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The zhipu recipe was embedding-only, so models.tier.subagent=zhipu:glm-5.1 threw "does not offer a chat touchpoint" — while the error hint falsely listed zhipu (and dashscope/minimax, also embedding-only) among providers with chat. - zhipu recipe: add a chat touchpoint (glm-5.1 family, supports_tools + supports_subagent_loop; no Anthropic-style prompt cache on the OpenAI-compat path, so the loop runs with the degraded:no_caching warn). openai-compat tier means newer GLM ids pass without a recipe edit. - capabilities.ts: compute the "Known providers with chat" hint from the recipe registry instead of a hardcoded list, so it can never drift into naming chat-less providers again. - Declines the originally requested models.anthropic_compatible_prefixes config: v0.38's recipe-driven capability gate already replaced the Anthropic-only enforcement, so a recipe chat touchpoint is the whole fix. Fixes #1157 Co-authored-by: Sinabina <sinabina@Sinabinas-MacBook-Pro-4.local> Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
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co-authored by
Sinabina
Claude Fable 5
parent
b139602119
commit
ef840d9561
@@ -22,6 +22,7 @@
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*/
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import { resolveRecipe } from './model-resolver.ts';
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import { listRecipes } from './recipes/index.ts';
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import { AIConfigError } from './errors.ts';
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export interface ProviderCapabilities {
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@@ -77,7 +78,10 @@ export function getProviderCapabilities(modelString: string): ProviderCapabiliti
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if (!chat) {
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throw new AIConfigError(
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`Provider "${recipe.id}" does not offer a chat touchpoint.`,
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`Known providers with chat: openai, anthropic, google, openrouter, litellm-proxy, deepseek, groq, together, azure-openai, dashscope, minimax, zhipu, ollama, llama-server. Pick one for models.tier.subagent.`,
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// Computed from the registry so the hint can't drift into listing
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// chat-less providers (the pre-fix list falsely included embedding-only
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// recipes, sending users in circles — #1157).
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`Known providers with chat: ${listRecipes().filter(r => r.touchpoints.chat).map(r => r.id).join(', ')}. Pick one for models.tier.subagent.`,
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);
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}
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@@ -1,9 +1,10 @@
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import type { Recipe } from '../types.ts';
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/**
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* Zhipu AI (智谱AI) BigModel Open Platform. OpenAI-compatible /embeddings
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* endpoint at open.bigmodel.cn. Hosts embedding-2 (1024d) and embedding-3
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* (Matryoshka up to 2048d).
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* Zhipu AI (智谱AI) BigModel Open Platform. OpenAI-compatible /embeddings and
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* /chat/completions endpoints at open.bigmodel.cn. Hosts embedding-2 (1024d),
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* embedding-3 (Matryoshka up to 2048d), and the GLM chat family (glm-5.1 etc.)
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* with native tool calling — usable for models.tier.subagent (#1157).
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*
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* embedding-3 at 2048 dims exceeds pgvector's HNSW cap of 2000 — those
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* brains fall back to exact vector scans (see
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@@ -25,6 +26,20 @@ export const zhipu: Recipe = {
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setup_url: 'https://open.bigmodel.cn/',
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},
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touchpoints: {
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chat: {
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// Informational list (openai-compat tier: assertTouchpoint doesn't
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// enforce it), so newer GLM ids pass without a recipe edit.
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models: ['glm-5.1', 'glm-4.6', 'glm-4.5'],
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supports_tools: true,
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// gbrain-side stable tool ids (v0.38 D11) decoupled the loop from
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// Anthropic response formats; GLM tool calling is stable through the
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// OpenAI-compat path, same as deepseek/groq.
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supports_subagent_loop: true,
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// Anthropic-style cache_control markers are not honored on the
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// OpenAI-compat path — the loop runs hot (degraded:no_caching warn).
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supports_prompt_cache: false,
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max_context_tokens: 128000,
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},
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embedding: {
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models: ['embedding-3', 'embedding-2'],
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default_dims: 1024,
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@@ -36,5 +51,5 @@ export const zhipu: Recipe = {
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},
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},
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setup_hint:
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'Get an API key at https://open.bigmodel.cn/, then `export ZHIPUAI_API_KEY=...`',
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'Get an API key at https://open.bigmodel.cn/, then `export ZHIPUAI_API_KEY=...`. Chat/subagent: use `zhipu:glm-5.1`.',
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};
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@@ -69,6 +69,45 @@ describe('recipe: zhipu', () => {
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expect(sql.toLowerCase()).toContain('hnsw');
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});
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test('chat touchpoint declares GLM models with tool + subagent-loop support (#1157)', () => {
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const r = getRecipe('zhipu')!;
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expect(r.touchpoints.chat).toBeDefined();
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expect(r.touchpoints.chat!.models).toContain('glm-5.1');
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expect(r.touchpoints.chat!.supports_tools).toBe(true);
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expect(r.touchpoints.chat!.supports_subagent_loop).toBe(true);
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expect(r.touchpoints.chat!.supports_prompt_cache).toBe(false);
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});
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test('zhipu:glm-5.1 passes the subagent capability gate (degraded:no_caching, not refused)', async () => {
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// Pre-fix: getProviderCapabilities threw "does not offer a chat touchpoint"
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// and classifyCapabilities returned 'unknown' → subagent submit refused.
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const { getProviderCapabilities, classifyCapabilities } =
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await import('../../src/core/ai/capabilities.ts');
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const caps = getProviderCapabilities('zhipu:glm-5.1');
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expect(caps.supportsToolCalling).toBe(true);
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expect(classifyCapabilities('zhipu:glm-5.1')).toBe('degraded:no_caching');
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});
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test('no-chat-touchpoint error hint lists only providers that actually have chat', async () => {
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// The hint is computed from the registry; every provider it names must
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// really carry a chat touchpoint (pre-fix it hardcoded zhipu/dashscope/
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// minimax, all embedding-only at the time).
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const { getProviderCapabilities } = await import('../../src/core/ai/capabilities.ts');
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const { listRecipes } = await import('../../src/core/ai/recipes/index.ts');
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let hint = '';
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try {
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getProviderCapabilities('voyage:voyage-3');
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throw new Error('expected AIConfigError for embedding-only provider');
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} catch (e) {
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hint = (e as { fix?: string }).fix ?? String(e);
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}
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const listed = hint.match(/chat: ([^.]+)\./)?.[1]?.split(', ') ?? [];
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expect(listed.length).toBeGreaterThan(0);
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const withChat = new Set(listRecipes().filter(r => r.touchpoints.chat).map(r => r.id));
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for (const id of listed) expect(withChat.has(id)).toBe(true);
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expect(listed).toContain('zhipu');
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});
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test('dimsProviderOptions threads dimensions for embedding-3 (Matryoshka)', async () => {
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// Codex finding #1: Zhipu embedding-3 is Matryoshka 256-2048. Without
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// `dimensions` on the wire, user-selected non-default dims are
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