Upload 2 files

app_dashboard.py

@@ -0,0 +1,170 @@
+"""Papaya dashboard (Streamlit).
+
+Start the backend first, then run from the project root:
+    streamlit run simulator/app_dashboard.py
+"""
+
+from __future__ import annotations
+
+import os
+import time
+from datetime import datetime
+
+import pandas as pd
+import plotly.graph_objects as go
+import requests
+import streamlit as st
+
+DEFAULT_BACKEND = os.getenv("PAPAYA_BACKEND_URL", "http://localhost:8000")
+API_KEY = os.getenv("PAPAYA_API_KEY", "")
+TIMEOUT = 15
+
+st.set_page_config(page_title="Papaya Dashboard", page_icon="🥭", layout="wide")
+
+if "history" not in st.session_state:
+    st.session_state.history = []  # one dict per billing cycle
+
+
+# ---------------------------------------------------------------------------
+# Backend helpers (errors are shown in the UI, never crash the page)
+# ---------------------------------------------------------------------------
+
+
+def api_get(base: str, path: str, params: dict | None = None):
+    try:
+        resp = requests.get(f"{base}{path}", params=params, timeout=TIMEOUT)
+        resp.raise_for_status()
+        return resp.json()
+    except requests.RequestException as exc:
+        st.error(f"Backend request failed ({path}): {exc}")
+        return None
+
+
+def api_post(base: str, path: str, payload: dict):
+    headers = {"X-API-Key": API_KEY} if API_KEY else {}
+    try:
+        resp = requests.post(f"{base}{path}", json=payload, headers=headers, timeout=TIMEOUT)
+        if resp.status_code >= 400:
+            st.error(f"Backend rejected {path}: {resp.status_code} {resp.text[:200]}")
+            return None
+        return resp.json()
+    except requests.RequestException as exc:
+        st.error(f"Backend request failed ({path}): {exc}")
+        return None
+
+
+def run_cycle(base: str, node_id: str, window: float) -> None:
+    """Sample telemetry, then price and pay it."""
+    sample = api_get(base, "/telemetry/sample", {"node_id": node_id, "window_seconds": window})
+    if not sample:
+        return
+    record = api_post(base, "/pay", sample)
+    if not record:
+        return
+    st.session_state.history.append(
+        {
+            "time": datetime.now().strftime("%H:%M:%S"),
+            "cpu": sample["cpu_percent"],
+            "memory": sample["memory_percent"],
+            "tokens": sample["tokens"],
+            "amount": float(record["amount"]),
+            "status": record["status"],
+            "mode": record["mode"],
+        }
+    )
+
+
+# ---------------------------------------------------------------------------
+# Sidebar controls
+# ---------------------------------------------------------------------------
+
+st.sidebar.title("🥭 Papaya")
+backend = st.sidebar.text_input("Backend URL", DEFAULT_BACKEND).rstrip("/")
+node_id = st.sidebar.text_input("Node ID", "local-node")
+window = st.sidebar.slider("Billing window (seconds)", 1, 60, 5)
+auto = st.sidebar.toggle("Auto-run cycles", value=False)
+interval = st.sidebar.slider("Auto-run interval (seconds)", 2, 30, 5, disabled=not auto)
+manual = st.sidebar.button("Run one cycle", type="primary", width="stretch")
+if st.sidebar.button("Clear history", width="stretch"):
+    st.session_state.history = []
+
+if manual or auto:
+    run_cycle(backend, node_id, float(window))
+
+# ---------------------------------------------------------------------------
+# Header + backend status
+# ---------------------------------------------------------------------------
+
+st.title("Papaya Billing Dashboard")
+st.caption("Machines track their own workload and pay for it through the PayPal Sandbox.")
+
+health = api_get(backend, "/health")
+if health:
+    c1, c2, c3 = st.columns(3)
+    c1.metric("Backend", "Online")
+    c2.metric("PayPal Sandbox", "Configured" if health["paypal_configured"] else "Not configured")
+    c3.metric("Stored payment source", "Yes" if health["vault_configured"] else "No")
+    if not health["paypal_configured"]:
+        st.warning(
+            "PayPal credentials are not set on the backend. Prices are calculated "
+            "locally and no payment is made."
+        )
+
+# ---------------------------------------------------------------------------
+# Metrics + charts
+# ---------------------------------------------------------------------------
+
+history = st.session_state.history
+df = pd.DataFrame(history)
+
+if df.empty:
+    st.info("Click **Run one cycle** in the sidebar to measure this machine and bill it.")
+else:
+    last = df.iloc[-1]
+    paid = df[df["status"] == "COMPLETED"]["amount"].sum()
+    m1, m2, m3, m4 = st.columns(4)
+    m1.metric("CPU load", f"{last['cpu']:.1f}%")
+    m2.metric("Data tokens", f"{int(last['tokens']):,}")
+    m3.metric("Last charge", f"${last['amount']:.2f}")
+    m4.metric("Paid so far (captured)", f"${paid:.2f}")
+
+    left, right = st.columns(2)
+
+    cpu_fig = go.Figure()
+    cpu_fig.add_trace(go.Scatter(x=df["time"], y=df["cpu"], mode="lines+markers", name="CPU %"))
+    cpu_fig.add_trace(go.Scatter(x=df["time"], y=df["memory"], mode="lines", name="Memory %"))
+    cpu_fig.update_layout(title="Server workload", yaxis_range=[0, 100], height=320,
+                          margin=dict(l=10, r=10, t=40, b=10))
+    left.plotly_chart(cpu_fig, width="stretch")
+
+    cost_fig = go.Figure(go.Bar(x=df["time"], y=df["amount"], name="Charge"))
+    cost_fig.update_layout(title="Charge per cycle (USD)", height=320,
+                           margin=dict(l=10, r=10, t=40, b=10))
+    right.plotly_chart(cost_fig, width="stretch")
+
+# ---------------------------------------------------------------------------
+# Payment log + node logs
+# ---------------------------------------------------------------------------
+
+st.subheader("Payment log")
+txs = api_get(backend, "/transactions", {"limit": 50})
+if txs:
+    table = pd.DataFrame(txs)[
+        ["timestamp", "node_id", "amount", "currency", "status", "mode", "order_id", "detail"]
+    ]
+    st.dataframe(table, width="stretch", hide_index=True)
+else:
+    st.caption("No payments yet.")
+
+st.subheader("Sovereign Node Logs")
+logs = api_get(backend, "/logs", {"limit": 100})
+st.code("\n".join(logs["lines"][::-1]) if logs and logs["lines"] else "No log lines yet.",
+        language="text")
+
+# ---------------------------------------------------------------------------
+# Auto-run loop
+# ---------------------------------------------------------------------------
+
+if auto:
+    time.sleep(interval)
+    st.rerun()