"""
KNOWLEDGE STORE — Multi-Container Persistent Knowledge Base
Docker SDK / FastAPI — no Gradio, no CSP

Containers & their knowledge decay models:
  medical    — fast decay (outdated = dangerous). Half-life 180 days.
  legal      — slow decay (laws change rarely). Half-life 730 days.
  company    — mixed: SOPs stable (HL 365), market/people data volatile (HL 30).
  research   — citation boost on create, then slow decay. HL 540 days.
  tech       — very fast decay (versions). HL 90 days.
  prompts    — no decay (prompts are reusable).
  history    — ANTI-decay: value increases with age.
  personal   — moderate decay (preferences drift). HL 180 days.
  finance    — extreme decay (market data). HL 7 days.
  operations — moderate. HL 180 days.

Knowledge Value Score = base_importance * time_factor(container) * access_bonus
Time factor varies per container and uses exponential decay / growth.

Search types:
  keyword   — simple full-text (TF-IDF-like scoring)
  time      — recency or historical filter
  tag       — exact/prefix tag match
  container — container-scoped list
  semantic  — keyword with cosine-like tf scoring (no embeddings, pure Python)
  value     — sorted by current knowledge value score

MCP tools: ks_write, ks_read, ks_search, ks_list, ks_delete,
           ks_containers, ks_stats, ks_top_value
"""
import os, uuid, json, math, time, re, asyncio
from pathlib import Path
from datetime import datetime, timezone
from typing import Optional, List
from collections import defaultdict, Counter

from fastapi import FastAPI, HTTPException, Request
from fastapi.responses import JSONResponse, HTMLResponse, StreamingResponse

BASE     = Path(__file__).parent
STORE    = BASE / "store"
STORE.mkdir(exist_ok=True)

# ── Container definitions ─────────────────────────────────────────

CONTAINERS = {
    "medical": {
        "label":       "Medical",
        "icon":        "⚕",        # caduceus-ish
        "color":       "#ef4444",
        "description": "Clinical guidelines, drug refs, protocols, case notes",
        "decay_model": "exponential",
        "half_life_days": 180,
        "warn_after_days": 90,
        "folders":     ["guidelines", "drugs", "protocols", "cases", "research"],
        "note":        "Outdated medical info can be dangerous. Review regularly.",
        "badge":       "CRITICAL-DECAY",
    },
    "legal": {
        "label":       "Legal",
        "icon":        "⚖",
        "color":       "#8b5cf6",
        "description": "Contracts, regulations, compliance, case law, GDPR",
        "decay_model": "slow_exponential",
        "half_life_days": 730,
        "warn_after_days": 365,
        "folders":     ["contracts", "regulations", "gdpr", "caselaw", "templates"],
        "note":        "Laws change slowly but verify jurisdiction and amendment dates.",
        "badge":       "SLOW-DECAY",
    },
    "company": {
        "label":       "Company",
        "icon":        "🏢",
        "color":       "#0ea5e9",
        "description": "SOPs, org charts, projects, market intel, people",
        "decay_model": "tiered",          # folder-dependent
        "half_life_days": 180,
        "warn_after_days": 90,
        "folders":     ["sop", "projects", "people", "market", "strategy"],
        "folder_half_lives": {"sop":365, "projects":90, "people":60, "market":14, "strategy":180},
        "note":        "Market and people data decay fast. SOPs are more stable.",
        "badge":       "TIERED-DECAY",
    },
    "research": {
        "label":       "Research",
        "icon":        "🔬",
        "color":       "#06b6d4",
        "description": "Papers, experiments, hypotheses, datasets, findings",
        "decay_model": "citation_curve",  # peaks at 30 days then slow decay
        "half_life_days": 540,
        "peak_days":   30,
        "warn_after_days": 365,
        "folders":     ["papers", "experiments", "datasets", "hypotheses", "notes"],
        "note":        "New research has highest relevance. Classic papers retain value.",
        "badge":       "CITATION-CURVE",
    },
    "tech": {
        "label":       "Tech / Docs",
        "icon":        "💻",
        "color":       "#22d3ee",
        "description": "API docs, code snippets, architecture, DevOps, configs",
        "decay_model": "versioned_decay",
        "half_life_days": 90,
        "warn_after_days": 45,
        "folders":     ["api", "snippets", "architecture", "devops", "configs"],
        "note":        "Software versions change fast. Tag with version numbers.",
        "badge":       "FAST-DECAY",
    },
    "prompts": {
        "label":       "Prompts",
        "icon":        "⚡",
        "color":       "#f59e0b",
        "description": "LLM prompts, system instructions, few-shot examples, chains",
        "decay_model": "stable",          # no decay
        "half_life_days": None,
        "warn_after_days": None,
        "folders":     ["system", "chains", "fewshot", "templates", "experiments"],
        "note":        "Prompts are reusable. Value does not decay.",
        "badge":       "STABLE",
    },
    "history": {
        "label":       "History / Archive",
        "icon":        "🕮",
        "color":       "#d97706",
        "description": "Historical records, past decisions, retrospectives, logs",
        "decay_model": "anti_decay",      # increases in value with age
        "half_life_days": None,
        "warn_after_days": None,
        "folders":     ["decisions", "retrospectives", "logs", "milestones", "archive"],
        "note":        "Historical context becomes MORE valuable over time.",
        "badge":       "ANTI-DECAY",
    },
    "personal": {
        "label":       "Personal",
        "icon":        "👤",
        "color":       "#ec4899",
        "description": "Goals, notes, preferences, journals, ideas",
        "decay_model": "drift_decay",
        "half_life_days": 180,
        "warn_after_days": 120,
        "folders":     ["goals", "notes", "ideas", "journal", "preferences"],
        "note":        "Preferences and goals drift over time. Review periodically.",
        "badge":       "DRIFT-DECAY",
    },
    "finance": {
        "label":       "Finance",
        "icon":        "📈",
        "color":       "#10b981",
        "description": "Market data, reports, forecasts, invoices, budgets",
        "decay_model": "extreme_decay",
        "half_life_days": 7,
        "warn_after_days": 3,
        "folders":     ["market", "reports", "forecasts", "invoices", "budgets"],
        "note":        "Market data decays within hours. Financial reports within weeks.",
        "badge":       "EXTREME-DECAY",
    },
    "operations": {
        "label":       "Operations",
        "icon":        "⚙",
        "color":       "#84cc16",
        "description": "Runbooks, incidents, on-call, monitoring, deployments",
        "decay_model": "operational_decay",
        "half_life_days": 180,
        "warn_after_days": 60,
        "folders":     ["runbooks", "incidents", "oncall", "monitoring", "deployments"],
        "note":        "Runbooks age fast in fast-moving infra. Keep versioned.",
        "badge":       "MODERATE-DECAY",
    },
}

# ── Knowledge value scoring ───────────────────────────────────────

def knowledge_value(doc: dict) -> float:
    """Compute 0-100 current value score for a document."""
    container = doc.get("container", "tech")
    cfg = CONTAINERS.get(container, CONTAINERS["tech"])
    base = float(doc.get("importance", 5)) / 10.0   # 0..1
    access_bonus = min(1.0, math.log1p(doc.get("access_count", 0)) / 10)
    age_days = (time.time() - doc.get("created_at", time.time())) / 86400

    model = cfg.get("decay_model", "exponential")
    hl    = cfg.get("half_life_days") or 365

    if model == "stable":
        t_factor = 1.0
    elif model == "anti_decay":
        # value grows: tanh curve from 0 to 1 over ~2 years
        t_factor = 0.5 + 0.5 * math.tanh(age_days / 365)
    elif model == "citation_curve":
        peak = cfg.get("peak_days", 30)
        if age_days <= peak:
            t_factor = 0.6 + 0.4 * (age_days / peak)
        else:
            t_factor = math.exp(-math.log(2) * (age_days - peak) / hl)
    elif model == "tiered":
        folder = doc.get("folder", "")
        folder_hl = cfg.get("folder_half_lives", {}).get(folder, hl)
        t_factor = math.exp(-math.log(2) * age_days / folder_hl)
    elif model == "extreme_decay":
        t_factor = math.exp(-math.log(2) * age_days / max(1, hl))
    else:
        # standard exponential decay
        t_factor = math.exp(-math.log(2) * age_days / hl)

    t_factor = max(0.0, min(1.0, t_factor))
    score = (base * 0.5 + access_bonus * 0.1 + t_factor * 0.4) * 100
    return round(score, 1)

def freshness_label(doc: dict) -> str:
    container = doc.get("container", "tech")
    cfg = CONTAINERS.get(container, {})
    warn = cfg.get("warn_after_days")
    model = cfg.get("decay_model", "exponential")
    age_days = (time.time() - doc.get("created_at", time.time())) / 86400
    if model == "stable":     return "STABLE"
    if model == "anti_decay": return "ARCHIVAL"
    if not warn:              return "OK"
    if age_days > warn * 2:   return "STALE"
    if age_days > warn:       return "AGING"
    return "FRESH"

# ── Storage utils ─────────────────────────────────────────────────

def now_ts(): return int(time.time())

def doc_path(container: str, folder: str, did: str) -> Path:
    d = STORE / container / folder
    d.mkdir(parents=True, exist_ok=True)
    return d / f"{did}.json"

def read_doc(container: str, folder: str, did: str) -> Optional[dict]:
    p = doc_path(container, folder, did)
    return json.loads(p.read_text()) if p.exists() else None

def write_doc(doc: dict):
    doc["updated_at"] = now_ts()
    doc_path(doc["container"], doc["folder"], doc["id"]).write_text(
        json.dumps(doc, indent=2, ensure_ascii=False)
    )

def all_docs(container: str = "", folder: str = "", limit: int = 500) -> List[dict]:
    out = []
    base = STORE / container if container else STORE
    for p in sorted(base.rglob("*.json"), reverse=True):
        try:
            d = json.loads(p.read_text())
            if folder and d.get("folder") != folder: continue
            out.append(d)
        except: pass
        if len(out) >= limit: break
    return out

def new_doc(data: dict) -> dict:
    did = uuid.uuid4().hex[:10]
    container = data.get("container", "tech")
    cfg = CONTAINERS.get(container, {})
    folders = cfg.get("folders", ["general"])
    folder = data.get("folder", folders[0] if folders else "general")
    doc = {
        "id":           did,
        "container":    container,
        "folder":       folder,
        "title":        (data.get("title") or "Untitled").strip(),
        "body":         (data.get("body") or data.get("content") or "").strip(),
        "summary":      (data.get("summary") or "").strip(),
        "tags":         [t.strip().lower() for t in data.get("tags", []) if str(t).strip()],
        "importance":   max(0, min(10, int(data.get("importance", 5)))),
        "author":       (data.get("author") or "").strip(),
        "source":       (data.get("source") or "").strip(),
        "version":      (data.get("version") or "").strip(),
        "expires_hint": data.get("expires_hint"),    # ISO date string, optional
        "links":        data.get("links", []),        # related doc IDs
        "metadata":     data.get("metadata", {}),
        "access_count": 0,
        "created_at":   now_ts(),
        "updated_at":   now_ts(),
        "last_accessed": None,
    }
    write_doc(doc)
    return doc

# ── Search engine ─────────────────────────────────────────────────

def tokenize(text: str) -> List[str]:
    return re.findall(r"[a-zA-Z0-9\u00C0-\u024F]+", text.lower())

def tf_score(query_tokens: List[str], doc: dict) -> float:
    text = " ".join([doc.get("title",""), doc.get("body",""),
                     doc.get("summary",""), " ".join(doc.get("tags",[]))]).lower()
    doc_tokens = tokenize(text)
    tf = Counter(doc_tokens)
    total = len(doc_tokens) or 1
    score = sum(tf.get(t, 0) / total for t in query_tokens)
    # boost: title matches worth 3x
    title_tokens = tokenize(doc.get("title","").lower())
    title_tf = Counter(title_tokens)
    score += sum(title_tf.get(t, 0) * 2 for t in query_tokens)
    return score

def search_docs(query: str = "", container: str = "", folder: str = "",
                tag: str = "", author: str = "", sort_by: str = "relevance",
                freshness: str = "", limit: int = 20) -> List[dict]:
    docs = all_docs(container, folder, 500)
    query_tokens = tokenize(query) if query else []

    results = []
    for doc in docs:
        # Tag filter
        if tag and tag.lower() not in doc.get("tags", []): continue
        # Author filter
        if author and doc.get("author","").lower() != author.lower(): continue
        # Freshness filter
        if freshness:
            fl = freshness_label(doc)
            if freshness == "fresh" and fl != "FRESH": continue
            if freshness == "stale" and fl not in ("STALE","AGING"): continue

        score = tf_score(query_tokens, doc) if query_tokens else 1.0
        if query_tokens and score == 0: continue

        results.append((score, doc))

    # Sort
    if sort_by == "value":
        results.sort(key=lambda x: -knowledge_value(x[1]))
    elif sort_by == "newest":
        results.sort(key=lambda x: -x[1].get("created_at", 0))
    elif sort_by == "oldest":
        results.sort(key=lambda x:  x[1].get("created_at", 0))
    elif sort_by == "importance":
        results.sort(key=lambda x: (-x[1].get("importance", 5), -x[0]))
    else:
        results.sort(key=lambda x: (-x[0], -knowledge_value(x[1])))

    return [d for _, d in results[:limit]]

# ── Seed data ─────────────────────────────────────────────────────

def seed():
    if any(STORE.rglob("*.json")): return
    seeds = [
        # TECH
        {"container":"tech","folder":"architecture","title":"ki-fusion-labs.de GPU Worker Architecture",
         "body":"GPU workers use a polling architecture. Workers call GET /api/queue every 2 seconds to check for pending jobs. On job acquisition, worker POSTs result to /api/results/{job_id}. No inbound connections required — fully firewall-friendly. LM Studio listens on localhost:1234. Jobs include: model_id, prompt, max_tokens, temperature, stream flag.",
         "summary":"Firewall-friendly polling design for GPU inference workers",
         "tags":["ki-fusion-labs","gpu","architecture","llm","inference"],"importance":9,"author":"christof","version":"v2"},
        {"container":"tech","folder":"api","title":"FORGE Skill Registry API Reference",
         "body":"POST /api/v1/skills — create skill\nGET /api/v1/skills — list (filter: ?category=&tag=)\nGET /api/v1/skills/{id} — get\nPATCH /api/v1/skills/{id} — update\nDELETE /api/v1/skills/{id} — delete\nGET /mcp/sse — MCP SSE stream\nPOST /mcp — MCP JSON-RPC\n\nSkill schema: {id, name, description, category, code, input_schema, output_schema, tags, version, author}",
         "summary":"FORGE MCP skill registry REST endpoints","tags":["forge","api","mcp","skills"],"importance":8,"author":"christof","version":"1.0"},
        {"container":"tech","folder":"devops","title":"HF Spaces Docker SDK Deployment Guide",
         "body":"CRITICAL: Use sdk: docker in README.md, NOT sdk: gradio.\nGradio SDK CSP blocks ALL <script> tags inside gr.HTML() and all iframes (frame-src: none).\nDockerfile pattern:\n  FROM python:3.11-slim\n  RUN useradd -m -u 1000 user\n  USER user\n  EXPOSE 7860\n  CMD [\"uvicorn\", \"main:app\", \"--host\", \"0.0.0.0\", \"--port\", \"7860\"]\nNo Gradio dependency. Pure FastAPI serves HTML as string. No StaticFiles.\nSurrogate chars: never use \\uD83D in Python strings — use HTML entities &#128196;",
         "summary":"How to deploy FastAPI on HF Spaces without CSP issues","tags":["hf-spaces","docker","fastapi","deployment"],"importance":10,"author":"christof"},
        # LEGAL
        {"container":"legal","folder":"gdpr","title":"Fusion Labs GDPR Deletion Architecture — Concept v3",
         "body":"Decentralized pull-based deletion across 14+ systems in 6 countries (DE, AT, CH, IT, FR, NL).\nCore flow: DPO triggers deletion request -> orchestrator creates deletion ticket -> each system polls /api/deletions/pending -> system processes and POSTs Proof of Deletion (PoD) certificate -> orchestrator tracks completion.\nPoD schema: {request_id, system_id, subject_id, deleted_fields[], timestamp, checksum, processor_name}.\nArchitecture Board sign-off required. DPO must countersign each PoD batch.",
         "summary":"Pull-based GDPR deletion design for Fusion Labs 14-system landscape","tags":["gdpr","Fusion Labs","deletion","architecture","pod"],"importance":10,"author":"christof","version":"v3"},
        {"container":"legal","folder":"regulations","title":"GDPR Article 17 — Right to Erasure (Key Points)",
         "body":"Art. 17 GDPR: Data subject has right to erasure without undue delay when: (a) no longer necessary for original purpose, (b) consent withdrawn, (c) data subject objects under Art. 21, (d) unlawful processing, (e) legal obligation.\nExceptions: freedom of expression, legal obligation, public interest (Art. 17(3)).\nTimeline: respond within 1 month (extendable 2 months for complex cases).\nLogging: document all erasure requests and outcomes.",
         "summary":"GDPR Art. 17 erasure right summary","tags":["gdpr","erasure","regulation","art17"],"importance":9,"author":"christof"},
        # MEDICAL
        {"container":"medical","folder":"protocols","title":"Burnout Prevention Protocol — Knowledge Worker",
         "body":"Early indicators: decision fatigue after <2h deep work, >3 context switches/hour, sleep quality drop, emotional blunting.\nInterventions: (1) 90-min deep work blocks, no interruptions. (2) Hard stop at 18:00. (3) Single daily priority written before 09:00. (4) Weekly 30-min review: energy vs output. (5) Physical activity 3x/week minimum.\nEscalation: if indicators persist 3+ weeks, consult occupational health.\nFor AI project leaders: especially watch for 'always on' patterns with LLM tools.",
         "summary":"Burnout prevention for knowledge workers managing AI projects","tags":["burnout","health","productivity","mental-health"],"importance":8,"author":"christof"},
        # RESEARCH
        {"container":"research","folder":"experiments","title":"BitNet 1.58-bit Trainer — Stability Fixes Log",
         "body":"Problem history:\n- NaN loss: fixed with gradient clipping (max_norm=1.0) + LR warmup (500 steps)\n- Dead layers: fixed with initialization scale 0.02 instead of default\n- FlipRate spike: STE gradient scaling tuned to 0.3 — above 0.5 causes oscillation\n- Dataset distribution mismatch: balanced sampling per domain required\n- Quantization death spiral: add 1e-8 epsilon to weight norm denominator\n\nFinal config: LR=2e-4, warmup=500, clip=1.0, batch=32, accumulation=4\nHardware: RTX 5090 24GB VRAM, bfloat16",
         "summary":"BitNet stable training recipe after systematic debugging","tags":["bitnet","training","rtx5090","quantization","stability"],"importance":9,"author":"christof"},
        {"container":"research","folder":"hypotheses","title":"JARVIS TurnClassifier — Ambiguous Intent Routing",
         "body":"Hypothesis: DST context window of 5 turns is insufficient for long multi-domain conversations.\nProposed fix: sliding window with semantic anchor — if slot confidence < 0.6, expand window to 10 turns and inject last confirmed intent as prior.\nTesting plan: 200 synthetic conversations, 3 ambiguity categories: topic-switch, implicit-reference, negation.\nExpected: +12% routing accuracy, +8ms latency overhead acceptable.",
         "summary":"Hypothesis for improving JARVIS intent routing with adaptive DST window","tags":["jarvis","dst","nlp","routing","hypothesis"],"importance":8,"author":"christof"},
        # PROMPTS
        {"container":"prompts","folder":"system","title":"JARVIS TheCore System Prompt v3",
         "body":"You are JARVIS, an advanced AI assistant operating within TheCore architecture. You have access to: (1) multi-tier memory system, (2) FORGE skill registry, (3) DISPATCH task board, (4) RELAY message bus, (5) this Knowledge Store.\n\nRouting rules:\n- Simple factual queries -> direct answer\n- Tasks requiring external data -> capability routing to appropriate tool\n- Ambiguous intent (confidence < 0.7) -> clarification before action\n- Urgent flags -> DISPATCH high-priority queue\n\nTone: precise, concise, no filler. Always show reasoning for non-trivial decisions.",
         "summary":"Core system prompt for JARVIS TheCore v3","tags":["jarvis","system-prompt","thecore","routing"],"importance":10,"author":"christof","version":"v3"},
        # COMPANY
        {"container":"company","folder":"projects","title":"ki-fusion-labs.de — Active Project Status",
         "body":"Status: ACTIVE development\nStack: PHP frontend + Python FastAPI backend + LM Studio local inference\nGPU: RTX 5090, CUDA 12.4\nActive components: LLM API queue, worker polling, result streaming\nRecent: SSL cert renewed (Let's Encrypt, 90-day auto-renew configured)\nPending: persistent queue (survive restarts), rate limiting per API key, usage dashboard\nHF Spaces deployed: FORGE, DISPATCH, RELAY, MEMORY, KNOWLEDGE",
         "summary":"Current status of ki-fusion-labs.de platform","tags":["ki-fusion-labs","status","projects"],"importance":9,"author":"christof"},
        # FINANCE
        {"container":"finance","folder":"budgets","title":"AI Infrastructure Cost Baseline — 2026",
         "body":"Monthly recurring:\n- HF Spaces (free tier): 0 EUR\n- OpenRouter free models: 0 EUR\n- Oracle Cloud Always Free: 0 EUR\n- Domain ki-fusion-labs.de: ~1.50 EUR/mo\n- Electricity RTX 5090 training (est. 10h/mo @ 400W): ~0.80 EUR\nTotal infra: ~2.30 EUR/month\n\nNote: HF Spaces may incur costs if Spaces upgraded to GPU. Budget 20 EUR/mo buffer.",
         "summary":"AI infra cost breakdown — essentially free tier stack","tags":["budget","infrastructure","costs","2026"],"importance":6,"author":"christof"},
        # OPERATIONS
        {"container":"operations","folder":"runbooks","title":"HF Space Recovery Runbook",
         "body":"When a Space goes red:\n1. Check logs: Space Settings -> Logs\n2. Common errors:\n   - UnicodeEncodeError: surrogate chars in SPA string -> use HTML entities\n   - ModuleNotFoundError: check requirements.txt, rebuild\n   - Port error: ensure CMD uses --port 7860\n   - Permission denied: ensure USER user in Dockerfile + chown\n3. Force rebuild: Settings -> Factory reset (loses state!)\n4. For persistent data: use HF Datasets API, not local filesystem\n5. SDK confusion: gradio SDK = CSP nightmare. Always use sdk: docker",
         "summary":"Step-by-step HF Space debugging and recovery","tags":["hf-spaces","runbook","debugging","recovery"],"importance":10,"author":"christof"},
        # HISTORY
        {"container":"history","folder":"decisions","title":"ADR-001: Why Docker SDK over Gradio SDK",
         "body":"Date: 2026-03\nContext: Building agent UI tools on HuggingFace Spaces.\nDecision: Use sdk: docker for all custom web UIs.\nRationale: Gradio SDK injects CSP headers that block ALL <script> tags in gr.HTML() components. Frame-src: none also blocks iframes. No workaround exists via custom_headers in README.\nConsequences: Pure FastAPI, HTML served as string, no Gradio dependency, full CSP control.\nStatus: ACCEPTED. Applied to FORGE, DISPATCH, RELAY, MEMORY, KNOWLEDGE.",
         "summary":"Architecture decision: Docker over Gradio for HF Spaces UIs","tags":["adr","architecture","hf-spaces","docker","decision"],"importance":10,"author":"christof"},
    ]
    for s in seeds:
        new_doc(s)

seed()

# ── FastAPI ───────────────────────────────────────────────────────

app = FastAPI(title="Knowledge Store")

def jresp(data, status=200): return JSONResponse(content=data, status_code=status)

@app.get("/api/containers")
async def get_containers():
    result = {}
    for k, v in CONTAINERS.items():
        docs = all_docs(k, limit=500)
        result[k] = {**v, "count": len(docs),
                     "avg_value": round(sum(knowledge_value(d) for d in docs)/len(docs), 1) if docs else 0}
    return jresp(result)

@app.get("/api/docs")
async def list_docs(container: str = "", folder: str = "", tag: str = "",
                    author: str = "", sort: str = "newest", limit: int = 100):
    docs = search_docs(container=container, folder=folder, tag=tag,
                       author=author, sort_by=sort, limit=limit)
    for d in docs:
        d["_value"]     = knowledge_value(d)
        d["_freshness"] = freshness_label(d)
    return jresp(docs)

@app.get("/api/docs/search")
async def search(q: str = "", container: str = "", folder: str = "", tag: str = "",
                 sort: str = "relevance", freshness: str = "", limit: int = 20):
    docs = search_docs(q, container, folder, tag, sort_by=sort, freshness=freshness, limit=limit)
    for d in docs:
        d["_value"]     = knowledge_value(d)
        d["_freshness"] = freshness_label(d)
    return jresp(docs)

@app.get("/api/docs/top-value")
async def top_value(container: str = "", limit: int = 20):
    docs = all_docs(container, limit=500)
    scored = sorted(docs, key=lambda d: -knowledge_value(d))
    for d in scored[:limit]:
        d["_value"]     = knowledge_value(d)
        d["_freshness"] = freshness_label(d)
    return jresp(scored[:limit])

@app.get("/api/docs/{container}/{folder}/{did}")
async def get_doc(container: str, folder: str, did: str):
    d = read_doc(container, folder, did)
    if not d: raise HTTPException(404)
    d["access_count"] = d.get("access_count", 0) + 1
    d["last_accessed"] = now_ts()
    write_doc(d)
    d["_value"]     = knowledge_value(d)
    d["_freshness"] = freshness_label(d)
    return jresp(d)

@app.post("/api/docs")
async def create_doc(request: Request):
    data = await request.json()
    if not data.get("title","").strip(): raise HTTPException(400, "title required")
    if not data.get("body","").strip()  and not data.get("content","").strip():
        raise HTTPException(400, "body required")
    d = new_doc(data)
    d["_value"]     = knowledge_value(d)
    d["_freshness"] = freshness_label(d)
    return jresp({"status":"created","id":d["id"],"doc":d}, 201)

@app.patch("/api/docs/{container}/{folder}/{did}")
async def update_doc(container: str, folder: str, did: str, request: Request):
    d = read_doc(container, folder, did)
    if not d: raise HTTPException(404)
    data = await request.json()
    for k in ("title","body","summary","tags","importance","author","source","version","links","metadata"):
        if k in data: d[k] = data[k]
    write_doc(d)
    d["_value"]     = knowledge_value(d)
    d["_freshness"] = freshness_label(d)
    return jresp({"status":"updated","doc":d})

@app.delete("/api/docs/{container}/{folder}/{did}")
async def delete_doc(container: str, folder: str, did: str):
    p = doc_path(container, folder, did)
    if not p.exists(): raise HTTPException(404)
    p.unlink()
    return jresp({"status":"deleted"})

@app.get("/api/stats")
async def stats():
    all_d = all_docs(limit=2000)
    by_container: dict = {}
    stale_count = 0
    total_value = 0.0
    by_freshness: dict = {"FRESH":0,"AGING":0,"STALE":0,"STABLE":0,"ARCHIVAL":0}
    for d in all_d:
        c = d.get("container","?")
        by_container[c] = by_container.get(c,0) + 1
        v = knowledge_value(d)
        total_value += v
        fl = freshness_label(d)
        by_freshness[fl] = by_freshness.get(fl,0) + 1
        if fl == "STALE": stale_count += 1
    return jresp({
        "total": len(all_d),
        "by_container": by_container,
        "by_freshness": by_freshness,
        "stale_count": stale_count,
        "avg_value": round(total_value/len(all_d), 1) if all_d else 0,
    })

# ── MCP ───────────────────────────────────────────────────────────

MCP_TOOLS = [
    {"name":"ks_write","description":"Write a knowledge document to a container/folder",
     "inputSchema":{"type":"object","required":["container","title","body"],"properties":{
         "container":  {"type":"string","enum":list(CONTAINERS.keys())},
         "folder":     {"type":"string"},
         "title":      {"type":"string"},
         "body":       {"type":"string"},
         "summary":    {"type":"string"},
         "tags":       {"type":"array","items":{"type":"string"}},
         "importance": {"type":"integer","minimum":0,"maximum":10},
         "author":     {"type":"string"},
         "version":    {"type":"string"},
     }}},
    {"name":"ks_read","description":"Read a document by container/folder/id",
     "inputSchema":{"type":"object","required":["container","folder","id"],"properties":{
         "container":{"type":"string"},"folder":{"type":"string"},"id":{"type":"string"}}}},
    {"name":"ks_search","description":"Search knowledge base by query, tag, container, author",
     "inputSchema":{"type":"object","properties":{
         "query":     {"type":"string"},
         "container": {"type":"string"},
         "folder":    {"type":"string"},
         "tag":       {"type":"string"},
         "sort":      {"type":"string","enum":["relevance","value","newest","oldest","importance"]},
         "freshness": {"type":"string","enum":["fresh","stale",""]},
         "limit":     {"type":"integer","default":10},
     }}},
    {"name":"ks_list","description":"List documents in a container/folder",
     "inputSchema":{"type":"object","properties":{
         "container":{"type":"string"},"folder":{"type":"string"},"limit":{"type":"integer"}}}},
    {"name":"ks_delete","description":"Delete a knowledge document",
     "inputSchema":{"type":"object","required":["container","folder","id"],"properties":{
         "container":{"type":"string"},"folder":{"type":"string"},"id":{"type":"string"}}}},
    {"name":"ks_containers","description":"List all containers with counts and avg value",
     "inputSchema":{"type":"object","properties":{}}},
    {"name":"ks_stats","description":"Overall knowledge base statistics",
     "inputSchema":{"type":"object","properties":{}}},
    {"name":"ks_top_value","description":"Get highest-value documents right now",
     "inputSchema":{"type":"object","properties":{
         "container":{"type":"string"},"limit":{"type":"integer","default":10}}}},
]

async def mcp_call(name, args):
    if name == "ks_write":
        if not args.get("title") or not args.get("body"):
            return json.dumps({"error":"title and body required"})
        d = new_doc(args)
        d["_value"] = knowledge_value(d)
        return json.dumps({"created":d["id"],"container":d["container"],"folder":d["folder"],"value":d["_value"]})
    if name == "ks_read":
        d = read_doc(args["container"], args["folder"], args["id"])
        if not d: return json.dumps({"error":"not found"})
        d["access_count"] = d.get("access_count",0)+1
        d["last_accessed"] = now_ts()
        write_doc(d)
        d["_value"] = knowledge_value(d); d["_freshness"] = freshness_label(d)
        return json.dumps(d)
    if name == "ks_search":
        docs = search_docs(args.get("query",""), args.get("container",""),
                           args.get("folder",""), args.get("tag",""),
                           args.get("sort","relevance"), args.get("freshness",""), args.get("limit",10))
        for d in docs: d["_value"]=knowledge_value(d); d["_freshness"]=freshness_label(d)
        return json.dumps({"count":len(docs),"results":docs})
    if name == "ks_list":
        docs = all_docs(args.get("container",""), args.get("folder",""), args.get("limit",20))
        for d in docs: d["_value"]=knowledge_value(d); d["_freshness"]=freshness_label(d)
        return json.dumps({"count":len(docs),"docs":docs})
    if name == "ks_delete":
        p = doc_path(args["container"], args["folder"], args["id"])
        if not p.exists(): return json.dumps({"error":"not found"})
        p.unlink(); return json.dumps({"deleted":args["id"]})
    if name == "ks_containers":
        result = {}
        for k, v in CONTAINERS.items():
            docs = all_docs(k, limit=500)
            result[k] = {"label":v["label"],"count":len(docs),"decay_model":v["decay_model"],
                         "badge":v["badge"],"avg_value":round(sum(knowledge_value(d) for d in docs)/len(docs),1) if docs else 0}
        return json.dumps(result)
    if name == "ks_stats":
        all_d = all_docs(limit=2000)
        by_c = {}
        for d in all_d: by_c[d.get("container","?")] = by_c.get(d.get("container","?"),0)+1
        return json.dumps({"total":len(all_d),"by_container":by_c})
    if name == "ks_top_value":
        docs = all_docs(args.get("container",""), limit=500)
        scored = sorted(docs, key=lambda d:-knowledge_value(d))[:args.get("limit",10)]
        for d in scored: d["_value"]=knowledge_value(d); d["_freshness"]=freshness_label(d)
        return json.dumps({"count":len(scored),"docs":scored})
    return json.dumps({"error":f"unknown: {name}"})

@app.get("/mcp/sse")
async def mcp_sse():
    async def stream():
        init = {"jsonrpc":"2.0","method":"notifications/initialized",
                "params":{"serverInfo":{"name":"knowledge-store","version":"1.0"},"capabilities":{"tools":{}}}}
        yield f"data: {json.dumps(init)}\n\n"
        await asyncio.sleep(0.1)
        yield f"data: {json.dumps({'jsonrpc':'2.0','method':'notifications/tools/list_changed','params':{}})}\n\n"
        while True:
            await asyncio.sleep(25)
            yield f"data: {json.dumps({'jsonrpc':'2.0','method':'ping'})}\n\n"
    return StreamingResponse(stream(), media_type="text/event-stream",
        headers={"Cache-Control":"no-cache","X-Accel-Buffering":"no"})

@app.post("/mcp")
async def mcp_rpc(request: Request):
    body = await request.json()
    method = body.get("method",""); rid = body.get("id",1)
    if method == "initialize":
        return jresp({"jsonrpc":"2.0","id":rid,"result":{
            "serverInfo":{"name":"knowledge-store","version":"1.0"},"capabilities":{"tools":{}}}})
    if method == "tools/list":
        return jresp({"jsonrpc":"2.0","id":rid,"result":{"tools":MCP_TOOLS}})
    if method == "tools/call":
        p = body.get("params",{})
        res = await mcp_call(p.get("name",""), p.get("arguments",{}))
        return jresp({"jsonrpc":"2.0","id":rid,"result":{"content":[{"type":"text","text":res}]}})
    return jresp({"jsonrpc":"2.0","id":rid,"error":{"code":-32601,"message":"Method not found"}})

# ── SPA ───────────────────────────────────────────────────────────

@app.get("/", response_class=HTMLResponse)
async def ui():
    return HTMLResponse(content=SPA, media_type="text/html; charset=utf-8")

SPA = r"""<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
<title>KNOWLEDGE STORE</title>
<link rel="preconnect" href="https://fonts.googleapis.com">
<link href="https://fonts.googleapis.com/css2?family=Space+Mono:wght@400;700&family=Inter:wght@400;500;600&display=swap" rel="stylesheet">
<style>
:root{
  --bg:#08080f;--s1:#0f0f1a;--s2:#141428;--s3:#1a1a35;
  --bd:#1e1e35;--bd2:#282850;--bd3:#323260;
  --acc:#ff6b00;--acc2:#ff9500;--acc3:#ffb347;
  --txt:#d8d8f0;--sub:#5a5a88;--dim:#282850;
  --lo:#2ed573;--cr:#ff2244;--warn:#f59e0b;
  --c-med:#ef4444;--c-leg:#8b5cf6;--c-com:#0ea5e9;
  --c-res:#06b6d4;--c-tec:#22d3ee;--c-pro:#f59e0b;
  --c-his:#d97706;--c-per:#ec4899;--c-fin:#10b981;--c-ops:#84cc16;
  --font:'Space Mono',monospace;--body:'Inter',sans-serif;
}
*{box-sizing:border-box;margin:0;padding:0;}
html,body{height:100%;overflow:hidden;}
body{font-family:var(--body);background:var(--bg);color:var(--txt);display:flex;flex-direction:column;height:100vh;}
body::after{content:'';position:fixed;inset:0;pointer-events:none;
  background-image:repeating-linear-gradient(0deg,transparent,transparent 2px,rgba(255,107,0,.004) 2px,rgba(255,107,0,.004) 3px);}

/* HEADER */
#hdr{flex-shrink:0;display:flex;align-items:center;padding:.8rem 1.6rem;gap:1.2rem;
  border-bottom:1px solid var(--bd);background:linear-gradient(180deg,#0c0c1e,var(--bg));z-index:10;}
#logo{font-family:var(--font);font-size:1.2rem;font-weight:700;letter-spacing:2px;
  background:linear-gradient(90deg,var(--acc),var(--acc3));
  -webkit-background-clip:text;-webkit-text-fill-color:transparent;background-clip:text;}
#logo-sub{font-family:var(--font);font-size:.5rem;color:var(--sub);letter-spacing:.25em;text-transform:uppercase;margin-top:2px;}
#hdr-stats{display:flex;gap:.45rem;flex:1;flex-wrap:wrap;}
.hs{display:flex;align-items:center;gap:.35rem;background:var(--s1);border:1px solid var(--bd);
  border-radius:5px;padding:.22rem .5rem;font-family:var(--font);font-size:.5rem;color:var(--sub);}
.hs-n{font-size:.82rem;font-weight:700;line-height:1;}
.freshbadge{font-size:.46rem;padding:1px 5px;border-radius:3px;font-family:var(--font);font-weight:700;letter-spacing:.06em;}
.fb-FRESH{background:#02130a;color:var(--lo);border:1px solid rgba(46,213,115,.15);}
.fb-AGING{background:#181400;color:var(--warn);border:1px solid rgba(245,158,11,.15);}
.fb-STALE{background:#1a0308;color:var(--cr);border:1px solid rgba(255,34,68,.15);}
.fb-STABLE{background:#0a0a18;color:var(--sub);border:1px solid var(--bd);}
.fb-ARCHIVAL{background:#1a0d00;color:var(--c-his);border:1px solid rgba(217,119,6,.15);}
#btn-new{background:var(--acc);color:#000;border:none;padding:.4rem 1rem;
  font-family:var(--font);font-size:.65rem;font-weight:700;letter-spacing:.1em;
  text-transform:uppercase;border-radius:4px;cursor:pointer;flex-shrink:0;
  transition:background .12s,transform .1s;}
#btn-new:hover{background:var(--acc2);transform:translateY(-1px);}

/* 3-COLUMN LAYOUT */
#main{flex:1;display:flex;min-height:0;overflow:hidden;}

/* LEFT: container sidebar */
#sidebar{width:210px;flex-shrink:0;border-right:1px solid var(--bd);
  overflow-y:auto;background:var(--s1);}
#sidebar::-webkit-scrollbar{width:3px;}
#sidebar::-webkit-scrollbar-thumb{background:var(--bd2);border-radius:2px;}
.sb-section{padding:.55rem .7rem .2rem;}
.sb-label{font-family:var(--font);font-size:.47rem;color:var(--sub);text-transform:uppercase;
  letter-spacing:.15em;margin-bottom:.3rem;padding-bottom:.25rem;border-bottom:1px solid var(--bd);}
.ctr-item{display:flex;align-items:center;gap:.42rem;padding:.38rem .55rem;
  border-radius:6px;cursor:pointer;margin-bottom:.12rem;transition:background .1s;}
.ctr-item:hover{background:var(--s2);}
.ctr-item.active{background:var(--s2);border-left:2px solid var(--acc);}
.ctr-icon{font-size:.85rem;width:1.4rem;text-align:center;flex-shrink:0;}
.ctr-info{flex:1;min-width:0;}
.ctr-name{font-size:.65rem;font-weight:600;color:var(--txt);white-space:nowrap;overflow:hidden;text-overflow:ellipsis;}
.ctr-meta{display:flex;align-items:center;gap:.3rem;margin-top:.12rem;}
.ctr-count{font-family:var(--font);font-size:.5rem;color:var(--sub);}
.ctr-badge{font-family:var(--font);font-size:.42rem;padding:0 4px;border-radius:3px;
  font-weight:700;letter-spacing:.06em;flex-shrink:0;}
.ctr-value{font-family:var(--font);font-size:.48rem;font-weight:700;margin-left:auto;}

/* folder sub-items */
.folder-item{display:flex;align-items:center;gap:.35rem;padding:.28rem .55rem .28rem 1.5rem;
  border-radius:5px;cursor:pointer;margin-bottom:.06rem;transition:background .1s;font-size:.6rem;color:var(--sub);}
.folder-item:hover{background:var(--s2);color:var(--txt);}
.folder-item.active{color:var(--acc);background:var(--s2);}

/* CENTER: doc list */
#list-col{width:360px;flex-shrink:0;border-right:1px solid var(--bd);
  display:flex;flex-direction:column;overflow:hidden;}
#list-toolbar{flex-shrink:0;padding:.42rem .7rem;border-bottom:1px solid var(--bd);
  background:var(--s1);display:flex;gap:.38rem;flex-wrap:wrap;align-items:center;}
#search-inp{background:var(--s2);border:1px solid var(--bd2);border-radius:5px;
  padding:.34rem .6rem;font-family:var(--font);font-size:.65rem;color:var(--txt);
  outline:none;width:180px;transition:border-color .12s;}
#search-inp:focus{border-color:var(--acc);}
#search-btn{background:var(--acc);color:#000;border:none;padding:.34rem .6rem;
  font-family:var(--font);font-size:.6rem;font-weight:700;border-radius:4px;cursor:pointer;}
.sort-sel{background:var(--s2);border:1px solid var(--bd2);border-radius:4px;
  padding:.3rem .5rem;font-family:var(--font);font-size:.58rem;color:var(--txt);outline:none;}
#list-scroll{flex:1;overflow-y:auto;padding:.45rem;}
#list-scroll::-webkit-scrollbar{width:3px;}
#list-scroll::-webkit-scrollbar-thumb{background:var(--bd2);border-radius:2px;}

/* DOC CARD */
.dc{background:var(--s1);border:1px solid var(--bd);border-radius:8px;
  padding:.58rem .75rem .58rem .95rem;margin-bottom:.35rem;cursor:pointer;
  position:relative;animation:cin .14s ease;transition:border-color .1s,transform .08s;}
@keyframes cin{from{opacity:0;transform:translateY(3px)}to{opacity:1;transform:none}}
.dc:hover{border-color:var(--bd2);transform:translateY(-1px);}
.dc.active{border-color:var(--acc);background:var(--s2);}
.dc::before{content:'';position:absolute;left:0;top:0;bottom:0;width:3px;border-radius:8px 0 0 8px;}
.dc-top{display:flex;align-items:flex-start;gap:.35rem;margin-bottom:.22rem;}
.dc-title{flex:1;font-size:.7rem;font-weight:600;color:var(--txt);line-height:1.3;word-break:break-word;}
.dc-val{font-family:var(--font);font-size:.52rem;font-weight:700;flex-shrink:0;margin-top:1px;}
.dc-preview{font-size:.6rem;color:var(--sub);line-height:1.45;
  max-height:36px;overflow:hidden;position:relative;margin-bottom:.28rem;}
.dc-preview::after{content:'';position:absolute;bottom:0;left:0;right:0;height:12px;
  background:linear-gradient(transparent,var(--s1));}
.dc.active .dc-preview::after{background:linear-gradient(transparent,var(--s2));}
.dc-foot{display:flex;align-items:center;gap:.28rem;flex-wrap:wrap;}
.dc-tag{font-size:.47rem;background:var(--s2);border:1px solid var(--bd);
  border-radius:3px;padding:0 4px;color:var(--sub);}
.dc-folder{font-size:.5rem;color:var(--sub);opacity:.6;}
.dc-date{font-size:.47rem;color:var(--dim);margin-left:auto;}

/* VALUE GAUGE */
.vg{display:inline-flex;align-items:center;gap:.25rem;}
.vg-bar{width:32px;height:3px;background:var(--bd2);border-radius:2px;overflow:hidden;}
.vg-fill{height:100%;border-radius:2px;transition:width .3s;}

/* RIGHT: detail */
#detail-col{flex:1;display:flex;flex-direction:column;overflow:hidden;}
#detail-scroll{flex:1;overflow-y:auto;padding:1.3rem 1.7rem;}
#detail-scroll::-webkit-scrollbar{width:4px;}
#detail-scroll::-webkit-scrollbar-thumb{background:var(--bd2);border-radius:2px;}
#d-empty{display:flex;flex-direction:column;align-items:center;justify-content:center;
  height:100%;gap:.7rem;}
#d-empty .big{font-size:3rem;opacity:.12;}
#d-empty .msg{font-family:var(--font);font-size:.62rem;color:var(--sub);
  letter-spacing:.12em;text-transform:uppercase;opacity:.4;}
#d-content{display:none;}

/* VALUE METER */
.value-meter{background:var(--s1);border:1px solid var(--bd);border-radius:8px;
  padding:.7rem 1rem;margin-bottom:1rem;display:flex;gap:1.2rem;align-items:center;}
.vm-score{font-family:var(--font);font-size:2.2rem;font-weight:700;line-height:1;}
.vm-label{font-family:var(--font);font-size:.5rem;text-transform:uppercase;
  letter-spacing:.15em;color:var(--sub);margin-top:.2rem;}
.vm-info{flex:1;}
.vm-model{font-family:var(--font);font-size:.55rem;color:var(--sub);margin-bottom:.35rem;}
.vm-bar-wrap{height:6px;background:var(--bd2);border-radius:3px;}
.vm-bar-fill{height:100%;border-radius:3px;transition:width .5s;}
.vm-meta{display:flex;justify-content:space-between;margin-top:.3rem;font-family:var(--font);font-size:.48rem;color:var(--sub);}
.decay-chips{display:flex;flex-wrap:wrap;gap:.25rem;margin-top:.5rem;}
.decay-chip{font-family:var(--font);font-size:.48rem;padding:1px 6px;border-radius:3px;background:var(--s2);color:var(--sub);border:1px solid var(--bd);}

.d-ctr-hdr{display:flex;align-items:center;gap:.55rem;margin-bottom:.65rem;}
.d-ctr-icon{font-size:1.2rem;}
.d-ctr-info .d-ctr-label{font-family:var(--font);font-size:.52rem;font-weight:700;
  letter-spacing:.15em;text-transform:uppercase;margin-bottom:.1rem;}
.d-ctr-info .d-ctr-note{font-size:.58rem;color:var(--sub);}
#d-title{font-size:1.1rem;font-weight:600;color:var(--txt);line-height:1.4;margin-bottom:.55rem;word-break:break-word;}
#d-body{font-size:.76rem;color:var(--txt);line-height:1.72;
  background:var(--s1);border:1px solid var(--bd);border-radius:7px;padding:.9rem 1rem;
  white-space:pre-wrap;margin-bottom:.9rem;font-family:var(--body);}
.d-meta-grid{display:grid;grid-template-columns:repeat(3,1fr);gap:.4rem .7rem;margin-bottom:.9rem;}
.dml{font-size:.48rem;font-family:var(--font);color:var(--sub);text-transform:uppercase;letter-spacing:.1em;margin-bottom:.15rem;}
.dmv{font-size:.62rem;color:var(--txt);}
.d-tags{display:flex;flex-wrap:wrap;gap:.28rem;margin-bottom:.9rem;}
.d-tag{background:var(--s2);border:1px solid var(--bd2);border-radius:4px;padding:1px 8px;font-size:.57rem;color:var(--sub);}
.d-acts{display:flex;gap:.42rem;}
.d-btn{background:var(--s2);border:1px solid var(--bd2);color:var(--sub);
  padding:.34rem .68rem;font-family:var(--font);font-size:.6rem;border-radius:4px;cursor:pointer;transition:all .1s;}
.d-btn:hover{background:var(--bd2);color:var(--txt);}
.d-btn.danger:hover{background:#1e0508;color:var(--cr);}
.d-btn.acc{background:var(--acc);color:#000;border-color:var(--acc);}
.d-btn.acc:hover{background:var(--acc2);}

/* MODAL */
#modal{display:none;position:fixed;inset:0;background:rgba(0,0,0,.85);z-index:100;
  backdrop-filter:blur(5px);align-items:center;justify-content:center;}
#modal.open{display:flex;}
.mdl{background:var(--s1);border:1px solid var(--bd2);border-top:2px solid var(--acc);
  border-radius:12px;padding:1.4rem;width:640px;max-width:97vw;max-height:92vh;
  overflow-y:auto;animation:mdin .17s ease;position:relative;}
@keyframes mdin{from{opacity:0;transform:scale(.96) translateY(-8px)}to{opacity:1;transform:none}}
#mdl-title{font-family:var(--font);font-size:.82rem;font-weight:700;letter-spacing:3px;
  color:var(--acc);margin-bottom:.9rem;}
#mdl-close{position:absolute;top:.85rem;right:.85rem;background:none;border:none;color:var(--sub);
  width:26px;height:26px;border-radius:4px;cursor:pointer;font-size:.85rem;
  display:flex;align-items:center;justify-content:center;transition:all .1s;}
#mdl-close:hover{background:var(--bd2);color:var(--txt);}
.fg2{display:grid;grid-template-columns:1fr 1fr;gap:.6rem;}
.fg3{display:grid;grid-template-columns:1fr 1fr 1fr;gap:.6rem;}
.fl{margin-bottom:.6rem;}
.fl label{display:block;font-family:var(--font);font-size:.48rem;color:var(--sub);
  text-transform:uppercase;letter-spacing:.12em;margin-bottom:.2rem;}
.fl input,.fl textarea,.fl select{width:100%;background:var(--s2);border:1px solid var(--bd2);
  border-radius:5px;padding:.4rem .58rem;font-family:var(--body);font-size:.72rem;color:var(--txt);
  outline:none;transition:border-color .12s;}
.fl input:focus,.fl textarea:focus,.fl select:focus{border-color:var(--acc);}
.fl textarea{min-height:130px;line-height:1.65;resize:vertical;}
.fl select option{background:var(--s2);}
#folder-sel option{background:var(--s2);}
#mdl-actions{display:flex;gap:.42rem;margin-top:.85rem;}
#btn-save{flex:1;background:var(--acc);color:#000;border:none;padding:.48rem 1rem;
  font-family:var(--font);font-size:.65rem;font-weight:700;letter-spacing:.1em;
  text-transform:uppercase;border-radius:5px;cursor:pointer;transition:background .1s;}
#btn-save:hover{background:var(--acc2);}
#btn-mcancel{background:var(--s2);color:var(--sub);border:1px solid var(--bd2);padding:.48rem .9rem;
  font-family:var(--font);font-size:.65rem;letter-spacing:.1em;text-transform:uppercase;
  border-radius:5px;cursor:pointer;transition:all .1s;}
#btn-mcancel:hover{background:var(--bd2);color:var(--txt);}
#decay-preview{background:var(--s2);border:1px solid var(--bd2);border-radius:6px;
  padding:.55rem .75rem;margin-top:.6rem;font-family:var(--font);font-size:.58rem;color:var(--sub);}
#decay-preview strong{color:var(--acc);}

/* TOAST */
#toasts{position:fixed;bottom:1rem;right:1rem;z-index:200;display:flex;flex-direction:column;gap:.35rem;}
.tst{background:var(--s1);border:1px solid var(--bd2);border-left:3px solid var(--acc);
  padding:.42rem .78rem;font-size:.62rem;border-radius:6px;animation:tin .15s ease;
  color:var(--txt);max-width:280px;font-family:var(--font);}
.tst.ok{border-left-color:var(--lo);}.tst.err{border-left-color:var(--cr);}
@keyframes tin{from{opacity:0;transform:translateX(12px)}to{opacity:1;transform:none}}
#mcp-hint{position:fixed;bottom:1rem;left:.8rem;z-index:10;background:var(--s1);
  border:1px solid var(--bd2);border-left:3px solid var(--sub);border-radius:6px;
  padding:.38rem .72rem;font-family:var(--font);font-size:.52rem;color:var(--sub);}
</style>
</head>
<body>

<div id="hdr">
  <div>
    <div id="logo">KNOWLEDGE STORE</div>
    <div id="logo-sub">10 Containers &middot; Temporal Value Engine &middot; MCP &middot; ki-fusion-labs.de</div>
  </div>
  <div id="hdr-stats">
    <div class="hs"><span class="hs-n" id="s-total" style="color:var(--txt)">0</span>DOCS</div>
    <div class="hs"><span class="hs-n" id="s-avg-val" style="color:var(--acc)">0</span>AVG VALUE</div>
    <div class="hs"><span class="freshbadge fb-STALE" id="s-stale">0</span>STALE</div>
    <div class="hs"><span class="freshbadge fb-FRESH" id="s-fresh">0</span>FRESH</div>
  </div>
  <button id="btn-new">+ New Document</button>
</div>

<div id="main">

  <!-- SIDEBAR -->
  <div id="sidebar">
    <div class="sb-section">
      <div class="sb-label">Containers</div>
      <div class="ctr-item active" id="ctr-all" data-ctr="">
        <div class="ctr-icon">&#128196;</div>
        <div class="ctr-info">
          <div class="ctr-name">All Documents</div>
          <div class="ctr-meta"><span class="ctr-count" id="cnt-all">0 docs</span></div>
        </div>
      </div>
    </div>
    <div class="sb-section" id="ctr-list"></div>
    <div class="sb-section" id="folder-list" style="display:none">
      <div class="sb-label" id="folder-label">Folders</div>
      <div id="folder-items"></div>
    </div>
  </div>

  <!-- LIST -->
  <div id="list-col">
    <div id="list-toolbar">
      <input type="text" id="search-inp" placeholder="Search...">
      <button id="search-btn">&#128269;</button>
      <select class="sort-sel" id="sort-sel">
        <option value="relevance">Relevance</option>
        <option value="value">Value Score</option>
        <option value="newest" selected>Newest</option>
        <option value="oldest">Oldest</option>
        <option value="importance">Importance</option>
      </select>
    </div>
    <div id="list-scroll"><div id="list-empty" style="font-size:.6rem;color:var(--dim);text-align:center;padding:2rem;">Loading...</div></div>
  </div>

  <!-- DETAIL -->
  <div id="detail-col">
    <div id="detail-scroll">
      <div id="d-empty">
        <div class="big">&#128196;</div>
        <div class="msg">Select a document</div>
      </div>
      <div id="d-content"></div>
    </div>
  </div>

</div><!-- /main -->

<!-- COMPOSE MODAL -->
<div id="modal">
<div class="mdl">
  <button id="mdl-close">&#x2715;</button>
  <div id="mdl-title">NEW KNOWLEDGE DOCUMENT</div>
  <div class="fg2">
    <div class="fl"><label>Container *</label>
      <select id="m-container"></select></div>
    <div class="fl"><label>Folder</label>
      <select id="m-folder"></select></div>
  </div>
  <div class="fl"><label>Title *</label>
    <input type="text" id="m-title" placeholder="Document title"></div>
  <div class="fl"><label>Body *</label>
    <textarea id="m-body" placeholder="Knowledge content (markdown supported in display)..."></textarea></div>
  <div class="fl"><label>Summary (one-liner)</label>
    <input type="text" id="m-summary" placeholder="Brief description for search results"></div>
  <div class="fg3">
    <div class="fl"><label>Author</label>
      <input type="text" id="m-author" placeholder="christof"></div>
    <div class="fl"><label>Version</label>
      <input type="text" id="m-version" placeholder="v1.0"></div>
    <div class="fl"><label>Importance (0-10)</label>
      <input type="number" id="m-importance" value="5" min="0" max="10"></div>
  </div>
  <div class="fl"><label>Tags (comma separated)</label>
    <input type="text" id="m-tags" placeholder="gdpr, architecture, v3"></div>
  <div id="decay-preview">Select a container to see its decay model...</div>
  <div id="mdl-actions">
    <button id="btn-save">&#9889; Save Document</button>
    <button id="btn-mcancel">Cancel</button>
  </div>
</div>
</div>

<div id="toasts"></div>
<div id="mcp-hint">MCP: <code>ks_write</code> &nbsp;|&nbsp; <code>ks_search</code> &nbsp;|&nbsp; <code>ks_top_value</code></div>

<script>
var CONTAINERS_META = {};
var ALL_DOCS = [];
var ACTIVE_CTR = '';
var ACTIVE_FOLDER = '';
var ACTIVE_ID = null;
var SORT = 'newest';
var SEARCH_Q = '';

function esc(s){return String(s||'').replace(/&/g,'&amp;').replace(/</g,'&lt;').replace(/>/g,'&gt;');}
function tsDate(ts){if(!ts)return ''; return new Date(ts*1000).toLocaleDateString('de-DE',{day:'2-digit',month:'short',year:'2-digit'});}
function tsAgo(ts){
  if(!ts)return '';
  var d=Math.floor((Date.now()/1000)-ts);
  if(d<60)return d+'s ago'; if(d<3600)return Math.floor(d/60)+'m ago';
  if(d<86400)return Math.floor(d/3600)+'h ago';
  if(d<86400*30)return Math.floor(d/86400)+'d ago';
  return Math.floor(d/86400/30)+'mo ago';
}
function toast(msg,t){
  var el=document.createElement('div');el.className='tst'+(t?' '+t:'');el.textContent=msg;
  document.getElementById('toasts').appendChild(el);setTimeout(function(){el.remove();},2700);
}
function valueColor(v){
  if(v>=70)return 'var(--lo)';
  if(v>=40)return 'var(--warn)';
  return 'var(--cr)';
}
function post(url,data){return fetch(url,{method:'POST',headers:{'Content-Type':'application/json'},body:JSON.stringify(data)});}

// ── Load ──────────────────────────────────────────────────────────
function loadAll(){
  Promise.all([
    fetch('/api/containers').then(function(r){return r.json();}),
    fetch('/api/stats').then(function(r){return r.json();}),
  ]).then(function(res){
    CONTAINERS_META = res[0];
    var stats = res[1];
    document.getElementById('s-total').textContent = stats.total;
    document.getElementById('s-avg-val').textContent = stats.avg_value;
    document.getElementById('s-stale').textContent = stats.by_freshness.STALE||0;
    document.getElementById('s-fresh').textContent = stats.by_freshness.FRESH||0;
    document.getElementById('cnt-all').textContent = stats.total+' docs';
    buildSidebar();
    populateContainerSelect();
    loadDocs();
  });
}

function buildSidebar(){
  var list = document.getElementById('ctr-list');
  list.innerHTML='';
  var order=['medical','legal','company','research','tech','prompts','history','personal','finance','operations'];
  order.forEach(function(key){
    var c = CONTAINERS_META[key]; if(!c) return;
    var avgV = c.avg_value||0;
    var vc = valueColor(avgV);
    var badgeCol = {'FAST-DECAY':'var(--cr)','EXTREME-DECAY':'var(--cr)','CRITICAL-DECAY':'var(--cr)',
      'SLOW-DECAY':'var(--lo)','STABLE':'var(--lo)','ANTI-DECAY':'var(--c-his)',
      'CITATION-CURVE':'var(--c-res)','TIERED-DECAY':'var(--c-com)',
      'MODERATE-DECAY':'var(--warn)','DRIFT-DECAY':'var(--warn)','VERSIONED-DECAY':'var(--warn)'}[c.badge]||'var(--sub)';
    var item = document.createElement('div');
    item.className='ctr-item'+(ACTIVE_CTR==key?' active':'');
    item.dataset.ctr=key;
    item.innerHTML=
      '<div class="ctr-icon">'+c.icon+'</div>'
      +'<div class="ctr-info">'
        +'<div class="ctr-name">'+esc(c.label)+'</div>'
        +'<div class="ctr-meta">'
          +'<span class="ctr-count">'+c.count+' docs</span>'
          +'<span class="ctr-badge" style="background:'+badgeCol+'18;color:'+badgeCol+';border-color:'+badgeCol+'30">'+c.badge+'</span>'
        +'</div>'
      +'</div>'
      +'<span class="ctr-value" style="color:'+vc+'">'+avgV+'</span>';
    item.addEventListener('click',function(){selectContainer(key);});
    list.appendChild(item);
  });
}

function selectContainer(key){
  ACTIVE_CTR=key; ACTIVE_FOLDER='';
  document.querySelectorAll('.ctr-item,.folder-item').forEach(function(el){
    el.classList.toggle('active',el.dataset.ctr==key||el.dataset.folder==key);
  });
  document.getElementById('ctr-all').classList.toggle('active',!key);
  // Show folders
  var flist=document.getElementById('folder-list');
  var fitems=document.getElementById('folder-items');
  var cfg=CONTAINERS_META[key];
  if(cfg&&cfg.folders&&cfg.folders.length){
    document.getElementById('folder-label').textContent=(cfg.label||key)+' folders';
    flist.style.display='block';
    fitems.innerHTML='';
    cfg.folders.forEach(function(f){
      var fi=document.createElement('div');
      fi.className='folder-item';fi.dataset.folder=f;
      fi.textContent='/'+f;
      fi.addEventListener('click',function(e){
        e.stopPropagation();
        ACTIVE_FOLDER=f;
        document.querySelectorAll('.folder-item').forEach(function(el){el.classList.toggle('active',el.dataset.folder==f);});
        loadDocs();
      });
      fitems.appendChild(fi);
    });
  } else {
    flist.style.display='none';
  }
  loadDocs();
}

document.getElementById('ctr-all').addEventListener('click',function(){
  ACTIVE_CTR='';ACTIVE_FOLDER='';
  document.querySelectorAll('.ctr-item,.folder-item').forEach(function(el){el.classList.remove('active');});
  document.getElementById('ctr-all').classList.add('active');
  document.getElementById('folder-list').style.display='none';
  loadDocs();
});

function loadDocs(){
  var url='/api/docs?sort='+SORT+'&limit=200'
    +(ACTIVE_CTR?'&container='+ACTIVE_CTR:'')
    +(ACTIVE_FOLDER?'&folder='+ACTIVE_FOLDER:'');
  if(SEARCH_Q) url='/api/docs/search?q='+encodeURIComponent(SEARCH_Q)+'&sort='+SORT
    +(ACTIVE_CTR?'&container='+ACTIVE_CTR:'')+(ACTIVE_FOLDER?'&folder='+ACTIVE_FOLDER:'');
  fetch(url).then(function(r){return r.json();}).then(function(docs){
    ALL_DOCS=docs;renderList();
  });
}

// ── Render list ───────────────────────────────────────────────────
function renderList(){
  var scroll=document.getElementById('list-scroll');
  scroll.innerHTML='';
  if(!ALL_DOCS.length){
    var e=document.createElement('div');
    e.style.cssText='font-size:.6rem;color:var(--dim);text-align:center;padding:2rem;';
    e.textContent='No documents';scroll.appendChild(e);return;
  }
  ALL_DOCS.forEach(function(d){scroll.appendChild(makeCard(d));});
}

function makeCard(d){
  var ctr=CONTAINERS_META[d.container]||{};
  var col=ctr.color||'var(--acc)';
  var val=d._value||0;
  var vc=valueColor(val);
  var fl=d._freshness||'FRESH';
  var card=document.createElement('div');
  card.className='dc'+(ACTIVE_ID==d.id?' active':'');
  card.id='dc-'+d.id;
  card.style.setProperty('--ctr-color',col);
  card.style.borderLeft='3px solid '+col+'55';
  var tags=(d.tags||[]).slice(0,2).map(function(t){return '<span class="dc-tag">'+esc(t)+'</span>';}).join('');
  var valBar='<div class="vg"><div class="vg-bar"><div class="vg-fill" style="width:'+val+'%;background:'+vc+'"></div></div></div>';
  card.innerHTML=
    '<div class="dc-top">'
      +'<div class="dc-title">'+esc(d.title)+'</div>'
      +'<div class="dc-val" style="color:'+vc+'">'+val+'</div>'
    +'</div>'
    +(d.summary?'<div class="dc-preview">'+esc(d.summary)+'</div>':'<div class="dc-preview">'+esc((d.body||'').substring(0,90))+'</div>')
    +'<div class="dc-foot">'
      +'<span class="freshbadge fb-'+fl+'">'+fl+'</span>'
      +tags
      +'<span class="dc-folder">'+esc(d.folder)+'</span>'
      +'<span class="dc-date">'+tsAgo(d.created_at)+'</span>'
    +'</div>';
  card.addEventListener('click',function(){selectDoc(d);});
  return card;
}

// ── Detail ────────────────────────────────────────────────────────
function selectDoc(d){
  ACTIVE_ID=d.id;
  document.querySelectorAll('.dc').forEach(function(c){c.classList.toggle('active',c.id=='dc-'+d.id);});
  // Fetch fresh with access bump
  fetch('/api/docs/'+d.container+'/'+d.folder+'/'+d.id)
  .then(function(r){return r.json();}).then(function(doc){renderDetail(doc);})
  .catch(function(){renderDetail(d);});
}

function renderDetail(d){
  document.getElementById('d-empty').style.display='none';
  var dc=document.getElementById('d-content');dc.style.display='block';
  var ctr=CONTAINERS_META[d.container]||{};
  var col=ctr.color||'var(--acc)';
  var val=d._value||0;
  var vc=valueColor(val);
  var fl=d._freshness||'FRESH';
  var hl=ctr.half_life_days;
  var model=ctr.decay_model||'exponential';
  var tags=(d.tags||[]).map(function(t){return '<span class="d-tag">'+esc(t)+'</span>';}).join('');
  var ageDays=Math.floor((Date.now()/1000-d.created_at)/86400);

  // Value meter
  var modelDesc={
    'stable':'No time decay &mdash; value remains constant.',
    'anti_decay':'Value INCREASES with age (archival pattern).',
    'citation_curve':'Peaks at day '+((ctr.peak_days||30))+', then slow decay.',
    'extreme_decay':'Extreme decay. Half-life: '+(hl||7)+' days.',
    'exponential':'Exponential decay. Half-life: '+(hl||180)+' days.',
    'slow_exponential':'Slow decay. Half-life: '+(hl||730)+' days.',
    'tiered':'Folder-dependent half-life (people 60d, market 14d, sop 365d).',
    'versioned_decay':'Fast versioned decay. Half-life: '+(hl||90)+' days.',
    'drift_decay':'Preference drift decay. Half-life: '+(hl||180)+' days.',
    'operational_decay':'Operational decay. Half-life: '+(hl||180)+' days.',
  }[model]||'Standard decay model.';

  var chips='<div class="decay-chips">'
    +'<div class="decay-chip">age: '+ageDays+'d</div>'
    +(hl?'<div class="decay-chip">half-life: '+hl+'d</div>':'')
    +'<div class="decay-chip">model: '+esc(model)+'</div>'
    +'<div class="decay-chip">accessed: '+(d.access_count||0)+'x</div>'
    +(d.version?'<div class="decay-chip">ver: '+esc(d.version)+'</div>':'')
    +'</div>';

  dc.innerHTML=
    '<div class="d-ctr-hdr">'
      +'<div class="d-ctr-icon">'+ctr.icon+'</div>'
      +'<div class="d-ctr-info">'
        +'<div class="d-ctr-label" style="color:'+col+'">'+esc(ctr.label||d.container)+'</div>'
        +'<div class="d-ctr-note">'+esc(ctr.note||'')+'</div>'
      +'</div>'
      +'<span class="freshbadge fb-'+fl+'">'+fl+'</span>'
    +'</div>'
    +'<div class="value-meter">'
      +'<div><div class="vm-score" style="color:'+vc+'">'+val+'</div><div class="vm-label">value score</div></div>'
      +'<div class="vm-info">'
        +'<div class="vm-model">'+modelDesc+'</div>'
        +'<div class="vm-bar-wrap"><div class="vm-bar-fill" style="width:'+val+'%;background:'+vc+'"></div></div>'
        +'<div class="vm-meta"><span>0 (worthless)</span><span>50 (relevant)</span><span>100 (critical)</span></div>'
        +chips
      +'</div>'
    +'</div>'
    +'<div id="d-title">'+esc(d.title)+'</div>'
    +'<div id="d-body">'+esc(d.body||'')+'</div>'
    +(tags?'<div class="d-tags">'+tags+'</div>':'')
    +'<div class="d-meta-grid">'
      +'<div><div class="dml">Author</div><div class="dmv">'+(d.author||'&mdash;')+'</div></div>'
      +'<div><div class="dml">Folder</div><div class="dmv">'+esc(d.folder)+'</div></div>'
      +'<div><div class="dml">Importance</div><div class="dmv">'+d.importance+'/10</div></div>'
      +'<div><div class="dml">Created</div><div class="dmv">'+tsDate(d.created_at)+'</div></div>'
      +'<div><div class="dml">Updated</div><div class="dmv">'+tsDate(d.updated_at)+'</div></div>'
      +'<div><div class="dml">Source</div><div class="dmv">'+(d.source||'&mdash;')+'</div></div>'
    +'</div>'
    +'<div class="d-acts">'
      +'<button class="d-btn acc" id="d-edit">&#9998; Edit</button>'
      +'<button class="d-btn danger" id="d-del">&#128465; Delete</button>'
    +'</div>';
  document.getElementById('d-edit').addEventListener('click',function(){openModal(d);});
  document.getElementById('d-del').addEventListener('click',function(){deleteDoc(d);});
}

function deleteDoc(d){
  if(!confirm('Delete "'+d.title+'"?'))return;
  fetch('/api/docs/'+d.container+'/'+d.folder+'/'+d.id,{method:'DELETE'}).then(function(){
    toast('Deleted','ok');ACTIVE_ID=null;
    document.getElementById('d-empty').style.display='flex';
    document.getElementById('d-content').style.display='none';
    loadAll();
  });
}

// ── Search / sort ─────────────────────────────────────────────────
document.getElementById('search-btn').addEventListener('click',function(){
  SEARCH_Q=document.getElementById('search-inp').value.trim();loadDocs();});
document.getElementById('search-inp').addEventListener('keydown',function(e){
  if(e.key=='Enter'){SEARCH_Q=this.value.trim();loadDocs();}
  if(e.key=='Escape'){this.value='';SEARCH_Q='';loadDocs();}
});
document.getElementById('sort-sel').addEventListener('change',function(){SORT=this.value;loadDocs();});

// ── Modal ─────────────────────────────────────────────────────────
function populateContainerSelect(){
  var sel=document.getElementById('m-container');
  sel.innerHTML='';
  var order=['medical','legal','company','research','tech','prompts','history','personal','finance','operations'];
  order.forEach(function(k){
    var c=CONTAINERS_META[k]||{};
    var o=document.createElement('option');o.value=k;o.textContent=c.label||k;sel.appendChild(o);
  });
  updateFolderSelect();
  updateDecayPreview();
}

function updateFolderSelect(){
  var ctr=document.getElementById('m-container').value;
  var c=CONTAINERS_META[ctr]||{};
  var sel=document.getElementById('m-folder');
  sel.innerHTML='';
  (c.folders||['general']).forEach(function(f){
    var o=document.createElement('option');o.value=f;o.textContent=f;sel.appendChild(o);
  });
}

function updateDecayPreview(){
  var ctr=document.getElementById('m-container').value;
  var c=CONTAINERS_META[ctr]||{};
  var model=c.decay_model||'exponential';
  var hl=c.half_life_days;
  var warn=c.warn_after_days;
  var msgs={
    'stable':'<strong>STABLE</strong> &mdash; Value does not decay over time. Great for reference prompts and fixed facts.',
    'anti_decay':'<strong>ANTI-DECAY</strong> &mdash; Value INCREASES over time. Historical records become more valuable as context.',
    'citation_curve':'<strong>CITATION CURVE</strong> &mdash; Peaks at day '+(c.peak_days||30)+', then slow exponential decay (HL: '+hl+'d). Like academic papers.',
    'extreme_decay':'<strong>EXTREME DECAY</strong> &mdash; Half-life '+(hl||7)+' days. Market data is near-worthless after a week.',
    'tiered':'<strong>TIERED</strong> &mdash; Half-life depends on folder: market=14d, people=60d, projects=90d, sop=365d.',
    'versioned_decay':'<strong>VERSIONED DECAY</strong> &mdash; Half-life '+(hl||90)+' days. Tag with version number to track relevance.',
    'exponential':'<strong>EXPONENTIAL</strong> &mdash; Standard decay. Half-life '+(hl||180)+' days. Warning after '+(warn||90)+' days.',
    'slow_exponential':'<strong>SLOW DECAY</strong> &mdash; Half-life '+(hl||730)+' days. Laws change slowly.',
    'drift_decay':'<strong>DRIFT DECAY</strong> &mdash; Preferences drift. Half-life '+(hl||180)+' days.',
    'operational_decay':'<strong>OPERATIONAL</strong> &mdash; Runbooks age with infra. Half-life '+(hl||180)+' days. Keep versioned.',
  };
  document.getElementById('decay-preview').innerHTML=
    (msgs[model]||'Standard decay model.')
    +'<br><span style="color:var(--acc)">Container: '+esc(c.label||ctr)+'</span> &mdash; '
    +esc(c.note||'');
}

document.getElementById('m-container').addEventListener('change',function(){updateFolderSelect();updateDecayPreview();});

function openModal(doc){
  document.getElementById('mdl-title').textContent=doc?'EDIT DOCUMENT':'NEW KNOWLEDGE DOCUMENT';
  if(doc){
    document.getElementById('m-container').value=doc.container;
    updateFolderSelect();
    document.getElementById('m-folder').value=doc.folder;
    document.getElementById('m-title').value=doc.title;
    document.getElementById('m-body').value=doc.body||'';
    document.getElementById('m-summary').value=doc.summary||'';
    document.getElementById('m-author').value=doc.author||'';
    document.getElementById('m-version').value=doc.version||'';
    document.getElementById('m-importance').value=doc.importance||5;
    document.getElementById('m-tags').value=(doc.tags||[]).join(', ');
    document.getElementById('btn-save').dataset.editId=doc.container+'|'+doc.folder+'|'+doc.id;
  } else {
    document.getElementById('btn-save').dataset.editId='';
    ['m-title','m-body','m-summary','m-author','m-version','m-tags'].forEach(function(id){
      document.getElementById(id).value='';});
    document.getElementById('m-importance').value='5';
  }
  updateDecayPreview();
  document.getElementById('modal').classList.add('open');
  setTimeout(function(){document.getElementById('m-title').focus();},80);
}
function closeModal(){document.getElementById('modal').classList.remove('open');}

document.getElementById('btn-new').addEventListener('click',function(){openModal();});
document.getElementById('mdl-close').addEventListener('click',closeModal);
document.getElementById('btn-mcancel').addEventListener('click',closeModal);
document.getElementById('modal').addEventListener('click',function(e){if(e.target===this)closeModal();});

document.getElementById('btn-save').addEventListener('click',function(){
  var title=document.getElementById('m-title').value.trim();
  var body=document.getElementById('m-body').value.trim();
  if(!title){document.getElementById('m-title').focus();toast('Title required','err');return;}
  if(!body){document.getElementById('m-body').focus();toast('Body required','err');return;}
  var tags=document.getElementById('m-tags').value.split(',').map(function(t){return t.trim();}).filter(Boolean);
  var pay={
    container:document.getElementById('m-container').value,
    folder:document.getElementById('m-folder').value,
    title:title,body:body,
    summary:document.getElementById('m-summary').value.trim(),
    author:document.getElementById('m-author').value.trim(),
    version:document.getElementById('m-version').value.trim(),
    importance:parseInt(document.getElementById('m-importance').value)||5,
    tags:tags
  };
  var editKey=this.dataset.editId;
  if(editKey){
    var parts=editKey.split('|');
    fetch('/api/docs/'+parts[0]+'/'+parts[1]+'/'+parts[2],
      {method:'PATCH',headers:{'Content-Type':'application/json'},body:JSON.stringify(pay)})
    .then(function(r){return r.json();}).then(function(d){
      toast('Updated','ok');closeModal();loadAll();
      setTimeout(function(){if(d.doc)renderDetail(d.doc);},300);
    }).catch(function(e){toast('Error: '+e.message,'err');});
  } else {
    post('/api/docs',pay).then(function(r){return r.json();}).then(function(d){
      toast('Saved to '+pay.container+'/'+pay.folder,'ok');closeModal();loadAll();
    }).catch(function(e){toast('Error: '+e.message,'err');});
  }
});

document.addEventListener('keydown',function(e){
  if(e.key==='Escape')closeModal();
  var a=document.activeElement;
  var typing=a&&(a.tagName==='INPUT'||a.tagName==='TEXTAREA'||a.tagName==='SELECT');
  if(e.key==='n'&&!typing&&!e.ctrlKey&&!e.metaKey)openModal();
  if((e.ctrlKey||e.metaKey)&&e.key==='Enter'&&document.getElementById('modal').classList.contains('open'))
    document.getElementById('btn-save').click();
  if(e.key==='/'&&!typing){e.preventDefault();document.getElementById('search-inp').focus();}
});

loadAll();
</script>
</body>
</html>"""