merge main into plano-session_pinning

.github/workflows/ci.yml

@@ -133,13 +133,13 @@ jobs:
           load: true
           tags: |
             ${{ env.PLANO_DOCKER_IMAGE }}
-            ${{ env.DOCKER_IMAGE }}:0.4.14
+            ${{ env.DOCKER_IMAGE }}:0.4.16
             ${{ env.DOCKER_IMAGE }}:latest
           cache-from: type=gha
           cache-to: type=gha,mode=max
 
       - name: Save image as artifact
-        run: docker save ${{ env.PLANO_DOCKER_IMAGE }} ${{ env.DOCKER_IMAGE }}:0.4.14 ${{ env.DOCKER_IMAGE }}:latest -o /tmp/plano-image.tar
+        run: docker save ${{ env.PLANO_DOCKER_IMAGE }} ${{ env.DOCKER_IMAGE }}:0.4.16 ${{ env.DOCKER_IMAGE }}:latest -o /tmp/plano-image.tar
 
       - name: Upload image artifact
         uses: actions/upload-artifact@v6
@@ -477,7 +477,7 @@ jobs:
           ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
         run: |
           source venv/bin/activate
-          cd demos/shared/test_runner && sh run_demo_tests.sh llm_routing/preference_based_routing
+          cd demos/shared/test_runner && bash run_demo_tests.sh llm_routing/preference_based_routing
 
   # ──────────────────────────────────────────────
   # E2E: demo — currency conversion
@@ -527,4 +527,4 @@ jobs:
           GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }}
         run: |
           source venv/bin/activate
-          cd demos/shared/test_runner && sh run_demo_tests.sh advanced/currency_exchange
+          cd demos/shared/test_runner && bash run_demo_tests.sh advanced/currency_exchange

.github/workflows/docker-push-release.yml

@@ -3,10 +3,13 @@ name: Publish docker image (release)
 env:
   DOCKER_IMAGE: katanemo/plano
   GHCR_IMAGE: ghcr.io/${{ github.repository_owner }}/plano
+  DOCR_IMAGE: registry.digitalocean.com/genai-prod/plano
+  DOCR_PREVIEW_IMAGE: registry.digitalocean.com/genai-preview/plano
 
 on:
   release:
     types: [published]
+  workflow_dispatch: # remove after testing
 
 permissions:
   contents: read
@@ -33,6 +36,14 @@ jobs:
           username: ${{ github.actor }}
           password: ${{ secrets.GITHUB_TOKEN }}
 
+      - name: Install doctl
+        uses: digitalocean/action-doctl@v2
+        with:
+          token: ${{ secrets.PLATFORM_DIGITALOCEAN_TOKEN }}
+
+      - name: Log in to DOCR (prod)
+        run: doctl registry login
+
       - name: Extract metadata for Docker
         id: meta
         uses: docker/metadata-action@v5
@@ -51,6 +62,21 @@ jobs:
           tags: |
             ${{ steps.meta.outputs.tags }}-arm64
             ${{ env.GHCR_IMAGE }}:${{ github.event.release.tag_name }}-arm64
+            ${{ env.DOCR_IMAGE }}:${{ github.event.release.tag_name }}-arm64
+
+      - name: Switch to DOCR preview
+        uses: digitalocean/action-doctl@v2
+        with:
+          token: ${{ secrets.PLATFORM_DIGITALOCEAN_TOKEN_PREVIEW }}
+
+      - name: Log in to DOCR (preview)
+        run: doctl registry login
+
+      - name: Push to DOCR Preview
+        run: |
+          docker buildx imagetools create \
+            -t ${{ env.DOCR_PREVIEW_IMAGE }}:${{ github.event.release.tag_name }}-arm64 \
+            ${{ steps.meta.outputs.tags }}-arm64
 
   # Build AMD64 image on GitHub's AMD64 runner — push to both registries
   build-amd64:
@@ -72,6 +98,14 @@ jobs:
           username: ${{ github.actor }}
           password: ${{ secrets.GITHUB_TOKEN }}
 
+      - name: Install doctl
+        uses: digitalocean/action-doctl@v2
+        with:
+          token: ${{ secrets.PLATFORM_DIGITALOCEAN_TOKEN }}
+
+      - name: Log in to DOCR (prod)
+        run: doctl registry login
+
       - name: Extract metadata for Docker
         id: meta
         uses: docker/metadata-action@v5
@@ -90,6 +124,21 @@ jobs:
           tags: |
             ${{ steps.meta.outputs.tags }}-amd64
             ${{ env.GHCR_IMAGE }}:${{ github.event.release.tag_name }}-amd64
+            ${{ env.DOCR_IMAGE }}:${{ github.event.release.tag_name }}-amd64
+
+      - name: Switch to DOCR preview
+        uses: digitalocean/action-doctl@v2
+        with:
+          token: ${{ secrets.PLATFORM_DIGITALOCEAN_TOKEN_PREVIEW }}
+
+      - name: Log in to DOCR (preview)
+        run: doctl registry login
+
+      - name: Push to DOCR Preview
+        run: |
+          docker buildx imagetools create \
+            -t ${{ env.DOCR_PREVIEW_IMAGE }}:${{ github.event.release.tag_name }}-amd64 \
+            ${{ steps.meta.outputs.tags }}-amd64
 
   # Combine ARM64 and AMD64 images into multi-arch manifests for both registries
   create-manifest:
@@ -109,6 +158,14 @@ jobs:
           username: ${{ github.actor }}
           password: ${{ secrets.GITHUB_TOKEN }}
 
+      - name: Install doctl
+        uses: digitalocean/action-doctl@v2
+        with:
+          token: ${{ secrets.PLATFORM_DIGITALOCEAN_TOKEN }}
+
+      - name: Log in to DOCR (prod)
+        run: doctl registry login
+
       - name: Extract metadata for Docker
         id: meta
         uses: docker/metadata-action@v5
@@ -131,3 +188,27 @@ jobs:
             -t ${{ env.GHCR_IMAGE }}:${TAG} \
             ${{ env.GHCR_IMAGE }}:${TAG}-arm64 \
             ${{ env.GHCR_IMAGE }}:${TAG}-amd64
+
+      - name: Create DOCR Prod Multi-Arch Manifest
+        run: |
+          TAG=${{ github.event.release.tag_name }}
+          docker buildx imagetools create \
+            -t ${{ env.DOCR_IMAGE }}:${TAG} \
+            ${{ env.DOCR_IMAGE }}:${TAG}-arm64 \
+            ${{ env.DOCR_IMAGE }}:${TAG}-amd64
+
+      - name: Switch to DOCR preview
+        uses: digitalocean/action-doctl@v2
+        with:
+          token: ${{ secrets.PLATFORM_DIGITALOCEAN_TOKEN_PREVIEW }}
+
+      - name: Log in to DOCR (preview)
+        run: doctl registry login
+
+      - name: Create DOCR Preview Multi-Arch Manifest
+        run: |
+          TAG=${{ github.event.release.tag_name }}
+          docker buildx imagetools create \
+            -t ${{ env.DOCR_PREVIEW_IMAGE }}:${TAG} \
+            ${{ steps.meta.outputs.tags }}-arm64 \
+            ${{ steps.meta.outputs.tags }}-amd64

.pre-commit-config.yaml

@@ -37,7 +37,7 @@ repos:
       - id: gitleaks
 
   - repo: https://github.com/psf/black
-    rev: 23.1.0
+    rev: 26.3.1
     hooks:
       - id: black
         language_version: python3

apps/katanemo-www/package.json

@@ -12,6 +12,7 @@
     "clean": "rm -rf .next"
   },
   "dependencies": {
+    "@heroicons/react": "^2.2.0",
     "@katanemo/shared-styles": "*",
     "@katanemo/ui": "*",
     "next": "^16.1.6",

apps/katanemo-www/src/app/layout.tsx

@@ -66,7 +66,9 @@ export default function RootLayout({
 }>) {
   return (
     <html lang="en">
-      <body className={`${ibmPlexSans.variable} antialiased text-white`}>
+      <body
+        className={`${ibmPlexSans.variable} overflow-hidden antialiased text-white`}
+      >
         {/* Google tag (gtag.js) */}
         <Script
           src="https://www.googletagmanager.com/gtag/js?id=G-RLD5BDNW5N"
@@ -80,7 +82,9 @@ export default function RootLayout({
             gtag('config', 'G-RLD5BDNW5N');
           `}
         </Script>
-        <div className="min-h-screen">{children}</div>
+        <div className="h-screen overflow-hidden">
+          {children}
+        </div>
       </body>
     </html>
   );

apps/katanemo-www/src/app/page.tsx

@@ -1,11 +1,23 @@
 import Image from "next/image";
 import Link from "next/link";
 import LogoSlider from "../components/LogoSlider";
+import { ArrowRightIcon } from "@heroicons/react/16/solid";
 
 export default function HomePage() {
   return (
-    <main className="relative flex min-h-screen items-center justify-center overflow-hidden px-6 pt-12 pb-16 font-sans sm:pt-20 lg:items-start lg:justify-start lg:pt-24">
+    <main className="relative flex h-full items-center justify-center overflow-hidden px-6 pt-12 pb-16 font-sans sm:pt-20 lg:items-start lg:justify-start lg:pt-24">
       <div className="relative mx-auto w-full max-w-6xl flex flex-col items-center justify-center text-left lg:items-start lg:justify-start">
+        <Link
+          href="https://digitalocean.com/blog/digitalocean-acquires-katanemo-labs-inc"
+          target="_blank"
+          rel="noopener noreferrer"
+          className="mb-7 inline-flex max-w-[20rem] items-center gap-1 self-start rounded-full border border-[#22A875]/30 bg-[#22A875]/30 px-2.5 py-1 text-left text-[12px] leading-tight font-medium text-white transition-opacity hover:opacity-90 lg:hidden"
+        >
+          <span>
+            DigitalOcean acquires Katanemo Labs, Inc.
+          </span>
+          <ArrowRightIcon aria-hidden className="h-3 w-3 shrink-0 text-white/90" />
+        </Link>
         <div className="pointer-events-none mb-6 w-full self-start lg:hidden">
           <Image
             src="/KatanemoLogo.svg"
@@ -17,6 +29,20 @@ export default function HomePage() {
           />
         </div>
         <div className="relative z-10 max-w-xl sm:max-w-2xl lg:max-w-2xl xl:max-w-8xl lg:pr-[26vw] xl:pr-[2vw] sm:right-0 md:right-0 lg:right-0 xl:right-20 2xl:right-50 sm:mt-36 mt-0">
+          <Link
+            href="https://digitalocean.com/blog/digitalocean-acquires-katanemo-labs-inc"
+            target="_blank"
+            rel="noopener noreferrer"
+            className="mb-4 hidden max-w-full items-center gap-2 rounded-full border border-[#22A875]/70 bg-[#22A875]/50 px-4 py-1 text-left text-sm font-medium text-white transition-opacity hover:opacity-90 lg:inline-flex"
+          >
+            <span>
+              DigitalOcean acquires Katanemo Labs, Inc.
+            </span>
+            <ArrowRightIcon
+              aria-hidden
+              className="h-4 w-4 shrink-0 text-white/90"
+            />
+          </Link>
           <h1 className="text-3xl sm:text-4xl md:text-5xl lg:text-6xl font-sans font-medium leading-tight tracking-tight text-white">
             Forward-deployed AI infrastructure engineers.
           </h1>

apps/www/package.json

@@ -16,6 +16,7 @@
     "migrate:blogs": "tsx scripts/migrate-blogs.ts"
   },
   "dependencies": {
+    "@heroicons/react": "^2.2.0",
     "@katanemo/shared-styles": "*",
     "@katanemo/ui": "*",
     "@portabletext/react": "^5.0.0",
@@ -32,8 +33,8 @@
     "next": "^16.1.6",
     "next-sanity": "^11.6.9",
     "papaparse": "^5.5.3",
-    "react": "19.2.0",
-    "react-dom": "19.2.0",
+    "react": "19.2.3",
+    "react-dom": "19.2.3",
     "react-markdown": "^10.1.0",
     "react-syntax-highlighter": "^16.1.0",
     "remark-gfm": "^4.0.1",

apps/www/src/app/api/og/[slug]/route.tsx

@@ -39,6 +39,10 @@ function loadFont(fileName: string, baseUrl: string) {
 }
 
 async function getBlogPost(slug: string) {
+  if (!client) {
+    return null;
+  }
+
   const query = `*[_type == "blog" && slug.current == $slug && published == true][0] {
     _id,
     title,
@@ -53,8 +57,13 @@ async function getBlogPost(slug: string) {
     }
   }`;
 
-  const post = await client.fetch(query, { slug });
-  return post;
+  try {
+    const post = await client.fetch(query, { slug });
+    return post;
+  } catch (error) {
+    console.error("Error fetching blog post for OG image:", error);
+    return null;
+  }
 }
 
 function formatDate(dateString: string): string {

apps/www/src/app/blog/[slug]/layout.tsx

@@ -17,6 +17,10 @@ interface BlogPost {
 }
 
 async function getBlogPost(slug: string): Promise<BlogPost | null> {
+  if (!client) {
+    return null;
+  }
+
   const query = `*[_type == "blog" && slug.current == $slug && published == true][0] {
     _id,
     title,
@@ -26,8 +30,13 @@ async function getBlogPost(slug: string): Promise<BlogPost | null> {
     author
   }`;
 
-  const post = await client.fetch(query, { slug });
-  return post || null;
+  try {
+    const post = await client.fetch(query, { slug });
+    return post || null;
+  } catch (error) {
+    console.error("Error fetching blog post metadata:", error);
+    return null;
+  }
 }
 
 export async function generateMetadata({

apps/www/src/app/blog/[slug]/page.tsx

@@ -25,6 +25,10 @@ interface BlogPost {
 }
 
 async function getBlogPost(slug: string): Promise<BlogPost | null> {
+  if (!client) {
+    return null;
+  }
+
   const query = `*[_type == "blog" && slug.current == $slug && published == true][0] {
     _id,
     title,
@@ -51,17 +55,31 @@ async function getBlogPost(slug: string): Promise<BlogPost | null> {
     author
   }`;
 
-  const post = await client.fetch(query, { slug });
-  return post || null;
+  try {
+    const post = await client.fetch(query, { slug });
+    return post || null;
+  } catch (error) {
+    console.error("Error fetching blog post:", error);
+    return null;
+  }
 }
 
 async function getAllBlogSlugs(): Promise<string[]> {
+  if (!client) {
+    return [];
+  }
+
   const query = `*[_type == "blog" && published == true] {
     "slug": slug.current
   }`;
 
-  const posts = await client.fetch(query);
-  return posts.map((post: { slug: string }) => post.slug);
+  try {
+    const posts = await client.fetch(query);
+    return posts.map((post: { slug: string }) => post.slug);
+  } catch (error) {
+    console.error("Error fetching blog slugs:", error);
+    return [];
+  }
 }
 
 export async function generateStaticParams() {

apps/www/src/app/blog/page.tsx

@@ -8,6 +8,7 @@ import { BlogSectionHeader } from "@/components/BlogSectionHeader";
 import { pageMetadata } from "@/lib/metadata";
 
 export const metadata: Metadata = pageMetadata.blog;
+export const dynamic = "force-dynamic";
 
 interface BlogPost {
   _id: string;
@@ -44,6 +45,10 @@ function formatDate(dateString: string): string {
 }
 
 async function getBlogPosts(): Promise<BlogPost[]> {
+  if (!client) {
+    return [];
+  }
+
   const query = `*[_type == "blog" && published == true] | order(publishedAt desc) {
     _id,
     title,
@@ -58,12 +63,48 @@ async function getBlogPosts(): Promise<BlogPost[]> {
     featured
   }`;
 
-  return await client.fetch(query);
+  try {
+    return await client.fetch(query);
+  } catch (error) {
+    console.error("Error fetching blog posts:", error);
+    return [];
+  }
+}
+
+async function getFeaturedBlogPost(): Promise<BlogPost | null> {
+  if (!client) {
+    return null;
+  }
+
+  const query = `*[_type == "blog" && published == true && featured == true] | order(_updatedAt desc, publishedAt desc)[0] {
+    _id,
+    title,
+    slug,
+    summary,
+    publishedAt,
+    mainImage,
+    mainImageUrl,
+    thumbnailImage,
+    thumbnailImageUrl,
+    author,
+    featured
+  }`;
+
+  try {
+    const post = await client.fetch(query);
+    return post || null;
+  } catch (error) {
+    console.error("Error fetching featured blog post:", error);
+    return null;
+  }
 }
 
 export default async function BlogPage() {
-  const posts = await getBlogPosts();
-  const featuredPost = posts.find((post) => post.featured) || posts[0];
+  const [posts, featuredCandidate] = await Promise.all([
+    getBlogPosts(),
+    getFeaturedBlogPost(),
+  ]);
+  const featuredPost = featuredCandidate || posts[0];
   const recentPosts = posts
     .filter((post) => post._id !== featuredPost?._id)
     .slice(0, 3);

apps/www/src/app/layout.tsx

@@ -1,4 +1,6 @@
 import type { Metadata } from "next";
+import { ArrowRightIcon } from "@heroicons/react/16/solid";
+import Link from "next/link";
 import Script from "next/script";
 import "@katanemo/shared-styles/globals.css";
 import { Analytics } from "@vercel/analytics/next";
@@ -35,6 +37,27 @@ export default function RootLayout({
             gtag('config', 'G-ML7B1X9HY2');
           `}
         </Script>
+        <Link
+          href="https://digitalocean.com/blog/digitalocean-acquires-katanemo-labs-inc"
+          target="_blank"
+          rel="noopener noreferrer"
+          className="block w-full bg-[#7780D9] py-3 text-white transition-opacity"
+        >
+          <div className="mx-auto flex max-w-[85rem] items-center justify-center gap-4 px-6 text-center md:justify-between md:text-left lg:px-8">
+            <span className="w-full text-xs font-medium leading-snug md:w-auto md:text-base flex items-center">
+              DigitalOcean acquires Katanemo Labs, Inc. to accelerate AI
+              development
+              <ArrowRightIcon
+                aria-hidden
+                className="ml-1 inline-block h-3 w-3 align-[-1px] text-white/90 md:hidden"
+              />
+            </span>
+            <span className="hidden shrink-0 items-center gap-1 text-base font-medium tracking-[-0.989px] font-mono leading-snug opacity-70 transition-opacity hover:opacity-100 md:inline-flex">
+              Read the announcement
+              <ArrowRightIcon aria-hidden className="h-3.5 w-3.5 text-white/70" />
+            </span>
+          </div>
+        </Link>
         <ConditionalLayout>{children}</ConditionalLayout>
         <Analytics />
       </body>

apps/www/src/app/sitemap.ts

@@ -10,6 +10,10 @@ interface BlogPost {
 }
 
 async function getBlogPosts(): Promise<BlogPost[]> {
+  if (!client) {
+    return [];
+  }
+
   const query = `*[_type == "blog" && published == true] | order(publishedAt desc) {
     slug,
     publishedAt,

apps/www/src/components/Hero.tsx

@@ -24,7 +24,7 @@ export function Hero() {
             >
               <div className="inline-flex flex-wrap items-center gap-1.5 sm:gap-2 px-3 sm:px-4 py-1 rounded-full bg-[rgba(185,191,255,0.4)] border border-[var(--secondary)] shadow backdrop-blur hover:bg-[rgba(185,191,255,0.6)] transition-colors cursor-pointer">
                 <span className="text-xs sm:text-sm font-medium text-black/65">
-                  v0.4.14
+                  v0.4.16
                 </span>
                 <span className="text-xs sm:text-sm font-medium text-black ">
                   —

apps/www/src/lib/sanity.ts

@@ -2,19 +2,33 @@ import { createClient } from "@sanity/client";
 import imageUrlBuilder from "@sanity/image-url";
 import type { SanityImageSource } from "@sanity/image-url/lib/types/types";
 
-const projectId = process.env.NEXT_PUBLIC_SANITY_PROJECT_ID;
-const dataset = process.env.NEXT_PUBLIC_SANITY_DATASET;
-const apiVersion = process.env.NEXT_PUBLIC_SANITY_API_VERSION;
+const projectId =
+  process.env.NEXT_PUBLIC_SANITY_PROJECT_ID ||
+  "71ny25bn";
+const dataset =
+  process.env.NEXT_PUBLIC_SANITY_DATASET ||
+  "production";
+const apiVersion =
+  process.env.NEXT_PUBLIC_SANITY_API_VERSION ||
+  "2025-01-01";
 
-export const client = createClient({
-  projectId,
-  dataset,
-  apiVersion,
-  useCdn: true, // Set to false if statically generating pages, using ISR or using the on-demand revalidation API
-});
+export const hasSanityConfig = Boolean(projectId && dataset && apiVersion);
 
-const builder = imageUrlBuilder(client);
+export const client = hasSanityConfig
+  ? createClient({
+      projectId,
+      dataset,
+      apiVersion,
+      // Keep blog/admin updates visible immediately after publishing.
+      useCdn: false,
+    })
+  : null;
+
+const builder = client ? imageUrlBuilder(client) : null;
 
 export function urlFor(source: SanityImageSource) {
+  if (!builder) {
+    throw new Error("Sanity client is not configured.");
+  }
   return builder.image(source);
 }

build_filter_image.sh

@@ -1 +1 @@
-docker build  -f Dockerfile . -t katanemo/plano -t katanemo/plano:0.4.14
+docker build  -f Dockerfile . -t katanemo/plano -t katanemo/plano:0.4.16

cli/planoai/__init__.py

@@ -1,3 +1,3 @@
 """Plano CLI - Intelligent Prompt Gateway."""
 
-__version__ = "0.4.14"
+__version__ = "0.4.16"

cli/planoai/consts.py

@@ -5,7 +5,7 @@ PLANO_COLOR = "#969FF4"
 
 SERVICE_NAME_ARCHGW = "plano"
 PLANO_DOCKER_NAME = "plano"
-PLANO_DOCKER_IMAGE = os.getenv("PLANO_DOCKER_IMAGE", "katanemo/plano:0.4.14")
+PLANO_DOCKER_IMAGE = os.getenv("PLANO_DOCKER_IMAGE", "katanemo/plano:0.4.16")
 DEFAULT_OTEL_TRACING_GRPC_ENDPOINT = "http://localhost:4317"
 
 # Native mode constants

cli/planoai/core.py

@@ -19,7 +19,6 @@ from planoai.docker_cli import (
     stream_gateway_logs,
 )
 
-
 log = getLogger(__name__)
 
 

cli/planoai/main.py

@@ -3,6 +3,8 @@ import os
 import multiprocessing
 import subprocess
 import sys
+import contextlib
+import logging
 import rich_click as click
 from planoai import targets
 
@@ -33,6 +35,7 @@ from planoai.consts import (
     DEFAULT_OTEL_TRACING_GRPC_ENDPOINT,
     DEFAULT_NATIVE_OTEL_TRACING_GRPC_ENDPOINT,
     NATIVE_PID_FILE,
+    PLANO_RUN_DIR,
     PLANO_DOCKER_IMAGE,
     PLANO_DOCKER_NAME,
 )
@@ -101,6 +104,20 @@ def _print_cli_header(console) -> None:
     )
 
 
+@contextlib.contextmanager
+def _temporary_cli_log_level(level: str | None):
+    if level is None:
+        yield
+        return
+
+    current_level = logging.getLevelName(logging.getLogger().level).lower()
+    set_log_level(level)
+    try:
+        yield
+    finally:
+        set_log_level(current_level)
+
+
 def _print_missing_keys(console, missing_keys: list[str]) -> None:
     console.print(f"\n[red]✗[/red] [red]Missing API keys![/red]\n")
     for key in missing_keys:
@@ -293,163 +310,204 @@ def build(docker):
     help="Run Plano inside Docker instead of natively.",
     is_flag=True,
 )
-def up(file, path, foreground, with_tracing, tracing_port, docker):
+@click.option(
+    "--verbose",
+    "-v",
+    default=False,
+    help="Show detailed startup logs with timestamps.",
+    is_flag=True,
+)
+def up(file, path, foreground, with_tracing, tracing_port, docker, verbose):
     """Starts Plano."""
     from rich.status import Status
 
     console = _console()
     _print_cli_header(console)
 
-    # Use the utility function to find config file
-    plano_config_file = find_config_file(path, file)
+    with _temporary_cli_log_level("warning" if not verbose else None):
+        # Use the utility function to find config file
+        plano_config_file = find_config_file(path, file)
 
-    # Check if the file exists
-    if not os.path.exists(plano_config_file):
-        console.print(
-            f"[red]✗[/red] Config file not found: [dim]{plano_config_file}[/dim]"
-        )
-        sys.exit(1)
-
-    if not docker:
-        from planoai.native_runner import native_validate_config
-
-        with Status(
-            "[dim]Validating configuration[/dim]",
-            spinner="dots",
-            spinner_style="dim",
-        ):
-            try:
-                native_validate_config(plano_config_file)
-            except SystemExit:
-                console.print(f"[red]✗[/red] Validation failed")
-                sys.exit(1)
-            except Exception as e:
-                console.print(f"[red]✗[/red] Validation failed")
-                console.print(f"  [dim]{str(e).strip()}[/dim]")
-                sys.exit(1)
-    else:
-        with Status(
-            "[dim]Validating configuration (Docker)[/dim]",
-            spinner="dots",
-            spinner_style="dim",
-        ):
-            (
-                validation_return_code,
-                _,
-                validation_stderr,
-            ) = docker_validate_plano_schema(plano_config_file)
-
-        if validation_return_code != 0:
-            console.print(f"[red]✗[/red] Validation failed")
-            if validation_stderr:
-                console.print(f"  [dim]{validation_stderr.strip()}[/dim]")
+        # Check if the file exists
+        if not os.path.exists(plano_config_file):
+            console.print(
+                f"[red]✗[/red] Config file not found: [dim]{plano_config_file}[/dim]"
+            )
             sys.exit(1)
 
-    log.info("Configuration valid")
+        if not docker:
+            from planoai.native_runner import native_validate_config
 
-    # Set up environment
-    default_otel = (
-        DEFAULT_OTEL_TRACING_GRPC_ENDPOINT
-        if docker
-        else DEFAULT_NATIVE_OTEL_TRACING_GRPC_ENDPOINT
-    )
-    env_stage = {
-        "OTEL_TRACING_GRPC_ENDPOINT": default_otel,
-    }
-    env = os.environ.copy()
-    env.pop("PATH", None)
-
-    # Check access keys
-    access_keys = get_llm_provider_access_keys(plano_config_file=plano_config_file)
-    access_keys = set(access_keys)
-    access_keys = [item[1:] if item.startswith("$") else item for item in access_keys]
-
-    missing_keys = []
-    if access_keys:
-        if file:
-            app_env_file = os.path.join(os.path.dirname(os.path.abspath(file)), ".env")
+            with Status(
+                "[dim]Validating configuration[/dim]",
+                spinner="dots",
+                spinner_style="dim",
+            ):
+                try:
+                    native_validate_config(plano_config_file)
+                except SystemExit:
+                    console.print(f"[red]✗[/red] Validation failed")
+                    sys.exit(1)
+                except Exception as e:
+                    console.print(f"[red]✗[/red] Validation failed")
+                    console.print(f"  [dim]{str(e).strip()}[/dim]")
+                    sys.exit(1)
         else:
-            app_env_file = os.path.abspath(os.path.join(path, ".env"))
+            with Status(
+                "[dim]Validating configuration (Docker)[/dim]",
+                spinner="dots",
+                spinner_style="dim",
+            ):
+                (
+                    validation_return_code,
+                    _,
+                    validation_stderr,
+                ) = docker_validate_plano_schema(plano_config_file)
 
-        if not os.path.exists(app_env_file):
-            for access_key in access_keys:
-                if env.get(access_key) is None:
-                    missing_keys.append(access_key)
-                else:
-                    env_stage[access_key] = env.get(access_key)
-        else:
-            env_file_dict = load_env_file_to_dict(app_env_file)
-            for access_key in access_keys:
-                if env_file_dict.get(access_key) is None:
-                    missing_keys.append(access_key)
-                else:
-                    env_stage[access_key] = env_file_dict[access_key]
-
-    if missing_keys:
-        _print_missing_keys(console, missing_keys)
-        sys.exit(1)
-
-    # Pass log level to the Docker container — supervisord uses LOG_LEVEL
-    # to set RUST_LOG (brightstaff) and envoy component log levels
-    env_stage["LOG_LEVEL"] = os.environ.get("LOG_LEVEL", "info")
-
-    # Start the local OTLP trace collector if --with-tracing is set
-    trace_server = None
-    if with_tracing:
-        if _is_port_in_use(tracing_port):
-            # A listener is already running (e.g. `planoai trace listen`)
-            console.print(
-                f"[green]✓[/green] Trace collector already running on port [cyan]{tracing_port}[/cyan]"
-            )
-        else:
-            try:
-                trace_server = start_trace_listener_background(grpc_port=tracing_port)
-                console.print(
-                    f"[green]✓[/green] Trace collector listening on [cyan]0.0.0.0:{tracing_port}[/cyan]"
-                )
-            except Exception as e:
-                console.print(
-                    f"[red]✗[/red] Failed to start trace collector on port {tracing_port}: {e}"
-                )
-                console.print(
-                    f"\n[dim]Check if another process is using port {tracing_port}:[/dim]"
-                )
-                console.print(f"  [cyan]lsof -i :{tracing_port}[/cyan]")
-                console.print(f"\n[dim]Or use a different port:[/dim]")
-                console.print(
-                    f"  [cyan]planoai up --with-tracing --tracing-port 4318[/cyan]\n"
-                )
+            if validation_return_code != 0:
+                console.print(f"[red]✗[/red] Validation failed")
+                if validation_stderr:
+                    console.print(f"  [dim]{validation_stderr.strip()}[/dim]")
                 sys.exit(1)
 
-        # Update the OTEL endpoint so the gateway sends traces to the right port
-        tracing_host = "host.docker.internal" if docker else "localhost"
-        otel_endpoint = f"http://{tracing_host}:{tracing_port}"
-        env_stage["OTEL_TRACING_GRPC_ENDPOINT"] = otel_endpoint
+        log.info("Configuration valid")
 
-    env.update(env_stage)
-    try:
-        if not docker:
-            from planoai.native_runner import start_native
+        # Set up environment
+        default_otel = (
+            DEFAULT_OTEL_TRACING_GRPC_ENDPOINT
+            if docker
+            else DEFAULT_NATIVE_OTEL_TRACING_GRPC_ENDPOINT
+        )
+        env_stage = {
+            "OTEL_TRACING_GRPC_ENDPOINT": default_otel,
+        }
+        env = os.environ.copy()
+        env.pop("PATH", None)
 
-            start_native(
-                plano_config_file, env, foreground=foreground, with_tracing=with_tracing
-            )
-        else:
-            start_plano(plano_config_file, env, foreground=foreground)
+        # Check access keys
+        access_keys = get_llm_provider_access_keys(plano_config_file=plano_config_file)
+        access_keys = set(access_keys)
+        access_keys = [
+            item[1:] if item.startswith("$") else item for item in access_keys
+        ]
 
-        # When tracing is enabled but --foreground is not, keep the process
-        # alive so the OTLP collector continues to receive spans.
-        if trace_server is not None and not foreground:
-            console.print(
-                f"[dim]Plano is running. Trace collector active on port {tracing_port}. Press Ctrl+C to stop.[/dim]"
-            )
-            trace_server.wait_for_termination()
-    except KeyboardInterrupt:
-        if trace_server is not None:
-            console.print(f"\n[dim]Stopping trace collector...[/dim]")
-    finally:
-        if trace_server is not None:
-            trace_server.stop(grace=2)
+        missing_keys = []
+        if access_keys:
+            if file:
+                app_env_file = os.path.join(
+                    os.path.dirname(os.path.abspath(file)), ".env"
+                )
+            else:
+                app_env_file = os.path.abspath(os.path.join(path, ".env"))
+
+            if not os.path.exists(app_env_file):
+                for access_key in access_keys:
+                    if env.get(access_key) is None:
+                        missing_keys.append(access_key)
+                    else:
+                        env_stage[access_key] = env.get(access_key)
+            else:
+                env_file_dict = load_env_file_to_dict(app_env_file)
+                for access_key in access_keys:
+                    if env_file_dict.get(access_key) is None:
+                        missing_keys.append(access_key)
+                    else:
+                        env_stage[access_key] = env_file_dict[access_key]
+
+        if missing_keys:
+            _print_missing_keys(console, missing_keys)
+            sys.exit(1)
+
+        # Pass log level to the Docker container — supervisord uses LOG_LEVEL
+        # to set RUST_LOG (brightstaff) and envoy component log levels
+        env_stage["LOG_LEVEL"] = os.environ.get("LOG_LEVEL", "info")
+
+        # Start the local OTLP trace collector if --with-tracing is set
+        trace_server = None
+        if with_tracing:
+            if _is_port_in_use(tracing_port):
+                # A listener is already running (e.g. `planoai trace listen`)
+                console.print(
+                    f"[green]✓[/green] Trace collector already running on port [cyan]{tracing_port}[/cyan]"
+                )
+            else:
+                try:
+                    trace_server = start_trace_listener_background(
+                        grpc_port=tracing_port
+                    )
+                    console.print(
+                        f"[green]✓[/green] Trace collector listening on [cyan]0.0.0.0:{tracing_port}[/cyan]"
+                    )
+                except Exception as e:
+                    console.print(
+                        f"[red]✗[/red] Failed to start trace collector on port {tracing_port}: {e}"
+                    )
+                    console.print(
+                        f"\n[dim]Check if another process is using port {tracing_port}:[/dim]"
+                    )
+                    console.print(f"  [cyan]lsof -i :{tracing_port}[/cyan]")
+                    console.print(f"\n[dim]Or use a different port:[/dim]")
+                    console.print(
+                        f"  [cyan]planoai up --with-tracing --tracing-port 4318[/cyan]\n"
+                    )
+                    sys.exit(1)
+
+            # Update the OTEL endpoint so the gateway sends traces to the right port
+            tracing_host = "host.docker.internal" if docker else "localhost"
+            otel_endpoint = f"http://{tracing_host}:{tracing_port}"
+            env_stage["OTEL_TRACING_GRPC_ENDPOINT"] = otel_endpoint
+
+        env.update(env_stage)
+        try:
+            if not docker:
+                from planoai.native_runner import start_native
+
+                if not verbose:
+                    with Status(
+                        f"[{PLANO_COLOR}]Starting Plano...[/{PLANO_COLOR}]",
+                        spinner="dots",
+                    ) as status:
+
+                        def _update_progress(message: str) -> None:
+                            console.print(f"[dim]{message}[/dim]")
+
+                        start_native(
+                            plano_config_file,
+                            env,
+                            foreground=foreground,
+                            with_tracing=with_tracing,
+                            progress_callback=_update_progress,
+                        )
+                    console.print("")
+                    console.print(
+                        "[green]✓[/green] Plano is running! [dim](native mode)[/dim]"
+                    )
+                    log_dir = os.path.join(PLANO_RUN_DIR, "logs")
+                    console.print(f"Logs: {log_dir}")
+                    console.print("Run 'planoai down' to stop.")
+                else:
+                    start_native(
+                        plano_config_file,
+                        env,
+                        foreground=foreground,
+                        with_tracing=with_tracing,
+                    )
+            else:
+                start_plano(plano_config_file, env, foreground=foreground)
+
+            # When tracing is enabled but --foreground is not, keep the process
+            # alive so the OTLP collector continues to receive spans.
+            if trace_server is not None and not foreground:
+                console.print(
+                    f"[dim]Plano is running. Trace collector active on port {tracing_port}. Press Ctrl+C to stop.[/dim]"
+                )
+                trace_server.wait_for_termination()
+        except KeyboardInterrupt:
+            if trace_server is not None:
+                console.print(f"\n[dim]Stopping trace collector...[/dim]")
+        finally:
+            if trace_server is not None:
+                trace_server.stop(grace=2)
 
 
 @click.command()
@@ -459,25 +517,46 @@ def up(file, path, foreground, with_tracing, tracing_port, docker):
     help="Stop a Docker-based Plano instance.",
     is_flag=True,
 )
-def down(docker):
+@click.option(
+    "--verbose",
+    "-v",
+    default=False,
+    help="Show detailed shutdown logs with timestamps.",
+    is_flag=True,
+)
+def down(docker, verbose):
     """Stops Plano."""
     console = _console()
     _print_cli_header(console)
 
-    if not docker:
-        from planoai.native_runner import stop_native
+    with _temporary_cli_log_level("warning" if not verbose else None):
+        if not docker:
+            from planoai.native_runner import stop_native
 
-        with console.status(
-            f"[{PLANO_COLOR}]Shutting down Plano...[/{PLANO_COLOR}]",
-            spinner="dots",
-        ):
-            stop_native()
-    else:
-        with console.status(
-            f"[{PLANO_COLOR}]Shutting down Plano (Docker)...[/{PLANO_COLOR}]",
-            spinner="dots",
-        ):
-            stop_docker_container()
+            with console.status(
+                f"[{PLANO_COLOR}]Shutting down Plano...[/{PLANO_COLOR}]",
+                spinner="dots",
+            ):
+                stopped = stop_native()
+            if not verbose:
+                if stopped:
+                    console.print(
+                        "[green]✓[/green] Plano stopped! [dim](native mode)[/dim]"
+                    )
+                else:
+                    console.print(
+                        "[dim]No Plano instance was running (native mode)[/dim]"
+                    )
+        else:
+            with console.status(
+                f"[{PLANO_COLOR}]Shutting down Plano (Docker)...[/{PLANO_COLOR}]",
+                spinner="dots",
+            ):
+                stop_docker_container()
+            if not verbose:
+                console.print(
+                    "[green]✓[/green] Plano stopped! [dim](docker mode)[/dim]"
+                )
 
 
 @click.command()

cli/planoai/native_runner.py

@@ -6,6 +6,7 @@ import signal
 import subprocess
 import sys
 import time
+from collections.abc import Callable
 
 from planoai.consts import (
     NATIVE_PID_FILE,
@@ -157,7 +158,13 @@ def render_native_config(plano_config_file, env, with_tracing=False):
     return envoy_config_path, plano_config_rendered_path
 
 
-def start_native(plano_config_file, env, foreground=False, with_tracing=False):
+def start_native(
+    plano_config_file,
+    env,
+    foreground=False,
+    with_tracing=False,
+    progress_callback: Callable[[str], None] | None = None,
+):
     """Start Envoy and brightstaff natively."""
     from planoai.core import _get_gateway_ports
 
@@ -174,6 +181,8 @@ def start_native(plano_config_file, env, foreground=False, with_tracing=False):
     )
 
     log.info("Configuration rendered")
+    if progress_callback:
+        progress_callback("Configuration valid...")
 
     log_dir = os.path.join(PLANO_RUN_DIR, "logs")
     os.makedirs(log_dir, exist_ok=True)
@@ -194,6 +203,8 @@ def start_native(plano_config_file, env, foreground=False, with_tracing=False):
         os.path.join(log_dir, "brightstaff.log"),
     )
     log.info(f"Started brightstaff (PID {brightstaff_pid})")
+    if progress_callback:
+        progress_callback(f"Started brightstaff (PID: {brightstaff_pid})...")
 
     # Start envoy
     envoy_pid = _daemon_exec(
@@ -210,6 +221,8 @@ def start_native(plano_config_file, env, foreground=False, with_tracing=False):
         os.path.join(log_dir, "envoy.log"),
     )
     log.info(f"Started envoy (PID {envoy_pid})")
+    if progress_callback:
+        progress_callback(f"Started envoy (PID: {envoy_pid})...")
 
     # Save PIDs
     os.makedirs(PLANO_RUN_DIR, exist_ok=True)
@@ -225,6 +238,8 @@ def start_native(plano_config_file, env, foreground=False, with_tracing=False):
     # Health check
     gateway_ports = _get_gateway_ports(plano_config_file)
     log.info("Waiting for listeners to become healthy...")
+    if progress_callback:
+        progress_callback("Waiting for listeners to become healthy...")
 
     start_time = time.time()
     timeout = 60
@@ -353,10 +368,15 @@ def _kill_pid(pid):
 
 
 def stop_native():
-    """Stop natively-running Envoy and brightstaff processes."""
+    """Stop natively-running Envoy and brightstaff processes.
+
+    Returns:
+        bool: True if at least one process was running and received a stop signal,
+        False if no running native Plano process was found.
+    """
     if not os.path.exists(NATIVE_PID_FILE):
         log.info("No native Plano instance found (PID file missing).")
-        return
+        return False
 
     with open(NATIVE_PID_FILE, "r") as f:
         pids = json.load(f)
@@ -364,12 +384,14 @@ def stop_native():
     envoy_pid = pids.get("envoy_pid")
     brightstaff_pid = pids.get("brightstaff_pid")
 
+    had_running_process = False
     for name, pid in [("envoy", envoy_pid), ("brightstaff", brightstaff_pid)]:
         if pid is None:
             continue
         try:
             os.kill(pid, signal.SIGTERM)
             log.info(f"Sent SIGTERM to {name} (PID {pid})")
+            had_running_process = True
         except ProcessLookupError:
             log.info(f"{name} (PID {pid}) already stopped")
             continue
@@ -394,7 +416,11 @@ def stop_native():
                 pass
 
     os.unlink(NATIVE_PID_FILE)
-    log.info("Plano stopped (native mode).")
+    if had_running_process:
+        log.info("Plano stopped (native mode).")
+    else:
+        log.info("No native Plano instance was running.")
+    return had_running_process
 
 
 def native_validate_config(plano_config_file):

cli/planoai/targets.py

@@ -189,26 +189,26 @@ def get_function_parameters(node: ast.FunctionDef, tree: ast.AST) -> list:
                 if isinstance(
                     arg.annotation.value, ast.Name
                 ) and arg.annotation.value.id in ["list", "tuple", "set", "dict"]:
-                    param_info[
-                        "type"
-                    ] = f"{arg.annotation.value.id}"  # e.g., "List", "Tuple", etc.
+                    param_info["type"] = (
+                        f"{arg.annotation.value.id}"  # e.g., "List", "Tuple", etc.
+                    )
                 else:
                     param_info["type"] = "[UNKNOWN - PLEASE FIX]"
 
             # Default for unknown types
             else:
-                param_info[
-                    "type"
-                ] = "[UNKNOWN - PLEASE FIX]"  # If unable to detect type
+                param_info["type"] = (
+                    "[UNKNOWN - PLEASE FIX]"  # If unable to detect type
+                )
 
             # Handle default values
             if default is not None:
                 if isinstance(default, ast.Constant) or isinstance(
                     default, ast.NameConstant
                 ):
-                    param_info[
-                        "default"
-                    ] = default.value  # Use the default value directly
+                    param_info["default"] = (
+                        default.value
+                    )  # Use the default value directly
                 else:
                     param_info["default"] = "[UNKNOWN DEFAULT]"  # Unknown default type
                 param_info["required"] = False  # Optional since it has a default value

cli/planoai/utils.py

@@ -6,7 +6,6 @@ import yaml
 import logging
 from planoai.consts import PLANO_DOCKER_NAME
 
-
 # Standard env var for log level across all Plano components
 LOG_LEVEL_ENV = "LOG_LEVEL"
 

cli/pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "planoai"
-version = "0.4.14"
+version = "0.4.16"
 description = "Python-based CLI tool to manage Plano."
 authors = [{name = "Katanemo Labs, Inc."}]
 readme = "README.md"
@@ -13,7 +13,7 @@ dependencies = [
     "opentelemetry-proto>=1.20.0",
     "questionary>=2.1.1,<3.0.0",
     "pyyaml>=6.0.2,<7.0.0",
-    "requests>=2.31.0,<3.0.0",
+    "requests>=2.33.0,<3.0.0",
     "urllib3>=2.6.3",
     "rich>=14.2.0",
     "rich-click>=1.9.5",

cli/uv.lock

@@ -337,7 +337,7 @@ wheels = [
 
 [[package]]
 name = "planoai"
-version = "0.4.14"
+version = "0.4.16"
 source = { editable = "." }
 dependencies = [
     { name = "click" },
@@ -373,7 +373,7 @@ requires-dist = [
     { name = "pytest", marker = "extra == 'dev'", specifier = ">=8.4.1,<9.0.0" },
     { name = "pyyaml", specifier = ">=6.0.2,<7.0.0" },
     { name = "questionary", specifier = ">=2.1.1,<3.0.0" },
-    { name = "requests", specifier = ">=2.31.0,<3.0.0" },
+    { name = "requests", specifier = ">=2.33.0,<3.0.0" },
     { name = "rich", specifier = ">=14.2.0" },
     { name = "rich-click", specifier = ">=1.9.5" },
     { name = "urllib3", specifier = ">=2.6.3" },
@@ -421,11 +421,11 @@ wheels = [
 
 [[package]]
 name = "pygments"
-version = "2.19.2"
+version = "2.20.0"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/b0/77/a5b8c569bf593b0140bde72ea885a803b82086995367bf2037de0159d924/pygments-2.19.2.tar.gz", hash = "sha256:636cb2477cec7f8952536970bc533bc43743542f70392ae026374600add5b887", size = 4968631, upload-time = "2025-06-21T13:39:12.283Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/c3/b2/bc9c9196916376152d655522fdcebac55e66de6603a76a02bca1b6414f6c/pygments-2.20.0.tar.gz", hash = "sha256:6757cd03768053ff99f3039c1a36d6c0aa0b263438fcab17520b30a303a82b5f", size = 4955991, upload-time = "2026-03-29T13:29:33.898Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl", hash = "sha256:86540386c03d588bb81d44bc3928634ff26449851e99741617ecb9037ee5ec0b", size = 1225217, upload-time = "2025-06-21T13:39:07.939Z" },
+    { url = "https://files.pythonhosted.org/packages/f4/7e/a72dd26f3b0f4f2bf1dd8923c85f7ceb43172af56d63c7383eb62b332364/pygments-2.20.0-py3-none-any.whl", hash = "sha256:81a9e26dd42fd28a23a2d169d86d7ac03b46e2f8b59ed4698fb4785f946d0176", size = 1231151, upload-time = "2026-03-29T13:29:30.038Z" },
 ]
 
 [[package]]
@@ -518,7 +518,7 @@ wheels = [
 
 [[package]]
 name = "requests"
-version = "2.32.5"
+version = "2.33.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "certifi" },
@@ -526,9 +526,9 @@ dependencies = [
     { name = "idna" },
     { name = "urllib3" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/c9/74/b3ff8e6c8446842c3f5c837e9c3dfcfe2018ea6ecef224c710c85ef728f4/requests-2.32.5.tar.gz", hash = "sha256:dbba0bac56e100853db0ea71b82b4dfd5fe2bf6d3754a8893c3af500cec7d7cf", size = 134517, upload-time = "2025-08-18T20:46:02.573Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/5f/a4/98b9c7c6428a668bf7e42ebb7c79d576a1c3c1e3ae2d47e674b468388871/requests-2.33.1.tar.gz", hash = "sha256:18817f8c57c6263968bc123d237e3b8b08ac046f5456bd1e307ee8f4250d3517", size = 134120, upload-time = "2026-03-30T16:09:15.531Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl", hash = "sha256:2462f94637a34fd532264295e186976db0f5d453d1cdd31473c85a6a161affb6", size = 64738, upload-time = "2025-08-18T20:46:00.542Z" },
+    { url = "https://files.pythonhosted.org/packages/d7/8e/7540e8a2036f79a125c1d2ebadf69ed7901608859186c856fa0388ef4197/requests-2.33.1-py3-none-any.whl", hash = "sha256:4e6d1ef462f3626a1f0a0a9c42dd93c63bad33f9f1c1937509b8c5c8718ab56a", size = 64947, upload-time = "2026-03-30T16:09:13.83Z" },
 ]
 
 [[package]]

config/plano_config_schema.yaml

@@ -9,6 +9,7 @@ properties:
       - 0.1-beta
       - 0.2.0
       - v0.3.0
+      - v0.4.0
 
   agents:
     type: array
@@ -486,6 +487,88 @@ properties:
         additionalProperties: false
         required:
           - jailbreak
+  routing_preferences:
+    type: array
+    items:
+      type: object
+      properties:
+        name:
+          type: string
+        description:
+          type: string
+        models:
+          type: array
+          items:
+            type: string
+          minItems: 1
+        selection_policy:
+          type: object
+          properties:
+            prefer:
+              type: string
+              enum:
+                - cheapest
+                - fastest
+                - none
+          additionalProperties: false
+          required:
+            - prefer
+      additionalProperties: false
+      required:
+        - name
+        - description
+        - models
+
+  model_metrics_sources:
+    type: array
+    items:
+      oneOf:
+        - type: object
+          properties:
+            type:
+              type: string
+              const: cost
+            provider:
+              type: string
+              enum:
+                - digitalocean
+            refresh_interval:
+              type: integer
+              minimum: 1
+              description: "Refresh interval in seconds"
+            model_aliases:
+              type: object
+              description: "Map DO catalog keys (lowercase(creator)/model_id) to Plano model names used in routing_preferences. Example: 'openai/openai-gpt-oss-120b: openai/gpt-4o'"
+              additionalProperties:
+                type: string
+          required:
+            - type
+            - provider
+          additionalProperties: false
+        - type: object
+          properties:
+            type:
+              type: string
+              const: latency
+            provider:
+              type: string
+              enum:
+                - prometheus
+            url:
+              type: string
+            query:
+              type: string
+            refresh_interval:
+              type: integer
+              minimum: 1
+              description: "Refresh interval in seconds"
+          required:
+            - type
+            - provider
+            - url
+            - query
+          additionalProperties: false
+
 additionalProperties: false
 required:
   - version

config/validate_plano_config.sh

@@ -1,6 +1,16 @@
 #!/bin/bash
 
 SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+REPO_ROOT="$(cd "$SCRIPT_DIR/.." && pwd)"
+CLI_DIR="$REPO_ROOT/cli"
+
+# Use uv run if available and cli/ has a pyproject.toml, otherwise fall back to bare python
+if command -v uv &> /dev/null && [ -f "$CLI_DIR/pyproject.toml" ]; then
+  PYTHON_CMD="uv run --directory $CLI_DIR python"
+else
+  PYTHON_CMD="python"
+fi
+
 failed_files=()
 
 for file in $(find . -name config.yaml -o -name plano_config_full_reference.yaml); do
@@ -14,7 +24,7 @@ for file in $(find . -name config.yaml -o -name plano_config_full_reference.yaml
   ENVOY_CONFIG_TEMPLATE_FILE="envoy.template.yaml" \
   PLANO_CONFIG_FILE_RENDERED="$rendered_file" \
   ENVOY_CONFIG_FILE_RENDERED="/dev/null" \
-  python -m planoai.config_generator 2>&1 > /dev/null
+  $PYTHON_CMD -m planoai.config_generator 2>&1 > /dev/null
 
   if [ $? -ne 0 ]; then
     echo "Validation failed for $file"

crates/brightstaff/src/handlers/function_calling.rs

@@ -762,7 +762,7 @@ impl ArchFunctionHandler {
 
         // Keep system message if present
         if let Some(first) = messages.first() {
-            if first.role == Role::System {
+            if first.role == Role::System || first.role == Role::Developer {
                 if let Some(MessageContent::Text(content)) = &first.content {
                     num_tokens += content.len() / 4; // Approximate 4 chars per token
                 }

crates/brightstaff/src/handlers/llm/mod.rs

@@ -38,6 +38,8 @@ use crate::tracing::{
 };
 use model_selection::router_chat_get_upstream_model;
 
+const PERPLEXITY_PROVIDER_PREFIX: &str = "perplexity/";
+
 pub async fn llm_chat(
     request: Request<hyper::body::Incoming>,
     state: Arc<AppState>,
@@ -134,7 +136,7 @@ async fn llm_chat_inner(
         temperature,
         tool_names,
         user_message_preview,
-        inline_routing_policy,
+        inline_routing_preferences,
         client_api,
         provider_id,
     } = parsed;
@@ -284,7 +286,7 @@ async fn llm_chat_inner(
                 &traceparent,
                 &request_path,
                 &request_id,
-                inline_routing_policy,
+                inline_routing_preferences,
             )
             .await
         }
@@ -357,7 +359,7 @@ struct PreparedRequest {
     temperature: Option<f32>,
     tool_names: Option<Vec<String>>,
     user_message_preview: Option<String>,
-    inline_routing_policy: Option<Vec<common::configuration::ModelUsagePreference>>,
+    inline_routing_preferences: Option<Vec<common::configuration::TopLevelRoutingPreference>>,
     client_api: Option<SupportedAPIsFromClient>,
     provider_id: hermesllm::ProviderId,
 }
@@ -386,16 +388,14 @@ async fn parse_and_validate_request(
         "request body received"
     );
 
-    // Extract routing_policy from request body if present
-    let (chat_request_bytes, inline_routing_policy) =
-        crate::handlers::routing_service::extract_routing_policy(&raw_bytes, false).map_err(
-            |err| {
-                warn!(error = %err, "failed to parse request JSON");
-                let mut r = Response::new(full(format!("Failed to parse request: {}", err)));
-                *r.status_mut() = StatusCode::BAD_REQUEST;
-                r
-            },
-        )?;
+    // Extract routing_preferences from request body if present
+    let (chat_request_bytes, inline_routing_preferences) =
+        crate::handlers::routing_service::extract_routing_policy(&raw_bytes).map_err(|err| {
+            warn!(error = %err, "failed to parse request JSON");
+            let mut r = Response::new(full(format!("Failed to parse request: {}", err)));
+            *r.status_mut() = StatusCode::BAD_REQUEST;
+            r
+        })?;
 
     let api_type = SupportedAPIsFromClient::from_endpoint(request_path).ok_or_else(|| {
         warn!(path = %request_path, "unsupported endpoint");
@@ -420,7 +420,7 @@ async fn parse_and_validate_request(
     let temperature = client_request.get_temperature();
     let is_streaming_request = client_request.is_streaming();
     let alias_resolved_model = resolve_model_alias(&model_from_request, model_aliases);
-    let (provider_id, _) = get_provider_info(llm_providers, &alias_resolved_model).await;
+    let (provider_id, _, _) = get_provider_info(llm_providers, &alias_resolved_model).await;
 
     // Validate model exists in configuration
     if llm_providers
@@ -473,7 +473,7 @@ async fn parse_and_validate_request(
         temperature,
         tool_names,
         user_message_preview,
-        inline_routing_policy,
+        inline_routing_preferences,
         client_api,
         provider_id,
     })
@@ -775,7 +775,8 @@ async fn get_upstream_path(
     resolved_model: &str,
     is_streaming: bool,
 ) -> String {
-    let (provider_id, base_url_path_prefix) = get_provider_info(llm_providers, model_name).await;
+    let (provider_id, base_url_path_prefix, use_unversioned_paths) =
+        get_provider_info(llm_providers, model_name).await;
 
     let Some(client_api) = SupportedAPIsFromClient::from_endpoint(request_path) else {
         return request_path.to_string();
@@ -787,6 +788,7 @@ async fn get_upstream_path(
         resolved_model,
         is_streaming,
         base_url_path_prefix.as_deref(),
+        use_unversioned_paths,
     )
 }
 
@@ -794,21 +796,124 @@ async fn get_upstream_path(
 async fn get_provider_info(
     llm_providers: &Arc<RwLock<LlmProviders>>,
     model_name: &str,
-) -> (hermesllm::ProviderId, Option<String>) {
+) -> (hermesllm::ProviderId, Option<String>, bool) {
     let providers_lock = llm_providers.read().await;
 
     if let Some(provider) = providers_lock.get(model_name) {
         let provider_id = provider.provider_interface.to_provider_id();
         let prefix = provider.base_url_path_prefix.clone();
-        return (provider_id, prefix);
+        let use_unversioned_paths = provider.name.starts_with(PERPLEXITY_PROVIDER_PREFIX);
+        return (provider_id, prefix, use_unversioned_paths);
     }
 
     if let Some(provider) = providers_lock.default() {
         let provider_id = provider.provider_interface.to_provider_id();
         let prefix = provider.base_url_path_prefix.clone();
-        (provider_id, prefix)
+        let use_unversioned_paths = provider.name.starts_with(PERPLEXITY_PROVIDER_PREFIX);
+        (provider_id, prefix, use_unversioned_paths)
     } else {
         warn!("No default provider found, falling back to OpenAI");
-        (hermesllm::ProviderId::OpenAI, None)
+        (hermesllm::ProviderId::OpenAI, None, false)
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::{get_provider_info, get_upstream_path};
+    use common::configuration::{LlmProvider, LlmProviderType};
+    use common::llm_providers::LlmProviders;
+    use hermesllm::apis::OpenAIApi;
+    use hermesllm::clients::SupportedAPIsFromClient;
+    use std::sync::Arc;
+    use tokio::sync::RwLock;
+
+    fn build_provider(name: &str, model: &str) -> LlmProvider {
+        LlmProvider {
+            name: name.to_string(),
+            provider_interface: LlmProviderType::OpenAI,
+            access_key: Some("test_key".to_string()),
+            model: Some(model.to_string()),
+            default: Some(false),
+            ..Default::default()
+        }
+    }
+
+    fn providers_lock(providers: Vec<LlmProvider>) -> Arc<RwLock<LlmProviders>> {
+        Arc::new(RwLock::new(
+            LlmProviders::try_from(providers).expect("test providers should be valid"),
+        ))
+    }
+
+    #[tokio::test]
+    async fn test_get_provider_info_marks_perplexity_as_unversioned() {
+        let providers = providers_lock(vec![build_provider("perplexity/sonar-pro", "sonar-pro")]);
+
+        let (provider_id, prefix, use_unversioned_paths) =
+            get_provider_info(&providers, "perplexity/sonar-pro").await;
+
+        assert_eq!(provider_id, hermesllm::ProviderId::OpenAI);
+        assert_eq!(prefix, None);
+        assert!(use_unversioned_paths);
+    }
+
+    #[tokio::test]
+    async fn test_get_upstream_path_for_perplexity_uses_unversioned_chat_endpoint() {
+        let providers = providers_lock(vec![build_provider("perplexity/sonar-pro", "sonar-pro")]);
+
+        let upstream_path = get_upstream_path(
+            &providers,
+            "perplexity/sonar-pro",
+            "/v1/chat/completions",
+            "sonar-pro",
+            false,
+        )
+        .await;
+
+        assert_eq!(upstream_path, "/chat/completions");
+    }
+
+    #[tokio::test]
+    async fn test_get_upstream_path_for_non_perplexity_keeps_v1_chat_endpoint() {
+        let providers = providers_lock(vec![build_provider("openai/gpt-4o-mini", "gpt-4o-mini")]);
+
+        let upstream_path = get_upstream_path(
+            &providers,
+            "openai/gpt-4o-mini",
+            "/v1/chat/completions",
+            "gpt-4o-mini",
+            false,
+        )
+        .await;
+
+        assert_eq!(upstream_path, "/v1/chat/completions");
+    }
+
+    #[tokio::test]
+    async fn test_perplexity_with_and_without_versioning_paths() {
+        let providers = providers_lock(vec![build_provider("perplexity/sonar-pro", "sonar-pro")]);
+
+        // This is the path Plano should use for Perplexity (works).
+        let success_path = get_upstream_path(
+            &providers,
+            "perplexity/sonar-pro",
+            "/v1/chat/completions",
+            "sonar-pro",
+            false,
+        )
+        .await;
+        assert_eq!(success_path, "/chat/completions");
+
+        // This is the generic OpenAI default path; for Perplexity this would 404.
+        let fail_path = SupportedAPIsFromClient::OpenAIChatCompletions(OpenAIApi::ChatCompletions)
+            .target_endpoint_for_provider(
+                &hermesllm::ProviderId::OpenAI,
+                "/v1/chat/completions",
+                "sonar-pro",
+                false,
+                None,
+                false,
+            );
+        assert_eq!(fail_path, "/v1/chat/completions");
+        assert_ne!(success_path, fail_path);
     }
 }

crates/brightstaff/src/handlers/llm/model_selection.rs

@@ -1,6 +1,6 @@
-use common::configuration::ModelUsagePreference;
+use common::configuration::TopLevelRoutingPreference;
 use hermesllm::clients::endpoints::SupportedUpstreamAPIs;
-use hermesllm::{ProviderRequest, ProviderRequestType};
+use hermesllm::ProviderRequestType;
 use hyper::StatusCode;
 use std::sync::Arc;
 use tracing::{debug, info, warn};
@@ -10,7 +10,10 @@ use crate::streaming::truncate_message;
 use crate::tracing::routing;
 
 pub struct RoutingResult {
+    /// Primary model to use (first in the ranked list).
     pub model_name: String,
+    /// Full ranked list — use subsequent entries as fallbacks on 429/5xx.
+    pub models: Vec<String>,
     pub route_name: Option<String>,
 }
 
@@ -39,11 +42,8 @@ pub async fn router_chat_get_upstream_model(
     traceparent: &str,
     request_path: &str,
     request_id: &str,
-    inline_usage_preferences: Option<Vec<ModelUsagePreference>>,
+    inline_routing_preferences: Option<Vec<TopLevelRoutingPreference>>,
 ) -> Result<RoutingResult, RoutingError> {
-    // Clone metadata for routing before converting (which consumes client_request)
-    let routing_metadata = client_request.metadata().clone();
-
     // Convert to ChatCompletionsRequest for routing (regardless of input type)
     let chat_request = match ProviderRequestType::try_from((
         client_request,
@@ -78,22 +78,6 @@ pub async fn router_chat_get_upstream_model(
         "router request"
     );
 
-    // Use inline preferences if provided, otherwise fall back to metadata extraction
-    let usage_preferences: Option<Vec<ModelUsagePreference>> = if inline_usage_preferences.is_some()
-    {
-        inline_usage_preferences
-    } else {
-        let usage_preferences_str: Option<String> =
-            routing_metadata.as_ref().and_then(|metadata| {
-                metadata
-                    .get("plano_preference_config")
-                    .map(|value| value.to_string())
-            });
-        usage_preferences_str
-            .as_ref()
-            .and_then(|s| serde_yaml::from_str(s).ok())
-    };
-
     // Prepare log message with latest message from chat request
     let latest_message_for_log = chat_request
         .messages
@@ -107,7 +91,6 @@ pub async fn router_chat_get_upstream_model(
     let latest_message_for_log = truncate_message(&latest_message_for_log, 50);
 
     info!(
-        has_usage_preferences = usage_preferences.is_some(),
         path = %request_path,
         latest_message = %latest_message_for_log,
         "processing router request"
@@ -121,7 +104,7 @@ pub async fn router_chat_get_upstream_model(
         .determine_route(
             &chat_request.messages,
             traceparent,
-            usage_preferences,
+            inline_routing_preferences,
             request_id,
         )
         .await;
@@ -132,10 +115,12 @@ pub async fn router_chat_get_upstream_model(
 
     match routing_result {
         Ok(route) => match route {
-            Some((route_name, model_name)) => {
+            Some((route_name, ranked_models)) => {
+                let model_name = ranked_models.first().cloned().unwrap_or_default();
                 current_span.record("route.selected_model", model_name.as_str());
                 Ok(RoutingResult {
                     model_name,
+                    models: ranked_models,
                     route_name: Some(route_name),
                 })
             }
@@ -147,6 +132,7 @@ pub async fn router_chat_get_upstream_model(
 
                 Ok(RoutingResult {
                     model_name: "none".to_string(),
+                    models: vec!["none".to_string()],
                     route_name: None,
                 })
             }

crates/brightstaff/src/handlers/routing_service.rs

@@ -1,5 +1,5 @@
 use bytes::Bytes;
-use common::configuration::{ModelUsagePreference, SpanAttributes};
+use common::configuration::{SpanAttributes, TopLevelRoutingPreference};
 use common::consts::{REQUEST_ID_HEADER, SESSION_ID_HEADER};
 use common::errors::BrightStaffError;
 use hermesllm::clients::SupportedAPIsFromClient;
@@ -15,56 +15,42 @@ use crate::handlers::llm::model_selection::router_chat_get_upstream_model;
 use crate::router::llm::RouterService;
 use crate::tracing::{collect_custom_trace_attributes, operation_component, set_service_name};
 
-const ROUTING_POLICY_SIZE_WARNING_BYTES: usize = 5120;
-
-/// Extracts `routing_policy` from a JSON body, returning the cleaned body bytes
-/// and parsed preferences. The `routing_policy` field is removed from the JSON
-/// before re-serializing so downstream parsers don't see the non-standard field.
-///
-/// If `warn_on_size` is true, logs a warning when the serialized policy exceeds 5KB.
+/// Extracts `routing_preferences` from a JSON body, returning the cleaned body bytes
+/// and the parsed preferences. The field is removed from the JSON before re-serializing
+/// so downstream parsers don't see it.
 pub fn extract_routing_policy(
     raw_bytes: &[u8],
-    warn_on_size: bool,
-) -> Result<(Bytes, Option<Vec<ModelUsagePreference>>), String> {
+) -> Result<(Bytes, Option<Vec<TopLevelRoutingPreference>>), String> {
     let mut json_body: serde_json::Value = serde_json::from_slice(raw_bytes)
         .map_err(|err| format!("Failed to parse JSON: {}", err))?;
 
-    let preferences = json_body
+    let routing_preferences = json_body
         .as_object_mut()
-        .and_then(|obj| obj.remove("routing_policy"))
-        .and_then(|policy_value| {
-            if warn_on_size {
-                let policy_str = serde_json::to_string(&policy_value).unwrap_or_default();
-                if policy_str.len() > ROUTING_POLICY_SIZE_WARNING_BYTES {
-                    warn!(
-                        size_bytes = policy_str.len(),
-                        limit_bytes = ROUTING_POLICY_SIZE_WARNING_BYTES,
-                        "routing_policy exceeds recommended size limit"
-                    );
-                }
-            }
-            match serde_json::from_value::<Vec<ModelUsagePreference>>(policy_value) {
+        .and_then(|o| o.remove("routing_preferences"))
+        .and_then(
+            |value| match serde_json::from_value::<Vec<TopLevelRoutingPreference>>(value) {
                 Ok(prefs) => {
                     info!(
-                        num_models = prefs.len(),
-                        "using inline routing_policy from request body"
+                        num_routes = prefs.len(),
+                        "using inline routing_preferences from request body"
                     );
                     Some(prefs)
                 }
                 Err(err) => {
-                    warn!(error = %err, "failed to parse routing_policy");
+                    warn!(error = %err, "failed to parse routing_preferences");
                     None
                 }
-            }
-        });
+            },
+        );
 
     let bytes = Bytes::from(serde_json::to_vec(&json_body).unwrap());
-    Ok((bytes, preferences))
+    Ok((bytes, routing_preferences))
 }
 
 #[derive(serde::Serialize)]
 struct RoutingDecisionResponse {
-    model: String,
+    /// Ranked model list — use first, fall back to next on 429/5xx.
+    models: Vec<String>,
     route: Option<String>,
     trace_id: String,
     #[serde(skip_serializing_if = "Option::is_none")]
@@ -148,7 +134,7 @@ async fn routing_decision_inner(
                 "returning pinned routing decision from cache"
             );
             let response = RoutingDecisionResponse {
-                model: cached.model_name,
+                models: vec![cached.model_name],
                 route: cached.route_name,
                 trace_id,
                 session_id: Some(sid.clone()),
@@ -174,8 +160,9 @@ async fn routing_decision_inner(
         "routing decision request body received"
     );
 
-    // Extract routing_policy from request body before parsing as ProviderRequestType
-    let (chat_request_bytes, inline_preferences) = match extract_routing_policy(&raw_bytes, true) {
+    // Extract routing_preferences from body before parsing as ProviderRequestType
+    let (chat_request_bytes, inline_routing_preferences) = match extract_routing_policy(&raw_bytes)
+    {
         Ok(result) => result,
         Err(err) => {
             warn!(error = %err, "failed to parse request JSON");
@@ -202,14 +189,13 @@ async fn routing_decision_inner(
         }
     };
 
-    // Call the existing routing logic with inline preferences
     let routing_result = router_chat_get_upstream_model(
         Arc::clone(&router_service),
         client_request,
         &traceparent,
         &request_path,
         &request_id,
-        inline_preferences,
+        inline_routing_preferences,
     )
     .await;
 
@@ -227,7 +213,7 @@ async fn routing_decision_inner(
             }
 
             let response = RoutingDecisionResponse {
-                model: result.model_name,
+                models: result.models,
                 route: result.route_name,
                 trace_id,
                 session_id,
@@ -235,7 +221,8 @@ async fn routing_decision_inner(
             };
 
             info!(
-                model = %response.model,
+                primary_model = %response.models.first().map(|s| s.as_str()).unwrap_or("none"),
+                total_models = response.models.len(),
                 route = ?response.route,
                 "routing decision completed"
             );
@@ -261,6 +248,7 @@ async fn routing_decision_inner(
 #[cfg(test)]
 mod tests {
     use super::*;
+    use common::configuration::SelectionPreference;
 
     fn make_chat_body(extra_fields: &str) -> Vec<u8> {
         let extra = if extra_fields.is_empty() {
@@ -278,95 +266,118 @@ mod tests {
     #[test]
     fn extract_routing_policy_no_policy() {
         let body = make_chat_body("");
-        let (cleaned, prefs) = extract_routing_policy(&body, false).unwrap();
+        let (cleaned, prefs) = extract_routing_policy(&body).unwrap();
 
         assert!(prefs.is_none());
         let cleaned_json: serde_json::Value = serde_json::from_slice(&cleaned).unwrap();
         assert_eq!(cleaned_json["model"], "gpt-4o-mini");
-        assert!(cleaned_json.get("routing_policy").is_none());
-    }
-
-    #[test]
-    fn extract_routing_policy_valid_policy() {
-        let policy = r#""routing_policy": [
-            {
-                "model": "openai/gpt-4o",
-                "routing_preferences": [
-                    {"name": "coding", "description": "code generation tasks"}
-                ]
-            },
-            {
-                "model": "openai/gpt-4o-mini",
-                "routing_preferences": [
-                    {"name": "general", "description": "general questions"}
-                ]
-            }
-        ]"#;
-        let body = make_chat_body(policy);
-        let (cleaned, prefs) = extract_routing_policy(&body, false).unwrap();
-
-        let prefs = prefs.expect("should have parsed preferences");
-        assert_eq!(prefs.len(), 2);
-        assert_eq!(prefs[0].model, "openai/gpt-4o");
-        assert_eq!(prefs[0].routing_preferences[0].name, "coding");
-        assert_eq!(prefs[1].model, "openai/gpt-4o-mini");
-        assert_eq!(prefs[1].routing_preferences[0].name, "general");
-
-        // routing_policy should be stripped from cleaned body
-        let cleaned_json: serde_json::Value = serde_json::from_slice(&cleaned).unwrap();
-        assert!(cleaned_json.get("routing_policy").is_none());
-        assert_eq!(cleaned_json["model"], "gpt-4o-mini");
-    }
-
-    #[test]
-    fn extract_routing_policy_invalid_policy_returns_none() {
-        // routing_policy is present but has wrong shape
-        let policy = r#""routing_policy": "not-an-array""#;
-        let body = make_chat_body(policy);
-        let (cleaned, prefs) = extract_routing_policy(&body, false).unwrap();
-
-        // Invalid policy should be ignored (returns None), not error
-        assert!(prefs.is_none());
-        // routing_policy should still be stripped from cleaned body
-        let cleaned_json: serde_json::Value = serde_json::from_slice(&cleaned).unwrap();
-        assert!(cleaned_json.get("routing_policy").is_none());
     }
 
     #[test]
     fn extract_routing_policy_invalid_json_returns_error() {
         let body = b"not valid json";
-        let result = extract_routing_policy(body, false);
+        let result = extract_routing_policy(body);
         assert!(result.is_err());
         assert!(result.unwrap_err().contains("Failed to parse JSON"));
     }
 
     #[test]
-    fn extract_routing_policy_empty_array() {
-        let policy = r#""routing_policy": []"#;
+    fn extract_routing_policy_routing_preferences() {
+        let policy = r#""routing_preferences": [
+            {
+                "name": "code generation",
+                "description": "generate new code",
+                "models": ["openai/gpt-4o", "openai/gpt-4o-mini"],
+                "selection_policy": {"prefer": "fastest"}
+            }
+        ]"#;
         let body = make_chat_body(policy);
-        let (_, prefs) = extract_routing_policy(&body, false).unwrap();
+        let (cleaned, prefs) = extract_routing_policy(&body).unwrap();
 
-        let prefs = prefs.expect("empty array is valid");
-        assert_eq!(prefs.len(), 0);
+        let prefs = prefs.expect("should have parsed routing_preferences");
+        assert_eq!(prefs.len(), 1);
+        assert_eq!(prefs[0].name, "code generation");
+        assert_eq!(prefs[0].models, vec!["openai/gpt-4o", "openai/gpt-4o-mini"]);
+
+        let cleaned_json: serde_json::Value = serde_json::from_slice(&cleaned).unwrap();
+        assert!(cleaned_json.get("routing_preferences").is_none());
     }
 
     #[test]
     fn extract_routing_policy_preserves_other_fields() {
-        let policy = r#""routing_policy": [{"model": "gpt-4o", "routing_preferences": [{"name": "test", "description": "test"}]}], "temperature": 0.5, "max_tokens": 100"#;
+        let policy = r#""routing_preferences": [{"name": "test", "description": "test", "models": ["gpt-4o"], "selection_policy": {"prefer": "none"}}], "temperature": 0.5, "max_tokens": 100"#;
         let body = make_chat_body(policy);
-        let (cleaned, prefs) = extract_routing_policy(&body, false).unwrap();
+        let (cleaned, prefs) = extract_routing_policy(&body).unwrap();
 
         assert!(prefs.is_some());
         let cleaned_json: serde_json::Value = serde_json::from_slice(&cleaned).unwrap();
         assert_eq!(cleaned_json["temperature"], 0.5);
         assert_eq!(cleaned_json["max_tokens"], 100);
-        assert!(cleaned_json.get("routing_policy").is_none());
+        assert!(cleaned_json.get("routing_preferences").is_none());
+    }
+
+    #[test]
+    fn extract_routing_policy_prefer_null_defaults_to_none() {
+        let policy = r#""routing_preferences": [
+            {
+                "name": "coding",
+                "description": "code generation, writing functions, debugging",
+                "models": ["openai/gpt-4o", "openai/gpt-4o-mini"],
+                "selection_policy": {"prefer": null}
+            }
+        ]"#;
+        let body = make_chat_body(policy);
+        let (_cleaned, prefs) = extract_routing_policy(&body).unwrap();
+
+        let prefs = prefs.expect("should parse routing_preferences when prefer is null");
+        assert_eq!(prefs.len(), 1);
+        assert_eq!(prefs[0].selection_policy.prefer, SelectionPreference::None);
+    }
+
+    #[test]
+    fn extract_routing_policy_selection_policy_missing_defaults_to_none() {
+        let policy = r#""routing_preferences": [
+            {
+                "name": "coding",
+                "description": "code generation, writing functions, debugging",
+                "models": ["openai/gpt-4o", "openai/gpt-4o-mini"]
+            }
+        ]"#;
+        let body = make_chat_body(policy);
+        let (_cleaned, prefs) = extract_routing_policy(&body).unwrap();
+
+        let prefs =
+            prefs.expect("should parse routing_preferences when selection_policy is missing");
+        assert_eq!(prefs.len(), 1);
+        assert_eq!(prefs[0].selection_policy.prefer, SelectionPreference::None);
+    }
+
+    #[test]
+    fn extract_routing_policy_prefer_empty_string_defaults_to_none() {
+        let policy = r#""routing_preferences": [
+            {
+                "name": "coding",
+                "description": "code generation, writing functions, debugging",
+                "models": ["openai/gpt-4o", "openai/gpt-4o-mini"],
+                "selection_policy": {"prefer": ""}
+            }
+        ]"#;
+        let body = make_chat_body(policy);
+        let (_cleaned, prefs) = extract_routing_policy(&body).unwrap();
+
+        let prefs =
+            prefs.expect("should parse routing_preferences when selection_policy.prefer is empty");
+        assert_eq!(prefs.len(), 1);
+        assert_eq!(prefs[0].selection_policy.prefer, SelectionPreference::None);
     }
 
     #[test]
     fn routing_decision_response_serialization() {
         let response = RoutingDecisionResponse {
-            model: "openai/gpt-4o".to_string(),
+            models: vec![
+                "openai/gpt-4o-mini".to_string(),
+                "openai/gpt-4o".to_string(),
+            ],
             route: Some("code_generation".to_string()),
             trace_id: "abc123".to_string(),
             session_id: Some("sess-abc".to_string()),
@@ -374,7 +385,8 @@ mod tests {
         };
         let json = serde_json::to_string(&response).unwrap();
         let parsed: serde_json::Value = serde_json::from_str(&json).unwrap();
-        assert_eq!(parsed["model"], "openai/gpt-4o");
+        assert_eq!(parsed["models"][0], "openai/gpt-4o-mini");
+        assert_eq!(parsed["models"][1], "openai/gpt-4o");
         assert_eq!(parsed["route"], "code_generation");
         assert_eq!(parsed["trace_id"], "abc123");
         assert_eq!(parsed["session_id"], "sess-abc");
@@ -384,7 +396,7 @@ mod tests {
     #[test]
     fn routing_decision_response_serialization_no_route() {
         let response = RoutingDecisionResponse {
-            model: "none".to_string(),
+            models: vec!["none".to_string()],
             route: None,
             trace_id: "abc123".to_string(),
             session_id: None,
@@ -392,7 +404,7 @@ mod tests {
         };
         let json = serde_json::to_string(&response).unwrap();
         let parsed: serde_json::Value = serde_json::from_str(&json).unwrap();
-        assert_eq!(parsed["model"], "none");
+        assert_eq!(parsed["models"][0], "none");
         assert!(parsed["route"].is_null());
         assert!(parsed.get("session_id").is_none());
         assert_eq!(parsed["pinned"], false);

crates/brightstaff/src/main.rs

@@ -6,6 +6,7 @@ use brightstaff::handlers::llm::llm_chat;
 use brightstaff::handlers::models::list_models;
 use brightstaff::handlers::routing_service::routing_decision;
 use brightstaff::router::llm::RouterService;
+use brightstaff::router::model_metrics::ModelMetricsService;
 use brightstaff::router::orchestrator::OrchestratorService;
 use brightstaff::state::memory::MemoryConversationalStorage;
 use brightstaff::state::postgresql::PostgreSQLConversationStorage;
@@ -40,6 +41,17 @@ const DEFAULT_ROUTING_MODEL_NAME: &str = "Arch-Router";
 const DEFAULT_ORCHESTRATOR_LLM_PROVIDER: &str = "plano-orchestrator";
 const DEFAULT_ORCHESTRATOR_MODEL_NAME: &str = "Plano-Orchestrator";
 
+/// Parse a version string like `v0.4.0`, `v0.3.0`, `0.2.0` into a `(major, minor, patch)` tuple.
+/// Missing parts default to 0. Non-numeric parts are treated as 0.
+fn parse_semver(version: &str) -> (u32, u32, u32) {
+    let v = version.trim_start_matches('v');
+    let mut parts = v.splitn(3, '.').map(|p| p.parse::<u32>().unwrap_or(0));
+    let major = parts.next().unwrap_or(0);
+    let minor = parts.next().unwrap_or(0);
+    let patch = parts.next().unwrap_or(0);
+    (major, minor, patch)
+}
+
 /// CORS pre-flight response for the models endpoint.
 fn cors_preflight() -> Result<Response<BoxBody<Bytes, hyper::Error>>, hyper::Error> {
     let mut response = Response::new(empty());
@@ -163,11 +175,131 @@ async fn init_app_state(
         .unwrap_or_else(|| DEFAULT_ROUTING_LLM_PROVIDER.to_string());
 
     let session_ttl_seconds = config.routing.as_ref().and_then(|r| r.session_ttl_seconds);
-
     let session_max_entries = config.routing.as_ref().and_then(|r| r.session_max_entries);
 
+    // Validate that top-level routing_preferences requires v0.4.0+.
+    let config_version = parse_semver(&config.version);
+    let is_v040_plus = config_version >= (0, 4, 0);
+
+    if !is_v040_plus && config.routing_preferences.is_some() {
+        return Err(
+            "top-level routing_preferences requires version v0.4.0 or above. \
+             Update the version field or remove routing_preferences."
+                .into(),
+        );
+    }
+
+    // Validate that all models referenced in top-level routing_preferences exist in model_providers.
+    // The CLI renders model_providers with `name` = "openai/gpt-4o" and `model` = "gpt-4o",
+    // so we accept a match against either field.
+    if let Some(ref route_prefs) = config.routing_preferences {
+        let provider_model_names: std::collections::HashSet<&str> = config
+            .model_providers
+            .iter()
+            .flat_map(|p| std::iter::once(p.name.as_str()).chain(p.model.as_deref()))
+            .collect();
+        for pref in route_prefs {
+            for model in &pref.models {
+                if !provider_model_names.contains(model.as_str()) {
+                    return Err(format!(
+                        "routing_preferences route '{}' references model '{}' \
+                         which is not declared in model_providers",
+                        pref.name, model
+                    )
+                    .into());
+                }
+            }
+        }
+    }
+
+    // Validate and initialize ModelMetricsService if model_metrics_sources is configured.
+    let metrics_service: Option<Arc<ModelMetricsService>> = if let Some(ref sources) =
+        config.model_metrics_sources
+    {
+        use common::configuration::MetricsSource;
+        let cost_count = sources
+            .iter()
+            .filter(|s| matches!(s, MetricsSource::Cost(_)))
+            .count();
+        let latency_count = sources
+            .iter()
+            .filter(|s| matches!(s, MetricsSource::Latency(_)))
+            .count();
+        if cost_count > 1 {
+            return Err("model_metrics_sources: only one cost metrics source is allowed".into());
+        }
+        if latency_count > 1 {
+            return Err("model_metrics_sources: only one latency metrics source is allowed".into());
+        }
+        let svc = ModelMetricsService::new(sources, reqwest::Client::new()).await;
+        Some(Arc::new(svc))
+    } else {
+        None
+    };
+
+    // Validate that selection_policy.prefer is compatible with the configured metric sources.
+    if let Some(ref prefs) = config.routing_preferences {
+        use common::configuration::{MetricsSource, SelectionPreference};
+
+        let has_cost_source = config
+            .model_metrics_sources
+            .as_deref()
+            .unwrap_or_default()
+            .iter()
+            .any(|s| matches!(s, MetricsSource::Cost(_)));
+        let has_latency_source = config
+            .model_metrics_sources
+            .as_deref()
+            .unwrap_or_default()
+            .iter()
+            .any(|s| matches!(s, MetricsSource::Latency(_)));
+
+        for pref in prefs {
+            if pref.selection_policy.prefer == SelectionPreference::Cheapest && !has_cost_source {
+                return Err(format!(
+                    "routing_preferences route '{}' uses prefer: cheapest but no cost metrics source is configured — \
+                     add a cost metrics source to model_metrics_sources",
+                    pref.name
+                )
+                .into());
+            }
+            if pref.selection_policy.prefer == SelectionPreference::Fastest && !has_latency_source {
+                return Err(format!(
+                    "routing_preferences route '{}' uses prefer: fastest but no latency metrics source is configured — \
+                     add a latency metrics source to model_metrics_sources",
+                    pref.name
+                )
+                .into());
+            }
+        }
+    }
+
+    // Warn about models in routing_preferences that have no matching pricing/latency data.
+    if let (Some(ref prefs), Some(ref svc)) = (&config.routing_preferences, &metrics_service) {
+        let cost_data = svc.cost_snapshot().await;
+        let latency_data = svc.latency_snapshot().await;
+        for pref in prefs {
+            use common::configuration::SelectionPreference;
+            for model in &pref.models {
+                let missing = match pref.selection_policy.prefer {
+                    SelectionPreference::Cheapest => !cost_data.contains_key(model.as_str()),
+                    SelectionPreference::Fastest => !latency_data.contains_key(model.as_str()),
+                    _ => false,
+                };
+                if missing {
+                    warn!(
+                        model = %model,
+                        route = %pref.name,
+                        "model has no metric data — will be ranked last"
+                    );
+                }
+            }
+        }
+    }
+
     let router_service = Arc::new(RouterService::new(
-        config.model_providers.clone(),
+        config.routing_preferences.clone(),
+        metrics_service,
         format!("{llm_provider_url}{CHAT_COMPLETIONS_PATH}"),
         routing_model_name,
         routing_llm_provider,

crates/brightstaff/src/router/llm.rs

@@ -1,9 +1,11 @@
 use std::{collections::HashMap, sync::Arc, time::Duration, time::Instant};
 
 use common::{
-    configuration::{LlmProvider, ModelUsagePreference, RoutingPreference},
+    configuration::TopLevelRoutingPreference,
     consts::{ARCH_PROVIDER_HINT_HEADER, REQUEST_ID_HEADER, TRACE_PARENT_HEADER},
 };
+
+use super::router_model::{ModelUsagePreference, RoutingPreference};
 use hermesllm::apis::openai::Message;
 use hyper::header;
 use thiserror::Error;
@@ -11,6 +13,7 @@ use tokio::sync::RwLock;
 use tracing::{debug, info};
 
 use super::http::{self, post_and_extract_content};
+use super::model_metrics::ModelMetricsService;
 use super::router_model::RouterModel;
 
 use crate::router::router_model_v1;
@@ -30,7 +33,8 @@ pub struct RouterService {
     client: reqwest::Client,
     router_model: Arc<dyn RouterModel>,
     routing_provider_name: String,
-    llm_usage_defined: bool,
+    top_level_preferences: HashMap<String, TopLevelRoutingPreference>,
+    metrics_service: Option<Arc<ModelMetricsService>>,
     session_cache: RwLock<HashMap<String, CachedRoute>>,
     session_ttl: Duration,
     session_max_entries: usize,
@@ -49,31 +53,39 @@ pub type Result<T> = std::result::Result<T, RoutingError>;
 
 impl RouterService {
     pub fn new(
-        providers: Vec<LlmProvider>,
+        top_level_prefs: Option<Vec<TopLevelRoutingPreference>>,
+        metrics_service: Option<Arc<ModelMetricsService>>,
         router_url: String,
         routing_model_name: String,
         routing_provider_name: String,
         session_ttl_seconds: Option<u64>,
         session_max_entries: Option<usize>,
     ) -> Self {
-        let providers_with_usage = providers
-            .iter()
-            .filter(|provider| provider.routing_preferences.is_some())
-            .cloned()
-            .collect::<Vec<LlmProvider>>();
+        let top_level_preferences: HashMap<String, TopLevelRoutingPreference> = top_level_prefs
+            .map_or_else(HashMap::new, |prefs| {
+                prefs.into_iter().map(|p| (p.name.clone(), p)).collect()
+            });
 
-        let llm_routes: HashMap<String, Vec<RoutingPreference>> = providers_with_usage
+        // Build sentinel routes for RouterModelV1: route_name → first model.
+        // RouterModelV1 uses this to build its prompt; RouterService overrides
+        // the model selection via rank_models() after the route is determined.
+        let sentinel_routes: HashMap<String, Vec<RoutingPreference>> = top_level_preferences
             .iter()
-            .filter_map(|provider| {
-                provider
-                    .routing_preferences
-                    .as_ref()
-                    .map(|prefs| (provider.name.clone(), prefs.clone()))
+            .filter_map(|(name, pref)| {
+                pref.models.first().map(|first_model| {
+                    (
+                        first_model.clone(),
+                        vec![RoutingPreference {
+                            name: name.clone(),
+                            description: pref.description.clone(),
+                        }],
+                    )
+                })
             })
             .collect();
 
         let router_model = Arc::new(router_model_v1::RouterModelV1::new(
-            llm_routes,
+            sentinel_routes,
             routing_model_name,
             router_model_v1::MAX_TOKEN_LEN,
         ));
@@ -87,7 +99,8 @@ impl RouterService {
             client: reqwest::Client::new(),
             router_model,
             routing_provider_name,
-            llm_usage_defined: !providers_with_usage.is_empty(),
+            top_level_preferences,
+            metrics_service,
             session_cache: RwLock::new(HashMap::new()),
             session_ttl,
             session_max_entries,
@@ -153,24 +166,43 @@ impl RouterService {
         &self,
         messages: &[Message],
         traceparent: &str,
-        usage_preferences: Option<Vec<ModelUsagePreference>>,
+        inline_routing_preferences: Option<Vec<TopLevelRoutingPreference>>,
         request_id: &str,
-    ) -> Result<Option<(String, String)>> {
+    ) -> Result<Option<(String, Vec<String>)>> {
         if messages.is_empty() {
             return Ok(None);
         }
 
-        if usage_preferences
-            .as_ref()
-            .is_none_or(|prefs| prefs.len() < 2)
-            && !self.llm_usage_defined
-        {
+        // Build inline top-level map from request if present (inline overrides config).
+        let inline_top_map: Option<HashMap<String, TopLevelRoutingPreference>> =
+            inline_routing_preferences
+                .map(|prefs| prefs.into_iter().map(|p| (p.name.clone(), p)).collect());
+
+        // No routing defined — skip the router call entirely.
+        if inline_top_map.is_none() && self.top_level_preferences.is_empty() {
             return Ok(None);
         }
 
+        // For inline overrides, build synthetic ModelUsagePreference list so RouterModelV1
+        // generates the correct prompt (route name + description pairs).
+        // For config-level prefs the sentinel routes are already baked into RouterModelV1.
+        let effective_usage_preferences: Option<Vec<ModelUsagePreference>> =
+            inline_top_map.as_ref().map(|inline_map| {
+                inline_map
+                    .values()
+                    .map(|p| ModelUsagePreference {
+                        model: p.models.first().cloned().unwrap_or_default(),
+                        routing_preferences: vec![RoutingPreference {
+                            name: p.name.clone(),
+                            description: p.description.clone(),
+                        }],
+                    })
+                    .collect()
+            });
+
         let router_request = self
             .router_model
-            .generate_request(messages, &usage_preferences);
+            .generate_request(messages, &effective_usage_preferences);
 
         debug!(
             model = %self.router_model.get_model_name(),
@@ -210,18 +242,38 @@ impl RouterService {
             return Ok(None);
         };
 
+        // Parse the route name from the router response.
         let parsed = self
             .router_model
-            .parse_response(&content, &usage_preferences)?;
+            .parse_response(&content, &effective_usage_preferences)?;
+
+        let result = if let Some((route_name, _sentinel)) = parsed {
+            let top_pref = inline_top_map
+                .as_ref()
+                .and_then(|m| m.get(&route_name))
+                .or_else(|| self.top_level_preferences.get(&route_name));
+
+            if let Some(pref) = top_pref {
+                let ranked = match &self.metrics_service {
+                    Some(svc) => svc.rank_models(&pref.models, &pref.selection_policy).await,
+                    None => pref.models.clone(),
+                };
+                Some((route_name, ranked))
+            } else {
+                None
+            }
+        } else {
+            None
+        };
 
         info!(
             content = %content.replace("\n", "\\n"),
-            selected_model = ?parsed,
+            selected_model = ?result,
             response_time_ms = elapsed.as_millis(),
             "arch-router determined route"
         );
 
-        Ok(parsed)
+        Ok(result)
     }
 }
 
@@ -231,7 +283,8 @@ mod tests {
 
     fn make_router_service(ttl_seconds: u64, max_entries: usize) -> RouterService {
         RouterService::new(
-            vec![],
+            None,
+            None,
             "http://localhost:12001/v1/chat/completions".to_string(),
             "Arch-Router".to_string(),
             "arch-router".to_string(),

crates/brightstaff/src/router/mod.rs

@@ -1,5 +1,6 @@
 pub(crate) mod http;
 pub mod llm;
+pub mod model_metrics;
 pub mod orchestrator;
 pub mod orchestrator_model;
 pub mod orchestrator_model_v1;

crates/brightstaff/src/router/model_metrics.rs

@@ -0,0 +1,388 @@
+use std::collections::HashMap;
+use std::sync::Arc;
+use std::time::Duration;
+
+use common::configuration::{
+    CostProvider, LatencyProvider, MetricsSource, SelectionPolicy, SelectionPreference,
+};
+use tokio::sync::RwLock;
+use tracing::{debug, info, warn};
+
+const DO_PRICING_URL: &str = "https://api.digitalocean.com/v2/gen-ai/models/catalog";
+
+pub struct ModelMetricsService {
+    cost: Arc<RwLock<HashMap<String, f64>>>,
+    latency: Arc<RwLock<HashMap<String, f64>>>,
+}
+
+impl ModelMetricsService {
+    pub async fn new(sources: &[MetricsSource], client: reqwest::Client) -> Self {
+        let cost_data = Arc::new(RwLock::new(HashMap::new()));
+        let latency_data = Arc::new(RwLock::new(HashMap::new()));
+
+        for source in sources {
+            match source {
+                MetricsSource::Cost(cfg) => match cfg.provider {
+                    CostProvider::Digitalocean => {
+                        let aliases = cfg.model_aliases.clone().unwrap_or_default();
+                        let data = fetch_do_pricing(&client, &aliases).await;
+                        info!(models = data.len(), "fetched digitalocean pricing");
+                        *cost_data.write().await = data;
+
+                        if let Some(interval_secs) = cfg.refresh_interval {
+                            let cost_clone = Arc::clone(&cost_data);
+                            let client_clone = client.clone();
+                            let interval = Duration::from_secs(interval_secs);
+                            tokio::spawn(async move {
+                                loop {
+                                    tokio::time::sleep(interval).await;
+                                    let data = fetch_do_pricing(&client_clone, &aliases).await;
+                                    info!(models = data.len(), "refreshed digitalocean pricing");
+                                    *cost_clone.write().await = data;
+                                }
+                            });
+                        }
+                    }
+                },
+                MetricsSource::Latency(cfg) => match cfg.provider {
+                    LatencyProvider::Prometheus => {
+                        let data = fetch_prometheus_metrics(&cfg.url, &cfg.query, &client).await;
+                        info!(models = data.len(), url = %cfg.url, "fetched latency metrics");
+                        *latency_data.write().await = data;
+
+                        if let Some(interval_secs) = cfg.refresh_interval {
+                            let latency_clone = Arc::clone(&latency_data);
+                            let client_clone = client.clone();
+                            let url = cfg.url.clone();
+                            let query = cfg.query.clone();
+                            let interval = Duration::from_secs(interval_secs);
+                            tokio::spawn(async move {
+                                loop {
+                                    tokio::time::sleep(interval).await;
+                                    let data =
+                                        fetch_prometheus_metrics(&url, &query, &client_clone).await;
+                                    info!(models = data.len(), url = %url, "refreshed latency metrics");
+                                    *latency_clone.write().await = data;
+                                }
+                            });
+                        }
+                    }
+                },
+            }
+        }
+
+        ModelMetricsService {
+            cost: cost_data,
+            latency: latency_data,
+        }
+    }
+
+    /// Rank `models` by `policy`, returning them in preference order.
+    /// Models with no metric data are appended at the end in their original order.
+    pub async fn rank_models(&self, models: &[String], policy: &SelectionPolicy) -> Vec<String> {
+        let cost_data = self.cost.read().await;
+        let latency_data = self.latency.read().await;
+        debug!(
+            input_models = ?models,
+            cost_data = ?cost_data.iter().collect::<Vec<_>>(),
+            latency_data = ?latency_data.iter().collect::<Vec<_>>(),
+            prefer = ?policy.prefer,
+            "rank_models called"
+        );
+
+        match policy.prefer {
+            SelectionPreference::Cheapest => {
+                for m in models {
+                    if !cost_data.contains_key(m.as_str()) {
+                        warn!(model = %m, "no cost data for model — ranking last (prefer: cheapest)");
+                    }
+                }
+                rank_by_ascending_metric(models, &cost_data)
+            }
+            SelectionPreference::Fastest => {
+                for m in models {
+                    if !latency_data.contains_key(m.as_str()) {
+                        warn!(model = %m, "no latency data for model — ranking last (prefer: fastest)");
+                    }
+                }
+                rank_by_ascending_metric(models, &latency_data)
+            }
+            SelectionPreference::None => models.to_vec(),
+        }
+    }
+
+    /// Returns a snapshot of the current cost data. Used at startup to warn about unmatched models.
+    pub async fn cost_snapshot(&self) -> HashMap<String, f64> {
+        self.cost.read().await.clone()
+    }
+
+    /// Returns a snapshot of the current latency data. Used at startup to warn about unmatched models.
+    pub async fn latency_snapshot(&self) -> HashMap<String, f64> {
+        self.latency.read().await.clone()
+    }
+}
+
+fn rank_by_ascending_metric(models: &[String], data: &HashMap<String, f64>) -> Vec<String> {
+    let mut with_data: Vec<(&String, f64)> = models
+        .iter()
+        .filter_map(|m| {
+            let v = *data.get(m.as_str())?;
+            if v.is_nan() {
+                None
+            } else {
+                Some((m, v))
+            }
+        })
+        .collect();
+    with_data.sort_by(|a, b| a.1.partial_cmp(&b.1).unwrap_or(std::cmp::Ordering::Equal));
+
+    let without_data: Vec<&String> = models
+        .iter()
+        .filter(|m| data.get(m.as_str()).is_none_or(|v| v.is_nan()))
+        .collect();
+
+    with_data
+        .iter()
+        .map(|(m, _)| (*m).clone())
+        .chain(without_data.iter().map(|m| (*m).clone()))
+        .collect()
+}
+
+#[derive(serde::Deserialize)]
+struct DoModelList {
+    data: Vec<DoModel>,
+}
+
+#[derive(serde::Deserialize)]
+struct DoModel {
+    model_id: String,
+    pricing: Option<DoPricing>,
+}
+
+#[derive(serde::Deserialize)]
+struct DoPricing {
+    input_price_per_million: Option<f64>,
+    output_price_per_million: Option<f64>,
+}
+
+async fn fetch_do_pricing(
+    client: &reqwest::Client,
+    aliases: &HashMap<String, String>,
+) -> HashMap<String, f64> {
+    match client.get(DO_PRICING_URL).send().await {
+        Ok(resp) => match resp.json::<DoModelList>().await {
+            Ok(list) => list
+                .data
+                .into_iter()
+                .filter_map(|m| {
+                    let pricing = m.pricing?;
+                    let raw_key = m.model_id.clone();
+                    let key = aliases.get(&raw_key).cloned().unwrap_or(raw_key);
+                    let cost = pricing.input_price_per_million.unwrap_or(0.0)
+                        + pricing.output_price_per_million.unwrap_or(0.0);
+                    Some((key, cost))
+                })
+                .collect(),
+            Err(err) => {
+                warn!(error = %err, url = DO_PRICING_URL, "failed to parse digitalocean pricing response");
+                HashMap::new()
+            }
+        },
+        Err(err) => {
+            warn!(error = %err, url = DO_PRICING_URL, "failed to fetch digitalocean pricing");
+            HashMap::new()
+        }
+    }
+}
+
+#[derive(serde::Deserialize)]
+struct PrometheusResponse {
+    data: PrometheusData,
+}
+
+#[derive(serde::Deserialize)]
+struct PrometheusData {
+    result: Vec<PrometheusResult>,
+}
+
+#[derive(serde::Deserialize)]
+struct PrometheusResult {
+    metric: HashMap<String, String>,
+    value: (f64, String), // (timestamp, value_str)
+}
+
+async fn fetch_prometheus_metrics(
+    url: &str,
+    query: &str,
+    client: &reqwest::Client,
+) -> HashMap<String, f64> {
+    let query_url = format!("{}/api/v1/query", url.trim_end_matches('/'));
+    match client
+        .get(&query_url)
+        .query(&[("query", query)])
+        .send()
+        .await
+    {
+        Ok(resp) => match resp.json::<PrometheusResponse>().await {
+            Ok(prom) => prom
+                .data
+                .result
+                .into_iter()
+                .filter_map(|r| {
+                    let model_name = r.metric.get("model_name")?.clone();
+                    let value: f64 = r.value.1.parse().ok()?;
+                    Some((model_name, value))
+                })
+                .collect(),
+            Err(err) => {
+                warn!(error = %err, url = %query_url, "failed to parse prometheus response");
+                HashMap::new()
+            }
+        },
+        Err(err) => {
+            warn!(error = %err, url = %query_url, "failed to fetch prometheus metrics");
+            HashMap::new()
+        }
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use common::configuration::SelectionPreference;
+
+    fn make_policy(prefer: SelectionPreference) -> SelectionPolicy {
+        SelectionPolicy { prefer }
+    }
+
+    #[test]
+    fn test_rank_by_ascending_metric_picks_lowest_first() {
+        let models = vec!["a".to_string(), "b".to_string(), "c".to_string()];
+        let mut data = HashMap::new();
+        data.insert("a".to_string(), 0.01);
+        data.insert("b".to_string(), 0.005);
+        data.insert("c".to_string(), 0.02);
+        assert_eq!(
+            rank_by_ascending_metric(&models, &data),
+            vec!["b", "a", "c"]
+        );
+    }
+
+    #[test]
+    fn test_rank_by_ascending_metric_no_data_preserves_order() {
+        let models = vec!["x".to_string(), "y".to_string()];
+        let data = HashMap::new();
+        assert_eq!(rank_by_ascending_metric(&models, &data), vec!["x", "y"]);
+    }
+
+    #[test]
+    fn test_rank_by_ascending_metric_partial_data() {
+        let models = vec!["a".to_string(), "b".to_string()];
+        let mut data = HashMap::new();
+        data.insert("b".to_string(), 100.0);
+        assert_eq!(rank_by_ascending_metric(&models, &data), vec!["b", "a"]);
+    }
+
+    #[tokio::test]
+    async fn test_rank_models_cheapest() {
+        let service = ModelMetricsService {
+            cost: Arc::new(RwLock::new({
+                let mut m = HashMap::new();
+                m.insert("gpt-4o".to_string(), 0.005);
+                m.insert("gpt-4o-mini".to_string(), 0.0001);
+                m
+            })),
+            latency: Arc::new(RwLock::new(HashMap::new())),
+        };
+        let models = vec!["gpt-4o".to_string(), "gpt-4o-mini".to_string()];
+        let result = service
+            .rank_models(&models, &make_policy(SelectionPreference::Cheapest))
+            .await;
+        assert_eq!(result, vec!["gpt-4o-mini", "gpt-4o"]);
+    }
+
+    #[tokio::test]
+    async fn test_rank_models_fastest() {
+        let service = ModelMetricsService {
+            cost: Arc::new(RwLock::new(HashMap::new())),
+            latency: Arc::new(RwLock::new({
+                let mut m = HashMap::new();
+                m.insert("gpt-4o".to_string(), 200.0);
+                m.insert("claude-sonnet".to_string(), 120.0);
+                m
+            })),
+        };
+        let models = vec!["gpt-4o".to_string(), "claude-sonnet".to_string()];
+        let result = service
+            .rank_models(&models, &make_policy(SelectionPreference::Fastest))
+            .await;
+        assert_eq!(result, vec!["claude-sonnet", "gpt-4o"]);
+    }
+
+    #[tokio::test]
+    async fn test_rank_models_fallback_no_metrics() {
+        let service = ModelMetricsService {
+            cost: Arc::new(RwLock::new(HashMap::new())),
+            latency: Arc::new(RwLock::new(HashMap::new())),
+        };
+        let models = vec!["model-a".to_string(), "model-b".to_string()];
+        let result = service
+            .rank_models(&models, &make_policy(SelectionPreference::Cheapest))
+            .await;
+        assert_eq!(result, vec!["model-a", "model-b"]);
+    }
+
+    #[tokio::test]
+    async fn test_rank_models_partial_data_appended_last() {
+        let service = ModelMetricsService {
+            cost: Arc::new(RwLock::new({
+                let mut m = HashMap::new();
+                m.insert("gpt-4o".to_string(), 0.005);
+                m
+            })),
+            latency: Arc::new(RwLock::new(HashMap::new())),
+        };
+        let models = vec!["gpt-4o-mini".to_string(), "gpt-4o".to_string()];
+        let result = service
+            .rank_models(&models, &make_policy(SelectionPreference::Cheapest))
+            .await;
+        assert_eq!(result, vec!["gpt-4o", "gpt-4o-mini"]);
+    }
+
+    #[tokio::test]
+    async fn test_rank_models_none_preserves_order() {
+        let service = ModelMetricsService {
+            cost: Arc::new(RwLock::new({
+                let mut m = HashMap::new();
+                m.insert("gpt-4o-mini".to_string(), 0.0001);
+                m.insert("gpt-4o".to_string(), 0.005);
+                m
+            })),
+            latency: Arc::new(RwLock::new(HashMap::new())),
+        };
+        let models = vec!["gpt-4o".to_string(), "gpt-4o-mini".to_string()];
+        let result = service
+            .rank_models(&models, &make_policy(SelectionPreference::None))
+            .await;
+        // none → original order, despite gpt-4o-mini being cheaper
+        assert_eq!(result, vec!["gpt-4o", "gpt-4o-mini"]);
+    }
+
+    #[test]
+    fn test_rank_by_ascending_metric_nan_treated_as_missing() {
+        let models = vec![
+            "a".to_string(),
+            "b".to_string(),
+            "c".to_string(),
+            "d".to_string(),
+        ];
+        let mut data = HashMap::new();
+        data.insert("a".to_string(), f64::NAN);
+        data.insert("b".to_string(), 0.5);
+        data.insert("c".to_string(), 0.1);
+        // "d" has no entry at all
+        let result = rank_by_ascending_metric(&models, &data);
+        // c (0.1) < b (0.5), then NaN "a" and missing "d" appended in original order
+        assert_eq!(result, vec!["c", "b", "a", "d"]);
+    }
+}

crates/brightstaff/src/router/orchestrator_model_v1.rs

@@ -183,6 +183,7 @@ impl OrchestratorModel for OrchestratorModelV1 {
             .iter()
             .filter(|m| {
                 m.role != Role::System
+                    && m.role != Role::Developer
                     && m.role != Role::Tool
                     && !m.content.extract_text().is_empty()
             })

crates/brightstaff/src/router/router_model.rs

@@ -1,5 +1,5 @@
-use common::configuration::ModelUsagePreference;
 use hermesllm::apis::openai::{ChatCompletionsRequest, Message};
+use serde::{Deserialize, Serialize};
 use thiserror::Error;
 
 #[derive(Debug, Error)]
@@ -10,6 +10,20 @@ pub enum RoutingModelError {
 
 pub type Result<T> = std::result::Result<T, RoutingModelError>;
 
+/// Internal route descriptor passed to the router model to build its prompt.
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct RoutingPreference {
+    pub name: String,
+    pub description: String,
+}
+
+/// Groups a model with its routing preferences (used internally by RouterModelV1).
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct ModelUsagePreference {
+    pub model: String,
+    pub routing_preferences: Vec<RoutingPreference>,
+}
+
 pub trait RouterModel: Send + Sync {
     fn generate_request(
         &self,

crates/brightstaff/src/router/router_model_v1.rs

@@ -1,6 +1,6 @@
 use std::collections::HashMap;
 
-use common::configuration::{ModelUsagePreference, RoutingPreference};
+use super::router_model::{ModelUsagePreference, RoutingPreference};
 use hermesllm::apis::openai::{ChatCompletionsRequest, Message, MessageContent, Role};
 use hermesllm::transforms::lib::ExtractText;
 use serde::{Deserialize, Serialize};
@@ -80,6 +80,7 @@ impl RouterModel for RouterModelV1 {
             .iter()
             .filter(|m| {
                 m.role != Role::System
+                    && m.role != Role::Developer
                     && m.role != Role::Tool
                     && !m.content.extract_text().is_empty()
             })

crates/common/src/api/open_ai.rs

@@ -2,7 +2,6 @@ use crate::{
     configuration::LlmProvider,
     consts::{ARCH_FC_MODEL_NAME, ASSISTANT_ROLE},
 };
-use core::{panic, str};
 use serde::{ser::SerializeMap, Deserialize, Serialize};
 use std::{
     collections::{HashMap, VecDeque},
@@ -193,7 +192,7 @@ impl Display for ContentType {
                             // skip image URLs or their data in text representation
                             None
                         } else {
-                            panic!("Unsupported content type: {:?}", part.content_type);
+                            None
                         }
                     })
                     .collect();

crates/common/src/configuration.rs

@@ -1,5 +1,5 @@
 use hermesllm::apis::openai::{ModelDetail, ModelObject, Models};
-use serde::{Deserialize, Serialize};
+use serde::{Deserialize, Deserializer, Serialize};
 use std::collections::HashMap;
 use std::fmt::Display;
 
@@ -112,6 +112,77 @@ pub enum StateStorageType {
     Postgres,
 }
 
+#[derive(Debug, Clone, Default, Serialize, Deserialize, PartialEq, Eq)]
+#[serde(rename_all = "lowercase")]
+pub enum SelectionPreference {
+    Cheapest,
+    Fastest,
+    /// Return models in the same order they were defined — no reordering.
+    #[default]
+    #[serde(alias = "")]
+    None,
+}
+
+#[derive(Debug, Clone, Default, Serialize, Deserialize)]
+pub struct SelectionPolicy {
+    #[serde(default, deserialize_with = "deserialize_selection_preference")]
+    pub prefer: SelectionPreference,
+}
+
+fn deserialize_selection_preference<'de, D>(
+    deserializer: D,
+) -> Result<SelectionPreference, D::Error>
+where
+    D: Deserializer<'de>,
+{
+    Ok(Option::<SelectionPreference>::deserialize(deserializer)?.unwrap_or_default())
+}
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct TopLevelRoutingPreference {
+    pub name: String,
+    pub description: String,
+    pub models: Vec<String>,
+    #[serde(default)]
+    pub selection_policy: SelectionPolicy,
+}
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+#[serde(tag = "type", rename_all = "snake_case")]
+pub enum MetricsSource {
+    Cost(CostMetricsConfig),
+    Latency(LatencyMetricsConfig),
+}
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct CostMetricsConfig {
+    pub provider: CostProvider,
+    pub refresh_interval: Option<u64>,
+    /// Map DO catalog keys (`lowercase(creator)/model_id`) to Plano model names.
+    /// Example: `openai/openai-gpt-oss-120b: openai/gpt-4o`
+    pub model_aliases: Option<HashMap<String, String>>,
+}
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+#[serde(rename_all = "snake_case")]
+pub enum CostProvider {
+    Digitalocean,
+}
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct LatencyMetricsConfig {
+    pub provider: LatencyProvider,
+    pub url: String,
+    pub query: String,
+    pub refresh_interval: Option<u64>,
+}
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+#[serde(rename_all = "snake_case")]
+pub enum LatencyProvider {
+    Prometheus,
+}
+
 #[derive(Debug, Clone, Serialize, Deserialize)]
 pub struct Configuration {
     pub version: String,
@@ -131,6 +202,8 @@ pub struct Configuration {
     pub filters: Option<Vec<Agent>>,
     pub listeners: Vec<Listener>,
     pub state_storage: Option<StateStorageConfig>,
+    pub routing_preferences: Option<Vec<TopLevelRoutingPreference>>,
+    pub model_metrics_sources: Option<Vec<MetricsSource>>,
 }
 
 #[derive(Debug, Clone, Serialize, Deserialize, Default)]
@@ -246,6 +319,8 @@ pub enum TimeUnit {
     Minute,
     #[serde(rename = "hour")]
     Hour,
+    #[serde(rename = "day")]
+    Day,
 }
 
 #[derive(Debug, Clone, Serialize, Deserialize, PartialEq, Eq, Hash)]
@@ -326,18 +401,6 @@ impl LlmProviderType {
     }
 }
 
-#[derive(Serialize, Deserialize, Debug)]
-pub struct ModelUsagePreference {
-    pub model: String,
-    pub routing_preferences: Vec<RoutingPreference>,
-}
-
-#[derive(Debug, Clone, Serialize, Deserialize)]
-pub struct RoutingPreference {
-    pub name: String,
-    pub description: String,
-}
-
 #[derive(Serialize, Deserialize, Debug)]
 pub struct AgentUsagePreference {
     pub model: String,
@@ -387,7 +450,6 @@ pub struct LlmProvider {
     pub port: Option<u16>,
     pub rate_limits: Option<LlmRatelimit>,
     pub usage: Option<String>,
-    pub routing_preferences: Option<Vec<RoutingPreference>>,
     pub cluster_name: Option<String>,
     pub base_url_path_prefix: Option<String>,
     pub internal: Option<bool>,
@@ -431,7 +493,6 @@ impl Default for LlmProvider {
             port: None,
             rate_limits: None,
             usage: None,
-            routing_preferences: None,
             cluster_name: None,
             base_url_path_prefix: None,
             internal: None,

crates/common/src/http.rs

@@ -75,7 +75,10 @@ pub trait Client: Context {
     fn add_call_context(&self, id: u32, call_context: Self::CallContext) {
         let callouts = self.callouts();
         if callouts.borrow_mut().insert(id, call_context).is_some() {
-            panic!("Duplicate http call with id={}", id);
+            log::warn!(
+                "Duplicate http call with id={}, previous context overwritten",
+                id
+            );
         }
         self.active_http_calls().increment(1);
     }

crates/common/src/llm_providers.rs

@@ -274,7 +274,6 @@ mod tests {
             port: None,
             rate_limits: None,
             usage: None,
-            routing_preferences: None,
             internal: None,
             stream: None,
             passthrough_auth: None,

crates/common/src/ratelimit.rs

@@ -73,7 +73,10 @@ impl RatelimitMap {
             match new_ratelimit_map.datastore.get_mut(&ratelimit_config.model) {
                 Some(limits) => match limits.get_mut(&ratelimit_config.selector) {
                     Some(_) => {
-                        panic!("repeated selector. Selectors per provider must be unique")
+                        log::error!(
+                            "repeated selector for model '{}'. Selectors per provider must be unique, skipping duplicate",
+                            ratelimit_config.model
+                        );
                     }
                     None => {
                         limits.insert(ratelimit_config.selector, limit);
@@ -150,6 +153,10 @@ fn get_quota(limit: Limit) -> Quota {
         TimeUnit::Second => Quota::per_second(tokens),
         TimeUnit::Minute => Quota::per_minute(tokens),
         TimeUnit::Hour => Quota::per_hour(tokens),
+        TimeUnit::Day => {
+            let per_hour = limit.tokens.saturating_div(24).max(1);
+            Quota::per_hour(NonZero::new(per_hour).expect("per_hour must be positive"))
+        }
     }
 }
 

crates/hermesllm/src/apis/anthropic.rs

@@ -572,7 +572,9 @@ impl ProviderRequest for MessagesRequest {
         let mut regular_messages = Vec::new();
 
         for msg in messages {
-            if msg.role == crate::apis::openai::Role::System {
+            if msg.role == crate::apis::openai::Role::System
+                || msg.role == crate::apis::openai::Role::Developer
+            {
                 system_messages.push(msg.clone());
             } else {
                 regular_messages.push(msg.clone());

crates/hermesllm/src/apis/openai.rs

@@ -150,6 +150,7 @@ pub enum Role {
     User,
     Assistant,
     Tool,
+    Developer,
 }
 
 #[skip_serializing_none]
@@ -736,6 +737,7 @@ impl ProviderStreamResponse for ChatCompletionsStreamResponse {
                 Role::User => "user",
                 Role::Assistant => "assistant",
                 Role::Tool => "tool",
+                Role::Developer => "developer",
             })
         })
     }

crates/hermesllm/src/clients/endpoints.rs

@@ -92,6 +92,7 @@ impl SupportedAPIsFromClient {
         model_id: &str,
         is_streaming: bool,
         base_url_path_prefix: Option<&str>,
+        use_unversioned_paths: bool,
     ) -> String {
         // Helper function to build endpoint with optional prefix override
         let build_endpoint = |provider_prefix: &str, suffix: &str| -> String {
@@ -161,7 +162,13 @@ impl SupportedAPIsFromClient {
                         build_endpoint("/v1", endpoint_suffix)
                     }
                 }
-                _ => build_endpoint("/v1", endpoint_suffix),
+                _ => {
+                    if use_unversioned_paths {
+                        build_endpoint("", endpoint_suffix)
+                    } else {
+                        build_endpoint("/v1", endpoint_suffix)
+                    }
+                }
             }
         };
 
@@ -343,7 +350,8 @@ mod tests {
                 "/v1/chat/completions",
                 "gpt-4",
                 false,
-                None
+                None,
+                false
             ),
             "/v1/chat/completions"
         );
@@ -355,7 +363,8 @@ mod tests {
                 "/v1/chat/completions",
                 "llama2",
                 false,
-                None
+                None,
+                false
             ),
             "/openai/v1/chat/completions"
         );
@@ -367,7 +376,8 @@ mod tests {
                 "/v1/chat/completions",
                 "chatglm",
                 false,
-                None
+                None,
+                false
             ),
             "/api/paas/v4/chat/completions"
         );
@@ -379,7 +389,8 @@ mod tests {
                 "/v1/chat/completions",
                 "qwen-turbo",
                 false,
-                None
+                None,
+                false
             ),
             "/compatible-mode/v1/chat/completions"
         );
@@ -391,7 +402,8 @@ mod tests {
                 "/v1/chat/completions",
                 "gpt-4",
                 false,
-                None
+                None,
+                false
             ),
             "/openai/deployments/gpt-4/chat/completions?api-version=2025-01-01-preview"
         );
@@ -403,12 +415,30 @@ mod tests {
                 "/v1/chat/completions",
                 "gemini-pro",
                 false,
-                None
+                None,
+                false
             ),
             "/v1beta/openai/chat/completions"
         );
     }
 
+    #[test]
+    fn test_target_endpoint_unversioned_paths() {
+        let api = SupportedAPIsFromClient::OpenAIChatCompletions(OpenAIApi::ChatCompletions);
+
+        assert_eq!(
+            api.target_endpoint_for_provider(
+                &ProviderId::OpenAI,
+                "/v1/chat/completions",
+                "sonar-pro",
+                false,
+                None,
+                true
+            ),
+            "/chat/completions"
+        );
+    }
+
     #[test]
     fn test_target_endpoint_with_base_url_prefix() {
         let api = SupportedAPIsFromClient::OpenAIChatCompletions(OpenAIApi::ChatCompletions);
@@ -420,7 +450,8 @@ mod tests {
                 "/v1/chat/completions",
                 "chatglm",
                 false,
-                Some("/api/coding/paas/v4")
+                Some("/api/coding/paas/v4"),
+                false
             ),
             "/api/coding/paas/v4/chat/completions"
         );
@@ -432,7 +463,8 @@ mod tests {
                 "/v1/chat/completions",
                 "chatglm",
                 false,
-                Some("api/coding/paas/v4")
+                Some("api/coding/paas/v4"),
+                false
             ),
             "/api/coding/paas/v4/chat/completions"
         );
@@ -444,7 +476,8 @@ mod tests {
                 "/v1/chat/completions",
                 "chatglm",
                 false,
-                Some("/api/coding/paas/v4/")
+                Some("/api/coding/paas/v4/"),
+                false
             ),
             "/api/coding/paas/v4/chat/completions"
         );
@@ -456,7 +489,8 @@ mod tests {
                 "/v1/chat/completions",
                 "gpt-4",
                 false,
-                Some("/custom/api/v2")
+                Some("/custom/api/v2"),
+                false
             ),
             "/custom/api/v2/chat/completions"
         );
@@ -468,7 +502,8 @@ mod tests {
                 "/v1/chat/completions",
                 "llama2",
                 false,
-                Some("/api/v2")
+                Some("/api/v2"),
+                false
             ),
             "/api/v2/v1/chat/completions"
         );
@@ -485,7 +520,8 @@ mod tests {
                 "/v1/chat/completions",
                 "chatglm",
                 false,
-                Some("/")
+                Some("/"),
+                false
             ),
             "/api/paas/v4/chat/completions"
         );
@@ -497,7 +533,8 @@ mod tests {
                 "/v1/chat/completions",
                 "chatglm",
                 false,
-                None
+                None,
+                false
             ),
             "/api/paas/v4/chat/completions"
         );
@@ -514,7 +551,8 @@ mod tests {
                 "/v1/messages",
                 "us.amazon.nova-pro-v1:0",
                 false,
-                None
+                None,
+                false
             ),
             "/model/us.amazon.nova-pro-v1:0/converse"
         );
@@ -526,7 +564,8 @@ mod tests {
                 "/v1/messages",
                 "us.amazon.nova-pro-v1:0",
                 true,
-                None
+                None,
+                false
             ),
             "/model/us.amazon.nova-pro-v1:0/converse-stream"
         );
@@ -538,7 +577,8 @@ mod tests {
                 "/v1/messages",
                 "us.amazon.nova-pro-v1:0",
                 false,
-                Some("/custom/path")
+                Some("/custom/path"),
+                false
             ),
             "/custom/path/model/us.amazon.nova-pro-v1:0/converse"
         );
@@ -550,7 +590,8 @@ mod tests {
                 "/v1/messages",
                 "us.amazon.nova-pro-v1:0",
                 true,
-                Some("/custom/path")
+                Some("/custom/path"),
+                false
             ),
             "/custom/path/model/us.amazon.nova-pro-v1:0/converse-stream"
         );
@@ -567,7 +608,8 @@ mod tests {
                 "/v1/messages",
                 "claude-3-opus",
                 false,
-                None
+                None,
+                false
             ),
             "/v1/messages"
         );
@@ -579,7 +621,8 @@ mod tests {
                 "/v1/messages",
                 "claude-3-opus",
                 false,
-                Some("/api/v2")
+                Some("/api/v2"),
+                false
             ),
             "/api/v2/messages"
         );
@@ -596,7 +639,8 @@ mod tests {
                 "/custom/path",
                 "llama2",
                 false,
-                None
+                None,
+                false
             ),
             "/v1/chat/completions"
         );
@@ -608,7 +652,8 @@ mod tests {
                 "/custom/path",
                 "chatglm",
                 false,
-                None
+                None,
+                false
             ),
             "/v1/chat/completions"
         );
@@ -620,7 +665,8 @@ mod tests {
                 "/custom/path",
                 "chatglm",
                 false,
-                Some("/api/v2")
+                Some("/api/v2"),
+                false
             ),
             "/api/v2/chat/completions"
         );
@@ -637,7 +683,8 @@ mod tests {
                 "/v1/chat/completions",
                 "gpt-4-deployment",
                 false,
-                None
+                None,
+                false
             ),
             "/openai/deployments/gpt-4-deployment/chat/completions?api-version=2025-01-01-preview"
         );
@@ -649,7 +696,8 @@ mod tests {
                 "/v1/chat/completions",
                 "gpt-4-deployment",
                 false,
-                Some("/custom/azure/path")
+                Some("/custom/azure/path"),
+                false
             ),
             "/custom/azure/path/gpt-4-deployment/chat/completions?api-version=2025-01-01-preview"
         );
@@ -664,7 +712,8 @@ mod tests {
                 "/v1/responses",
                 "grok-4-1-fast-reasoning",
                 false,
-                None
+                None,
+                false
             ),
             "/v1/responses"
         );

crates/hermesllm/src/transforms/request/from_openai.rs

@@ -97,7 +97,7 @@ impl TryFrom<ResponsesInputConverter> for Vec<Message> {
                                 MessageRole::User => Role::User,
                                 MessageRole::Assistant => Role::Assistant,
                                 MessageRole::System => Role::System,
-                                MessageRole::Developer => Role::System, // Map developer to system
+                                MessageRole::Developer => Role::Developer,
                                 MessageRole::Tool => Role::Tool,
                             };
 
@@ -281,7 +281,7 @@ impl TryFrom<Message> for MessagesMessage {
                     ]),
                 });
             }
-            Role::System => {
+            Role::System | Role::Developer => {
                 return Err(TransformError::UnsupportedConversion(
                     "System messages should be handled separately".to_string(),
                 ));
@@ -303,7 +303,7 @@ impl TryFrom<Message> for BedrockMessage {
             Role::User => ConversationRole::User,
             Role::Assistant => ConversationRole::Assistant,
             Role::Tool => ConversationRole::User, // Tool results become user messages in Bedrock
-            Role::System => {
+            Role::System | Role::Developer => {
                 return Err(TransformError::UnsupportedConversion(
                     "System messages should be handled separately in Bedrock".to_string(),
                 ));
@@ -452,7 +452,7 @@ impl TryFrom<Message> for BedrockMessage {
                     },
                 });
             }
-            Role::System => {
+            Role::System | Role::Developer => {
                 // Already handled above with early return
                 unreachable!()
             }
@@ -706,7 +706,7 @@ impl TryFrom<ChatCompletionsRequest> for AnthropicMessagesRequest {
 
         for message in req.messages {
             match message.role {
-                Role::System => {
+                Role::System | Role::Developer => {
                     system_prompt = Some(message.into());
                 }
                 _ => {
@@ -755,7 +755,7 @@ impl TryFrom<ChatCompletionsRequest> for ConverseRequest {
 
         for message in req.messages {
             match message.role {
-                Role::System => {
+                Role::System | Role::Developer => {
                     let system_text = message.content.extract_text();
                     system_messages.push(SystemContentBlock::Text { text: system_text });
                 }

crates/hermesllm/src/transforms/response/to_openai.rs

@@ -95,6 +95,7 @@ impl TryFrom<ChatCompletionsResponse> for ResponsesAPIResponse {
                         Role::Assistant => "assistant".to_string(),
                         Role::System => "system".to_string(),
                         Role::Tool => "tool".to_string(),
+                        Role::Developer => "developer".to_string(),
                     },
                     content,
                 });

crates/llm_gateway/src/stream_context.rs

@@ -122,6 +122,7 @@ impl StreamContext {
                     .unwrap_or(&"".to_string()),
                 self.streaming_response,
                 self.llm_provider().base_url_path_prefix.as_deref(),
+                self.llm_provider().name.starts_with("perplexity/"),
             );
             if target_endpoint != request_path {
                 self.set_http_request_header(":path", Some(&target_endpoint));

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 [[package]]
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-version = "4.67.1"
+version = "4.67.3"
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 dependencies = [
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 wheels = [
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 ]
+
+[[package]]
+name = "wcwidth"
+version = "0.6.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/35/a2/8e3becb46433538a38726c948d3399905a4c7cabd0df578ede5dc51f0ec2/wcwidth-0.6.0.tar.gz", hash = "sha256:cdc4e4262d6ef9a1a57e018384cbeb1208d8abbc64176027e2c2455c81313159", size = 159684, upload-time = "2026-02-06T19:19:40.919Z" }
+wheels = [
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+]

demos/agent_orchestration/multi_agent_crewai_langchain/crewai/flight_agent.py

@@ -287,12 +287,16 @@ async def fetch_flights(
                     "flight_number": flight.get("ident_iata") or flight.get("ident"),
                     "departure_time": flight.get("scheduled_out"),
                     "arrival_time": flight.get("scheduled_in"),
-                    "origin": flight["origin"].get("code_iata")
-                    if isinstance(flight.get("origin"), dict)
-                    else None,
-                    "destination": flight["destination"].get("code_iata")
-                    if isinstance(flight.get("destination"), dict)
-                    else None,
+                    "origin": (
+                        flight["origin"].get("code_iata")
+                        if isinstance(flight.get("origin"), dict)
+                        else None
+                    ),
+                    "destination": (
+                        flight["destination"].get("code_iata")
+                        if isinstance(flight.get("destination"), dict)
+                        else None
+                    ),
                     "aircraft_type": flight.get("aircraft_type"),
                     "status": flight.get("status"),
                     "terminal_origin": flight.get("terminal_origin"),

demos/agent_orchestration/travel_agents/src/travel_agents/flight_agent.py

@@ -197,12 +197,16 @@ async def fetch_flights(
                     "flight_number": flight.get("ident_iata") or flight.get("ident"),
                     "departure_time": flight.get("scheduled_out"),
                     "arrival_time": flight.get("scheduled_in"),
-                    "origin": flight["origin"].get("code_iata")
-                    if isinstance(flight.get("origin"), dict)
-                    else None,
-                    "destination": flight["destination"].get("code_iata")
-                    if isinstance(flight.get("destination"), dict)
-                    else None,
+                    "origin": (
+                        flight["origin"].get("code_iata")
+                        if isinstance(flight.get("origin"), dict)
+                        else None
+                    ),
+                    "destination": (
+                        flight["destination"].get("code_iata")
+                        if isinstance(flight.get("destination"), dict)
+                        else None
+                    ),
                     "aircraft_type": flight.get("aircraft_type"),
                     "status": flight.get("status"),
                     "terminal_origin": flight.get("terminal_origin"),

demos/filter_chains/http_filter/pyproject.toml

@@ -7,7 +7,7 @@ requires-python = ">=3.10,<3.14"
 dependencies = [
     "click>=8.2.1",
     "mcp>=1.13.1",
-    "fastmcp>=2.14",
+    "fastmcp>=3.2.0",
     "pydantic>=2.11.7",
     "fastapi>=0.104.1",
     "uvicorn>=0.24.0",

demos/filter_chains/mcp_filter/pyproject.toml

@@ -7,7 +7,7 @@ requires-python = ">=3.10,<3.14"
 dependencies = [
     "click>=8.2.1",
     "mcp>=1.13.1",
-    "fastmcp>=2.14",
+    "fastmcp>=3.2.0",
     "pydantic>=2.11.7",
     "fastapi>=0.104.1",
     "uvicorn>=0.24.0",

demos/getting_started/weather_forecast/main.py

@@ -12,7 +12,6 @@ from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExport
 from opentelemetry.sdk.trace.export import BatchSpanProcessor
 from opentelemetry.sdk.resources import Resource
 
-
 resource = Resource.create(
     {
         "service.name": "weather-forecast-service",

demos/llm_routing/model_routing_service/README.md

@@ -18,37 +18,40 @@ Plano is an AI-native proxy and data plane for agentic apps — with built-in or
 
 ## How Routing Works
 
-The entire routing configuration is plain YAML — no code:
+Routing is configured in top-level `routing_preferences` (requires `version: v0.4.0`):
 
 ```yaml
-model_providers:
-  - model: openai/gpt-4o-mini
-    default: true                    # fallback for unmatched requests
+version: v0.4.0
 
-  - model: openai/gpt-4o
-    routing_preferences:
-      - name: complex_reasoning
-        description: complex reasoning tasks, multi-step analysis
+routing_preferences:
+  - name: complex_reasoning
+    description: complex reasoning tasks, multi-step analysis, or detailed explanations
+    models:
+      - openai/gpt-4o
+      - openai/gpt-4o-mini
 
-  - model: anthropic/claude-sonnet-4-20250514
-    routing_preferences:
-      - name: code_generation
-        description: generating new code, writing functions
+  - name: code_generation
+    description: generating new code, writing functions, or creating boilerplate
+    models:
+      - anthropic/claude-sonnet-4-20250514
+      - openai/gpt-4o
 ```
 
-When a request arrives, Plano sends the conversation and routing preferences to Arch-Router, which classifies the intent and returns the matching route:
+When a request arrives, Plano:
+
+1. Sends the conversation + route descriptions to Arch-Router for intent classification
+2. Looks up the matched route and returns its candidate models
+3. Returns an ordered list — client uses `models[0]`, falls back to `models[1]` on 429/5xx
 
 ```
 1. Request arrives          → "Write binary search in Python"
-2. Preferences serialized   → [{"name":"code_generation", ...}, {"name":"complex_reasoning", ...}]
-3. Arch-Router classifies   → {"route": "code_generation"}
-4. Route → Model lookup     → code_generation → anthropic/claude-sonnet-4-20250514
-5. Request forwarded        → Claude generates the response
+2. Arch-Router classifies   → route: "code_generation"
+3. Response                 → models: ["anthropic/claude-sonnet-4-20250514", "openai/gpt-4o"]
 ```
 
-No match? Arch-Router returns `other` → Plano falls back to the default model.
+No match? Arch-Router returns `null` route → client falls back to the model in the original request.
 
-The `/routing/v1/*` endpoints return the routing decision **without** forwarding to the LLM — useful for testing and validating routing behavior before going to production.
+The `/routing/v1/*` endpoints return the routing decision **without** forwarding to the LLM — useful for testing routing behavior before going to production.
 
 ## Setup
 
@@ -60,9 +63,9 @@ export ANTHROPIC_API_KEY=<your-key>
 ```
 
 Start Plano:
+
 ```bash
-cd demos/llm_routing/model_routing_service
-planoai up config.yaml
+planoai up demos/llm_routing/model_routing_service/config.yaml
 ```
 
 ## Run the demo
@@ -95,13 +98,13 @@ curl http://localhost:12000/routing/v1/chat/completions \
 Response:
 ```json
 {
-    "model": "anthropic/claude-sonnet-4-20250514",
+    "models": ["anthropic/claude-sonnet-4-20250514", "openai/gpt-4o"],
     "route": "code_generation",
     "trace_id": "c16d1096c1af4a17abb48fb182918a88"
 }
 ```
 
-The response tells you which model would handle this request and which route was matched, without actually making the LLM call.
+The response contains the model list — your client should try `models[0]` first and fall back to `models[1]` on 429 or 5xx errors.
 
 ## Session Pinning
 
@@ -176,7 +179,6 @@ GPU nodes commonly have a `nvidia.com/gpu:NoSchedule` taint — `vllm-deployment
 **1. Deploy Arch-Router and Plano:**
 
 ```bash
-
 # arch-router deployment
 kubectl apply -f vllm-deployment.yaml
 
@@ -223,6 +225,7 @@ kubectl create configmap plano-config \
 kubectl rollout restart deployment/plano
 ```
 
+
 ## Demo Output
 
 ```
@@ -230,35 +233,35 @@ kubectl rollout restart deployment/plano
 
 --- 1. Code generation query (OpenAI format) ---
 {
-    "model": "anthropic/claude-sonnet-4-20250514",
+    "models": ["anthropic/claude-sonnet-4-20250514", "openai/gpt-4o"],
     "route": "code_generation",
     "trace_id": "c16d1096c1af4a17abb48fb182918a88"
 }
 
 --- 2. Complex reasoning query (OpenAI format) ---
 {
-    "model": "openai/gpt-4o",
+    "models": ["openai/gpt-4o", "openai/gpt-4o-mini"],
     "route": "complex_reasoning",
     "trace_id": "30795e228aff4d7696f082ed01b75ad4"
 }
 
 --- 3. Simple query - no routing match (OpenAI format) ---
 {
-    "model": "none",
+    "models": ["none"],
     "route": null,
     "trace_id": "ae0b6c3b220d499fb5298ac63f4eac0e"
 }
 
 --- 4. Code generation query (Anthropic format) ---
 {
-    "model": "anthropic/claude-sonnet-4-20250514",
+    "models": ["anthropic/claude-sonnet-4-20250514", "openai/gpt-4o"],
     "route": "code_generation",
     "trace_id": "26be822bbdf14a3ba19fe198e55ea4a9"
 }
 
 --- 7. Session pinning - first call (fresh routing decision) ---
 {
-    "model": "anthropic/claude-sonnet-4-20250514",
+    "models": ["anthropic/claude-sonnet-4-20250514", "openai/gpt-4o"],
     "route": "code_generation",
     "trace_id": "f1a2b3c4d5e6f7a8b9c0d1e2f3a4b5c6",
     "session_id": "demo-session-001",
@@ -277,7 +280,7 @@ kubectl rollout restart deployment/plano
 
 --- 9. Different session gets its own fresh routing ---
 {
-    "model": "openai/gpt-4o",
+    "models": ["openai/gpt-4o", "openai/gpt-4o-mini"],
     "route": "complex_reasoning",
     "trace_id": "1a2b3c4d5e6f7a8b9c0d1e2f3a4b5c6d",
     "session_id": "demo-session-002",

demos/llm_routing/model_routing_service/config.yaml

@@ -1,4 +1,4 @@
-version: v0.3.0
+version: v0.4.0
 
 listeners:
   - type: model
@@ -6,22 +6,25 @@ listeners:
     port: 12000
 
 model_providers:
-
   - model: openai/gpt-4o-mini
     access_key: $OPENAI_API_KEY
     default: true
 
   - model: openai/gpt-4o
     access_key: $OPENAI_API_KEY
-    routing_preferences:
-      - name: complex_reasoning
-        description: complex reasoning tasks, multi-step analysis, or detailed explanations
 
   - model: anthropic/claude-sonnet-4-20250514
     access_key: $ANTHROPIC_API_KEY
-    routing_preferences:
-      - name: code_generation
-        description: generating new code, writing functions, or creating boilerplate
 
-tracing:
-  random_sampling: 100
+routing_preferences:
+  - name: complex_reasoning
+    description: complex reasoning tasks, multi-step analysis, or detailed explanations
+    models:
+      - openai/gpt-4o
+      - openai/gpt-4o-mini
+
+  - name: code_generation
+    description: generating new code, writing functions, or creating boilerplate
+    models:
+      - anthropic/claude-sonnet-4-20250514
+      - openai/gpt-4o

demos/llm_routing/model_routing_service/demo.sh

@@ -8,9 +8,12 @@ echo ""
 echo "This demo shows how to use the /routing/v1/* endpoints to get"
 echo "routing decisions without actually proxying the request to an LLM."
 echo ""
+echo "The response includes a ranked 'models' list — use models[0] as the"
+echo "primary and fall back to models[1] on 429/5xx errors."
+echo ""
 
-# --- Example 1: OpenAI Chat Completions format ---
-echo "--- 1. Code generation query (OpenAI format) ---"
+# --- Example 1: Code generation (ranked by fastest) ---
+echo "--- 1. Code generation query (prefer: fastest) ---"
 echo ""
 curl -s "$PLANO_URL/routing/v1/chat/completions" \
   -H "Content-Type: application/json" \
@@ -22,8 +25,8 @@ curl -s "$PLANO_URL/routing/v1/chat/completions" \
   }' | python3 -m json.tool
 echo ""
 
-# --- Example 2: Complex reasoning query ---
-echo "--- 2. Complex reasoning query (OpenAI format) ---"
+# --- Example 2: Complex reasoning (ranked by cheapest) ---
+echo "--- 2. Complex reasoning query (prefer: cheapest) ---"
 echo ""
 curl -s "$PLANO_URL/routing/v1/chat/completions" \
   -H "Content-Type: application/json" \
@@ -36,7 +39,7 @@ curl -s "$PLANO_URL/routing/v1/chat/completions" \
 echo ""
 
 # --- Example 3: Simple query (no routing match) ---
-echo "--- 3. Simple query - no routing match (OpenAI format) ---"
+echo "--- 3. Simple query - no routing match (falls back to request model) ---"
 echo ""
 curl -s "$PLANO_URL/routing/v1/chat/completions" \
   -H "Content-Type: application/json" \
@@ -62,8 +65,31 @@ curl -s "$PLANO_URL/routing/v1/messages" \
   }' | python3 -m json.tool
 echo ""
 
-# --- Example 5: Inline routing policy in request body ---
-echo "--- 5. Inline routing_policy (no config needed) ---"
+# --- Example 5: Inline routing_preferences with prefer:cheapest ---
+echo "--- 5. Inline routing_preferences (prefer: cheapest) ---"
+echo "    models[] will be sorted by ascending cost from DigitalOcean pricing"
+echo ""
+curl -s "$PLANO_URL/routing/v1/chat/completions" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "gpt-4o-mini",
+    "messages": [
+      {"role": "user", "content": "Summarize the key differences between TCP and UDP"}
+    ],
+    "routing_preferences": [
+      {
+        "name": "general",
+        "description": "general questions, explanations, and summaries",
+        "models": ["openai/gpt-4o", "openai/gpt-4o-mini"],
+        "selection_policy": {"prefer": "cheapest"}
+      }
+    ]
+  }' | python3 -m json.tool
+echo ""
+
+# --- Example 6: Inline routing_preferences with prefer:fastest ---
+echo "--- 6. Inline routing_preferences (prefer: fastest) ---"
+echo "    models[] will be sorted by ascending P95 latency from Prometheus"
 echo ""
 curl -s "$PLANO_URL/routing/v1/chat/completions" \
   -H "Content-Type: application/json" \
@@ -72,46 +98,12 @@ curl -s "$PLANO_URL/routing/v1/chat/completions" \
     "messages": [
       {"role": "user", "content": "Write a quicksort implementation in Go"}
     ],
-    "routing_policy": [
+    "routing_preferences": [
       {
-        "model": "openai/gpt-4o",
-        "routing_preferences": [
-          {"name": "coding", "description": "code generation, writing functions, debugging"}
-        ]
-      },
-      {
-        "model": "openai/gpt-4o-mini",
-        "routing_preferences": [
-          {"name": "general", "description": "general questions, simple lookups, casual conversation"}
-        ]
-      }
-    ]
-  }' | python3 -m json.tool
-echo ""
-
-# --- Example 6: Inline routing policy with Anthropic format ---
-echo "--- 6. Inline routing_policy (Anthropic format) ---"
-echo ""
-curl -s "$PLANO_URL/routing/v1/messages" \
-  -H "Content-Type: application/json" \
-  -d '{
-    "model": "gpt-4o-mini",
-    "max_tokens": 1024,
-    "messages": [
-      {"role": "user", "content": "What is the weather like today?"}
-    ],
-    "routing_policy": [
-      {
-        "model": "openai/gpt-4o",
-        "routing_preferences": [
-          {"name": "coding", "description": "code generation, writing functions, debugging"}
-        ]
-      },
-      {
-        "model": "openai/gpt-4o-mini",
-        "routing_preferences": [
-          {"name": "general", "description": "general questions, simple lookups, casual conversation"}
-        ]
+        "name": "coding",
+        "description": "code generation, writing functions, debugging",
+        "models": ["anthropic/claude-sonnet-4-20250514", "openai/gpt-4o", "openai/gpt-4o-mini"],
+        "selection_policy": {"prefer": "fastest"}
       }
     ]
   }' | python3 -m json.tool

demos/llm_routing/model_routing_service/docker-compose.yaml

@@ -0,0 +1,17 @@
+services:
+  prometheus:
+    image: prom/prometheus:latest
+    ports:
+      - "9090:9090"
+    volumes:
+      - ./prometheus.yaml:/etc/prometheus/prometheus.yml:ro
+    depends_on:
+      - model-metrics
+
+  model-metrics:
+    image: python:3.11-slim
+    ports:
+      - "8080:8080"
+    volumes:
+      - ./metrics_server.py:/metrics_server.py:ro
+    command: python /metrics_server.py

demos/llm_routing/model_routing_service/metrics_server.py

@@ -0,0 +1,52 @@
+"""
+Demo metrics server.
+
+Exposes two endpoints:
+  GET /metrics  — Prometheus text format, P95 latency per model (scraped by Prometheus)
+  GET /costs    — JSON cost data per model, compatible with cost_metrics source
+"""
+
+import json
+from http.server import HTTPServer, BaseHTTPRequestHandler
+
+PROMETHEUS_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()
+
+COST_DATA = {
+    "anthropic/claude-sonnet-4-20250514": {
+        "input_per_million": 3.0,
+        "output_per_million": 15.0,
+    },
+    "openai/gpt-4o": {"input_per_million": 5.0, "output_per_million": 20.0},
+    "openai/gpt-4o-mini": {"input_per_million": 0.15, "output_per_million": 0.6},
+}
+
+
+class MetricsHandler(BaseHTTPRequestHandler):
+    def do_GET(self):
+        if self.path == "/costs":
+            body = json.dumps(COST_DATA).encode()
+            self.send_response(200)
+            self.send_header("Content-Type", "application/json")
+            self.end_headers()
+            self.wfile.write(body)
+        else:
+            # /metrics and everything else → Prometheus format
+            self.send_response(200)
+            self.send_header("Content-Type", "text/plain; version=0.0.4; charset=utf-8")
+            self.end_headers()
+            self.wfile.write(PROMETHEUS_METRICS)
+
+    def log_message(self, fmt, *args):
+        pass  # suppress access logs
+
+
+if __name__ == "__main__":
+    server = HTTPServer(("", 8080), MetricsHandler)
+    print("metrics server listening on :8080 (/metrics, /costs)", flush=True)
+    server.serve_forever()

demos/llm_routing/model_routing_service/prometheus.yaml

@@ -0,0 +1,8 @@
+global:
+  scrape_interval: 15s
+
+scrape_configs:
+  - job_name: model_latency
+    static_configs:
+      - targets:
+          - model-metrics:8080

demos/shared/test_runner/common.py

@@ -1,6 +1,5 @@
 import json
 
-
 ARCH_STATE_HEADER = "x-arch-state"
 
 

demos/shared/test_runner/pyproject.toml

@@ -8,7 +8,7 @@ readme = "README.md"
 requires-python = ">=3.12"
 dependencies = [
     "pytest>=8.3.3",
-    "requests>=2.29.0",
+    "requests>=2.33.0",
     "pytest-sugar>=1.0.0",
     "deepdiff>=8.0.1",
     "pytest-retry>=1.6.3",

demos/shared/test_runner/run_demo_tests.sh

@@ -14,6 +14,30 @@ DEMOS="$@"
 
 echo "Running tests for demos: $DEMOS"
 
+run_hurl_with_retries() {
+  local demo_name="$1"
+  local max_attempts=1
+  local attempt=1
+
+  if [ "$demo_name" = "llm_routing/preference_based_routing" ]; then
+    max_attempts=3
+  fi
+
+  while true; do
+    if hurl hurl_tests/*.hurl; then
+      return 0
+    fi
+
+    if [ "$attempt" -ge "$max_attempts" ]; then
+      return 1
+    fi
+
+    attempt=$((attempt + 1))
+    echo "hurl failed for $demo_name, retrying (attempt $attempt/$max_attempts) ..."
+    sleep 2
+  done
+}
+
 for demo in $DEMOS
 do
   echo "******************************************"
@@ -31,7 +55,7 @@ do
     echo "skipping docker compose for $demo"
   fi
   echo "starting hurl tests"
-  if ! hurl hurl_tests/*.hurl; then
+  if ! run_hurl_with_retries "$demo"; then
     echo "Hurl tests failed for $demo"
     echo "docker logs for plano:"
     docker logs plano | tail -n 100

demos/shared/test_runner/uv.lock

@@ -1,165 +1,192 @@
 version = 1
+revision = 3
 requires-python = ">=3.12"
 
 [[package]]
 name = "certifi"
-version = "2025.11.12"
+version = "2026.2.25"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/a2/8c/58f469717fa48465e4a50c014a0400602d3c437d7c0c468e17ada824da3a/certifi-2025.11.12.tar.gz", hash = "sha256:d8ab5478f2ecd78af242878415affce761ca6bc54a22a27e026d7c25357c3316", size = 160538 }
+sdist = { url = "https://files.pythonhosted.org/packages/af/2d/7bf41579a8986e348fa033a31cdd0e4121114f6bce2457e8876010b092dd/certifi-2026.2.25.tar.gz", hash = "sha256:e887ab5cee78ea814d3472169153c2d12cd43b14bd03329a39a9c6e2e80bfba7", size = 155029, upload-time = "2026-02-25T02:54:17.342Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/70/7d/9bc192684cea499815ff478dfcdc13835ddf401365057044fb721ec6bddb/certifi-2025.11.12-py3-none-any.whl", hash = "sha256:97de8790030bbd5c2d96b7ec782fc2f7820ef8dba6db909ccf95449f2d062d4b", size = 159438 },
+    { url = "https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl", hash = "sha256:027692e4402ad994f1c42e52a4997a9763c646b73e4096e4d5d6db8af1d6f0fa", size = 153684, upload-time = "2026-02-25T02:54:15.766Z" },
 ]
 
 [[package]]
 name = "charset-normalizer"
-version = "3.4.4"
+version = "3.4.7"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/13/69/33ddede1939fdd074bce5434295f38fae7136463422fe4fd3e0e89b98062/charset_normalizer-3.4.4.tar.gz", hash = "sha256:94537985111c35f28720e43603b8e7b43a6ecfb2ce1d3058bbe955b73404e21a", size = 129418 }
+sdist = { url = "https://files.pythonhosted.org/packages/e7/a1/67fe25fac3c7642725500a3f6cfe5821ad557c3abb11c9d20d12c7008d3e/charset_normalizer-3.4.7.tar.gz", hash = "sha256:ae89db9e5f98a11a4bf50407d4363e7b09b31e55bc117b4f7d80aab97ba009e5", size = 144271, upload-time = "2026-04-02T09:28:39.342Z" }
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docs/routing-api.md

@@ -0,0 +1,128 @@
+# Plano Routing API — Request & Response Format
+
+## Overview
+
+Plano intercepts LLM requests and routes them to the best available model based on semantic intent and live cost/latency data. The developer sends a standard OpenAI-compatible request with an optional `routing_preferences` field. Plano returns an ordered list of candidate models; the client uses the first and falls back to the next on 429 or 5xx errors.
+
+---
+
+## Request Format
+
+Standard OpenAI chat completion body. The only addition is the optional `routing_preferences` field, which is stripped before the request is forwarded upstream.
+
+```json
+POST /v1/chat/completions
+{
+  "model": "openai/gpt-4o-mini",
+  "messages": [
+    {"role": "user", "content": "write a sorting algorithm in Python"}
+  ],
+  "routing_preferences": [
+    {
+      "name": "code generation",
+      "description": "generating new code snippets",
+      "models": ["anthropic/claude-sonnet-4-20250514", "openai/gpt-4o", "openai/gpt-4o-mini"]
+    },
+    {
+      "name": "general questions",
+      "description": "casual conversation and simple queries",
+      "models": ["openai/gpt-4o-mini"]
+    }
+  ]
+}
+```
+
+### `routing_preferences` fields
+
+| Field | Type | Required | Description |
+|---|---|---|---|
+| `name` | string | yes | Route identifier. Must match the LLM router's route classification. |
+| `description` | string | yes | Natural language description used by the router to match user intent. |
+| `models` | string[] | yes | Ordered candidate pool. At least one entry required. Must be declared in `model_providers`. |
+
+### Notes
+
+- `routing_preferences` is **optional**. If omitted, the config-defined preferences are used.
+- If provided in the request body, it **overrides** the config for that single request only.
+- `model` is still required and is used as the fallback if no route is matched.
+
+---
+
+## Response Format
+
+```json
+{
+  "models": [
+    "anthropic/claude-sonnet-4-20250514",
+    "openai/gpt-4o",
+    "openai/gpt-4o-mini"
+  ],
+  "route": "code generation",
+  "trace_id": "4bf92f3577b34da6a3ce929d0e0e4736"
+}
+```
+
+### Fields
+
+| Field | Type | Description |
+|---|---|---|
+| `models` | string[] | Ranked model list. Use `models[0]` as primary; retry with `models[1]` on 429/5xx, and so on. |
+| `route` | string \| null | Name of the matched route. `null` if no route matched — client should use the original request `model`. |
+| `trace_id` | string | Trace ID for distributed tracing and observability. |
+
+---
+
+## Client Usage Pattern
+
+```python
+response = plano.routing_decision(request)
+models = response["models"]
+
+for model in models:
+    try:
+        result = call_llm(model, messages)
+        break  # success — stop trying
+    except (RateLimitError, ServerError):
+        continue  # try next model in the ranked list
+```
+
+---
+
+## Configuration (set by platform/ops team)
+
+Requires `version: v0.4.0` or above. Models listed under `routing_preferences` must be declared in `model_providers`.
+
+```yaml
+version: v0.4.0
+
+model_providers:
+  - model: anthropic/claude-sonnet-4-20250514
+    access_key: $ANTHROPIC_API_KEY
+  - model: openai/gpt-4o
+    access_key: $OPENAI_API_KEY
+  - model: openai/gpt-4o-mini
+    access_key: $OPENAI_API_KEY
+    default: true
+
+routing_preferences:
+  - name: code generation
+    description: generating new code snippets or boilerplate
+    models:
+      - anthropic/claude-sonnet-4-20250514
+      - openai/gpt-4o
+
+  - name: general questions
+    description: casual conversation and simple queries
+    models:
+      - openai/gpt-4o-mini
+      - openai/gpt-4o
+```
+
+---
+
+## Version Requirements
+
+| Version | Top-level `routing_preferences` |
+|---|---|
+| `< v0.4.0` | Not allowed — startup error if present |
+| `v0.4.0+` | Supported (required for model routing) |

docs/source/_ext/provider_models.py

@@ -1,4 +1,5 @@
 """Sphinx extension to copy provider_models.yaml to build output."""
+
 from __future__ import annotations
 
 from pathlib import Path

docs/source/conf.py

@@ -15,9 +15,9 @@ from sphinxawesome_theme import ThemeOptions
 from sphinxawesome_theme.postprocess import Icons
 
 project = "Plano Docs"
-copyright = "2025, Katanemo Labs, Inc"
+copyright = "2026, Katanemo Labs, a DigitalOcean Company"
 author = "Katanemo Labs, Inc"
-release = " v0.4.14"
+release = " v0.4.16"
 
 # -- General configuration ---------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration

docs/source/get_started/quickstart.rst

@@ -43,7 +43,7 @@ Plano's CLI allows you to manage and interact with the Plano efficiently. To ins
 
 .. code-block:: console
 
-   $ uv tool install planoai==0.4.14
+   $ uv tool install planoai==0.4.16
 
 **Option 2: Install with pip (Traditional)**
 
@@ -51,7 +51,7 @@ Plano's CLI allows you to manage and interact with the Plano efficiently. To ins
 
    $ python -m venv venv
    $ source venv/bin/activate   # On Windows, use: venv\Scripts\activate
-   $ pip install planoai==0.4.14
+   $ pip install planoai==0.4.16
 
 
 .. _llm_routing_quickstart:

docs/source/resources/deployment.rst

@@ -65,7 +65,7 @@ Create a ``docker-compose.yml`` file with the following configuration:
    # docker-compose.yml
    services:
      plano:
-       image: katanemo/plano:0.4.14
+       image: katanemo/plano:0.4.16
        container_name: plano
        ports:
          - "10000:10000" # ingress (client -> plano)
@@ -153,7 +153,7 @@ Create a ``plano-deployment.yaml``:
        spec:
          containers:
            - name: plano
-             image: katanemo/plano:0.4.14
+             image: katanemo/plano:0.4.16
              ports:
                - containerPort: 12000  # LLM gateway (chat completions, model routing)
                  name: llm-gateway

docs/source/resources/includes/agents/weather.py

@@ -230,12 +230,12 @@ async def get_weather_data(request: Request, messages: list, days: int = 1):
                     "day_name": date_obj.strftime("%A"),
                     "temperature_c": round(temp_c, 1) if temp_c is not None else None,
                     "temperature_f": celsius_to_fahrenheit(temp_c),
-                    "temperature_max_c": round(temp_max, 1)
-                    if temp_max is not None
-                    else None,
-                    "temperature_min_c": round(temp_min, 1)
-                    if temp_min is not None
-                    else None,
+                    "temperature_max_c": (
+                        round(temp_max, 1) if temp_max is not None else None
+                    ),
+                    "temperature_min_c": (
+                        round(temp_min, 1) if temp_min is not None else None
+                    ),
                     "weather_code": weather_code,
                     "sunrise": sunrise.split("T")[1] if sunrise else None,
                     "sunset": sunset.split("T")[1] if sunset else None,

docs/source/resources/includes/plano_config_full_reference.yaml

@@ -32,13 +32,30 @@ model_providers:
   - model: mistral/ministral-3b-latest
     access_key: $MISTRAL_API_KEY
 
-  # Example: Passthrough authentication for LiteLLM or similar proxies
-  # When passthrough_auth is true, client's Authorization header is forwarded
-  # instead of using the configured access_key
+  # routing_preferences: tags a model with named capabilities so Plano's LLM router
+  # can select the best model for each request based on intent. Requires the
+  # Arch-Router model (or equivalent) to be configured in overrides.llm_routing_model.
+  # Each preference has a name (short label) and a description (used for intent matching).
+  - model: groq/llama-3.3-70b-versatile
+    access_key: $GROQ_API_KEY
+    routing_preferences:
+      - name: code generation
+        description: generating new code snippets, functions, or boilerplate based on user prompts or requirements
+      - name: code review
+        description: reviewing, analyzing, and suggesting improvements to existing code
+
+  # passthrough_auth: forwards the client's Authorization header upstream instead of
+  # using the configured access_key. Useful for LiteLLM or similar proxy setups.
   - model: openai/gpt-4o-litellm
     base_url: https://litellm.example.com
     passthrough_auth: true
 
+  # Custom/self-hosted endpoint with explicit http_host override
+  - model: openai/llama-3.3-70b
+    base_url: https://api.custom-provider.com
+    http_host: api.custom-provider.com
+    access_key: $CUSTOM_API_KEY
+
 # Model aliases - use friendly names instead of full provider model names
 model_aliases:
   fast-llm:
@@ -66,26 +83,38 @@ listeners:
     name: model_1
     address: 0.0.0.0
     port: 12000
-    # Optional: attach input filters for guardrails on direct LLM requests
-    # input_filters:
-    #   - input_guards
+    timeout: 30s          # Request timeout (e.g. "30s", "60s")
+    max_retries: 3        # Number of retries on upstream failure
+    input_filters:        # Filters applied before forwarding to LLM
+      - input_guards
+    output_filters:       # Filters applied to LLM responses before returning to client
+      - input_guards
 
   # Prompt listener for function calling (for prompt_targets)
   - type: prompt
     name: prompt_function_listener
     address: 0.0.0.0
     port: 10000
-    # This listener is used for prompt_targets and function calling
 
 # Reusable service endpoints
 endpoints:
   app_server:
     endpoint: 127.0.0.1:80
     connect_timeout: 0.005s
+    protocol: http        # http or https
 
   mistral_local:
     endpoint: 127.0.0.1:8001
 
+  secure_service:
+    endpoint: api.example.com:443
+    protocol: https
+    http_host: api.example.com  # Override the Host header sent upstream
+
+# Optional top-level system prompt applied to all prompt_targets
+system_prompt: |
+  You are a helpful assistant. Always respond concisely and accurately.
+
 # Prompt targets for function calling and API orchestration
 prompt_targets:
   - name: get_current_weather
@@ -104,8 +133,75 @@ prompt_targets:
       name: app_server
       path: /weather
       http_method: POST
+    # Per-target system prompt (overrides top-level system_prompt for this target)
+    system_prompt: You are a weather expert. Provide accurate and concise weather information.
+    # auto_llm_dispatch_on_response: when true, the LLM is called again with the
+    # function response to produce a final natural-language answer for the user
+    auto_llm_dispatch_on_response: true
+
+# Rate limits - control token usage per model and request selector
+ratelimits:
+  - model: openai/gpt-4o
+    selector:
+      key: x-user-id       # HTTP header key used to identify the rate-limit subject
+      value: "*"           # Wildcard matches any value; use a specific string to target one
+    limit:
+      tokens: 100000       # Maximum tokens allowed in the given time unit
+      unit: hour           # Time unit: "minute", "hour", or "day"
+
+  - model: openai/gpt-4o-mini
+    selector:
+      key: x-org-id
+      value: acme-corp
+    limit:
+      tokens: 500000
+      unit: day
+
+# Global behavior overrides
+overrides:
+  # Threshold for routing a request to a prompt_target (0.0–1.0). Lower = more permissive.
+  prompt_target_intent_matching_threshold: 0.7
+  # Trim conversation history to fit within the model's context window
+  optimize_context_window: true
+  # Use Plano's agent orchestrator for multi-agent request routing
+  use_agent_orchestrator: false
+  # Connect timeout for upstream provider clusters (e.g., "5s", "10s"). Default: "5s"
+  upstream_connect_timeout: 10s
+  # Path to the trusted CA bundle for upstream TLS verification
+  upstream_tls_ca_path: /etc/ssl/certs/ca-certificates.crt
+  # Model used for intent-based LLM routing (must be listed in model_providers)
+  llm_routing_model: Arch-Router
+  # Model used for agent orchestration (must be listed in model_providers)
+  agent_orchestration_model: Plano-Orchestrator
+
+# State storage for multi-turn conversation history
+state_storage:
+  type: memory            # "memory" (in-process) or "postgres" (persistent)
+  # connection_string is required when type is postgres.
+  # Supports environment variable substitution: $VAR or ${VAR}
+  # connection_string: postgresql://user:$DB_PASS@localhost:5432/plano
+
+# Input guardrails applied globally to all incoming requests
+prompt_guards:
+  input_guards:
+    jailbreak:
+      on_exception:
+        message: "I'm sorry, I can't help with that request."
 
 # OpenTelemetry tracing configuration
 tracing:
   # Random sampling percentage (1-100)
   random_sampling: 100
+  # Include internal Plano spans in traces
+  trace_arch_internal: false
+  # gRPC endpoint for OpenTelemetry collector (e.g., Jaeger, Tempo)
+  opentracing_grpc_endpoint: http://localhost:4317
+  span_attributes:
+    # Propagate request headers whose names start with these prefixes as span attributes
+    header_prefixes:
+      - x-user-
+      - x-org-
+    # Static key/value pairs added to every span
+    static:
+      environment: production
+      service.team: platform

docs/source/resources/includes/plano_config_full_reference_rendered.yaml

@@ -8,6 +8,7 @@ endpoints:
     connect_timeout: 0.005s
     endpoint: 127.0.0.1
     port: 80
+    protocol: http
   flight_agent:
     endpoint: localhost
     port: 10520
@@ -19,6 +20,11 @@ endpoints:
   mistral_local:
     endpoint: 127.0.0.1
     port: 8001
+  secure_service:
+    endpoint: api.example.com
+    http_host: api.example.com
+    port: 443
+    protocol: https
   weather_agent:
     endpoint: localhost
     port: 10510
@@ -38,6 +44,9 @@ listeners:
   router: plano_orchestrator_v1
   type: agent
 - address: 0.0.0.0
+  input_filters:
+  - input_guards
+  max_retries: 3
   model_providers:
   - access_key: $OPENAI_API_KEY
     default: true
@@ -56,6 +65,16 @@ listeners:
     model: ministral-3b-latest
     name: mistral/ministral-3b-latest
     provider_interface: mistral
+  - access_key: $GROQ_API_KEY
+    model: llama-3.3-70b-versatile
+    name: groq/llama-3.3-70b-versatile
+    provider_interface: groq
+    routing_preferences:
+    - description: generating new code snippets, functions, or boilerplate based on
+        user prompts or requirements
+      name: code generation
+    - description: reviewing, analyzing, and suggesting improvements to existing code
+      name: code review
   - base_url: https://litellm.example.com
     cluster_name: openai_litellm.example.com
     endpoint: litellm.example.com
@@ -65,8 +84,21 @@ listeners:
     port: 443
     protocol: https
     provider_interface: openai
+  - access_key: $CUSTOM_API_KEY
+    base_url: https://api.custom-provider.com
+    cluster_name: openai_api.custom-provider.com
+    endpoint: api.custom-provider.com
+    http_host: api.custom-provider.com
+    model: llama-3.3-70b
+    name: openai/llama-3.3-70b
+    port: 443
+    protocol: https
+    provider_interface: openai
   name: model_1
+  output_filters:
+  - input_guards
   port: 12000
+  timeout: 30s
   type: model
 - address: 0.0.0.0
   name: prompt_function_listener
@@ -95,6 +127,16 @@ model_providers:
   model: ministral-3b-latest
   name: mistral/ministral-3b-latest
   provider_interface: mistral
+- access_key: $GROQ_API_KEY
+  model: llama-3.3-70b-versatile
+  name: groq/llama-3.3-70b-versatile
+  provider_interface: groq
+  routing_preferences:
+  - description: generating new code snippets, functions, or boilerplate based on
+      user prompts or requirements
+    name: code generation
+  - description: reviewing, analyzing, and suggesting improvements to existing code
+    name: code review
 - base_url: https://litellm.example.com
   cluster_name: openai_litellm.example.com
   endpoint: litellm.example.com
@@ -104,6 +146,20 @@ model_providers:
   port: 443
   protocol: https
   provider_interface: openai
+- access_key: $CUSTOM_API_KEY
+  base_url: https://api.custom-provider.com
+  cluster_name: openai_api.custom-provider.com
+  endpoint: api.custom-provider.com
+  http_host: api.custom-provider.com
+  model: llama-3.3-70b
+  name: openai/llama-3.3-70b
+  port: 443
+  protocol: https
+  provider_interface: openai
+- internal: true
+  model: Arch-Router
+  name: arch-router
+  provider_interface: plano
 - internal: true
   model: Arch-Function
   name: arch-function
@@ -112,8 +168,22 @@ model_providers:
   model: Plano-Orchestrator
   name: plano/orchestrator
   provider_interface: plano
+overrides:
+  agent_orchestration_model: Plano-Orchestrator
+  llm_routing_model: Arch-Router
+  optimize_context_window: true
+  prompt_target_intent_matching_threshold: 0.7
+  upstream_connect_timeout: 10s
+  upstream_tls_ca_path: /etc/ssl/certs/ca-certificates.crt
+  use_agent_orchestrator: false
+prompt_guards:
+  input_guards:
+    jailbreak:
+      on_exception:
+        message: I'm sorry, I can't help with that request.
 prompt_targets:
-- description: Get current weather at a location.
+- auto_llm_dispatch_on_response: true
+  description: Get current weather at a location.
   endpoint:
     http_method: POST
     name: app_server
@@ -129,7 +199,36 @@ prompt_targets:
     name: days
     required: true
     type: int
+  system_prompt: You are a weather expert. Provide accurate and concise weather information.
+ratelimits:
+- limit:
+    tokens: 100000
+    unit: hour
+  model: openai/gpt-4o
+  selector:
+    key: x-user-id
+    value: '*'
+- limit:
+    tokens: 500000
+    unit: day
+  model: openai/gpt-4o-mini
+  selector:
+    key: x-org-id
+    value: acme-corp
+state_storage:
+  type: memory
+system_prompt: 'You are a helpful assistant. Always respond concisely and accurately.
+
+  '
 tracing:
   opentracing_grpc_endpoint: http://localhost:4317
   random_sampling: 100
+  span_attributes:
+    header_prefixes:
+    - x-user-
+    - x-org-
+    static:
+      environment: production
+      service.team: platform
+  trace_arch_internal: false
 version: v0.3.0

package.json

@@ -21,6 +21,9 @@
     "node": ">=18.0.0"
   },
   "packageManager": "npm@10.0.0",
+  "overrides": {
+    "undici": "^7.0.0"
+  },
   "dependencies": {
     "next": "^16.1.6",
     "react": "^19.2.3",

packages/ui/src/components/Footer.tsx

@@ -36,7 +36,7 @@ export function Footer() {
             {/* Copyright */}
             <div className="mt-auto">
               <p className="font-sans text-sm sm:text-base text-black/63 tracking-[-0.6px] sm:tracking-[-0.8px]!">
-                © Katanemo Labs, Inc. 2025 / Plano by Katanemo Labs, Inc.
+                © 2026 Katanemo Labs, a DigitalOcean Company / Plano by Katanemo Labs
               </p>
             </div>
           </div>

tests/archgw/common.py

@@ -1,7 +1,6 @@
 import json
 import os
 
-
 PROMPT_GATEWAY_ENDPOINT = os.getenv(
     "PROMPT_GATEWAY_ENDPOINT", "http://localhost:10000/v1/chat/completions"
 )

tests/archgw/pyproject.toml

@@ -7,7 +7,7 @@ license = {text = "Apache 2.0"}
 requires-python = ">=3.12"
 dependencies = [
     "pytest>=8.3.3",
-    "requests>=2.29.0",
+    "requests>=2.33.0",
     "selenium>=4.11.2",
     "pytest-sugar>=1.0.0",
     "deepdiff>=8.0.1",

tests/archgw/uv.lock

@@ -4,20 +4,20 @@ requires-python = ">=3.12"
 
 [[package]]
 name = "attrs"
-version = "25.4.0"
+version = "26.1.0"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/6b/5c/685e6633917e101e5dcb62b9dd76946cbb57c26e133bae9e0cd36033c0a9/attrs-25.4.0.tar.gz", hash = "sha256:16d5969b87f0859ef33a48b35d55ac1be6e42ae49d5e853b597db70c35c57e11", size = 934251, upload-time = "2025-10-06T13:54:44.725Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/9a/8e/82a0fe20a541c03148528be8cac2408564a6c9a0cc7e9171802bc1d26985/attrs-26.1.0.tar.gz", hash = "sha256:d03ceb89cb322a8fd706d4fb91940737b6642aa36998fe130a9bc96c985eff32", size = 952055, upload-time = "2026-03-19T14:22:25.026Z" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl", hash = "sha256:c647aa4a12dfbad9333ca4e71fe62ddc36f4e63b2d260a37a8b83d2f043ac309", size = 67548, upload-time = "2026-03-19T14:22:23.645Z" },
 ]
 
 [[package]]
 name = "certifi"
-version = "2025.11.12"
+version = "2026.2.25"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/a2/8c/58f469717fa48465e4a50c014a0400602d3c437d7c0c468e17ada824da3a/certifi-2025.11.12.tar.gz", hash = "sha256:d8ab5478f2ecd78af242878415affce761ca6bc54a22a27e026d7c25357c3316", size = 160538, upload-time = "2025-11-12T02:54:51.517Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/af/2d/7bf41579a8986e348fa033a31cdd0e4121114f6bce2457e8876010b092dd/certifi-2026.2.25.tar.gz", hash = "sha256:e887ab5cee78ea814d3472169153c2d12cd43b14bd03329a39a9c6e2e80bfba7", size = 155029, upload-time = "2026-02-25T02:54:17.342Z" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl", hash = "sha256:027692e4402ad994f1c42e52a4997a9763c646b73e4096e4d5d6db8af1d6f0fa", size = 153684, upload-time = "2026-02-25T02:54:15.766Z" },
 ]
 
 [[package]]
@@ -45,59 +45,75 @@ wheels = [
 
 [[package]]
 name = "charset-normalizer"
-version = "3.4.4"
+version = "3.4.7"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/13/69/33ddede1939fdd074bce5434295f38fae7136463422fe4fd3e0e89b98062/charset_normalizer-3.4.4.tar.gz", hash = "sha256:94537985111c35f28720e43603b8e7b43a6ecfb2ce1d3058bbe955b73404e21a", size = 129418, upload-time = "2025-10-14T04:42:32.879Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/e7/a1/67fe25fac3c7642725500a3f6cfe5821ad557c3abb11c9d20d12c7008d3e/charset_normalizer-3.4.7.tar.gz", hash = "sha256:ae89db9e5f98a11a4bf50407d4363e7b09b31e55bc117b4f7d80aab97ba009e5", size = 144271, upload-time = "2026-04-02T09:28:39.342Z" }
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 [[package]]