import streamlit as st
from core import bidder_processor, evaluator
from core.config import BIDDER_NAMES, DATA_DIR
from core.fallback import load_criteria
from core.schemas import Criterion
from ui.components import category_badge, confidence_bar, mandatory_badge, ocr_tier_badge, verdict_pill
_BIDDER_META = {
"bidder_a": ("Apex Constructions Pvt. Ltd.", "Clearly Eligible", "#22C55E"),
"bidder_b": ("BuildRight Enterprises", "Ineligible — Low Turnover", "#EF4444"),
"bidder_c": ("Shree Constructions & Services", "Needs Review — Scanned Cert", "#F59E0B"),
}
def _get_criteria() -> list[Criterion]:
data = st.session_state.get("criteria")
return [Criterion(**c) for c in data] if data else load_criteria()
def _overall(verdicts: list[dict], crit_map: dict) -> str:
mand = [v for v in verdicts if crit_map.get(v["criterion_id"]) and
crit_map[v["criterion_id"]].mandatory]
src = mand or verdicts
if any(v["verdict"] == "not_eligible" for v in src): return "not_eligible"
if any(v["verdict"] == "needs_review" for v in src): return "needs_review"
return "eligible"
def render() -> None:
st.markdown(
'Bidder Evaluation
'
''
'Evaluate each bidder against all extracted criteria.
',
unsafe_allow_html=True,
)
selected = st.multiselect(
"Select bidders",
options=list(BIDDER_NAMES.keys()),
default=list(BIDDER_NAMES.keys()),
format_func=lambda x: _BIDDER_META.get(x, (x, "", ""))[0],
)
criteria_loaded = bool(st.session_state.get("criteria"))
if not criteria_loaded:
st.info(
"**Criteria not loaded yet.** Go to **Tender Analysis** and click "
"**Extract Criteria**, or use **Load Pre-computed Demo** on the Overview tab."
)
if st.button("▶ Run Evaluation", type="primary", disabled=not criteria_loaded):
criteria = _get_criteria()
prog = st.progress(0, text="Starting…")
total = len(selected) * len(criteria)
done, vd = 0, {}
for bid in selected:
files = sorted(f for f in (DATA_DIR / "bidders" / bid).iterdir()
if f.suffix.lower() in {".pdf", ".png", ".jpg"})
with st.spinner(f"Indexing {_BIDDER_META.get(bid,(bid,'',''))[0]}…"):
bidder_processor.process_bidder(bid, files)
vlist = []
for c in criteria:
v = evaluator.evaluate(bid, c)
vlist.append(v.model_dump())
done += 1
prog.progress(done / total,
text=f"{c.id} · {_BIDDER_META.get(bid,(bid,'',''))[0]}")
vd[bid] = vlist
st.session_state["verdicts"] = vd
prog.empty()
st.success("Evaluation complete.")
st.rerun()
vdata = st.session_state.get("verdicts", {})
criteria = _get_criteria()
crit_map = {c.id: c for c in criteria}
if not vdata:
st.info("No results yet — click **Run Evaluation** above, or load the demo from Overview.")
return
if st.session_state.get("fallback_active"):
st.warning("⚠ Live API unavailable — showing pre-computed results.")
for bid in (selected or list(vdata.keys())):
if bid not in vdata:
continue
verdicts = vdata[bid]
name, tagline, accent = _BIDDER_META.get(bid, (bid, "", "#3B82F6"))
ov = _overall(verdicts, crit_map)
passed = sum(1 for v in verdicts if v["verdict"] == "eligible" and
crit_map.get(v["criterion_id"]) and crit_map[v["criterion_id"]].mandatory)
total_m = sum(1 for v in verdicts if crit_map.get(v["criterion_id"]) and
crit_map[v["criterion_id"]].mandatory)
st.markdown("", unsafe_allow_html=True)
with st.container(border=True):
# Header
st.markdown(
f''
f'
'
f'
🏢
'
f'
'
f'
{name}
'
f'
'
f'{tagline}
'
f'
'
f'{verdict_pill(ov)}'
f''
f'{passed}/{total_m} mandatory passed'
f'
'
+ "".join(
f'
{h}
'
for h in ["Criterion", "Verdict", "Extracted Value", "Source & Tier", "Category"]
)
+ "
{tier}
'
)
extracted_cell = (
f'{extracted}'
if extracted else
'—'
)
st.markdown(
f''
f'
{mb}
'
f'{v["criterion_id"]}: {title}
'
f'
{verdict_pill(v["verdict"])}
'
f'
{extracted_cell}
'
f'
{src_html}
'
f'
{cat}
'
f'
'
f'Reason: {reason}
',
unsafe_allow_html=True,
)
if snippet:
st.markdown(
f''
f'“{snippet}”
',
unsafe_allow_html=True,
)
st.markdown(
'
',
unsafe_allow_html=True,
)