Meridian Edge + Gradio

import gradio as gr
import requests
import pandas as pd

API_KEY = "me_live_YOUR_KEY"

def fetch_consensus(sport: str) -> pd.DataFrame:
    r = requests.get(
        "https://meridianedge.io/api/v1/consensus",
        headers={"X-API-Key": API_KEY},
        params={"sport": sport, "limit": 15}
    )
    events = r.json().get("events", [])
    if not events:
        return pd.DataFrame({"Message": ["No events found"]})
    df = pd.DataFrame(events)
    df["Consensus"] = (df["consensus_prob"] * 100).round(1).astype(str) + "%"
    df["Divergence"] = (df.get("divergence_pct", 0) * 100).round(1).astype(str) + "%"
    return df[["title","Consensus","Divergence","market_count"]].rename(
        columns={"title":"Event","market_count":"Markets"})

with gr.Blocks(title="Prediction Market Consensus") as demo:
    gr.Markdown("## 📊 Prediction Market Consensus\n*meridianedge.io — Not investment advice*")
    sport_dd = gr.Dropdown(["NBA","NHL","MLB","MLS"], value="NBA", label="Sport")
    out      = gr.DataFrame(label="Live Consensus Data")
    btn      = gr.Button("Fetch Consensus", variant="primary")
    btn.click(fetch_consensus, inputs=sport_dd, outputs=out)

demo.launch(share=True)  # share=True for public URL