fix(backend): reject compound provider credentials
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@@ -167,6 +167,17 @@ recognized child variable (for example `ANTHROPIC_API_KEY`, `OPENAI_API_KEY`, `G
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`ZAI_API_KEY`). Neither the generic file path nor deprecated `PI_PROVIDER_API_KEY` is inherited by
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Pi. Local providers such as Ollama require no model key.
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`THT_MODEL_API_KEY_FILE` supports Pi providers whose authentication is exactly one key:
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`ant-ling`, `anthropic`, `cerebras`, `deepseek`, `fireworks`, `github-copilot`, `google`
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(including the `gemini` alias), `google-vertex` when using its API-key mode, `groq`,
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`huggingface`, `kimi-coding`, `minimax`, `minimax-cn`, `mistral`, `moonshotai`,
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`moonshotai-cn`, `nvidia`, `openai`, `opencode`, `opencode-go`, `openrouter`, `together`,
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`vercel-ai-gateway`, `xai`, the four `xiaomi*` providers, `zai`, and `zai-coding-cn`.
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Compound providers are deliberately unsupported: `amazon-bedrock`, `azure-openai-responses`,
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`cloudflare-workers-ai`, and `cloudflare-ai-gateway` require multiple credential/configuration
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values. Selecting one fails before Pi starts; ambient AWS, Azure, and Cloudflare credentials are
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still scrubbed. Supporting them requires a future dedicated provider-specific configuration.
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## Reproducible image verification
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Base images use exact tags and immutable multi-platform manifest digests. Dependency update and
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@@ -23,13 +23,9 @@ export const PI_0803_CREDENTIAL_ENV_NAMES = Object.freeze([
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]);
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const PROVIDER_KEY_ENV: Readonly<Record<string, string>> = {
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"amazon-bedrock": "AWS_BEARER_TOKEN_BEDROCK",
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"ant-ling": "ANT_LING_API_KEY",
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anthropic: "ANTHROPIC_API_KEY",
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"azure-openai-responses": "AZURE_OPENAI_API_KEY",
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cerebras: "CEREBRAS_API_KEY",
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"cloudflare-ai-gateway": "CLOUDFLARE_API_KEY",
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"cloudflare-workers-ai": "CLOUDFLARE_API_KEY",
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deepseek: "DEEPSEEK_API_KEY", fireworks: "FIREWORKS_API_KEY",
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"github-copilot": "COPILOT_GITHUB_TOKEN", google: "GEMINI_API_KEY",
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"google-vertex": "GOOGLE_CLOUD_API_KEY", groq: "GROQ_API_KEY", huggingface: "HF_TOKEN",
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@@ -43,6 +39,9 @@ const PROVIDER_KEY_ENV: Readonly<Record<string, string>> = {
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"xiaomi-token-plan-sgp": "XIAOMI_TOKEN_PLAN_SGP_API_KEY", zai: "ZAI_API_KEY",
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"zai-coding-cn": "ZAI_CODING_CN_API_KEY",
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};
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const COMPOUND_PROVIDERS = new Set([
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"amazon-bedrock", "azure-openai-responses", "cloudflare-ai-gateway", "cloudflare-workers-ai",
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]);
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const LOCAL_PROVIDERS = new Set(["ollama", "lmstudio", "local", "aritmolab", "faux"]);
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export function canonicalPiProvider(provider: string | undefined): string | undefined {
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@@ -109,6 +108,12 @@ export function buildPiChildEnv(opts: {
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delete env.THT_MODEL_API_KEY_FILE;
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for (const name of PI_0803_CREDENTIAL_ENV_NAMES) delete env[name];
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const provider = canonicalPiProvider(opts.provider);
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if (provider && COMPOUND_PROVIDERS.has(provider)) {
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throw new Error(
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"compound credential bundles are unsupported by THT_MODEL_API_KEY_FILE; "
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+ "dedicated provider configuration is required",
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);
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}
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if (provider && !LOCAL_PROVIDERS.has(provider)) {
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const envName = PROVIDER_KEY_ENV[provider];
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if (!envName || !opts.credentialFile) throw new Error("model provider credential is unavailable");
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@@ -141,3 +141,25 @@ test("model-list spawn loads only the selected canonical provider credential", a
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rmSync(path.dirname(script), { recursive: true, force: true });
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}
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});
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test.each(["amazon-bedrock", "azure-openai-responses", "cloudflare-workers-ai", "cloudflare-ai-gateway"])(
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"model listing rejects compound provider %s before spawning Pi", async (provider) => {
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const script = scriptWith([]);
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const secret = join(path.dirname(script), "model-key");
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writeFileSync(secret, "selected-secret", { mode: 0o600 });
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let spawns = 0;
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const lister = createPiModelLister(loadConfig({
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PI_PROVIDER: provider, THT_MODEL_API_KEY_FILE: secret,
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}), {
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spawnFn: () => { spawns += 1; throw new Error("must not spawn"); },
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});
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try {
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await expect(lister()).rejects.toThrow(
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"compound credential bundles are unsupported by THT_MODEL_API_KEY_FILE; dedicated provider configuration is required",
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);
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expect(spawns).toBe(0);
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} finally {
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rmSync(path.dirname(script), { recursive: true, force: true });
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}
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},
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);
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@@ -262,6 +262,25 @@ test("local providers spawn without a model key and scrub ambient generic creden
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}
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});
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test.each(["amazon-bedrock", "azure-openai-responses", "cloudflare-workers-ai", "cloudflare-ai-gateway"])(
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"session spawn rejects compound provider %s before spawning Pi", async (provider) => {
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const secret = path.resolve(__dirname, `.compound-key-${process.pid}-${provider}`);
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writeFileSync(secret, "provider-secret", { mode: 0o600 });
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let spawns = 0;
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const mgr = new PiProcessManager(loadConfig({ THT_MODEL_API_KEY_FILE: secret }), {
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spawnFn: () => { spawns += 1; throw new Error("must not spawn"); },
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});
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try {
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await expect(mgr.spawnFor("compound-provider", { provider })).rejects.toThrow(
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"compound credential bundles are unsupported by THT_MODEL_API_KEY_FILE; dedicated provider configuration is required",
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);
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expect(spawns).toBe(0);
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} finally {
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await import("node:fs/promises").then((fs) => fs.unlink(secret));
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}
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},
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);
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test.each(["missing", "permissive", "unreadable", "directory", "symlink", "unsupported"])(
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"hosted provider credential failure is sanitized: %s", async (kind) => {
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const target = path.resolve(__dirname, `.bad-model-key-${process.pid}-${kind}`);
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@@ -74,3 +74,44 @@ test("Docker secrets require a secure root-owned /run/secrets parent and 0444 fi
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},
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})).toThrow("model provider credential is unavailable");
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});
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test.each(["amazon-bedrock", "azure-openai-responses", "cloudflare-workers-ai", "cloudflare-ai-gateway"])(
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"compound provider %s fails closed before opening the generic secret", (provider) => {
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let opens = 0;
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expect(() => buildPiChildEnv({
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ambient: {}, provider, credentialFile: "/unused",
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fsOps: {
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lstat: () => { throw new Error("must not inspect file"); },
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open: () => { opens += 1; return 9; },
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fstat: () => { throw new Error("must not inspect file"); },
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read: () => "secret", close: () => undefined,
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},
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})).toThrow(
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"compound credential bundles are unsupported by THT_MODEL_API_KEY_FILE; dedicated provider configuration is required",
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);
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expect(opens).toBe(0);
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},
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);
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test("single-key providers scrub ambient compound companions before injecting their key", () => {
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const stat = {
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dev: 7, ino: 1, uid: process.getuid?.() ?? 0, mode: 0o100600, nlink: 1, size: 6,
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isFile: () => true, isDirectory: () => false, isSymbolicLink: () => false,
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};
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const env = buildPiChildEnv({
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ambient: {
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AWS_ACCESS_KEY_ID: "ambient", AWS_SECRET_ACCESS_KEY: "ambient",
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CLOUDFLARE_ACCOUNT_ID: "ambient", CLOUDFLARE_GATEWAY_ID: "ambient",
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},
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provider: "openai", credentialFile: "/safe/key",
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fsOps: {
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lstat: () => stat as any, open: () => 9, fstat: () => stat as any,
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read: () => "secret", close: () => undefined,
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},
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});
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expect(env.OPENAI_API_KEY).toBe("secret");
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expect(env).not.toHaveProperty("AWS_ACCESS_KEY_ID");
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expect(env).not.toHaveProperty("AWS_SECRET_ACCESS_KEY");
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expect(env).not.toHaveProperty("CLOUDFLARE_ACCOUNT_ID");
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expect(env).not.toHaveProperty("CLOUDFLARE_GATEWAY_ID");
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});
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@@ -12,6 +12,19 @@ le chiavi di provider non selezionati e il vecchio `PI_PROVIDER_API_KEY` vengono
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del child. Provider locali come `ollama`, `lmstudio` e `aritmolab` continuano senza chiave; un provider
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hosted non mappato o un secret mancante/non sicuro fallisce prima dello spawn con errore sanitizzato.
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La sorgente generica supporta soltanto provider con una singola chiave: `ant-ling`, `anthropic`,
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`cerebras`, `deepseek`, `fireworks`, `github-copilot`, `google` (anche tramite alias `gemini`),
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`google-vertex` in modalità API key, `groq`, `huggingface`, `kimi-coding`, `minimax`, `minimax-cn`,
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`mistral`, `moonshotai`, `moonshotai-cn`, `nvidia`, `openai`, `opencode`, `opencode-go`,
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`openrouter`, `together`, `vercel-ai-gateway`, `xai`, i quattro provider `xiaomi*`, `zai` e
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`zai-coding-cn`.
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I provider composti `amazon-bedrock`, `azure-openai-responses`, `cloudflare-workers-ai` e
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`cloudflare-ai-gateway` non sono rappresentabili da un solo file. La selezione fallisce prima
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dello spawn (anche durante l'elenco modelli); tutte le credenziali ambientali AWS, Azure e
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Cloudflare restano comunque rimosse. Servirà una futura configurazione dedicata per provider per
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supportare questi bundle senza ambiguità.
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## I tre livelli di provenienza di un modello
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### 1. Built-in (compilato dentro Pi)
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