FM / resources

/opt/canhelp/node_modules/@anthropic-ai/sdk/resources/

/opt/canhelp/node_modules/@anthropic-ai/sdk/resources

Name	Size	Mode	Actions
beta/	-	0755	rm
messages/	-	0755	rm
beta.d.mts	69	0644	edit dl rm
beta.d.mts.map	113	0644	edit dl rm
beta.d.ts	67	0644	edit dl rm
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beta.js	304	0644	edit dl rm
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beta.mjs	154	0644	edit dl rm
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completions.d.mts	7233	0644	edit dl rm
completions.d.mts.map	1949	0644	edit dl rm
completions.d.ts	7225	0644	edit dl rm
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completions.js	922	0644	edit dl rm
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completions.mjs	766	0644	edit dl rm
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index.d.mts	5835	0644	edit dl rm
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messages.d.mts	77	0644	edit dl rm
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models.d.mts	5783	0644	edit dl rm
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shared.d.mts	1337	0644	edit dl rm
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shared.mjs.map	126	0644	edit dl rm
top-level.d.mts	51	0644	edit dl rm
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top-level.mjs.map	132	0644	edit dl rm

Edit: /opt/canhelp/node_modules/@anthropic-ai/sdk/resources/completions.d.ts (7225B)

import { APIResource } from "../core/resource.js";
import * as CompletionsAPI from "./completions.js";
import * as BetaAPI from "./beta/beta.js";
import * as MessagesAPI from "./messages/messages.js";
import { APIPromise } from "../core/api-promise.js";
import { Stream } from "../core/streaming.js";
import { RequestOptions } from "../internal/request-options.js";
export declare class Completions extends APIResource {
    /**
     * [Legacy] Create a Text Completion.
     *
     * The Text Completions API is a legacy API. We recommend using the
     * [Messages API](https://docs.claude.com/en/api/messages) going forward.
     *
     * Future models and features will not be compatible with Text Completions. See our
     * [migration guide](https://docs.claude.com/en/api/migrating-from-text-completions-to-messages)
     * for guidance in migrating from Text Completions to Messages.
     *
     * @example
     * ```ts
     * const completion = await client.completions.create({
     *   max_tokens_to_sample: 256,
     *   model: 'claude-opus-4-6',
     *   prompt: '\n\nHuman: Hello, world!\n\nAssistant:',
     * });
     * ```
     */
    create(params: CompletionCreateParamsNonStreaming, options?: RequestOptions): APIPromise<Completion>;
    create(params: CompletionCreateParamsStreaming, options?: RequestOptions): APIPromise<Stream<Completion>>;
    create(params: CompletionCreateParamsBase, options?: RequestOptions): APIPromise<Stream<Completion> | Completion>;
}
export interface Completion {
    /**
     * Unique object identifier.
     *
     * The format and length of IDs may change over time.
     */
    id: string;
    /**
     * The resulting completion up to and excluding the stop sequences.
     */
    completion: string;
    /**
     * The model that will complete your prompt.\n\nSee
     * [models](https://docs.anthropic.com/en/docs/models-overview) for additional
     * details and options.
     */
    model: MessagesAPI.Model;
    /**
     * The reason that we stopped.
     *
     * This may be one the following values:
     *
     * - `"stop_sequence"`: we reached a stop sequence — either provided by you via the
     *   `stop_sequences` parameter, or a stop sequence built into the model
     * - `"max_tokens"`: we exceeded `max_tokens_to_sample` or the model's maximum
     */
    stop_reason: string | null;
    /**
     * Object type.
     *
     * For Text Completions, this is always `"completion"`.
     */
    type: 'completion';
}
export type CompletionCreateParams = CompletionCreateParamsNonStreaming | CompletionCreateParamsStreaming;
export interface CompletionCreateParamsBase {
    /**
     * Body param: The maximum number of tokens to generate before stopping.
     *
     * Note that our models may stop _before_ reaching this maximum. This parameter
     * only specifies the absolute maximum number of tokens to generate.
     */
    max_tokens_to_sample: number;
    /**
     * Body param: The model that will complete your prompt.\n\nSee
     * [models](https://docs.anthropic.com/en/docs/models-overview) for additional
     * details and options.
     */
    model: MessagesAPI.Model;
    /**
     * Body param: The prompt that you want Claude to complete.
     *
     * For proper response generation you will need to format your prompt using
     * alternating `\n\nHuman:` and `\n\nAssistant:` conversational turns. For example:
     *
     * ```
     * "\n\nHuman: {userQuestion}\n\nAssistant:"
     * ```
     *
     * See [prompt validation](https://docs.claude.com/en/api/prompt-validation) and
     * our guide to [prompt design](https://docs.claude.com/en/docs/intro-to-prompting)
     * for more details.
     */
    prompt: string;
    /**
     * Body param: An object describing metadata about the request.
     */
    metadata?: MessagesAPI.Metadata;
    /**
     * Body param: Sequences that will cause the model to stop generating.
     *
     * Our models stop on `"\n\nHuman:"`, and may include additional built-in stop
     * sequences in the future. By providing the stop_sequences parameter, you may
     * include additional strings that will cause the model to stop generating.
     */
    stop_sequences?: Array<string>;
    /**
     * Body param: Whether to incrementally stream the response using server-sent
     * events.
     *
     * See [streaming](https://docs.claude.com/en/api/streaming) for details.
     */
    stream?: boolean;
    /**
     * Body param: Amount of randomness injected into the response.
     *
     * Defaults to `1.0`. Ranges from `0.0` to `1.0`. Use `temperature` closer to `0.0`
     * for analytical / multiple choice, and closer to `1.0` for creative and
     * generative tasks.
     *
     * Note that even with `temperature` of `0.0`, the results will not be fully
     * deterministic.
     */
    temperature?: number;
    /**
     * Body param: Only sample from the top K options for each subsequent token.
     *
     * Used to remove "long tail" low probability responses.
     * [Learn more technical details here](https://towardsdatascience.com/how-to-sample-from-language-models-682bceb97277).
     *
     * Recommended for advanced use cases only. You usually only need to use
     * `temperature`.
     */
    top_k?: number;
    /**
     * Body param: Use nucleus sampling.
     *
     * In nucleus sampling, we compute the cumulative distribution over all the options
     * for each subsequent token in decreasing probability order and cut it off once it
     * reaches a particular probability specified by `top_p`. You should either alter
     * `temperature` or `top_p`, but not both.
     *
     * Recommended for advanced use cases only. You usually only need to use
     * `temperature`.
     */
    top_p?: number;
    /**
     * Header param: Optional header to specify the beta version(s) you want to use.
     */
    betas?: Array<BetaAPI.AnthropicBeta>;
}
export declare namespace CompletionCreateParams {
    /**
     * @deprecated use `Anthropic.Messages.Metadata` instead
     */
    type Metadata = MessagesAPI.Metadata;
    type CompletionCreateParamsNonStreaming = CompletionsAPI.CompletionCreateParamsNonStreaming;
    type CompletionCreateParamsStreaming = CompletionsAPI.CompletionCreateParamsStreaming;
}
export interface CompletionCreateParamsNonStreaming extends CompletionCreateParamsBase {
    /**
     * Body param: Whether to incrementally stream the response using server-sent
     * events.
     *
     * See [streaming](https://docs.claude.com/en/api/streaming) for details.
     */
    stream?: false;
}
export interface CompletionCreateParamsStreaming extends CompletionCreateParamsBase {
    /**
     * Body param: Whether to incrementally stream the response using server-sent
     * events.
     *
     * See [streaming](https://docs.claude.com/en/api/streaming) for details.
     */
    stream: true;
}
export declare namespace Completions {
    export { type Completion as Completion, type CompletionCreateParams as CompletionCreateParams, type CompletionCreateParamsNonStreaming as CompletionCreateParamsNonStreaming, type CompletionCreateParamsStreaming as CompletionCreateParamsStreaming, };
}
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