Delete app.py

app.py

@@ -1,103 +0,0 @@
-import streamlit as st
-import pandas as pd
-import numpy as np
-from PIL import Image
-import base64
-from io import BytesIO
-
-# --- Page config ---
-st.set_page_config(page_title="VeriFact Leaderboard", layout="wide")
-
-# --- Load images ---
-@st.cache_data
-def load_image(path):
-    return Image.open(path)
-
-logo = load_image("factrbench.png")
-chart = load_image("test.png")
-
-# Display logo
-buf = BytesIO()
-logo.save(buf, format="PNG")
-logo_b64 = base64.b64encode(buf.getvalue()).decode("utf-8")
-st.markdown(f"""
-    <div style="text-align:center; margin-bottom:20px;">
-        <img src="data:image/png;base64,{logo_b64}" style="width:50%; max-width:700px;"/>
-    </div>
-""", unsafe_allow_html=True)
-
-# Header
-st.markdown("""
-<div style="text-align:center;">
-  <p style="font-size:22px;">
-    VERIFACT: Enhancing Long-Form Factuality Evaluation...
-  </p>
-  <p style="font-size:20px;">
-    # 📑 <a href="">Paper</a> | 💻 <a href="">GitHub</a> | 🤗 <a href="">HuggingFace</a> | 
-    ⚙️ <strong>Version</strong>: <strong>V1</strong> | <strong># Models</strong>: 11 | Updated: <strong>April 2025</strong>
-  </p>
-</div>
-""", unsafe_allow_html=True)
-
-# --- Load data ---
-@st.cache_data
-def load_data(path="models.json"):
-    df = pd.read_json(path, lines=True)
-    df["Avg"] = df[[f"T{i}" for i in range(1,12)]].mean(axis=1).round(1)
-    # Compute rank per column
-    for col in [f"T{i}" for i in range(1,12)] + ["Avg"]:
-        df[f"{col}_rank"] = df[col].rank(ascending=False, method="min").astype(int)
-    return df
-
-df = load_data()
-
-# --- Tabs ---
-tab1, tab2 = st.tabs(["Leaderboard", "Benchmark Details"])
-
-with tab1:
-    st.markdown("**Leaderboard:** Higher scores shaded green; best models bolded.")
-    # Build HTML table
-    cols = ["Model"] + [f"T{i}" for i in range(1,12)] + ["Avg"]
-    max_ranks = {col: df[f"{col}_rank"].max() for col in cols if col!="Model"}
-    
-    html = "<table style='border-collapse:collapse; width:100%;'>"
-    # header
-    html += "<tr>" + "".join(f"<th style='padding:4px;'>{c}</th>" for c in cols) + "</tr>"
-    # rows
-    for _, row in df.iterrows():
-        html += "<tr>"
-        for c in cols:
-            val = row[c] if c!="Model" else row[c]
-            if c=="Model":
-                html += f"<td style='padding:4px;text-align:left;'>{val}</td>"
-            else:
-                # color gradient
-                rank = row[f"{c}_rank"]
-                norm = 1 - (rank-1)/(max_ranks[c]-1 or 1)
-                # interpolate green-white
-                r = int(255 - norm*(255-182))
-                g = int(255 - norm*(255-243))
-                b = 255
-                style = f"background-color:rgb({r},{g},{b}); padding:4px;"
-                bold = "font-weight:bold;" if rank==1 else ""
-                html += f"<td style='{style}{bold}'>{val}</td>"
-        html += "</tr>"
-    html += "</table>"
-    st.markdown(html, unsafe_allow_html=True)
-
-with tab2:
-    buf2 = BytesIO()
-    chart.save(buf2, format="PNG")
-    chart_b64 = base64.b64encode(buf2.getvalue()).decode("utf-8")
-    st.markdown(f"""
-        <div style="text-align:center;">
-          <img src="data:image/png;base64,{chart_b64}" style="width:65%;"/>
-        </div>
-    """, unsafe_allow_html=True)
-    st.markdown("### What is VERIFACT?")
-    st.write("VERIFACT is a factuality evaluation framework...")
-    st.markdown("### What is FACTRBENCH?")
-    st.write("FACTRBENCH is the first benchmark for long-form factuality evaluation...")
-    st.markdown("### Key Findings")
-    st.write("VERIFACT outperforms prior methods [...]")
-