import { BaseChatModel, type BaseChatModelParams } from '@langchain/core/language_models/chat_models';
import { OpenAIChatInput } from '@langchain/openai';
import { ChatOpenAIFields } from '@langchain/openai';
/**
 * Hugging Face Inference Providers — OpenAI-compatible router.
 *
 * HF exposes a single OpenAI-compatible Chat Completions endpoint at
 * `https://router.huggingface.co/v1` that fans requests out to the configured
 * inference provider (Cerebras, Groq, Together, SambaNova, hf-inference, …). It
 * supports tool/function calling, streaming and structured outputs, so we reuse
 * LangChain's `ChatOpenAI` exactly like the OpenRouter provider — no dedicated
 * `@langchain/huggingface` package is needed (the JS `@langchain/community`
 * `HuggingFaceInference` is a text-completion LLM with no `bindTools`, so it is
 * unusable for the agent loop).
 *
 * Auth uses a Hugging Face user access token with the "Inference Providers"
 * permission, read from `HF_TOKEN` (canonical) or the `HUGGINGFACEHUB_API_TOKEN`
 * / `HF_API_KEY` aliases.
 *
 * Model ids are Hub repo ids, e.g. `openai/gpt-oss-120b`. You may append a
 * provider/policy suffix understood by the router (`:groq`, `:cheapest`,
 * `:fastest`); it is part of the model id and passes straight through.
 */
export declare function processJsonConfig(llmConfig: OpenAIChatInput & ChatOpenAIFields & BaseChatModelParams): Promise<BaseChatModel>;
export declare function init(configFileName: string, force?: boolean, model?: string): void;