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pewdiepie-archdaemon
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// Per-backend × per-model install recipes for the Dependencies tab.
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//
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// Each entry says: when you're about to serve `model` on `backend`, here's
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// the exact shell sequence to make the venv + install the right packages.
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// Entries are matched first-hit; put the more specific patterns ABOVE the
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// generic fallback for that backend.
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// Recipes carry two variants per entry:
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// variants.pip → install into the configured venv via pip/uv
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// variants.docker → pull the official container image
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//
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// The renderer prepends a `source <venv>/bin/activate` for the pip variant
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// (env_prefix handles activation for Run). The docker variant skips the
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// activate line — `docker pull` doesn't need a venv.
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const _RECIPES = [
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// ── vllm ──────────────────────────────────────────────────────────────
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// MiniMax M2/M2.7 — same as the generic vllm install/image for now;
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// kept as its own entry so future model-specific patches land in one
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// obvious place without touching the catch-all.
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{
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backend: 'vllm',
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label: 'MiniMax M2 / M2.7',
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match: (m) => /minimax[-_]?m\s?2(\.7)?/i.test(m || ''),
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variants: {
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pip: { commands: ['uv pip install -U vllm --torch-backend auto'] },
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docker: { commands: ['docker pull vllm/vllm-openai:latest'] },
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},
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},
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// Generic vllm fallback.
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{
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backend: 'vllm',
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label: 'Any vLLM model',
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match: () => true,
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variants: {
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pip: { commands: ['uv pip install -U vllm --torch-backend auto'] },
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docker: { commands: ['docker pull vllm/vllm-openai:latest'] },
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},
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},
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// ── sglang ────────────────────────────────────────────────────────────
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{
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backend: 'sglang',
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label: 'Any SGLang model',
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match: () => true,
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variants: {
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pip: { commands: ['uv pip install -U "sglang[all]" --torch-backend auto'] },
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docker: { commands: ['docker pull lmsysorg/sglang:latest'] },
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},
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},
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// ── MLX ───────────────────────────────────────────────────────────────
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{
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backend: 'mlx_lm',
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label: 'Any MLX model',
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match: () => true,
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variants: {
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pip: { commands: ['python -m pip install -U mlx-lm'] },
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},
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},
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{
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backend: 'mflux',
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label: 'mflux-compatible MLX image models',
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match: () => true,
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variants: {
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pip: { commands: ['python -m pip install -U mflux fastapi uvicorn python-multipart'] },
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},
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},
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{
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backend: 'boogu_image_mlx',
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label: 'MLX image models (Boogu)',
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match: () => true,
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variants: {
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pip: { commands: ['python -m pip install -U git+https://github.com/xocialize/boogu-image-mlx.git fastapi uvicorn python-multipart pillow'] },
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},
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},
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{
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backend: 'mlx_vlm',
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label: 'MLX image models (HiDream)',
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match: () => true,
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variants: {
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pip: { commands: ['python -m pip install -U fastapi uvicorn python-multipart mlx mlx-vlm "transformers>=4.57.0,<6.0" huggingface_hub safetensors numpy pillow tqdm sentencepiece hf_transfer'] },
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},
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},
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{
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backend: 'mlx_lama_swift',
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label: 'MLX image editing (LaMa / MI-GAN)',
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match: () => true,
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variants: {
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pip: {
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commands: [
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'python -m pip install -U fastapi uvicorn python-multipart pillow huggingface_hub',
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'BRIDGE_DIR="${ODYSSEUS_ROOT:-$PWD}/swift/odysseus-mlx-image-bridge"; test -d "$BRIDGE_DIR" || { echo "Run this from an Odysseus checkout that includes swift/odysseus-mlx-image-bridge, or set ODYSSEUS_ROOT=/path/to/odysseus."; exit 1; }',
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'BRIDGE_DIR="${ODYSSEUS_ROOT:-$PWD}/swift/odysseus-mlx-image-bridge"; cd "$BRIDGE_DIR" && swift build -c release --product odysseus-mlx-inpaint',
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'BRIDGE_DIR="${ODYSSEUS_ROOT:-$PWD}/swift/odysseus-mlx-image-bridge"; mkdir -p "$HOME/.local/bin" && cp "$BRIDGE_DIR/.build/release/odysseus-mlx-inpaint" "$HOME/.local/bin/odysseus-mlx-inpaint"',
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'MLX_METALLIB="$(python - <<\'PY\'\nimport pathlib, sys\ntry:\n import mlx\nexcept Exception as exc:\n raise SystemExit(f"mlx Python package is required for mlx.metallib: {exc}")\nroot = pathlib.Path(mlx.__file__).resolve().parent\nfor name in ("lib/mlx.metallib", "mlx.metallib", "lib/default.metallib", "default.metallib"):\n path = root / name\n if path.exists():\n print(path)\n break\nelse:\n raise SystemExit(f"No MLX metallib found under {root}")\nPY\n)"; mkdir -p "$HOME/.local/bin" && cp "$MLX_METALLIB" "$HOME/.local/bin/mlx.metallib" && cp "$MLX_METALLIB" "$HOME/.local/bin/default.metallib"',
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],
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},
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},
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},
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{
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backend: 'mlx_ddcolor_swift',
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label: 'MLX image editing (DDColor)',
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match: () => true,
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variants: {
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pip: {
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commands: [
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'python -m pip install -U fastapi uvicorn python-multipart pillow huggingface_hub',
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'BRIDGE_DIR="${ODYSSEUS_ROOT:-$PWD}/swift/odysseus-mlx-image-bridge"; test -d "$BRIDGE_DIR" || { echo "Run this from an Odysseus checkout that includes swift/odysseus-mlx-image-bridge, or set ODYSSEUS_ROOT=/path/to/odysseus."; exit 1; }',
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'BRIDGE_DIR="${ODYSSEUS_ROOT:-$PWD}/swift/odysseus-mlx-image-bridge"; cd "$BRIDGE_DIR" && swift build -c release --product odysseus-mlx-colorize',
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'BRIDGE_DIR="${ODYSSEUS_ROOT:-$PWD}/swift/odysseus-mlx-image-bridge"; mkdir -p "$HOME/.local/bin" && cp "$BRIDGE_DIR/.build/release/odysseus-mlx-colorize" "$HOME/.local/bin/odysseus-mlx-colorize"',
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'MLX_METALLIB="$(python - <<\'PY\'\nimport pathlib, sys\ntry:\n import mlx\nexcept Exception as exc:\n raise SystemExit(f"mlx Python package is required for mlx.metallib: {exc}")\nroot = pathlib.Path(mlx.__file__).resolve().parent\nfor name in ("lib/mlx.metallib", "mlx.metallib", "lib/default.metallib", "default.metallib"):\n path = root / name\n if path.exists():\n print(path)\n break\nelse:\n raise SystemExit(f"No MLX metallib found under {root}")\nPY\n)"; mkdir -p "$HOME/.local/bin" && cp "$MLX_METALLIB" "$HOME/.local/bin/mlx.metallib" && cp "$MLX_METALLIB" "$HOME/.local/bin/default.metallib"',
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],
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},
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},
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},
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// ── Diffusers ────────────────────────────────────────────────────────
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{
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backend: 'diffusers',
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label: 'Any Diffusers image model',
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match: () => true,
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variants: {
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pip: { commands: ['python -m pip install -U "diffusers[torch]" torchvision accelerate scipy python-multipart'] },
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},
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},
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{
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backend: 'krea_diffusers',
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label: 'Latest Diffusers from Git',
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match: () => true,
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variants: {
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pip: { commands: ['python -m pip install -U git+https://github.com/huggingface/diffusers.git torchvision accelerate scipy python-multipart'] },
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},
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},
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{
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backend: 'sam_mask',
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label: 'SAM object mask tools',
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match: () => true,
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variants: {
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pip: { commands: ['python -m pip install -U torch torchvision transformers accelerate pillow'] },
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},
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},
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// ── llama.cpp ─────────────────────────────────────────────────────────
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{
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backend: 'llama_cpp',
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label: 'Any GGUF model',
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match: () => true,
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variants: {
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pip: { commands: ['CMAKE_ARGS="-DGGML_CUDA=on" uv pip install -U "llama-cpp-python[server]"'] },
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docker: { commands: ['docker pull ghcr.io/ggml-org/llama.cpp:server-cuda'] },
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},
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},
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];
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export const RECIPE_VARIANTS = ['pip', 'docker'];
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export const RECIPE_DEFAULT_VARIANT = 'pip';
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// Get the commands array for a recipe + variant. Falls back to pip when
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// the requested variant isn't defined for the recipe.
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export function recipeCommands(recipe, variant) {
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if (!recipe) return [];
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const v = (recipe.variants || {})[variant] || (recipe.variants || {}).pip;
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return (v && v.commands) || [];
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}
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// Backends we surface a recipe panel for. Other rows in the Dependencies
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// list keep the existing flat Install/Reinstall button without an expand
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// affordance.
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export const RECIPE_BACKENDS = new Set(['vllm', 'sglang', 'mlx_lm', 'mflux', 'boogu_image_mlx', 'mlx_vlm', 'mlx_lama_swift', 'mlx_ddcolor_swift', 'diffusers', 'krea_diffusers', 'sam_mask', 'llama_cpp']);
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// All recipe entries for a given backend, in catalog order. The first one
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// is the model-specific match (when present); the last is always the
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// generic fallback.
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export function recipesForBackend(backend) {
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return _RECIPES.filter((r) => r.backend === backend);
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}
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// Pick the best recipe for a backend + model id. Returns the catalog
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// fallback when nothing more specific matches, or null if the backend
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// isn't in the catalog at all.
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export function pickRecipe(backend, modelId) {
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const candidates = recipesForBackend(backend);
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if (!candidates.length) return null;
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for (const r of candidates) {
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try { if (r.match(modelId)) return r; } catch (_) {}
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}
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return candidates[candidates.length - 1] || null;
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}
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