import type { EmbeddingsProvider } from './codebase-context/context-status';
import type { FileURI } from './common/uri';
import type { PromptString } from './prompt/prompt-string';
export type ConfigurationUseContext = 'embeddings' | 'keyword' | 'none' | 'blended' | 'unified';
/**
 * Get the numeric ID corresponding to the ConfigurationUseContext mode.
 */
export declare const CONTEXT_SELECTION_ID: Record<ConfigurationUseContext, number>;
export interface ConfigGetter<T> {
    get<T>(section: string, defaultValue?: T): T;
}
export interface Configuration {
    proxy?: string | null;
    codebase?: string;
    debugFilter: RegExp | null;
    debugVerbose: boolean;
    telemetryLevel: 'all' | 'off' | 'agent';
    telemetryClientName?: string;
    useContext: ConfigurationUseContext;
    customHeaders: Record<string, string>;
    chatPreInstruction: PromptString;
    editPreInstruction: PromptString;
    codeActions: boolean;
    commandHints: boolean;
    commandCodeLenses: boolean;
    /**
     * Autocomplete
     */
    autocomplete: boolean;
    autocompleteLanguages: Record<string, boolean>;
    autocompleteAdvancedProvider: 'anthropic' | 'fireworks' | 'unstable-gemini' | 'unstable-openai' | 'experimental-openaicompatible' | 'experimental-ollama' | null;
    autocompleteAdvancedModel: string | null;
    autocompleteCompleteSuggestWidgetSelection?: boolean;
    autocompleteFormatOnAccept?: boolean;
    autocompleteDisableInsideComments: boolean;
    /**
     * Experimental
     */
    experimentalTracing: boolean;
    experimentalChatContextRanker: boolean | undefined;
    experimentalSupercompletions: boolean;
    experimentalCommitMessage: boolean;
    experimentalNoodle: boolean;
    experimentalMinionAnthropicKey: string | undefined;
    experimentalGuardrailsTimeoutSeconds: number | undefined;
    /**
     * Unstable Features for internal testing only
     */
    internalUnstable: boolean;
    /**
     * Experimental autocomplete
     */
    autocompleteExperimentalGraphContext: 'lsp-light' | 'bfg' | 'bfg-mixed' | 'tsc' | 'tsc-mixed' | null;
    autocompleteExperimentalOllamaOptions: OllamaOptions;
    autocompleteExperimentalFireworksOptions?: FireworksOptions;
    autocompleteExperimentalMultiModelCompletions?: MultimodelSingleModelConfig[];
    autocompleteExperimentalHotStreakAndSmartThrottle?: boolean;
    /**
     * Hidden settings
     */
    isRunningInsideAgent?: boolean;
    agentIDE?: CodyIDE;
    agentIDEVersion?: string;
    agentExtensionVersion?: string;
    autocompleteTimeouts: AutocompleteTimeouts;
    autocompleteFirstCompletionTimeout: number;
    testingModelConfig: EmbeddingsModelConfig | undefined;
}
export declare enum CodyIDE {
    VSCode = "VSCode",
    JetBrains = "JetBrains",
    Neovim = "Neovim",
    Emacs = "Emacs",
    Web = "Web",
    VisualStudio = "VisualStudio"
}
export interface AutocompleteTimeouts {
    multiline?: number;
    singleline?: number;
}
export interface ConfigurationWithAccessToken extends Configuration {
    serverEndpoint: string;
    /** The access token, which is stored in the secret storage (not configuration). */
    accessToken: string | null;
}
export interface OllamaOptions {
    /**
     * URL to the Ollama server.
     * @example http://localhost:11434
     */
    url: string;
    /**
     * The Ollama model to use. Currently only codellama and derived models are supported.
     * @example codellama:7b-code
     */
    model: string;
    /**
     * Parameters for how Ollama will run the model. See Ollama PARAMETER documentation.
     */
    parameters?: OllamaGenerateParameters;
}
/**
 * @see https://sourcegraph.com/github.com/jmorganca/ollama/-/blob/docs/modelfile.md#valid-parameters-and-values
 * @see https://sourcegraph.com/github.com/jmorganca/ollama/-/blob/api/types.go?L143
 */
export interface OllamaGenerateParameters {
    /**
     * Sets the random number seed to use for generation. Setting this to a specific number will make the model generate the same text for the same prompt.
     * (Default: 0)
     */
    seed?: number;
    /**
     * Sets the size of the context window used to generate the next token.
     * (Default: 2048)
     */
    num_ctx?: number;
    /**
     * The temperature of the model. Increasing the temperature will make the model answer more creatively.
     * (Default: 0.8)
     */
    temperature?: number;
    /**
     * Sets the stop sequences to use. When this pattern is encountered the LLM will stop generating text and return.
     * Multiple stop patterns may be set by specifying multiple separate stop parameters in a modelfile.
     */
    stop?: string[];
    /**
     * Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers,
     * while a lower value (e.g. 10) will be more conservative.
     * (Default: 40)
     */
    top_k?: number;
    /**
     * Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text,
     * while a lower value (e.g., 0.5) will generate more focused and conservative text.
     * (Default: 0.9)
     */
    top_p?: number;
    /**
     * Sets the number of threads to use during computation.
     * By default, Ollama will detect this for optimal performance.
     * It is recommended to set this value to the number of physical CPU cores
     * your system has (as opposed to the logical number of cores).
     */
    num_thread?: number;
    /**
     * Maximum number of tokens to predict when generating text.
     * (Default: 128, -1 = infinite generation, -2 = fill context)
     */
    num_predict?: number;
    /**
     * Enable Mirostat sampling for controlling perplexity.
     * (default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)
     */
    mirostat?: number;
    /**
     * Influences how quickly the algorithm responds to feedback from the generated text. A lower learning rate will result in slower adjustments,
     * while a higher learning rate will make the algorithm more responsive.
     * (Default: 0.1)
     */
    mirostat_eta?: number;
    /**
     * Controls the balance between coherence and diversity of the output. A lower value will result in more focused and coherent text.
     * (Default: 5.0)
     */
    mirostat_tau?: number;
    /**
     * The number of GQA groups in the transformer layer. Required for some models, for example it is 8 for llama2:70b.
     */
    num_gqa?: number;
    /**
     * The number of layers to send to the GPU(s). On macOS it defaults to 1 to enable metal support, 0 to disable.
     */
    num_gpu?: number;
    /**
     * Sets how far back for the model to look back to prevent repetition.
     * (Default: 64, 0 = disabled, -1 = num_ctx)
     */
    repeat_last_n?: number;
    /**
     * Sets how strongly to penalize repetitions. A higher value (e.g., 1.5) will penalize repetitions more strongly,
     * while a lower value (e.g., 0.9) will be more lenient.
     * (Default: 1.1)
     */
    repeat_penalty?: number;
    /**
     * Tail free sampling is used to reduce the impact of less probable tokens from the output.
     * A higher value (e.g., 2.0) will reduce the impact more, while a value of 1.0 disables this setting.
     * (default: 1)
     */
    tfs_z?: number;
}
export interface FireworksOptions {
    url: string;
    token: string;
    model: string;
    parameters?: {
        temperature?: number;
        top_k?: number;
        top_p?: number;
        stop?: string[];
    };
}
export interface MultimodelSingleModelConfig {
    provider: string;
    model: string;
    enableExperimentalFireworksOverrides: boolean;
}
export interface EmbeddingsModelConfig {
    model: string;
    dimension: number;
    provider: EmbeddingsProvider;
    endpoint: string;
    indexPath: FileURI;
}
/**
 * @see https://console.groq.com/docs/text-chat
 */
export interface GroqCompletionOptions {
    /**
     *An optional name to disambiguate messages from different users with the same role.
     */
    name?: string;
    /**
     *Seed used for sampling. Groq attempts to return the same response to the same request with an identical seed.
     */
    seed?: number;
    /**
     *The maximum number of tokens that the model can process in a single response. This limits ensures computational efficiency and resource management.
     */
    max_tokens?: number;
    /**
     *A method of text generation where a model will only consider the most probable next tokens that make up the probability p. 0.5 means half of all likelihood-weighted options are considered.
     */
    top_p?: number;
    /**
     *Controls randomness of responses. A lower temperature leads to more predictable outputs while a higher temperature results in more varies and sometimes more creative outputs.
     */
    temperature?: number;
    /**
     *User server-side events to send the completion in small deltas rather than in a single batch after all processing has finished. This reduces the time to first token received.
     */
    stream?: boolean;
    /**
     *A stop sequence is a predefined or user-specified text string that signals an AI to stop generating content, ensuring its responses remain focused and concise.
     */
    stop?: string[];
}
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