add DigitalOcean pricing, startup validation, and demo update

- MetricsSource::DigitalOceanPricing variant: fetch public DO Gen-AI pricing, normalize as lowercase(creator)/model_id, cost = input + output per million
- cost_metrics endpoint format updated to { "model": { "input_per_million": X, "output_per_million": Y } }
- Startup errors: prefer:cheapest requires cost source, prefer:fastest requires prometheus
- Startup warning: models with no pricing/latency data ranked last
- One-per-type enforcement: digitalocean_pricing; error if cost_metrics + digitalocean_pricing both configured
- cost_snapshot() / latency_snapshot() on ModelMetricsService for startup checks
- Demo config updated to v0.4.0 top-level routing_preferences with cheapest + fastest policies
- docker-compose.yaml + prometheus.yaml + metrics_server.py for demo latency metrics
- Schema and docs updated

demos/llm_routing/model_routing_service/metrics_server.py

@@ -0,0 +1,30 @@
+"""
+Minimal Prometheus metrics server for demo purposes.
+Exposes mock P95 latency data for model routing.
+"""
+from http.server import HTTPServer, BaseHTTPRequestHandler
+
+METRICS = """\
+# HELP model_latency_p95_seconds P95 request latency in seconds per model
+# TYPE model_latency_p95_seconds gauge
+model_latency_p95_seconds{model_name="anthropic/claude-sonnet-4-20250514"} 0.85
+model_latency_p95_seconds{model_name="openai/gpt-4o"} 1.20
+model_latency_p95_seconds{model_name="openai/gpt-4o-mini"} 0.40
+""".encode()
+
+
+class MetricsHandler(BaseHTTPRequestHandler):
+    def do_GET(self):
+        self.send_response(200)
+        self.send_header("Content-Type", "text/plain; version=0.0.4; charset=utf-8")
+        self.end_headers()
+        self.wfile.write(METRICS)
+
+    def log_message(self, fmt, *args):
+        pass  # suppress access logs
+
+
+if __name__ == "__main__":
+    server = HTTPServer(("", 8080), MetricsHandler)
+    print("metrics server listening on :8080", flush=True)
+    server.serve_forever()