Create app.py

app.py

@@ -0,0 +1,59 @@
+import streamlit as st
+import pandas as pd
+from datetime import datetime, timedelta
+import random
+
+# In-memory storage for validator submissions
+submitted_scores = []
+
+# Function to submit score
+def submit_score(validator_id, miner_id, score, model_type, timestamp):
+    submitted_scores.append({
+        "validator_id": validator_id,
+        "miner_id": miner_id,
+        "score": score,
+        "model_type": model_type,
+        "timestamp": timestamp
+    })
+
+# Function to calculate the average score for each miner
+def calculate_top_miners():
+    miner_scores = {}
+    for entry in submitted_scores:
+        miner_id = entry["miner_id"]
+        score = entry["score"]
+        
+        if miner_id not in miner_scores:
+            miner_scores[miner_id] = {"SNR": 0, "HNR": 0, "CLAP": 0, "count": 0}
+        
+        miner_scores[miner_id]["SNR"] += score["SNR"]
+        miner_scores[miner_id]["HNR"] += score["HNR"]
+        miner_scores[miner_id]["CLAP"] += score["CLAP"]
+        miner_scores[miner_id]["count"] += 1
+    
+    # Calculate average score
+    for miner_id, scores in miner_scores.items():
+        scores["SNR"] /= scores["count"]
+        scores["HNR"] /= scores["count"]
+        scores["CLAP"] /= scores["count"]
+    
+    # Sort by total score (sum of SNR, HNR, CLAP)
+    sorted_miners = sorted(miner_scores.items(), key=lambda x: (x[1]["SNR"] + x[1]["HNR"] + x[1]["CLAP"]), reverse=True)
+    
+    return sorted_miners[:10]  # Return top 10 miners
+
+# Streamlit UI
+st.title("Top 10 Miner Scores")
+
+# Display top 10 miners
+if st.button("Display Top 10 Scores"):
+    top_miners = calculate_top_miners()
+    st.write("Top 10 Miners based on aggregated scores:")
+    
+    # Prepare data for the table
+    miner_data = []
+    for miner, scores in top_miners:
+        miner_data.append([miner, scores["SNR"], scores["HNR"], scores["CLAP"]])
+    
+    df = pd.DataFrame(miner_data, columns=["Miner ID", "SNR", "HNR", "CLAP"])
+    st.table(df)