom: 8px; border-radius: 4px; box-shadow: 0 1px 3px rgba(0,0,0,0.1);">
|
||||
<b>{sugg.get('target_title')}</b> <small>({sugg.get('type')})</small><br>
|
||||
<i>{sugg.get('reason')}</i><br>
|
||||
<code>{link_text}</code>
|
||||
</div>
|
||||
""", 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('<div class="preview-box">', unsafe_allow_html=True)
|
||||
st.markdown(final_doc)
|
||||
st.markdown('</div>', 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("</div>", unsafe_allow_html=True)
|
||||
|
||||
def render_chat_interface(top_k, explain):
|
||||
for idx, msg in enumerate(st.session_state.messages):
|
||||
with st.chat_message(msg["role"]):
|
||||
if msg["role"] == "assistant":
|
||||
intent = msg.get("intent", "UNKNOWN")
|
||||
src = msg.get("intent_source", "?")
|
||||
icon = {"EMPATHY":"❤️", "DECISION":"⚖️", "CODING":"💻", "FACT":"📚", "INTERVIEW":"📝"}.get(intent, "🧠")
|
||||
st.markdown(f'<div class="intent-badge">{icon} Intent: {intent} <span style="opacity:0.6; font-size:0.8em">({src})</span></div>', 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()
|
||||
render_graph_explorer(graph_service)
|
||||
37
app/frontend/ui_api.py
Normal file
37
app/frontend/ui_api.py
Normal file
|
|
@ -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
|
||||
305
app/frontend/ui_components.py
Normal file
305
app/frontend/ui_components.py
Normal file
|
|
@ -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'<div class="draft-box">', 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"""
|
||||
<div style="border-left: {border}; background-color: {bg_color}; padding: 10px; margin-bottom: 8px; border-radius: 4px; box-shadow: 0 1px 3px rgba(0,0,0,0.1);">
|
||||
<b>{sugg.get('target_title')}</b> <small>({sugg.get('type')})</small><br>
|
||||
<i>{sugg.get('reason')}</i><br>
|
||||
<code>{link_text}</code>
|
||||
</div>
|
||||
""", 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('<div class="preview-box">', unsafe_allow_html=True)
|
||||
st.markdown(final_doc)
|
||||
st.markdown('</div>', 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("</div>", unsafe_allow_html=True)
|
||||
|
||||
def render_chat_interface(top_k, explain):
|
||||
for idx, msg in enumerate(st.session_state.messages):
|
||||
with st.chat_message(msg["role"]):
|
||||
if msg["role"] == "assistant":
|
||||
intent = msg.get("intent", "UNKNOWN")
|
||||
src = msg.get("intent_source", "?")
|
||||
icon = {"EMPATHY":"❤️", "DECISION":"⚖️", "CODING":"💻", "FACT":"📚", "INTERVIEW":"📝"}.get(intent, "🧠")
|
||||
st.markdown(f'<div class="intent-badge">{icon} Intent: {intent} <span style="opacity:0.6; font-size:0.8em">({src})</span></div>', 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.")
|
||||
49
app/frontend/ui_config.py
Normal file
49
app/frontend/ui_config.py
Normal file
|
|
@ -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!)
|
||||
}
|
||||
181
app/frontend/ui_praph_service.py
Normal file
181
app/frontend/ui_praph_service.py
Normal file
|
|
@ -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'}
|
||||
)
|
||||
137
app/frontend/ui_utils.py
Normal file
137
app/frontend/ui_utils.py
Normal file
|
|
@ -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
|
||||
Loading…
Reference in New Issue
Block a user