mindnet/app/frontend/ui.py

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 ---
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")
    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")

# --- CSS STYLING ---
st.markdown("""
<style>
    .block-container { padding-top: 2rem; max_width: 1200px; margin: auto; }
    
    .intent-badge {
        background-color: #e8f0fe; color: #1a73e8;
        padding: 4px 10px; border-radius: 12px;
        font-size: 0.8rem; font-weight: 600;
        border: 1px solid #d2e3fc; display: inline-block; margin-bottom: 0.5rem;
    }
    
    .draft-box {
        border: 1px solid #d0d7de;
        border-radius: 6px;
        padding: 16px;
        background-color: #f6f8fa;
        margin-top: 10px;
        margin-bottom: 10px;
    }
    
    .preview-box {
        border: 1px solid #e0e0e0;
        border-radius: 6px;
        padding: 24px;
        background-color: white;
        font-family: -apple-system,BlinkMacSystemFont,"Segoe UI",Helvetica,Arial,sans-serif;
    }
</style>
""", unsafe_allow_html=True)

# --- SESSION STATE ---
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
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'<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 ---
mode, top_k, explain = render_sidebar()

if mode == "💬 Chat":
    render_chat_interface(top_k, explain)
elif mode == "📝 Manueller Editor":
    render_manual_editor()
elif mode == "🕸️ Graph Explorer":
    render_graph_explorer()