Update dashboard.py

dashboard.py

@@ -1,73 +1,6 @@
-import firebase_admin
-from firebase_admin import credentials, firestore
-import pandas as pd
-import matplotlib.pyplot as plt
-import io
-import gradio as gr
-
-# Initialize Firebase Admin SDK
-if not firebase_admin._apps:
-    cred = credentials.Certificate("firebase_key.json")
-    firebase_admin.initialize_app(cred)
-
-db = firestore.client()
-
-def fetch_logs():
-    docs = db.collection("evo_feedback_logs").stream()
-    data = []
-    for doc in docs:
-        d = doc.to_dict()
-        if all(k in d for k in ["goal", "evo", "gpt", "correct"]):
-            data.append(d)
-    return pd.DataFrame(data)
-
-def generate_dashboard():
-    df = fetch_logs()
-    if df.empty:
-        return "No data yet.", None
-
-    df["evo_correct"] = df["evo"] == df["correct"]
-    df["gpt_correct"] = df["gpt"] == df["correct"]
-
-    evo_acc = df["evo_correct"].mean()
-    gpt_acc = df["gpt_correct"].mean()
-    agreement = (df["evo"] == df["gpt"]).mean()
+# dashboard.py
 
-    fig, ax = plt.subplots(figsize=(6, 4))
-    counts = [
-        df["evo_correct"].sum(),
-        df["evo_correct"].count() - df["evo_correct"].sum(),
-        df["gpt_correct"].sum(),
-        df["gpt_correct"].count() - df["gpt_correct"].sum()
-    ]
-    bars = ax.bar(["Evo Correct", "Evo Wrong", "GPT Correct", "GPT Wrong"], counts)
-    ax.set_title("Model Accuracy Summary")
-    ax.set_ylabel("Count")
-
-    buf = io.BytesIO()
-    plt.tight_layout()
-    plt.savefig(buf, format="png")
-    plt.close(fig)
-    buf.seek(0)
-
-    summary = (
-        f"🧠 Evo Accuracy: {evo_acc:.2%}\n"
-        f"🤖 GPT-3.5 Accuracy: {gpt_acc:.2%}\n"
-        f"⚖️ Agreement Rate: {agreement:.2%}\n"
-        f"📝 Total Examples Logged: {len(df)}"
-    )
-
-    return summary, buf
-
-def render_dashboard():
-    with gr.Blocks() as dashboard:
-        gr.Markdown("## 📊 EvoTransformer Live Evolution Dashboard")
-        gr.Markdown("> 🔄 *Below metrics are based on real-time user feedback.*")
-        
-        summary_text = gr.Textbox(label="Summary", interactive=False)
-        plot = gr.Image(type="pil", label="Accuracy Plot")
-
-        refresh = gr.Button("🔁 Refresh Data")
-        refresh.click(fn=generate_dashboard, outputs=[summary_text, plot])
+import gradio as gr
 
-    return dashboard
+def display_dashboard():
+    return gr.Markdown("## 📊 EvoTransformer Live Dashboard\n\nComing soon!")