Blame for app.py

"""DiagraMine Streamlit demo.

Upload an architecture diagram → see annotated overlay, structured JSON, and
the relationship graph side-by-side. The point: show that the same upload
returns the same schema every call (the 1.000 schema-valid-JSON-rate story).

Run:  streamlit run app.py
"""
from __future__ import annotations

import io
import json
import os
import tempfile
import time

import cv2
import streamlit as st
from PIL import Image

import ui_theme
from src import pipeline as pl
from src.graph import builder
from src.schemas import PipelineConfig

st.set_page_config(page_title="DiagraMine", page_icon=":triangular_ruler:", layout="wide")

# mark.dev paper ground, Fraunces/Inter/JetBrains Mono, cerulean accent. The
# same base colours are mirrored in .streamlit/config.toml, which is the only
# way to reach widgets CSS cannot touch — change one, change both.
ui_theme.apply_theme()

# App-specific: what the shared theme cannot know about — the result images and
# the JSON panel, which need to sit on a card rather than float on the paper
# ground, and the status banners (the schema-valid badge is one). Tokens come
# from ui_theme's :root block.
st.markdown(
    """
<style>
[data-testid="stImage"] img, [data-testid="stImageContainer"] img {
  background: var(--card); border: 1px solid var(--line);
  border-radius: 14px; box-shadow: var(--shadow-sm); }
[data-testid="stImageCaption"], [data-testid="stCaptionContainer"] p {
  font-family: 'Inter', -apple-system, 'Segoe UI', sans-serif;
  font-size: .8rem; color: var(--ink-3); }
[data-testid="stJson"] { background: var(--card); border: 1px solid var(--line);
  border-radius: 12px; padding: .5rem .75rem; box-shadow: var(--shadow-sm); }
[data-testid="stSidebar"] h2 { font-size: 1.05rem; }

/* status alerts: the portfolio's ok / warn / bad / info, always on their tint.
   Streamlit paints the tint on the outer container; the kind is only named on
   an inner child, hence :has(). */
[data-testid="stAlertContainer"] { border: 1px solid transparent; }
[data-testid="stAlertContainer"]:has([data-testid="stAlertContentInfo"]) {
  background-color: rgba(47, 95, 138, .09); border-color: rgba(47, 95, 138, .22); color: #2f5f8a; }
[data-testid="stAlertContainer"]:has([data-testid="stAlertContentSuccess"]) {
  background-color: rgba(63, 122, 58, .10); border-color: rgba(63, 122, 58, .25); color: #3f7a3a; }
[data-testid="stAlertContainer"]:has([data-testid="stAlertContentWarning"]) {
  background-color: rgba(168, 106, 18, .10); border-color: rgba(168, 106, 18, .25); color: #a86a12; }
[data-testid="stAlertContainer"]:has([data-testid="stAlertContentError"]) {
  background-color: rgba(179, 38, 30, .08); border-color: rgba(179, 38, 30, .22); color: #b3261e; }
[data-testid="stAlertContainer"] p, [data-testid="stAlertContainer"] li { color: inherit; }
</style>
""",
    unsafe_allow_html=True,
)

st.title("DiagraMine — Diagram Structure Extraction")
st.caption(
    "Upload an architecture diagram. The pipeline returns schema-valid JSON, "
    "an annotated overlay, and a data-driven relationship graph. Compared to "
    "vision LLMs (which return strict-parseable JSON ~13% of the time under "
    "structured prompting), DiagraMine returns it 100% of the time by "
    "construction — every output field is a typed Pydantic model."
)

# ── Sidebar config ───────────────────────────────────────────────────────────
st.sidebar.header("Pipeline configuration")
# "none" skips that stage entirely; it contributes an empty list to the result.
text_detector = st.sidebar.selectbox("Text detector", ["paddleocr", "easyocr", "none"], index=0)
box_detector = st.sidebar.selectbox("Box detector", ["canny_contours", "hough", "yolo", "none"], index=0)
arrow_detector = st.sidebar.selectbox(
    "Arrow detector", ["directed_lines", "hough_lines", "pixel_scan", "cnn", "none"], index=0)
icon_detector = st.sidebar.selectbox("Icon detector", ["template_matching", "clip", "hsv", "none"], index=0)
outside_box_gate = st.sidebar.checkbox(
    "Outside-box gate (Day-3 fix)", value=False,
    help="Rejects arrow segments whose midpoint sits inside a box (border artifacts). "
         "Calibrated for hough_lines; off by default because with directed_lines "
         "it costs ~0.10 rel-F1.",
)
graph_layout = st.sidebar.selectbox("Graph layout", ["kamada_kawai", "spring"], index=0)
st.sidebar.markdown(
    "**Default config** — PaddleOCR + Canny+contours + directed lines + template-matching, "
    "the Phase-2 leaderboard champions. Pick **none** to skip a stage."
)

# ── Upload ───────────────────────────────────────────────────────────────────
# Sample diagrams from the eval sets, so the demo works without a file of your
# own. Only the ones present are offered (a deployment may ship a subset).
_HERE = os.path.dirname(os.path.abspath(__file__))
SAMPLES = {
    label: path for label, path in {
        "Real draw.io export (search architecture)": "search_interview_test.png",
        "Synthetic: microservices with API gateway": "data/eval/diagrams_15/diagram_02.png",
        "draw.io style: Kubernetes microservices": "data/eval/drawio_style/diagrams/drawio_03.png",
    }.items() if os.path.isfile(os.path.join(_HERE, path))
}

uploaded = st.file_uploader(
    "Upload an architecture diagram (PNG, JPG, WebP)",
    type=["png", "jpg", "jpeg", "webp"],
)
sample = None
if uploaded is None and SAMPLES:
    sample = st.selectbox("…or try a sample diagram", ["—"] + list(SAMPLES), index=0)
    if sample == "—":
        sample = None

if uploaded is None and sample is None:
    st.info("Upload a diagram, or pick a sample above, to run the pipeline.")
    st.stop()

# Save the image to a temp file for the pipeline.
if uploaded is not None:
    name, data = uploaded.name, uploaded.read()
else:
    name = os.path.basename(SAMPLES[sample])
    with open(os.path.join(_HERE, SAMPLES[sample]), "rb") as f:
        data = f.read()
suffix = os.path.splitext(name)[1] or ".png"
with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as tmp:
    tmp.write(data)
    tmp_path = tmp.name
if sample is not None:
    st.image(data, caption=sample, width=480)

config = PipelineConfig(
    text_detector=text_detector, box_detector=box_detector,
    arrow_detector=arrow_detector, icon_detector=icon_detector,
    outside_box_gate=outside_box_gate, graph_layout=graph_layout,
)

with st.spinner("Extracting structure (OCR model weights download on first run)..."):
    t0 = time.perf_counter()
    result = pl.extract(tmp_path, config)
    annotated = pl.annotate(tmp_path, result)
    rt_total = time.perf_counter() - t0

# Render the relationship graph to a temp PNG.
graph_path = os.path.join(tempfile.gettempdir(), f"diagramine_graph_{os.getpid()}.png")
graph_ok = builder.draw_graph(
    [r.model_dump() for r in result.relationships], graph_path, layout=graph_layout
)

# ── Metrics row ──────────────────────────────────────────────────────────────
c1, c2, c3, c4, c5 = st.columns(5)
c1.metric("Texts", len(result.texts))
c2.metric("Boxes", len(result.boxes))
c3.metric("Arrows", len(result.arrows))
c4.metric("Relationships", len(result.relationships))
c5.metric("Runtime", f"{rt_total:.2f}s")

# Schema-valid badge — the headline reliability claim.
st.success(
    f"Schema-valid JSON: ✓ (every field validated by Pydantic v2). "
    f"`result.model_dump()` round-trips through `json.dumps` without loss."
)
# A stage that fails returns an empty list (that is what keeps the JSON valid),
# so say which one failed rather than leave its count silently at zero.
for stage, err in result.detectors.get("errors", {}).items():
    st.warning(f"The {stage} detector failed and was skipped — {err}")

# ── Two-column visual ────────────────────────────────────────────────────────
left, right = st.columns(2)

with left:
    st.subheader("Annotated overlay")
    annotated_rgb = cv2.cvtColor(annotated, cv2.COLOR_BGR2RGB)
    st.image(annotated_rgb, use_container_width=True,
             caption="Green = boxes, blue = text, red = arrows, magenta = icons, orange = regions")

with right:
    st.subheader("Relationship graph (data-driven layout)")
    if graph_ok and os.path.exists(graph_path):
        st.image(graph_path, use_container_width=True)
    else:
        st.warning("No relationships detected — the data-driven graph is empty. "
                   "(Previously the legacy pipeline would have injected 8 hardcoded "
                   "ELSER/Plant-An-App edges here; that was removed on Day 4.)")

# ── JSON / CSV downloads ────────────────────────────────────────────────────
st.subheader("Structured JSON output")
structured = result.model_dump()
st.json(structured, expanded=False)

dl1, dl2 = st.columns(2)
dl1.download_button(
    "Download structure.json",
    data=json.dumps(structured, indent=2, ensure_ascii=False),
    file_name=f"{os.path.splitext(name)[0]}_structure.json",
    mime="application/json",
)
import csv as _csv
csv_buf = io.StringIO()
w = _csv.writer(csv_buf)
w.writerow(["source", "target", "line_style", "direction", "relationship", "bidirectional"])
for r in result.relationships:
    w.writerow([r.source, r.target, r.line_style, r.direction, r.relationship, r.bidirectional])
dl2.download_button(
    "Download relationships.csv",
    data=csv_buf.getvalue(),
    file_name=f"{os.path.splitext(name)[0]}_relationships.csv",
    mime="text/csv",
)

# ── Footer ──────────────────────────────────────────────────────────────────
st.markdown("---")
st.caption(
    "DiagraMine v4.0 · modular pipeline (Day-4 refactor) · "
    "data-driven relationships (no `_known_connections` hardcoding) · "
    "schema-valid by construction (typed Pydantic models)"
)

try:
    os.unlink(tmp_path)
except OSError:
    pass