Initial portal commit: landing + 9 AI-powered apps

Apps:
- dwg-rooms: extract room numbers from DWG/DXF
- dwg-counting: count symbols in PDF drawings (OpenCV template matching)
- contract-check: review PDF contracts against a checklist (Claude vision + Tesseract OCR fallback)
- email-drafter: bullet notes → polished Czech/English business emails
- invoice-extractor: PDF/image invoice → structured data → Excel
- translator: Czech-first translator across 19 languages with tone control
- vv-check: find inconsistent unit prices across VV sheets in one workbook
- vv-compare: diff original vs new VV files (changes / added / removed)
- feature-request: portal users submit ideas + sample files

Infrastructure:
- LiteLLM gateway with per-app virtual keys + budgets
- Langfuse observability
- Geist font, shared theme, cross-subdomain back link + theme sync via cookie/URL
- Caddy reverse proxy on *.klas.chat

dwg-rooms/main.py

@@ -0,0 +1,143 @@
+"""FastAPI app: upload DWG/DXF → extract rooms → export Excel."""
+import json
+import logging
+import os
+import subprocess
+import uuid
+from pathlib import Path
+
+from fastapi import FastAPI, File, Form, HTTPException, UploadFile
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import FileResponse
+from fastapi.staticfiles import StaticFiles
+
+from excel_export import export_to_excel
+from extractor import DEFAULT_EXAMPLES, extract_rooms
+from llm_helper import enhance_with_llm
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+app = FastAPI(title="DWG Room Extractor")
+app.add_middleware(CORSMiddleware, allow_origins=["*"], allow_methods=["*"], allow_headers=["*"])
+
+WORK_DIR = Path(os.getenv("WORK_DIR", "/tmp/dwg-rooms"))
+WORK_DIR.mkdir(parents=True, exist_ok=True)
+
+jobs: dict[str, dict] = {}
+
+
+def _dwg_to_dxf(dwg_path: Path, out_dir: Path) -> Path:
+    """Convert DWG → DXF using LibreDWG dwgread. Returns DXF path."""
+    dxf_path = out_dir / f"{dwg_path.stem}.dxf"
+    r = subprocess.run(
+        ["dwgread", "-O", "DXF", "-o", str(dxf_path), str(dwg_path)],
+        capture_output=True,
+        text=True,
+        timeout=120,
+    )
+    if not dxf_path.exists():
+        raise RuntimeError(
+            f"DWG conversion failed (exit {r.returncode}): {r.stderr or r.stdout or 'no output'}"
+        )
+    return dxf_path
+
+
+@app.get("/")
+async def root():
+    return FileResponse("static/index.html")
+
+
+@app.get("/api/defaults")
+async def defaults():
+    return {"examples": DEFAULT_EXAMPLES}
+
+
+@app.post("/api/upload")
+async def upload(
+    file: UploadFile = File(...),
+    examples: str = Form(default=""),  # JSON array of strings
+):
+    suffix = Path(file.filename or "input.dxf").suffix.lower()
+    if suffix not in (".dwg", ".dxf"):
+        raise HTTPException(400, "Supported formats: .dwg, .dxf")
+
+    try:
+        ex_list = json.loads(examples) if examples else None
+        if ex_list is not None and not isinstance(ex_list, list):
+            ex_list = None
+    except json.JSONDecodeError:
+        ex_list = None
+
+    job_id = str(uuid.uuid4())
+    job_dir = WORK_DIR / job_id
+    job_dir.mkdir()
+
+    input_path = job_dir / f"input{suffix}"
+    content = await file.read()
+    input_path.write_bytes(content)
+    logger.info("Job %s: %s (%d bytes), examples=%r", job_id, file.filename, len(content), ex_list)
+
+    steps: list[str] = []
+
+    try:
+        if suffix == ".dwg":
+            steps.append("Konverze DWG → DXF")
+            dxf_path = _dwg_to_dxf(input_path, job_dir)
+        else:
+            dxf_path = input_path
+
+        steps.append("Extrakce místností (pravidla)")
+        rooms, unmatched = extract_rooms(str(dxf_path), examples=ex_list)
+        logger.info("Job %s: %d rooms, %d unmatched texts", job_id, len(rooms), len(unmatched))
+
+        if unmatched and os.getenv("LITELLM_API_KEY", ""):
+            steps.append("AI rozšíření")
+            llm_rooms = await enhance_with_llm(unmatched)
+            logger.info("Job %s: LLM added %d rooms", job_id, len(llm_rooms))
+            rooms.extend(llm_rooms)
+
+        jobs[job_id] = {"filename": file.filename, "rooms": rooms}
+        return {"job_id": job_id, "room_count": len(rooms), "steps": steps}
+
+    except Exception as exc:
+        logger.error("Job %s failed: %s", job_id, exc)
+        raise HTTPException(500, str(exc))
+
+
+@app.get("/api/rooms/{job_id}")
+async def get_rooms(job_id: str):
+    if job_id not in jobs:
+        raise HTTPException(404, "Not found")
+    return jobs[job_id]["rooms"]
+
+
+@app.put("/api/rooms/{job_id}")
+async def update_rooms(job_id: str, rooms: list[dict]):
+    if job_id not in jobs:
+        raise HTTPException(404, "Not found")
+    jobs[job_id]["rooms"] = rooms
+    return {"ok": True, "count": len(rooms)}
+
+
+@app.get("/api/export/{job_id}")
+async def export(job_id: str):
+    if job_id not in jobs:
+        raise HTTPException(404, "Not found")
+    job = jobs[job_id]
+    excel_path = WORK_DIR / job_id / "rooms.xlsx"
+    export_to_excel(job["rooms"], str(excel_path))
+    stem = Path(job["filename"]).stem
+    return FileResponse(
+        str(excel_path),
+        media_type="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
+        filename=f"mistnosti_{stem}.xlsx",
+    )
+
+
+@app.get("/health")
+async def health():
+    return {"status": "ok"}
+
+
+app.mount("/static", StaticFiles(directory="static"), name="static")