Licence
MIT
Version
0.1.0-alpha.24
Deps
1
Size
796 kB
Vulns
0
Weekly
498
Install scriptsThis package runs scripts during installation (preinstall/install/postinstall)
@llm-ports/core
The foundation of llm-ports. SDK-independent interfaces, multimodal content blocks, registry with cost-and-budget gating, validation strategies. Zero dependencies on any LLM SDK.
Installation
pnpm add @llm-ports/core
# Plus at least one adapter:
pnpm add @llm-ports/adapter-anthropicWhat you get
| Export | Purpose |
|---|---|
LLMPort |
The interface adapters implement: generateText, generateStructured, streamText, streamStructured, runAgent |
EmbeddingsPort |
Sibling interface for embeddings (most chat adapters do not implement this) |
ContentBlock, MessageContent |
Multimodal message content (text, image, audio, tool_use, tool_result) |
createRegistryFromEnv() |
Builds a routing registry from LLM_PROVIDER_* and LLM_TASK_ROUTE_* env vars |
declareTasks<T>() |
Type-safe task name helper with autocomplete |
InMemoryBudget, InMemoryCost |
Default backends; replace with Redis-backed for multi-process |
ValidationStrategy |
Pluggable strategies for handling failed structured-output validation |
BudgetExceededError, NoProvidersAvailableError, ValidationError, ... |
Typed error classes |
Minimal example
import { createRegistryFromEnv } from "@llm-ports/core";
import { createAnthropicAdapter } from "@llm-ports/adapter-anthropic";
const registry = createRegistryFromEnv({
adapters: {
anthropic: createAnthropicAdapter({
apiKey: process.env.ANTHROPIC_API_KEY!,
}),
},
});
export const llm = registry.getPort();
// Then anywhere in your codebase:
const result = await llm.generateText({
taskType: "triage",
prompt: "Classify this email: ...",
});.env:
LLM_PROVIDER_FAST=anthropic|claude-haiku-4-5|cost:5/day
LLM_PROVIDER_SMART=anthropic|claude-sonnet-4-6|cost:50/day
LLM_TASK_ROUTE_TRIAGE=fast,smartLicense
MIT