Update app.py

app.py

@@ -1,11 +1,3 @@
-# app.py
-# This is a self-contained Python script implementing a simplified version of PowerGrid Guardian.
-# It includes data ingestion (with mocks), data fusion, PyPSA simulation wrapper, LLM orchestration (with mock),
-# FastAPI backend (embedded), Gradio frontend, and basic tests (runnable via pytest if saved separately).
-# For Hugging Face Spaces deployment, this file can be used directly as the entrypoint.
-# Note: This is a demo system for decision-support only. Not for automatic grid control.
-# Updated to use Qwen model from Hugging Face, and incorporated provided API keys for services.
-
 import os
 import json
 import datetime
@@ -13,8 +5,6 @@ import random
 import asyncio
 import logging
 from typing import List, Dict, Any
-
-# Dependencies (ensure these are in requirements.txt for HF Spaces)
 import pandas as pd
 import numpy as np
 import pypsa
@@ -24,6 +14,7 @@ from pydantic import BaseModel
 import uvicorn
 import httpx
 from dotenv import load_dotenv
+import plotly.express as px
 
 # Load environment variables
 load_dotenv()
@@ -35,7 +26,7 @@ logger = logging.getLogger(__name__)
 # === CONFIGURATION ===
 DEMO_MODE = True  # Use mock data if True
 HF_API_KEY = os.getenv("HF_API_KEY")
-# Provided API keys
+# API keys
 GRIDSTATUS_API_KEY = os.getenv("GRIDSTATUS_API_KEY", "e9f1146bc3d242d19f7d64cf00f9fdd3")
 WEATHERAPI_KEY = os.getenv("WEATHERAPI_KEY", "6325087c017744b0b0d13950252307")
 EIA_API_KEY = os.getenv("EIA_API_KEY", "l0LsSOevbx1XqUMSEdEP7qVwDQXoeC3bFw8LPdGZ")
@@ -225,10 +216,13 @@ async def fetch_events(params: Dict) -> List[Event]:
             ))
         return events
 
-async def load_topology() -> Dict:
-    # Load from examples/toy_topology.json or mock
+def load_topology() -> Dict:
+    # Load from examples/toy_topology.json or mock (made sync for simplicity in map generation)
     topology = {
-        "nodes": [Node(node_id="node1", name="Substation A", type="substation", lat=29.76, lon=-95.37, voltage_kv=138, capacity_mw=500, connected_edges=["edge1"]).dict()],
+        "nodes": [
+            Node(node_id="node1", name="Substation A", type="substation", lat=29.7604, lon=-95.3698, voltage_kv=138, capacity_mw=500, connected_edges=["edge1"]).dict(),
+            Node(node_id="node2", name="Substation B", type="substation", lat=29.75, lon=-95.36, voltage_kv=138, capacity_mw=400, connected_edges=["edge1"]).dict()
+        ],
         "edges": [Edge(edge_id="edge1", from_node="node1", to_node="node2", r_ohm_per_km=0.1, x_ohm_per_km=0.2, length_km=12.3, thermal_limit_mw=300).dict()]
     }
     return topology
@@ -292,7 +286,7 @@ def run_n_minus_1(net: pypsa.Network) -> List[Dict]:
 # === LLM ORCHESTRATOR ===
 class LLMOrchestrator:
     async def build_context(self, node_id: str, timestamp: str) -> Dict:
-        topology = await load_topology()
+        topology = load_topology()
         timeseries = await fetch_grid_data({"respondent": "CISO", "start": (datetime.datetime.fromisoformat(timestamp) - datetime.timedelta(hours=24)).strftime("%Y-%m-%dT%H")})
         weather = await fetch_weather({"latitude": topology["nodes"][0]["lat"], "longitude": topology["nodes"][0]["lon"]})
         events = await fetch_events({"location": "Houston"})
@@ -347,6 +341,30 @@ class LLMOrchestrator:
         except:
             return False
 
+# === MAP GENERATION ===
+def generate_map():
+    topology = load_topology()
+    nodes = topology['nodes']
+    df = pd.DataFrame(nodes)
+    # Mock risks for each node
+    df['risk'] = np.random.uniform(0, 1, len(df))
+    df['color'] = df['risk']  # For continuous color
+    df['size'] = 10  # Fixed size
+    fig = px.scatter_mapbox(
+        df,
+        lat="lat",
+        lon="lon",
+        color="risk",
+        size="size",
+        hover_name="name",
+        color_continuous_scale="RdYlGn_r",  # Red for high risk, green for low
+        zoom=10,
+        height=500,
+        mapbox_style="open-street-map"
+    )
+    fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
+    return fig
+
 # === FASTAPI BACKEND ===
 app = FastAPI()
 
@@ -380,9 +398,8 @@ with gr.Blocks() as demo:
     gr.Markdown("# PowerGrid Guardian Demo")
     with gr.Row():
         with gr.Column(scale=2):
-            gr.Markdown("## Map Panel (Mock)")
-            # In real: Use Plotly for map, but for simplicity, text
-            map_output = gr.Textbox(value="Node1 (lat:29.76, lon:-95.37) - Risk: Red", label="Map")
+            gr.Markdown("## Map Panel")
+            map_plot = gr.Plot(label="Grid Map")
         with gr.Column(scale=1):
             gr.Markdown("## Alert Timeline")
             alerts = gr.JSON(value=get_alerts(), label="Alerts")
@@ -394,6 +411,7 @@ with gr.Blocks() as demo:
 
     rec_button.click(fn=lambda node: asyncio.run(get_recommendation(node)), inputs=node_input, outputs=rec_output)
     sim_button.click(fn=run_simulation, outputs=sim_output)
+    demo.load(generate_map, outputs=map_plot)
 
 # === TESTS (Pytest compatible - can be extracted to tests/ files) ===
 def test_fusion():
@@ -424,20 +442,4 @@ if __name__ == "__main__":
         uvicorn.run(app, host="0.0.0.0", port=8000)
     threading.Thread(target=run_api, daemon=True).start()
     # Launch Gradio
-    demo.launch(server_name="0.0.0.0", server_port=7860)
-
-# For HF Spaces, the demo.launch() will be the entrypoint.
-# To run tests: python -m pytest app.py (if pytest installed)
-# requirements.txt example:
-# fastapi==0.104.1
-# uvicorn==0.24.0
-# gradio==4.1.2
-# pypsa==0.26.0
-# pandas==2.1.3
-# numpy==1.26.2
-# httpx==0.25.2
-# python-dotenv==1.0.0
-# To create toy files (if needed):
-# toy_topology.json: {"nodes": [{"node_id": "node1", "name": "A", "type": "substation", "lat": 29.76, "lon": -95.37, "voltage_kv": 138, "capacity_mw": 500, "connected_edges": ["edge1"]}], "edges": [{"edge_id": "edge1", "from_node": "node1", "to_node": "node2", "r_ohm_per_km": 0.1, "x_ohm_per_km": 0.2, "length_km": 12.3, "thermal_limit_mw": 300}]}
-# toy_timeseries.csv: node_id,timestamp,measured_load_mw,measured_generation_mw,forecast_load_mw,reserve_margin_percent
-# node1,2023-01-01T00:00:00,100,120,110,10
+    demo.launch(server_name="0.0.0.0", server_port=7860)