/**
 * The input to OpenAI API, directly adopted from openai-node with small tweaks:
 * https://github.com/openai/openai-node/blob/master/src/resources/chat/completions.ts
 *
 * Copyright 2024 OpenAI
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *      http://www.apache.org/licenses/LICENSE-2.0
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
import { MLCEngineInterface } from "../types";
export declare class Chat {
    private engine;
    completions: Completions;
    constructor(engine: MLCEngineInterface);
}
export declare class Completions {
    private engine;
    constructor(engine: MLCEngineInterface);
    create(request: ChatCompletionRequestNonStreaming): Promise<ChatCompletion>;
    create(request: ChatCompletionRequestStreaming): Promise<AsyncIterable<ChatCompletionChunk>>;
    create(request: ChatCompletionRequestBase): Promise<AsyncIterable<ChatCompletionChunk> | ChatCompletion>;
}
/**
 * OpenAI chat completion request protocol.
 *
 * API reference: https://platform.openai.com/docs/api-reference/chat/create
 * Followed: https://github.com/openai/openai-node/blob/master/src/resources/chat/completions.ts
 *
 * @note `model` is excluded. Instead, call `CreateMLCEngine(model)` or `engine.reload(model)` explicitly before calling this API.
 */
export interface ChatCompletionRequestBase {
    /**
     * A list of messages comprising the conversation so far.
     */
    messages: Array<ChatCompletionMessageParam>;
    /**
     * If set, partial message deltas will be sent. It will be terminated by an empty chunk.
     */
    stream?: boolean | null;
    /**
     * Options for streaming response. Only set this when you set `stream: true`.
     */
    stream_options?: ChatCompletionStreamOptions | null;
    /**
     * How many chat completion choices to generate for each input message.
     */
    n?: number | null;
    /**
     * Number between -2.0 and 2.0. Positive values penalize new tokens based on their
     * existing frequency in the text so far, decreasing the model's likelihood to
     * repeat the same line verbatim.
     *
     * [See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation/parameter-details)
     */
    frequency_penalty?: number | null;
    /**
     * Number between -2.0 and 2.0. Positive values penalize new tokens based on
     * whether they appear in the text so far, increasing the model's likelihood to
     * talk about new topics.
     *
     * [See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation/parameter-details)
     */
    presence_penalty?: number | null;
    /**
     * The maximum number of [tokens](/tokenizer) that can be generated in the chat
     * completion.
     *
     * The total length of input tokens and generated tokens is limited by the model's
     * context length.
     */
    max_tokens?: number | null;
    /**
     * Sequences where the API will stop generating further tokens.
     */
    stop?: string | null | Array<string>;
    /**
     * What sampling temperature to use, between 0 and 2. Higher values like 0.8 will
     * make the output more random, while lower values like 0.2 will make it more
     * focused and deterministic.
     */
    temperature?: number | null;
    /**
     * An alternative to sampling with temperature, called nucleus sampling, where the
     * model considers the results of the tokens with top_p probability mass. So 0.1
     * means only the tokens comprising the top 10% probability mass are considered.
     */
    top_p?: number | null;
    /**
     * Modify the likelihood of specified tokens appearing in the completion.
     *
     * Accepts a JSON object that maps tokens (specified by their token ID, which varies per model)
     * to an associated bias value from -100 to 100. Typically, you can see `tokenizer.json` of the
     * model to see which token ID maps to what string. Mathematically, the bias is added to the
     * logits generated by the model prior to sampling. The exact effect will vary per model, but
     * values between -1 and 1 should decrease or increase likelihood of selection; values like -100
     * or 100 should result in a ban or exclusive selection of the relevant token.
     *
     * As an example, you can pass `{"16230": -100}` to prevent the `Hello` token from being
     * generated in Mistral-7B-Instruct-v0.2, according to the mapping in
     * https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2/raw/main/tokenizer.json.
     *
     * @note For stateful and customizable / flexible logit processing, see `webllm.LogitProcessor`.
     * @note If used in combination with `webllm.LogitProcessor`, `logit_bias` is applied after
     * `LogitProcessor.processLogits()` is called.
     */
    logit_bias?: Record<string, number> | null;
    /**
     * Whether to return log probabilities of the output tokens or not.
     *
     * If true, returns the log probabilities of each output token returned in the `content` of
     * `message`.
     */
    logprobs?: boolean | null;
    /**
     * An integer between 0 and 5 specifying the number of most likely tokens to return
     * at each token position, each with an associated log probability. `logprobs` must
     * be set to `true` if this parameter is used.
     */
    top_logprobs?: number | null;
    /**
     * If specified, our system will make a best effort to sample deterministically, such that
     * repeated requests with the same `seed` and parameters should return the same result.
     *
     * @note Seeding is done on a request-level rather than choice-level. That is, if `n > 1`, you
     * would still get different content for each `Choice`. But if two requests with `n = 2` are
     * processed with the same seed, the two results should be the same (two choices are different).
     */
    seed?: number | null;
    /**
     * Controls which (if any) function is called by the model. `none` means the model
     * will not call a function and instead generates a message. `auto` means the model
     * can pick between generating a message or calling a function. Specifying a
     * particular function via
     * `{"type": "function", "function": {"name": "my_function"}}` forces the model to
     * call that function.
     *
     * `none` is the default when no functions are present. `auto` is the default if
     * functions are present.
     */
    tool_choice?: ChatCompletionToolChoiceOption;
    /**
     * A list of tools the model may call. Currently, only functions are supported as a
     * tool. Use this to provide a list of functions the model may generate JSON inputs
     * for.
     *
     * The corresponding reply would populate the `tool_calls` field. If used with streaming,
     * the last chunk would contain the `tool_calls` field, while the intermediate chunks would
     * contain the raw string.
     *
     * If the generation terminates due to FinishReason other than "stop" (i.e. "length" or "abort"),
     * then no `tool_calls` will be returned. User can still get the raw string output.
     */
    tools?: Array<ChatCompletionTool>;
    /**
     * An object specifying the format that the model must output.
     *
     * Setting to `{ "type": "json_object" }` enables JSON mode, which guarantees the
     * message the model generates is valid JSON.
     *
     * **Important:** when using JSON mode, you **must** also instruct the model to
     * produce JSON yourself via a system or user message. Without this, the model may
     * generate an unending stream of whitespace until the generation reaches the token
     * limit, resulting in a long-running and seemingly "stuck" request. Also note that
     * the message content may be partially cut off if `finish_reason="length"`, which
     * indicates the generation exceeded `max_tokens` or the conversation exceeded the
     * max context length.
     */
    response_format?: ResponseFormat;
    /**
     * ID of the model to use. This equals to `ModelRecord.model_id`, which needs to either be in
     * `webllm.prebuiltAppConfig` or in `engineConfig.appConfig`.
     *
     * @note Call `CreateMLCEngine(model)` or `engine.reload(model)` ahead of time.
     * @note If only one model is loaded in the engine, this field is optional. If multiple models
     *   are loaded, this is required.
     */
    model?: string | null;
}
export interface ChatCompletionRequestNonStreaming extends ChatCompletionRequestBase {
    /**
     * If set, partial message deltas will be sent. It will be terminated by an empty chunk.
     */
    stream?: false | null;
}
export interface ChatCompletionRequestStreaming extends ChatCompletionRequestBase {
    /**
     * If set, partial message deltas will be sent. It will be terminated by an empty chunk.
     */
    stream: true;
}
export type ChatCompletionRequest = ChatCompletionRequestNonStreaming | ChatCompletionRequestStreaming;
/**
 * Represents a chat completion response returned by model, based on the provided input.
 */
export interface ChatCompletion {
    /**
     * A unique identifier for the chat completion.
     */
    id: string;
    /**
     * A list of chat completion choices. Can be more than one if `n` is greater than 1.
     */
    choices: Array<ChatCompletion.Choice>;
    /**
     * The model used for the chat completion.
     */
    model: string;
    /**
     * The object type, which is always `chat.completion`.
     */
    object: "chat.completion";
    /**
     * The Unix timestamp (in seconds) of when the chat completion was created.
     *
     */
    created: number;
    /**
     * Usage statistics for the completion request.
     *
     * @note If we detect user is performing multi-round chatting, only the new portion of the
     * prompt is counted for prompt_tokens. If `n > 1`, all choices' generation usages combined.
     */
    usage?: CompletionUsage;
    /**
     * This fingerprint represents the backend configuration that the model runs with.
     *
     * Can be used in conjunction with the `seed` request parameter to understand when
     * backend changes have been made that might impact determinism.
     *
     * @note Not supported yet.
     */
    system_fingerprint?: string;
}
/**
 * Represents a streamed chunk of a chat completion response returned by model,
 * based on the provided input.
 */
export interface ChatCompletionChunk {
    /**
     * A unique identifier for the chat completion. Each chunk has the same ID.
     */
    id: string;
    /**
     * A list of chat completion choices. Can contain more than one elements if `n` is
     * greater than 1. Can also be empty for the last chunk if you set
     * `stream_options: {"include_usage": true}`.
     */
    choices: Array<ChatCompletionChunk.Choice>;
    /**
     * The Unix timestamp (in seconds) of when the chat completion was created. Each
     * chunk has the same timestamp.
     */
    created: number;
    /**
     * The model to generate the completion.
     */
    model: string;
    /**
     * The object type, which is always `chat.completion.chunk`.
     */
    object: "chat.completion.chunk";
    /**
     * This fingerprint represents the backend configuration that the model runs with.
     * Can be used in conjunction with the `seed` request parameter to understand when
     * backend changes have been made that might impact determinism.
     *
     * @note Not supported yet.
     */
    system_fingerprint?: string;
    /**
     * An optional field that will only be present when you set
     * `stream_options: {"include_usage": true}` in your request. When present, it
     * contains a null value except for the last chunk which contains the token usage
     * statistics for the entire request.
     */
    usage?: CompletionUsage;
}
export declare const ChatCompletionRequestUnsupportedFields: Array<string>;
/**
 * Post init and verify whether the input of the request is valid. Thus, this function can throw
 * error or in-place update request.
 * @param request User's input request.
 * @param currentModelId The current model loaded that will perform this request.
 */
export declare function postInitAndCheckFields(request: ChatCompletionRequest, currentModelId: string): void;
export type ChatCompletionContentPart = ChatCompletionContentPartText | ChatCompletionContentPartImage;
export interface ChatCompletionContentPartText {
    /**
     * The text content.
     */
    text: string;
    /**
     * The type of the content part.
     */
    type: "text";
}
export declare namespace ChatCompletionContentPartImage {
    interface ImageURL {
        /**
         * Either a URL of the image or the base64 encoded image data.
         */
        url: string;
        /**
         * Specifies the detail level of the image.
         */
        detail?: "auto" | "low" | "high";
    }
}
export interface ChatCompletionContentPartImage {
    image_url: ChatCompletionContentPartImage.ImageURL;
    /**
     * The type of the content part.
     */
    type: "image_url";
}
export interface ChatCompletionMessageToolCall {
    /**
     * The ID of the tool call. In WebLLM, it is used as the index of the tool call among all
     * the tools calls in this request generation.
     */
    id: string;
    /**
     * The function that the model called.
     */
    function: ChatCompletionMessageToolCall.Function;
    /**
     * The type of the tool. Currently, only `function` is supported.
     */
    type: "function";
}
export declare namespace ChatCompletionMessageToolCall {
    /**
     * The function that the model called.
     */
    interface Function {
        /**
         * The arguments to call the function with, as generated by the model in JSON
         * format.
         */
        arguments: string;
        /**
         * The name of the function to call.
         */
        name: string;
    }
}
/**
 * The role of the author of a message
 */
export type ChatCompletionRole = "system" | "user" | "assistant" | "tool" | "function";
/**
 * Options for streaming response. Only set this when you set `stream: true`.
 */
export interface ChatCompletionStreamOptions {
    /**
     * If set, an additional chunk will be streamed after the last empty chunk.
     * The `usage` field on this chunk shows the token usage statistics for the entire
     * request, and the `choices` field will always be an empty array. All other chunks
     * will also include a `usage` field, but with a null value.
     */
    include_usage?: boolean;
}
export interface ChatCompletionSystemMessageParam {
    /**
     * The contents of the system message.
     */
    content: string;
    /**
     * The role of the messages author, in this case `system`.
     */
    role: "system";
}
export interface ChatCompletionUserMessageParam {
    /**
     * The contents of the user message.
     */
    content: string | Array<ChatCompletionContentPart>;
    /**
     * The role of the messages author, in this case `user`.
     */
    role: "user";
    /**
     * An optional name for the participant. Provides the model information to
     * differentiate between participants of the same role.
     *
     * @note This is experimental, as models typically have predefined names for the user.
     */
    name?: string;
}
export interface ChatCompletionAssistantMessageParam {
    /**
     * The role of the messages author, in this case `assistant`.
     */
    role: "assistant";
    /**
     * The contents of the assistant message. Required unless `tool_calls` is specified.
     */
    content?: string | null;
    /**
     * An optional name for the participant. Provides the model information to
     * differentiate between participants of the same role.
     *
     * @note This is experimental, as models typically have predefined names for the user.
     */
    name?: string;
    /**
     * The tool calls generated by the model, such as function calls.
     */
    tool_calls?: Array<ChatCompletionMessageToolCall>;
}
export interface ChatCompletionToolMessageParam {
    /**
     * The contents of the tool message.
     */
    content: string;
    /**
     * The role of the messages author, in this case `tool`.
     */
    role: "tool";
    /**
     * Tool call that this message is responding to.
     */
    tool_call_id: string;
}
export type ChatCompletionMessageParam = ChatCompletionSystemMessageParam | ChatCompletionUserMessageParam | ChatCompletionAssistantMessageParam | ChatCompletionToolMessageParam;
/**
 * The parameters the functions accepts, described as a JSON Schema object. See the
 * [guide](https://platform.openai.com/docs/guides/text-generation/function-calling)
 * for examples, and the
 * [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for
 * documentation about the format.
 *
 * Omitting `parameters` defines a function with an empty parameter list.
 */
export type FunctionParameters = Record<string, unknown>;
export interface FunctionDefinition {
    /**
     * The name of the function to be called. Must be a-z, A-Z, 0-9, or contain
     * underscores and dashes, with a maximum length of 64.
     */
    name: string;
    /**
     * A description of what the function does, used by the model to choose when and
     * how to call the function.
     */
    description?: string;
    /**
     * The parameters the functions accepts, described as a JSON Schema object. See the
     * [guide](https://platform.openai.com/docs/guides/text-generation/function-calling)
     * for examples, and the
     * [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for
     * documentation about the format.
     *
     * Omitting `parameters` defines a function with an empty parameter list.
     */
    parameters?: FunctionParameters;
}
export interface ChatCompletionTool {
    function: FunctionDefinition;
    /**
     * The type of the tool. Currently, only `function` is supported.
     */
    type: "function";
}
/**
 * Specifies a tool the model should use. Use to force the model to call a specific
 * function.
 */
export interface ChatCompletionNamedToolChoice {
    function: ChatCompletionNamedToolChoice.Function;
    /**
     * The type of the tool. Currently, only `function` is supported.
     */
    type: "function";
}
export declare namespace ChatCompletionNamedToolChoice {
    interface Function {
        /**
         * The name of the function to call.
         */
        name: string;
    }
}
/**
 * Controls which (if any) function is called by the model. `none` means the model
 * will not call a function and instead generates a message. `auto` means the model
 * can pick between generating a message or calling a function. Specifying a
 * particular function via
 * `{"type": "function", "function": {"name": "my_function"}}` forces the model to
 * call that function.
 *
 * `none` is the default when no functions are present. `auto` is the default if
 * functions are present.
 */
export type ChatCompletionToolChoiceOption = "none" | "auto" | ChatCompletionNamedToolChoice;
export interface TopLogprob {
    /**
     * The token.
     */
    token: string;
    /**
     * A list of integers representing the UTF-8 bytes representation of the token.
     * Useful in instances where characters are represented by multiple tokens and
     * their byte representations must be combined to generate the correct text
     * representation. Can be `null` if there is no bytes representation for the token.
     *
     * @note Encoded with `TextEncoder.encode()` and can be decoded with `TextDecoder.decode()`.
     * For details, see https://developer.mozilla.org/en-US/docs/Web/API/TextEncoder/encode.
     */
    bytes: Array<number> | null;
    /**
     * The log probability of this token.
     */
    logprob: number;
}
export interface ChatCompletionTokenLogprob {
    /**
     * The token.
     */
    token: string;
    /**
     * A list of integers representing the UTF-8 bytes representation of the token.
     * Useful in instances where characters are represented by multiple tokens and
     * their byte representations must be combined to generate the correct text
     * representation. Can be `null` if there is no bytes representation for the token.
     *
     * @note Encoded with `TextEncoder.encode()` and can be decoded with `TextDecoder.decode()`.
     * For details, see https://developer.mozilla.org/en-US/docs/Web/API/TextEncoder/encode.
     */
    bytes: Array<number> | null;
    /**
     * The log probability of this token.
     */
    logprob: number;
    /**
     * List of the most likely tokens and their log probability, at this token
     * position. In rare cases, there may be fewer than the number of requested
     * `top_logprobs` returned.
     */
    top_logprobs: Array<TopLogprob>;
}
/**
 * A chat completion message generated by the model.
 */
export interface ChatCompletionMessage {
    /**
     * The contents of the message.
     */
    content: string | null;
    /**
     * The role of the author of this message.
     */
    role: "assistant";
    /**
     * The tool calls generated by the model, such as function calls.
     */
    tool_calls?: Array<ChatCompletionMessageToolCall>;
}
/**
 * Usage statistics for the completion request.
 */
export interface CompletionUsage {
    /**
     * Number of tokens in the generated completion.
     */
    completion_tokens: number;
    /**
     * Number of tokens in the prompt.
     *
     * @note If we detect user is performing multi-round chatting, only the new portion of the
     * prompt is counted for prompt_tokens.
     */
    prompt_tokens: number;
    /**
     * Total number of tokens used in the request (prompt + completion).
     */
    total_tokens: number;
    /**
     * Fields specific to WebLLM, not present in OpenAI.
     */
    extra: {
        /**
         * Number of tokens per second for prefilling.
         */
        prefill_tokens_per_s: number;
        /**
         * Number of tokens per second for autoregressive decoding.
         */
        decode_tokens_per_s: number;
    };
}
/**
 * The reason the model stopped generating tokens. This will be `stop` if the model
 * hit a natural stop point or a provided stop sequence, `length` if the maximum
 * number of tokens specified in the request was reached or the context_window_size will
 * be exceeded, `tool_calls` if the model called a tool, or `abort` if user manually stops the
 * generation.
 */
export type ChatCompletionFinishReason = "stop" | "length" | "tool_calls" | "abort";
export declare namespace ChatCompletion {
    interface Choice {
        /**
         * The reason the model stopped generating tokens. This will be `stop` if the model
         * hit a natural stop point or a provided stop sequence, `length` if the maximum
         * number of tokens specified in the request was reached, `tool_calls` if the
         * model called a tool, or `abort` if user manually stops the generation.
         */
        finish_reason: ChatCompletionFinishReason;
        /**
         * The index of the choice in the list of choices.
         */
        index: number;
        /**
         * Log probability information for the choice.
         */
        logprobs: Choice.Logprobs | null;
        /**
         * A chat completion message generated by the model.
         */
        message: ChatCompletionMessage;
    }
    namespace Choice {
        /**
         * Log probability information for the choice.
         */
        interface Logprobs {
            /**
             * A list of message content tokens with log probability information.
             */
            content: Array<ChatCompletionTokenLogprob> | null;
        }
    }
}
export declare namespace ChatCompletionChunk {
    interface Choice {
        /**
         * A chat completion delta generated by streamed model responses.
         */
        delta: Choice.Delta;
        /**
         * The reason the model stopped generating tokens. This will be `stop` if the model
         * hit a natural stop point or a provided stop sequence, `length` if the maximum
         * number of tokens specified in the request was reached, `tool_calls` if the
         * model called a tool, or `abort` if user manually stops the generation.
         */
        finish_reason: ChatCompletionFinishReason | null;
        /**
         * The index of the choice in the list of choices.
         */
        index: number;
        /**
         * Log probability information for the choice.
         */
        logprobs?: Choice.Logprobs | null;
    }
    namespace Choice {
        /**
         * A chat completion delta generated by streamed model responses.
         */
        interface Delta {
            /**
             * The contents of the chunk message.
             */
            content?: string | null;
            /**
             * The role of the author of this message.
             */
            role?: "system" | "user" | "assistant" | "tool";
            tool_calls?: Array<Delta.ToolCall>;
        }
        namespace Delta {
            interface ToolCall {
                /**
                 * The index of the tool call among all the tools calls in this request generation.
                 */
                index: number;
                /**
                 * The ID of the tool call. Not used in WebLLM.
                 */
                id?: string;
                function?: ToolCall.Function;
                /**
                 * The type of the tool. Currently, only `function` is supported.
                 */
                type?: "function";
            }
            namespace ToolCall {
                interface Function {
                    /**
                     * The arguments to call the function with, as generated by the model in JSON
                     * format. Note that the model does not always generate valid JSON, and may
                     * hallucinate parameters not defined by your function schema. Validate the
                     * arguments in your code before calling your function.
                     */
                    arguments?: string;
                    /**
                     * The name of the function to call.
                     */
                    name?: string;
                }
            }
        }
        /**
         * Log probability information for the choice.
         */
        interface Logprobs {
            /**
             * A list of message content tokens with log probability information.
             */
            content: Array<ChatCompletionTokenLogprob> | null;
        }
    }
}
/**
 * An object specifying the format that the model must output.
 *
 * Setting to `{ "type": "json_object" }` enables JSON mode, which guarantees the
 * message the model generates is valid JSON.
 *
 * Setting `schema` specifies the output format of the json object such as properties to include.
 *
 * **Important:** when using JSON mode, you **must** also instruct the model to produce JSON
 * following the schema (if specified) yourself via a system or user message. Without this,
 * the model may generate an unending stream of whitespace until the generation reaches the token
 * limit, resulting in a long-running and seemingly "stuck" request. Also note that
 * the message content may be partially cut off if `finish_reason="length"`, which
 * indicates the generation exceeded `max_tokens` or the conversation exceeded the
 * max context length.
 */
export interface ResponseFormat {
    /**
     * Must be one of `text` or `json_object`.
     */
    type?: "text" | "json_object";
    /**
     * A schema string in the format of the schema of a JSON file. `type` needs to be `json_object`.
     */
    schema?: string;
}
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