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* refactor: extract reusable AI runtime package * refactor: complete AI provider relocation * refactor: keep llm core internal * refactor(ai): make @openclaw/ai self-contained with host policy ports Move pure transport helpers (tool projections, strict-schema normalization, prompt-cache boundary, stream guards, anthropic/openai compat, request activity) from src into packages/ai; move utf16-slice into normalization-core. Inject host policy (guarded fetch, redaction, strict-tool defaults, diagnostics logging) through AiTransportHost with inert library defaults installed by src/llm/stream.ts. Narrow the public barrel to instance-scoped createApiRegistry/createLlmRuntime; the process-default runtime moves behind internal/ and registerBuiltInApiProviders takes an explicit registry. Delete the src/llm/api-registry re-export facade. * fix(ai): teach node, jiti, and vite resolvers the @openclaw/ai and utf16-slice subpaths The workspace alias tables in root-alias.cjs, plugin-sdk-native-resolver, sdk-alias, the shared vitest config, and the Control UI vite config only knew @openclaw/llm-core; Node-side plugin loading resolved @openclaw/ai through the pnpm symlink to the unbuilt dist (checks-node-compact CI failures), and the Control UI build broke on the new normalization-core/utf16-slice subpath. * chore(ui): drop leftover service-worker debug logging * build(release): ship @openclaw/ai with its own shrinkwrap and honest dependency set packages/ai declares only its six real runtime deps (kysely, chalk, json5, tslog, zod, fs-safe, and proxyline were never imported); orphaned root deps removed. generate-npm-shrinkwrap now treats publishable packages/* like publishable plugins so the AI tarball pins its transitive tree even though workspace deps are omitted from the root shrinkwrap. knip learns the package entry points; the tsdown dts neverBundle option moves to its documented deps.dts home; the README documents the no-semver internal/* contract and host ports. * docs(ai): add minimal external-consumer example app examples/ai-chat consumes only the public @openclaw/ai surface (built dist via the workspace link): isolated runtime, built-in provider registration, one streamed completion. Supports Anthropic/OpenAI via env keys and a keyless local Ollama target; live-verified against Ollama. * docs(ai): document the @openclaw/ai package and workspace shrinkwrap boundary * chore(check): include examples/ in duplicate-scan targets * fix: emit normalization package subpaths * fix: complete AI package boundary artifacts * fix: align AI package boundary contracts * fix(ci): stabilize package release contracts * test: align documentation contract checks * test: keep cron docs guard aligned * test: align restored docs contract guards * test: follow upstream docs contracts * docs: drop superseded talk wording
60 lines
1.7 KiB
TypeScript
60 lines
1.7 KiB
TypeScript
// LLM Runtime module implements stream behavior.
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import type {
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Api,
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AssistantMessage,
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AssistantMessageEventStreamContract,
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Context,
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Model,
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ProviderStreamOptions,
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SimpleStreamOptions,
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StreamOptions,
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} from "@openclaw/llm-core";
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import { createApiRegistry, type ApiRegistry } from "./api-registry.js";
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/** Creates an isolated LLM runtime backed by the supplied provider registry. */
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export function createLlmRuntime(registry: ApiRegistry = createApiRegistry()) {
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function resolveApiProvider(api: Api) {
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const provider = registry.getApiProvider(api);
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if (!provider) {
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throw new Error(`No API provider registered for api: ${api}`);
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}
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return provider;
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}
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function stream<TApi extends Api>(
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model: Model<TApi>,
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context: Context,
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options?: ProviderStreamOptions,
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): AssistantMessageEventStreamContract {
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return resolveApiProvider(model.api).stream(model, context, options as StreamOptions);
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}
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async function complete<TApi extends Api>(
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model: Model<TApi>,
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context: Context,
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options?: ProviderStreamOptions,
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): Promise<AssistantMessage> {
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return stream(model, context, options).result();
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}
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function streamSimple<TApi extends Api>(
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model: Model<TApi>,
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context: Context,
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options?: SimpleStreamOptions,
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): AssistantMessageEventStreamContract {
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return resolveApiProvider(model.api).streamSimple(model, context, options);
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}
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async function completeSimple<TApi extends Api>(
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model: Model<TApi>,
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context: Context,
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options?: SimpleStreamOptions,
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): Promise<AssistantMessage> {
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return streamSimple(model, context, options).result();
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}
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return { registry, stream, complete, streamSimple, completeSimple };
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}
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export type LlmRuntime = ReturnType<typeof createLlmRuntime>;
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