Retail Branch Performance Agent

import requests, json, pandas as pd

API_POS = "https://api.retail.com/v2/branches/performance"

def fetch_branch_data(month):
    resp = requests.get(API_POS, params={"month": month})
    return resp.json().get("branches", [])

def analyze_branches(branches):
    df = pd.DataFrame(branches)
    df["conversion"] = df["sales"] / df["traffic"] * 100
    df["rank"] = df["conversion"].rank(ascending=False)
    gaps = df[df["conversion"] < df["conversion"].median()]
    return {
        "avg_conversion": round(df["conversion"].mean(), 1),
        "total_sales": round(df["sales"].sum(), 2),
        "top_branch": df.loc[df["conversion"].idxmax(), "name"],
        "improvement": len(gaps),
        "gap_actions": round(gaps["sales"].sum() * 0.05, 2)
    }

report = analyze_branches(fetch_branch_data("2026-06"))
print(json.dumps(report))