from __future__ import annotations

import base64
import json
import os
import inspect
from pathlib import Path
from typing import Any

import gradio as gr

from src.board_export import create_board_artifacts
from src.cad_parser import candidate_to_selection, parse_dxf
from src.climate import fetch_climate_bundle
from src.diagrams import create_diagrams
from src.earth_reference import build_earth_reference
from src.evidence import evidence_to_html_table, make_evidence, reset_evidence_counter
from src.export import write_markdown_export
from src.geocoding import reverse_geocode_site
from src.geojson_parser import parse_geojson_file
from src.geometry import normalize_map_state, selection_from_lat_lon
from src.kml_parser import parse_kml_file
from src.location import extract_coordinates_from_text
from src.models import BoundaryCandidate, ReportBundle, SiteSelection
from src.osm_context import fetch_osm_context
from src.report import build_board_bundle, build_markdown_report
from src.sample_data import apply_chorwad_sample_fallbacks
from src.small_model_assistant import build_assistant_brief
from src.soil import fetch_soil
from src.sun import summarize_sun_wind
from src.topography import fetch_topography
from src.upload_limits import (
    MAX_BOARD_PREVIEW_MB,
    MAX_DXF_MB,
    MAX_GEOJSON_MB,
    MAX_KML_MB,
    MAX_PDF_REFERENCE_MB,
    validate_upload,
)


ROOT = Path(__file__).parent
ASSETS = ROOT / "assets"


def read_asset(name: str) -> str:
    path = ASSETS / name
    return path.read_text(encoding="utf-8") if path.exists() else ""


def image_preview_html(path: str | None) -> str:
    if not path:
        return """
        <div class="board-preview-empty board-preview-waiting">
          <div class="empty-board-grid">
            <div class="empty-board-title">
              <span>Waiting for selected land</span>
              <b>Presentation board will appear here</b>
              <small>Draw a site boundary, drop a pin radius, or upload CAD/KML/GeoJSON. Optional project fields can stay blank.</small>
            </div>
            <div class="empty-board-card"><b>01</b><span>Boundary metrics</span></div>
            <div class="empty-board-card"><b>02</b><span>Climate + sun/wind</span></div>
            <div class="empty-board-card"><b>03</b><span>OSM context</span></div>
            <div class="empty-board-card"><b>04</b><span>Terrain + soil caution</span></div>
            <div class="empty-board-card"><b>05</b><span>Site-visit checklist</span></div>
            <div class="empty-board-card"><b>06</b><span>Evidence table</span></div>
          </div>
        </div>
        """
    try:
        source = validate_upload(
            path,
            allowed_suffixes={".png"},
            max_mb=MAX_BOARD_PREVIEW_MB,
            label="Presentation board preview",
        )
        data = base64.b64encode(source.read_bytes()).decode("ascii")
    except Exception as exc:  # noqa: BLE001
        return f"<div class='board-preview-empty'>Board preview unavailable: {type(exc).__name__}: {exc}</div>"
    return (
        "<div class='board-preview-frame'>"
        "<img alt='Generated site-analysis presentation board' "
        f"src='data:image/png;base64,{data}' />"
        "</div>"
    )


def gradio_js_callback(script: str) -> str:
    return "() => {\n" + script + "\n}"


MAP_HTML = """
<div id="sis-map-shell">
  <div class="map-topbar">
    <div>
      <strong>Boundary Desk</strong>
      <span>Trace a site, drop a radius pin, or anchor uploaded CAD/KML/GeoJSON before generating the board pack.</span>
    </div>
    <div class="map-confidence">Approximate trace</div>
  </div>
  <div class="map-controls">
    <button type="button" id="mode-pin">Pin radius</button>
    <button type="button" id="mode-polygon">Polygon</button>
    <button type="button" id="mode-rectangle">Rect</button>
    <button type="button" id="finish-shape">Finish</button>
    <button type="button" id="undo-point">Undo</button>
    <button type="button" id="clear-map">Clear</button>
    <label>Radius
      <select id="radius-select">
        <option value="50">50 m</option>
        <option value="100">100 m</option>
        <option value="250" selected>250 m</option>
        <option value="500">500 m</option>
        <option value="1000">1 km</option>
      </select>
    </label>
  </div>
  <div id="site-map"></div>
  <div id="map-status">Map loading. Drawn boundaries are approximate; upload CAD/KML/GeoJSON for better accuracy.</div>
</div>
"""

DELIVERABLES_HTML = """
<div class="deliverables-strip">
  <div><b>Board PNG/PDF</b><span>sheet-style artifact</span></div>
  <div><b>6 diagrams</b><span>climate, context, edge, matrix</span></div>
  <div><b>Evidence</b><span>source / limit / verification</span></div>
  <div><b>Report</b><span>editable workbook text</span></div>
</div>
"""

SAMPLE_MAP_STATE = json.dumps(
    {
        "mode": "polygon",
        "geometry": {
            "type": "Polygon",
            "coordinates": [
                [
                    [70.24495, 21.00195],
                    [70.24605, 21.00210],
                    [70.24578, 21.00302],
                    [70.24470, 21.00286],
                    [70.24495, 21.00195],
                ]
            ],
        },
    }
)


def load_sample_site():
    return (
        "Chorwad Coastal Thesis Sample",
        "Chorwad site - sample boundary",
        "Architecture thesis / resort concept",
        "Sample drawn boundary; replace with faculty CAD, KML/KMZ, GeoJSON, or real site survey for actual work.",
        "21.00245, 70.24550",
        (
            "Use as validation notes only: check fishing/tourism activity, seasonal visitor movement, local material language, "
            "coastal humidity, service access, and public/private edge conditions during site visit."
        ),
        (
            "Before treating the sample as a real submission, compare with Google Earth/KML or faculty CAD. Manually mark visible trees, "
            "water edge, road approach, surrounding structures, open ground, drainage signs, and any construction activity."
        ),
        SAMPLE_MAP_STATE,
    )

def build_head_html() -> str:
    shell_css = """
    <style>
      html, body {
        margin: 0 !important;
        width: 100% !important;
        max-width: 100vw !important;
        overflow-x: hidden !important;
        background: #e9eef0 !important;
      }
      gradio-app {
        display: block !important;
        width: 100% !important;
        max-width: 100vw !important;
        background: #e9eef0 !important;
      }
      @media (max-width: 920px) {
        html, body, gradio-app {
          min-width: 0 !important;
          width: 100vw !important;
          max-width: 100vw !important;
        }
      }
    </style>
    """
    leaflet_css = read_asset("leaflet.css")
    leaflet_js = read_asset("leaflet.js")
    if leaflet_css and leaflet_js:
        return f"{shell_css}\n<style>{leaflet_css}</style>\n<script>{leaflet_js}</script>"
    return shell_css + """
    <link rel="stylesheet" href="https://unpkg.com/leaflet@1.9.4/dist/leaflet.css"
     integrity="sha256-p4NxAoJBhIIN+hmNHrzRCf9tD/miZyoHS5obTRR9BMY=" crossorigin=""/>
    <script src="https://unpkg.com/leaflet@1.9.4/dist/leaflet.js"
     integrity="sha256-20nQCchB9co0qIjJZRGuk2/Z9VM+kNiyxNV1lvTlZBo=" crossorigin=""></script>
    """


HEAD_HTML = build_head_html()


def parse_dxf_candidates(dxf_file: Any):
    if not dxf_file:
        return gr.update(choices=[], value=None), "Upload a DXF to inspect boundary candidates.", None
    try:
        path = validate_upload(
            _file_path(dxf_file),
            allowed_suffixes={".dxf"},
            max_mb=MAX_DXF_MB,
            label="DXF",
        )
        parsed = parse_dxf(path)
        candidates: list[BoundaryCandidate] = parsed["boundary_candidates"]  # type: ignore[assignment]
        choices = [(f"{c.id} | {c.layer_name} | {c.area_sqm:,.1f} sqm | {c.vertex_count} vertices", c.id) for c in candidates]
        context = parsed.get("context_layers", {})
        layers = parsed.get("layers", [])
        summary = [
            f"**DXF:** `{path.name}`",
            f"**Detected unit:** {parsed.get('unit')}",
            f"**Layers found:** {len(layers)}",
            f"**Boundary candidates:** {len(candidates)}",
        ]
        if context:
            summary.append("**Context layers:** " + ", ".join(f"{k}: {v}" for k, v in context.items()))
        if not candidates:
            summary.append("No boundary candidate was found. Try drawing the boundary or exporting a simpler DXF with a site boundary layer.")
        return gr.update(choices=choices, value=choices[0][1] if choices else None), "\n\n".join(summary), parsed
    except Exception as exc:  # noqa: BLE001
        return gr.update(choices=[], value=None), f"DXF parse failed: {type(exc).__name__}: {exc}", None


def generate_site_analysis(
    project_name: str,
    site_name: str,
    project_type: str,
    boundary_source: str,
    culture_notes: str,
    earth_observation_notes: str,
    map_state: str,
    manual_location: str,
    dxf_file: Any,
    selected_candidate_id: str,
    dxf_state: dict[str, Any] | None,
    geojson_file: Any,
    kml_file: Any,
    pdf_file: Any,
):
    reset_evidence_counter()
    warnings: list[str] = []
    try:
        selection, setup_evidence, setup_warnings = _build_selection(
            map_state=map_state,
            manual_location=manual_location,
            dxf_file=dxf_file,
            selected_candidate_id=selected_candidate_id,
            dxf_state=dxf_state,
            geojson_file=geojson_file,
            kml_file=kml_file,
        )
        warnings.extend(setup_warnings)
    except Exception as exc:  # noqa: BLE001
        message = f"### Input Needed\n\n{exc}"
        return None, None, None, message, None, None, None, None, None, None, None, "", message, ""

    if pdf_file:
        try:
            validate_upload(
                _file_path(pdf_file),
                allowed_suffixes={".pdf"},
                max_mb=MAX_PDF_REFERENCE_MB,
                label="PDF reference",
            )
        except Exception as exc:  # noqa: BLE001
            warnings.append(f"PDF reference ignored: {type(exc).__name__}: {exc}")
        warnings.append("PDF upload is reference-only in this MVP; geometry is not extracted from PDFs.")

    evidence = list(setup_evidence)
    evidence.append(
        make_evidence(
            category="Soil / ground",
            finding="Soil and foundation are treated as site-visit/professional verification items in this MVP.",
            source_name="Safety rule",
            source_url="",
            source_type="application policy",
            resolution_or_scope="project-wide",
            confidence="high",
            limitation="No geotechnical survey or final foundation recommendation is generated.",
            design_implication="Use only as a prompt to request soil reports or professional input.",
            verification_needed="Obtain geotechnical/professional verification before foundation decisions.",
            output_label="professional_verification_required",
        )
    )
    if culture_notes:
        evidence.append(
            make_evidence(
                category="Region / culture",
                finding="User supplied local/culture/site-observation notes.",
                source_name="User note",
                source_url="",
                source_type="user-provided",
                resolution_or_scope="editable observation",
                confidence="medium",
                limitation="Not independently verified by the app.",
                design_implication="Use as a prompt for site visit and studio discussion.",
                verification_needed="Verify with site visit, local interviews, or faculty-approved sources.",
                output_label="user_input",
            )
        )
    earth_reference, earth_evidence = build_earth_reference(selection, earth_observation_notes or "")
    evidence.extend(earth_evidence)

    lat, lon = selection.anchor_lat, selection.anchor_lon
    climate: dict[str, Any] = {"forecast": None, "recent_historical": None, "climate_normal": None}
    osm_context: dict[str, Any] = {"counts": {}, "features": []}
    topography: dict[str, Any] = {}
    soil: dict[str, Any] = {}
    site_identity: dict[str, Any] | None = None
    sun_summary: dict[str, str] = {
        "orientation_note": "Sun/orientation summary unavailable because no anchor coordinate is available.",
        "east_west_note": "",
        "wind_note": "",
        "limitation": "Provide a real-world anchor coordinate for public-data analysis.",
    }
    if lat is not None and lon is not None:
        site_identity, identity_evidence = reverse_geocode_site(lat, lon)
        evidence.extend(identity_evidence)
        climate, climate_evidence = fetch_climate_bundle(lat, lon)
        evidence.extend(climate_evidence)
        wind_dir = _current_wind_direction(climate)
        sun_summary, sun_evidence = summarize_sun_wind(lat, lon, wind_dir)
        evidence.extend(sun_evidence)
        osm_context, osm_evidence = fetch_osm_context(selection)
        evidence.extend(osm_evidence)
        topography, topography_evidence = fetch_topography(selection)
        evidence.extend(topography_evidence)
        soil, soil_evidence = fetch_soil(selection)
        evidence.extend(soil_evidence)
    else:
        warnings.append("No anchor coordinate was available, so climate, sun, OSM, terrain, and soil public-data layers were skipped.")
    (
        site_identity,
        climate,
        osm_context,
        topography,
        soil,
        sample_evidence,
        sample_warnings,
    ) = apply_chorwad_sample_fallbacks(
        project_name=project_name,
        site_name=site_name,
        boundary_source=boundary_source,
        site_identity=site_identity,
        climate=climate,
        osm_context=osm_context,
        topography=topography,
        soil=soil,
        anchor_lat=selection.anchor_lat,
        anchor_lon=selection.anchor_lon,
    )
    evidence.extend(sample_evidence)
    warnings.extend(sample_warnings)

    (
        project_name,
        site_name,
        project_type,
        boundary_source,
        auto_label_warnings,
    ) = _resolve_project_fields(
        project_name=project_name,
        site_name=site_name,
        project_type=project_type,
        boundary_source=boundary_source,
        selection=selection,
        site_identity=site_identity,
    )
    warnings.extend(auto_label_warnings)

    diagram_paths = create_diagrams(
        selection,
        climate,
        osm_context,
        sun_summary,
        topography=topography,
        soil=soil,
    )
    if len(diagram_paths) < 3:
        warnings.append(
            "One or more diagrams could not be generated; use the Markdown report and evidence table, then retry if needed."
        )
    assistant_md = build_assistant_brief(
        selection=selection,
        evidence_rows=evidence,
        warnings=warnings,
        project_type=project_type,
    )
    bundle = build_board_bundle(
        project_name=project_name,
        site_name=site_name,
        selection=selection,
        climate=climate,
        osm_context=osm_context,
        sun_summary=sun_summary,
        site_identity=site_identity,
        evidence_rows=evidence,
        diagram_paths=diagram_paths,
        topography=topography,
        soil=soil,
        warnings=warnings,
    )
    if boundary_source:
        bundle.board_markdown += f"\n\n### Boundary Source\n\n{boundary_source}\n"
    if culture_notes:
        bundle.board_markdown += f"\n\n### Editable Local / Culture Notes\n\n{culture_notes}\n"
    bundle.board_markdown += "\n\n" + earth_reference["markdown"]
    bundle.board_markdown += "\n\n### Small Model Assistant / Template Brief\n\n" + assistant_md
    report = build_markdown_report(project_name, site_name, selection, bundle)
    export_path = write_markdown_export(report, project_name or site_name or "site-intelligence")
    board_artifacts = create_board_artifacts(
        project_name=project_name,
        site_name=site_name,
        project_type=project_type,
        boundary_source=boundary_source,
        culture_notes=culture_notes,
        selection=selection,
        climate=climate,
        osm_context=osm_context,
        sun_summary=sun_summary,
        site_identity=site_identity,
        evidence_rows=evidence,
        diagram_paths=diagram_paths,
        warnings=warnings,
        topography=topography,
        soil=soil,
    )
    evidence_html = evidence_to_html_table(evidence)
    padded_paths = diagram_paths + [None] * (6 - len(diagram_paths))
    warning_md = "### Warnings / Limits\n\n" + ("\n".join(f"- {w}" for w in warnings) if warnings else "- No additional warnings.")
    return (
        image_preview_html(board_artifacts["png"]),
        board_artifacts["png"],
        board_artifacts["pdf"],
        report,
        export_path,
        padded_paths[0],
        padded_paths[1],
        padded_paths[2],
        padded_paths[3],
        padded_paths[4],
        padded_paths[5],
        evidence_html,
        warning_md,
        assistant_md,
    )


def _build_selection(
    *,
    map_state: str,
    manual_location: str,
    dxf_file: Any,
    selected_candidate_id: str,
    dxf_state: dict[str, Any] | None,
    geojson_file: Any,
    kml_file: Any,
) -> tuple[SiteSelection, list[Any], list[str]]:
    evidence = []
    warnings = []
    anchor = extract_coordinates_from_text(manual_location)

    if dxf_file and selected_candidate_id and dxf_state:
        validate_upload(
            _file_path(dxf_file),
            allowed_suffixes={".dxf"},
            max_mb=MAX_DXF_MB,
            label="DXF",
        )
        candidates: list[BoundaryCandidate] = dxf_state.get("boundary_candidates", [])
        selected = next((c for c in candidates if c.id == selected_candidate_id), None)
        if not selected:
            raise ValueError("Select a DXF boundary candidate before generating.")
        if not anchor:
            anchor = _anchor_from_map_state(map_state)
        if not anchor:
            raise ValueError("CAD/DXF boundaries need an anchor lat/lon or map pin before public data can run.")
        selection = candidate_to_selection(selected, anchor[0], anchor[1])
        evidence.append(
            make_evidence(
                category="Boundary",
                finding=f"DXF boundary candidate `{selected.id}` was selected from layer `{selected.layer_name}`.",
                source_name=selected.source_file,
                source_url="",
                source_type="uploaded DXF",
                resolution_or_scope=f"{selected.unit}; local CAD geometry",
                confidence="medium",
                limitation="CAD may use local coordinates and is not legal/cadastral verification.",
                design_implication="Use for preliminary board area/perimeter and site-form understanding.",
                verification_needed="Confirm with faculty drawing, survey, or official project documents.",
                output_label="cad_derived",
            )
        )
        context = dxf_state.get("context_layers") or {}
        if context:
            evidence.append(
                make_evidence(
                    category="Existing conditions",
                    finding="DXF contains context layers: " + ", ".join(f"{k}: {v}" for k, v in context.items()),
                    source_name=selected.source_file,
                    source_url="",
                    source_type="uploaded DXF",
                    resolution_or_scope="CAD layer names and entity counts",
                    confidence="medium",
                    limitation="Layer names are user/CAD-authored and may be inconsistent.",
                    design_implication="Use layers as prompts for roads, water, vegetation, built-up, and contour checks.",
                    verification_needed="Visually inspect CAD and verify conditions on site.",
                    output_label="cad_derived",
                )
            )
        return selection, evidence, warnings

    if geojson_file:
        geojson_path = validate_upload(
            _file_path(geojson_file),
            allowed_suffixes={".geojson", ".json"},
            max_mb=MAX_GEOJSON_MB,
            label="GeoJSON",
        )
        selection = parse_geojson_file(geojson_path)
        evidence.append(
            make_evidence(
                category="Boundary",
                finding="GeoJSON boundary was uploaded and treated as WGS84 geometry.",
                source_name=geojson_path.name,
                source_url="",
                source_type="uploaded GeoJSON",
                resolution_or_scope="uploaded polygon",
                confidence="high",
                limitation="Boundary is only as reliable as the uploaded GeoJSON source.",
                design_implication="Use for boundary-based first-pass site analysis.",
                verification_needed="Confirm with original source or site survey.",
                output_label="user_input",
            )
        )
        return selection, evidence, warnings

    if kml_file:
        kml_path = validate_upload(
            _file_path(kml_file),
            allowed_suffixes={".kml", ".kmz"},
            max_mb=MAX_KML_MB,
            label="KML/KMZ",
        )
        selection = parse_kml_file(kml_path)
        evidence.append(
            make_evidence(
                category="Boundary",
                finding="KML/KMZ boundary was uploaded and treated as Google Earth / WGS84 geometry.",
                source_name=kml_path.name,
                source_url="",
                source_type="uploaded KML/KMZ",
                resolution_or_scope="uploaded polygon; Google Earth/GIS-style coordinates",
                confidence="medium",
                limitation="Boundary is only as reliable as the exported KML/KMZ source and is not legal/cadastral verification.",
                design_implication="Use for boundary-based first-pass site analysis and board generation.",
                verification_needed="Confirm with faculty CAD, survey, or official project documents.",
                output_label="user_input",
            )
        )
        return selection, evidence, warnings

    try:
        if map_state and map_state.strip() and map_state.strip() != "{}":
            selection = normalize_map_state(map_state)
            evidence.append(
                make_evidence(
                    category="Boundary",
                    finding=f"Map selection was created using `{selection.selection_type}` mode.",
                    source_name="User map input",
                    source_url="",
                    source_type="drawn map / pin",
                    resolution_or_scope=selection.accuracy_label,
                    confidence="low" if selection.selection_type == "pin_radius" else "medium",
                    limitation="Drawn and pin-radius boundaries are approximate.",
                    design_implication="Use for early studio context and verification planning.",
                    verification_needed="Verify with CAD, KML, GeoJSON, faculty drawing, or site survey.",
                    output_label="user_input",
                )
            )
            return selection, evidence, warnings
    except Exception as exc:  # noqa: BLE001
        warnings.append(f"Map selection could not be used: {exc}")

    if anchor:
        selection = selection_from_lat_lon(anchor[0], anchor[1], radius_m=250)
        evidence.append(
            make_evidence(
                category="Boundary",
                finding="Manual coordinate input was converted to pin-radius context analysis.",
                source_name="User coordinate input",
                source_url="",
                source_type="manual lat/lon or parsed URL",
                resolution_or_scope="250 m radius",
                confidence="low",
                limitation="Point-radius mode is not exact boundary analysis.",
                design_implication="Use for neighborhood/context analysis only.",
                verification_needed="Add a drawn or uploaded boundary for plot-level analysis.",
                output_label="user_input",
            )
        )
        return selection, evidence, warnings

    raise ValueError("Draw, pin, upload GeoJSON/DXF, or enter coordinates first.")


def _anchor_from_map_state(map_state: str) -> tuple[float, float] | None:
    try:
        selection = normalize_map_state(map_state)
        if selection.anchor_lat is not None and selection.anchor_lon is not None:
            return selection.anchor_lat, selection.anchor_lon
    except Exception:
        return None
    return None


def _current_wind_direction(climate: dict[str, Any]) -> float | None:
    forecast = climate.get("forecast") or {}
    value = forecast.get("current_wind_direction_deg")
    try:
        return float(value) if value is not None else None
    except (TypeError, ValueError):
        return None


def _resolve_project_fields(
    *,
    project_name: str,
    site_name: str,
    project_type: str,
    boundary_source: str,
    selection: SiteSelection,
    site_identity: dict[str, Any] | None,
) -> tuple[str, str, str, str, list[str]]:
    warnings: list[str] = []
    project = (project_name or "").strip()
    site = (site_name or "").strip()
    ptype = (project_type or "").strip()
    source = (boundary_source or "").strip()

    if not project:
        project = "Preliminary Site Analysis"
        warnings.append("Project name was not provided; the app used a generic title.")
    if not site or site.lower() in {"untitled site", "untitled", "site"}:
        site = _auto_site_name(selection, site_identity)
        warnings.append("Site name was not provided; the app generated a label from the selected area.")
    if not ptype:
        ptype = "Early-stage architecture site analysis"
    if not source:
        source = _auto_boundary_source(selection)
        warnings.append("Boundary source was not provided; the report labels the selection from the input mode.")
    return project, site, ptype, source, warnings


def _auto_site_name(selection: SiteSelection, site_identity: dict[str, Any] | None) -> str:
    if site_identity:
        for key in ("city", "town", "village", "district", "state"):
            value = site_identity.get(key)
            if value:
                return f"{value} selected site"
        display = site_identity.get("display_name")
        if display:
            return f"{str(display).split(',')[0]} selected site"
    if selection.anchor_lat is not None and selection.anchor_lon is not None:
        return f"Selected site {selection.anchor_lat:.5f}, {selection.anchor_lon:.5f}"
    return "Selected site area"


def _auto_boundary_source(selection: SiteSelection) -> str:
    if selection.selection_type in {"drawn_polygon", "rectangle"}:
        return "User-drawn boundary on OpenStreetMap base map; approximate and not legal/cadastral."
    if selection.selection_type == "pin_radius":
        return "User-selected pin and radius; approximate context analysis, not exact boundary."
    if selection.selection_type == "dxf_boundary":
        return "Uploaded DXF boundary candidate selected by user."
    if selection.selection_type == "geojson_boundary":
        return "Uploaded GeoJSON boundary selected by user."
    if selection.selection_type == "kml_boundary":
        return "Uploaded KML/KMZ boundary selected by user."
    return "User-provided site selection."


def _file_path(file_obj: Any) -> str:
    return str(getattr(file_obj, "name", file_obj))


def build_app() -> gr.Blocks:
    map_js = read_asset("map.js")
    map_js_callback = gradio_js_callback(map_js)
    block_kwargs: dict[str, Any] = {"title": "Site Intelligence Studio"}
    block_parameters = inspect.signature(gr.Blocks).parameters
    if "css" in block_parameters:
        block_kwargs["css"] = read_asset("style.css")
    if "head" in block_parameters:
        block_kwargs["head"] = HEAD_HTML
    if "js" in block_parameters:
        block_kwargs["js"] = map_js_callback
    with gr.Blocks(**block_kwargs) as demo:
        gr.HTML(
            """
            <div class="studio-shell">
              <div class="studio-topbar">
                <div>
                  <span class="studio-kicker">Build Small Hackathon / Backyard AI</span>
                  <h1>Site Intelligence Studio</h1>
                </div>
                <div class="studio-meta">
                  <span>Boundary first</span>
                  <span>Open data</span>
                  <span>Field verify</span>
                </div>
              </div>
              <div class="studio-briefing">
                <div>
                  <b>Start with land, not a prompt.</b>
                  <span>Draw a boundary, drop a radius pin, or upload CAD/KML/GeoJSON. The app turns that selection into a sourced site-analysis board pack.</span>
                </div>
                <div>
                  <b>Only the site is required.</b>
                  <span>Project fields are optional. Blank names are auto-labelled from coordinates or approximate address.</span>
                </div>
                <div>
                  <b>Output stays cautious.</b>
                  <span>Climate, terrain, soil, OSM, and AI text are labelled by source, confidence, and verification need.</span>
                </div>
              </div>
              <div class="studio-proof-row">
                <div><b>For students</b><span>faster studio sheets</span></div>
                <div><b>For reviewers</b><span>sources and limits visible</span></div>
                <div><b>For safety</b><span>no final foundation or legal claims</span></div>
                <div><b>For demo</b><span>works from polygon only</span></div>
              </div>
              """ + DELIVERABLES_HTML + """
            </div>
            """
        )
        with gr.Row(elem_classes=["studio-workbench"]):
            with gr.Column(scale=3, elem_classes=["brief-pane"]):
                gr.HTML(
                    """
                    <div class="pane-heading">
                      <span>01</span>
                      <div><b>Site brief</b><small>Optional context for cleaner board copy</small></div>
                    </div>
                    <div class="minimum-card">
                      <b>Minimum input</b>
                      <span>Draw a polygon, draw a rectangle, drop a pin radius, or paste coordinates. Everything else can be blank.</span>
                    </div>
                    """
                )
                with gr.Accordion("Optional labels and manual anchor", open=False, elem_classes=["brief-accordion"]):
                    project_name = gr.Textbox(
                        label="Project name (optional)",
                        placeholder="Auto: Preliminary Site Analysis",
                        info="Leave blank if you only want to draw/select a site and generate analysis.",
                    )
                    site_name = gr.Textbox(
                        label="Site name (optional)",
                        placeholder="Auto-filled from approximate address or coordinates",
                        info="If blank, the app labels the selected polygon/pin from reverse geocoding or coordinates.",
                    )
                    project_type = gr.Textbox(
                        label="Project type (optional)",
                        placeholder="Thesis, resort, housing, institute...",
                    )
                    boundary_source = gr.Textbox(
                        label="Boundary source (optional)",
                        placeholder="Auto-labelled from map draw, pin radius, CAD, KML/KMZ, or GeoJSON",
                    )
                    manual_location = gr.Textbox(
                        label="Lat/lon or Google Maps URL",
                        placeholder="21.002, 70.245 or a Google Maps URL with coordinates",
                        info="Used as fallback input and as CAD anchor. Drawn polygons use their centroid.",
                    )
                    culture_notes = gr.Textbox(
                        label="Editable region / culture / activity notes",
                        lines=4,
                        placeholder="Local activity, user groups, culture, materials, typology, observed movement patterns...",
                        info="This remains user-provided evidence, not AI-invented demographic analysis.",
                    )
            with gr.Column(scale=6, elem_classes=["canvas-pane"]):
                gr.HTML(
                    """
                    <div class="pane-heading canvas-heading">
                      <span>02</span>
                      <div><b>Boundary canvas</b><small>Trace land first. Files and forms are secondary.</small></div>
                    </div>
                    """
                )
                map_generate_btn = gr.Button("Generate from selected site", variant="primary", elem_classes=["map-generate-button"])
                gr.HTML(MAP_HTML)
                map_state = gr.Textbox(label="Map state", elem_id="map_state", lines=4)
                gr.HTML(
                    "<p class='warning-note'><strong>Boundary accuracy:</strong> map tracing is useful for early context only. Upload CAD/DXF, KML, or GeoJSON when available. Public climate and map layers use the selected anchor or centroid, not legal plot data.</p>"
                )
            with gr.Column(scale=3, elem_classes=["source-pane"]):
                gr.HTML(
                    """
                    <div class="pane-heading">
                      <span>03</span>
                      <div><b>Source intake</b><small>Optional files, sample data, and final run</small></div>
                    </div>
                    <div class="source-card">
                      <b>No upload required</b>
                      <span>Uploads improve accuracy, but map selection alone still creates a full preliminary board pack.</span>
                    </div>
                    """
                )
                with gr.Accordion("Optional Google Earth / field notes", open=False, elem_classes=["brief-accordion"]):
                    earth_observation_notes = gr.Textbox(
                        label="Satellite / Google Earth / site-observation notes",
                        lines=4,
                        placeholder="Visible trees, water edge, existing structures, access roads, open ground, slope/drainage signs, construction nearby...",
                        info="Optional. These are user observations and visual-reference notes, not app-verified satellite facts.",
                    )
                sample_btn = gr.Button("Use Chorwad sample site", variant="secondary")
                with gr.Accordion("Boundary and reference uploads", open=False, elem_classes=["upload-panel"]):
                    dxf_file = gr.File(label="DXF upload", file_types=[".dxf"], type="filepath")
                    geojson_file = gr.File(label="GeoJSON upload", file_types=[".geojson", ".json"], type="filepath")
                    kml_file = gr.File(label="Google Earth KML/KMZ upload", file_types=[".kml", ".kmz"], type="filepath")
                    pdf_file = gr.File(label="PDF reference only", file_types=[".pdf"], type="filepath")
                    dxf_candidate = gr.Dropdown(label="DXF boundary candidate", choices=[], interactive=True)
                    dxf_summary = gr.Markdown("Upload a DXF to inspect boundary candidates.")
                gr.HTML(
                    """
                    <div class="run-card">
                      <b>Generated board pack</b>
                      <span>Identity, area/perimeter, address context, climate views, sun/wind, OSM context, terrain/soil caution, diagrams, checklist, evidence, PNG/PDF/Markdown.</span>
                    </div>
                    """
                )
                generate_btn = gr.Button("Generate board pack", variant="primary", elem_classes=["generate-button"])
                dxf_state = gr.State(None)
        gr.HTML(
            """
            <div class="review-header">
              <span>04</span>
              <div>
                <b>Review desk</b>
                <small>Generated sheet material appears here after the boundary run.</small>
              </div>
            </div>
            """
        )
        with gr.Tabs(elem_classes=["review-tabs"]):
            with gr.Tab("Presentation Board"):
                gr.HTML(
                    "<div class='output-intro'><strong>Sheet-ready first pass.</strong><span>This is the main artifact: a 16:9 architecture board. Preview is scaled in the browser; download PNG/PDF for full resolution.</span></div>"
                )
                board_preview = gr.HTML(value=image_preview_html(None))
                with gr.Row():
                    board_png_file = gr.File(label="Download board PNG")
                    board_pdf_file = gr.File(label="Download board PDF")
                warnings_output = gr.Markdown()
            with gr.Tab("Report"):
                gr.HTML(
                    "<div class='output-intro'><strong>Editable report text.</strong><span>Use this for copy, review, and source checking. It is intentionally more verbose than the board.</span></div>"
                )
                board_output = gr.Markdown()
                export_file = gr.File(label="Download Markdown report")
            with gr.Tab("Diagrams"):
                gr.HTML(
                    "<div class='output-intro'><strong>Studio diagram pack.</strong><span>The first row is the core prototype output. The second row is the submission upgrade: edge/access mapping, climate strategy, and a constraints-verification matrix.</span></div>"
                )
                with gr.Row():
                    climate_image = gr.Image(label="Climate diagram", type="filepath")
                    sun_image = gr.Image(label="Sun / wind diagram", type="filepath")
                    context_image = gr.Image(label="Geographic context diagram", type="filepath")
                with gr.Row():
                    access_image = gr.Image(label="Access / edge context", type="filepath")
                    strategy_image = gr.Image(label="Climate strategy sheet", type="filepath")
                    matrix_image = gr.Image(label="Constraints / verification matrix", type="filepath")
            with gr.Tab("Evidence Table"):
                evidence_table = gr.HTML()
            with gr.Tab("Small Model Brief"):
                gr.HTML(
                    "<div class='output-intro'><strong>Bounded AI layer.</strong><span>Uses a <=4B Hugging Face model only when configured; otherwise the deterministic fallback keeps the app usable.</span></div>"
                )
                assistant_output = gr.Markdown()
        dxf_file.change(
            fn=parse_dxf_candidates,
            inputs=dxf_file,
            outputs=[dxf_candidate, dxf_summary, dxf_state],
        )
        sample_btn.click(
            fn=load_sample_site,
            inputs=[],
            outputs=[
                project_name,
                site_name,
                project_type,
                boundary_source,
                manual_location,
                culture_notes,
                earth_observation_notes,
                map_state,
            ],
        )
        analysis_inputs = [
                project_name,
                site_name,
                project_type,
                boundary_source,
                culture_notes,
                earth_observation_notes,
                map_state,
                manual_location,
                dxf_file,
                dxf_candidate,
                dxf_state,
                geojson_file,
                kml_file,
                pdf_file,
            ]
        analysis_outputs = [
                board_preview,
                board_png_file,
                board_pdf_file,
                board_output,
                export_file,
                climate_image,
                sun_image,
                context_image,
                access_image,
                strategy_image,
                matrix_image,
                evidence_table,
                warnings_output,
                assistant_output,
            ]
        generate_btn.click(
            fn=generate_site_analysis,
            inputs=analysis_inputs,
            outputs=analysis_outputs,
        )
        map_generate_btn.click(
            fn=generate_site_analysis,
            inputs=analysis_inputs,
            outputs=analysis_outputs,
        )
        if "js" not in block_parameters:
            demo.load(fn=None, js=map_js_callback)
    return demo


demo = build_app()

if __name__ == "__main__":
    launch_kwargs: dict[str, Any] = {
        "server_name": "0.0.0.0",
        "server_port": int(os.environ.get("PORT", "7860")),
    }
    launch_parameters = inspect.signature(demo.launch).parameters
    if "css" in launch_parameters:
        launch_kwargs["css"] = read_asset("style.css")
    if "head" in launch_parameters:
        launch_kwargs["head"] = HEAD_HTML
    if "js" in launch_parameters:
        launch_kwargs["js"] = gradio_js_callback(read_asset("map.js"))
    if "ssr_mode" in launch_parameters:
        launch_kwargs["ssr_mode"] = False
    demo.launch(**launch_kwargs)