AEM MCP Server
messages.d.ts•23.2 kB
import * as Core from '@anthropic-ai/sdk/core';
import { APIPromise } from '@anthropic-ai/sdk/core';
import { APIResource } from '@anthropic-ai/sdk/resource';
import { MessageStream } from '@anthropic-ai/sdk/lib/MessageStream';
export { MessageStream } from '@anthropic-ai/sdk/lib/MessageStream';
import * as MessagesAPI from '@anthropic-ai/sdk/resources/messages';
import { Stream } from '@anthropic-ai/sdk/streaming';
export declare class Messages extends APIResource {
/**
* Create a Message.
*
* Send a structured list of input messages with text and/or image content, and the
* model will generate the next message in the conversation.
*
* The Messages API can be used for for either single queries or stateless
* multi-turn conversations.
*/
create(body: MessageCreateParamsNonStreaming, options?: Core.RequestOptions): APIPromise<Message>;
create(body: MessageCreateParamsStreaming, options?: Core.RequestOptions): APIPromise<Stream<MessageStreamEvent>>;
create(body: MessageCreateParamsBase, options?: Core.RequestOptions): APIPromise<Stream<MessageStreamEvent> | Message>;
/**
* Create a Message stream
*/
stream(body: MessageStreamParams, options?: Core.RequestOptions): MessageStream;
}
export interface ContentBlock {
text: string;
type: 'text';
}
export interface ContentBlockDeltaEvent {
delta: TextDelta;
index: number;
type: 'content_block_delta';
}
export interface ContentBlockStartEvent {
content_block: ContentBlock;
index: number;
type: 'content_block_start';
}
export interface ContentBlockStopEvent {
index: number;
type: 'content_block_stop';
}
export interface ImageBlockParam {
source: ImageBlockParam.Source;
type?: 'image';
}
export declare namespace ImageBlockParam {
interface Source {
data: string;
media_type: 'image/jpeg' | 'image/png' | 'image/gif' | 'image/webp';
type?: 'base64';
}
}
export interface Message {
/**
* Unique object identifier.
*
* The format and length of IDs may change over time.
*/
id: string;
/**
* Content generated by the model.
*
* This is an array of content blocks, each of which has a `type` that determines
* its shape. Currently, the only `type` in responses is `"text"`.
*
* Example:
*
* ```json
* [{ "type": "text", "text": "Hi, I'm Claude." }]
* ```
*
* If the request input `messages` ended with an `assistant` turn, then the
* response `content` will continue directly from that last turn. You can use this
* to constrain the model's output.
*
* For example, if the input `messages` were:
*
* ```json
* [
* {
* "role": "user",
* "content": "What's the Greek name for Sun? (A) Sol (B) Helios (C) Sun"
* },
* { "role": "assistant", "content": "The best answer is (" }
* ]
* ```
*
* Then the response `content` might be:
*
* ```json
* [{ "type": "text", "text": "B)" }]
* ```
*/
content: Array<ContentBlock>;
/**
* The model that handled the request.
*/
model: string;
/**
* Conversational role of the generated message.
*
* This will always be `"assistant"`.
*/
role: 'assistant';
/**
* The reason that we stopped.
*
* This may be one the following values:
*
* - `"end_turn"`: the model reached a natural stopping point
* - `"max_tokens"`: we exceeded the requested `max_tokens` or the model's maximum
* - `"stop_sequence"`: one of your provided custom `stop_sequences` was generated
*
* Note that these values are different than those in `/v1/complete`, where
* `end_turn` and `stop_sequence` were not differentiated.
*
* In non-streaming mode this value is always non-null. In streaming mode, it is
* null in the `message_start` event and non-null otherwise.
*/
stop_reason: 'end_turn' | 'max_tokens' | 'stop_sequence' | null;
/**
* Which custom stop sequence was generated, if any.
*
* This value will be a non-null string if one of your custom stop sequences was
* generated.
*/
stop_sequence: string | null;
/**
* Object type.
*
* For Messages, this is always `"message"`.
*/
type: 'message';
/**
* Billing and rate-limit usage.
*
* Anthropic's API bills and rate-limits by token counts, as tokens represent the
* underlying cost to our systems.
*
* Under the hood, the API transforms requests into a format suitable for the
* model. The model's output then goes through a parsing stage before becoming an
* API response. As a result, the token counts in `usage` will not match one-to-one
* with the exact visible content of an API request or response.
*
* For example, `output_tokens` will be non-zero, even for an empty string response
* from Claude.
*/
usage: Usage;
}
export interface MessageDeltaEvent {
delta: MessageDeltaEvent.Delta;
type: 'message_delta';
/**
* Billing and rate-limit usage.
*
* Anthropic's API bills and rate-limits by token counts, as tokens represent the
* underlying cost to our systems.
*
* Under the hood, the API transforms requests into a format suitable for the
* model. The model's output then goes through a parsing stage before becoming an
* API response. As a result, the token counts in `usage` will not match one-to-one
* with the exact visible content of an API request or response.
*
* For example, `output_tokens` will be non-zero, even for an empty string response
* from Claude.
*/
usage: MessageDeltaUsage;
}
export declare namespace MessageDeltaEvent {
interface Delta {
stop_reason: 'end_turn' | 'max_tokens' | 'stop_sequence' | null;
stop_sequence: string | null;
}
}
export interface MessageDeltaUsage {
/**
* The cumulative number of output tokens which were used.
*/
output_tokens: number;
}
export interface MessageParam {
content: string | Array<TextBlock | ImageBlockParam>;
role: 'user' | 'assistant';
}
export interface MessageStartEvent {
message: Message;
type: 'message_start';
}
export interface MessageStopEvent {
type: 'message_stop';
}
export type MessageStreamEvent = MessageStartEvent | MessageDeltaEvent | MessageStopEvent | ContentBlockStartEvent | ContentBlockDeltaEvent | ContentBlockStopEvent;
export interface TextBlock {
text: string;
type?: 'text';
}
export interface TextDelta {
text: string;
type: 'text_delta';
}
export interface Usage {
/**
* The number of input tokens which were used.
*/
input_tokens: number;
/**
* The number of output tokens which were used.
*/
output_tokens: number;
}
export type MessageCreateParams = MessageCreateParamsNonStreaming | MessageCreateParamsStreaming;
export interface MessageCreateParamsBase {
/**
* 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.
*
* Different models have different maximum values for this parameter. See
* [models](https://docs.anthropic.com/claude/docs/models-overview) for details.
*/
max_tokens: number;
/**
* Input messages.
*
* Our models are trained to operate on alternating `user` and `assistant`
* conversational turns. When creating a new `Message`, you specify the prior
* conversational turns with the `messages` parameter, and the model then generates
* the next `Message` in the conversation.
*
* Each input message must be an object with a `role` and `content`. You can
* specify a single `user`-role message, or you can include multiple `user` and
* `assistant` messages. The first message must always use the `user` role.
*
* If the final message uses the `assistant` role, the response content will
* continue immediately from the content in that message. This can be used to
* constrain part of the model's response.
*
* Example with a single `user` message:
*
* ```json
* [{ "role": "user", "content": "Hello, Claude" }]
* ```
*
* Example with multiple conversational turns:
*
* ```json
* [
* { "role": "user", "content": "Hello there." },
* { "role": "assistant", "content": "Hi, I'm Claude. How can I help you?" },
* { "role": "user", "content": "Can you explain LLMs in plain English?" }
* ]
* ```
*
* Example with a partially-filled response from Claude:
*
* ```json
* [
* {
* "role": "user",
* "content": "What's the Greek name for Sun? (A) Sol (B) Helios (C) Sun"
* },
* { "role": "assistant", "content": "The best answer is (" }
* ]
* ```
*
* Each input message `content` may be either a single `string` or an array of
* content blocks, where each block has a specific `type`. Using a `string` for
* `content` is shorthand for an array of one content block of type `"text"`. The
* following input messages are equivalent:
*
* ```json
* { "role": "user", "content": "Hello, Claude" }
* ```
*
* ```json
* { "role": "user", "content": [{ "type": "text", "text": "Hello, Claude" }] }
* ```
*
* Starting with Claude 3 models, you can also send image content blocks:
*
* ```json
* {
* "role": "user",
* "content": [
* {
* "type": "image",
* "source": {
* "type": "base64",
* "media_type": "image/jpeg",
* "data": "/9j/4AAQSkZJRg..."
* }
* },
* { "type": "text", "text": "What is in this image?" }
* ]
* }
* ```
*
* We currently support the `base64` source type for images, and the `image/jpeg`,
* `image/png`, `image/gif`, and `image/webp` media types.
*
* See [examples](https://docs.anthropic.com/claude/reference/messages-examples)
* for more input examples.
*
* Note that if you want to include a
* [system prompt](https://docs.anthropic.com/claude/docs/system-prompts), you can
* use the top-level `system` parameter — there is no `"system"` role for input
* messages in the Messages API.
*/
messages: Array<MessageParam>;
/**
* The model that will complete your prompt.
*
* See [models](https://docs.anthropic.com/claude/docs/models-overview) for
* additional details and options.
*/
model: (string & {}) | 'claude-3-opus-20240229' | 'claude-3-sonnet-20240229' | 'claude-3-haiku-20240307' | 'claude-2.1' | 'claude-2.0' | 'claude-instant-1.2';
/**
* An object describing metadata about the request.
*/
metadata?: MessageCreateParams.Metadata;
/**
* Custom text sequences that will cause the model to stop generating.
*
* Our models will normally stop when they have naturally completed their turn,
* which will result in a response `stop_reason` of `"end_turn"`.
*
* If you want the model to stop generating when it encounters custom strings of
* text, you can use the `stop_sequences` parameter. If the model encounters one of
* the custom sequences, the response `stop_reason` value will be `"stop_sequence"`
* and the response `stop_sequence` value will contain the matched stop sequence.
*/
stop_sequences?: Array<string>;
/**
* Whether to incrementally stream the response using server-sent events.
*
* See [streaming](https://docs.anthropic.com/claude/reference/messages-streaming)
* for details.
*/
stream?: boolean;
/**
* System prompt.
*
* A system prompt is a way of providing context and instructions to Claude, such
* as specifying a particular goal or role. See our
* [guide to system prompts](https://docs.anthropic.com/claude/docs/system-prompts).
*/
system?: string;
/**
* 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;
/**
* 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;
/**
* 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;
}
export declare namespace MessageCreateParams {
/**
* An object describing metadata about the request.
*/
interface Metadata {
/**
* An external identifier for the user who is associated with the request.
*
* This should be a uuid, hash value, or other opaque identifier. Anthropic may use
* this id to help detect abuse. Do not include any identifying information such as
* name, email address, or phone number.
*/
user_id?: string | null;
}
type MessageCreateParamsNonStreaming = MessagesAPI.MessageCreateParamsNonStreaming;
type MessageCreateParamsStreaming = MessagesAPI.MessageCreateParamsStreaming;
}
export interface MessageCreateParamsNonStreaming extends MessageCreateParamsBase {
/**
* Whether to incrementally stream the response using server-sent events.
*
* See [streaming](https://docs.anthropic.com/claude/reference/messages-streaming)
* for details.
*/
stream?: false;
}
export interface MessageCreateParamsStreaming extends MessageCreateParamsBase {
/**
* Whether to incrementally stream the response using server-sent events.
*
* See [streaming](https://docs.anthropic.com/claude/reference/messages-streaming)
* for details.
*/
stream: true;
}
export interface MessageStreamParams {
/**
* 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.
*
* Different models have different maximum values for this parameter. See
* [models](https://docs.anthropic.com/claude/docs/models-overview) for details.
*/
max_tokens: number;
/**
* Input messages.
*
* Our models are trained to operate on alternating `user` and `assistant`
* conversational turns. When creating a new `Message`, you specify the prior
* conversational turns with the `messages` parameter, and the model then generates
* the next `Message` in the conversation.
*
* Each input message must be an object with a `role` and `content`. You can
* specify a single `user`-role message, or you can include multiple `user` and
* `assistant` messages. The first message must always use the `user` role.
*
* If the final message uses the `assistant` role, the response content will
* continue immediately from the content in that message. This can be used to
* constrain part of the model's response.
*
* Example with a single `user` message:
*
* ```json
* [{ "role": "user", "content": "Hello, Claude" }]
* ```
*
* Example with multiple conversational turns:
*
* ```json
* [
* { "role": "user", "content": "Hello there." },
* { "role": "assistant", "content": "Hi, I'm Claude. How can I help you?" },
* { "role": "user", "content": "Can you explain LLMs in plain English?" }
* ]
* ```
*
* Example with a partially-filled response from Claude:
*
* ```json
* [
* {
* "role": "user",
* "content": "What's the Greek name for Sun? (A) Sol (B) Helios (C) Sun"
* },
* { "role": "assistant", "content": "The best answer is (" }
* ]
* ```
*
* Each input message `content` may be either a single `string` or an array of
* content blocks, where each block has a specific `type`. Using a `string` for
* `content` is shorthand for an array of one content block of type `"text"`. The
* following input messages are equivalent:
*
* ```json
* { "role": "user", "content": "Hello, Claude" }
* ```
*
* ```json
* { "role": "user", "content": [{ "type": "text", "text": "Hello, Claude" }] }
* ```
*
* Starting with Claude 3 models, you can also send image content blocks:
*
* ```json
* {
* "role": "user",
* "content": [
* {
* "type": "image",
* "source": {
* "type": "base64",
* "media_type": "image/jpeg",
* "data": "/9j/4AAQSkZJRg..."
* }
* },
* { "type": "text", "text": "What is in this image?" }
* ]
* }
* ```
*
* We currently support the `base64` source type for images, and the `image/jpeg`,
* `image/png`, `image/gif`, and `image/webp` media types.
*
* See [examples](https://docs.anthropic.com/claude/reference/messages-examples)
* for more input examples.
*
* Note that if you want to include a
* [system prompt](https://docs.anthropic.com/claude/docs/system-prompts), you can
* use the top-level `system` parameter — there is no `"system"` role for input
* messages in the Messages API.
*/
messages: Array<MessageParam>;
/**
* The model that will complete your prompt.
*
* See [models](https://docs.anthropic.com/claude/docs/models-overview) for
* additional details and options.
*/
model: (string & {}) | 'claude-3-opus-20240229' | 'claude-3-sonnet-20240229' | 'claude-3-haiku-20240307' | 'claude-2.1' | 'claude-2.0' | 'claude-instant-1.2';
/**
* An object describing metadata about the request.
*/
metadata?: MessageStreamParams.Metadata;
/**
* Custom text sequences that will cause the model to stop generating.
*
* Our models will normally stop when they have naturally completed their turn,
* which will result in a response `stop_reason` of `"end_turn"`.
*
* If you want the model to stop generating when it encounters custom strings of
* text, you can use the `stop_sequences` parameter. If the model encounters one of
* the custom sequences, the response `stop_reason` value will be `"stop_sequence"`
* and the response `stop_sequence` value will contain the matched stop sequence.
*/
stop_sequences?: Array<string>;
/**
* System prompt.
*
* A system prompt is a way of providing context and instructions to Claude, such
* as specifying a particular goal or role. See our
* [guide to system prompts](https://docs.anthropic.com/claude/docs/system-prompts).
*/
system?: string;
/**
* 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;
/**
* 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;
/**
* 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;
}
export declare namespace MessageStreamParams {
/**
* An object describing metadata about the request.
*/
interface Metadata {
/**
* An external identifier for the user who is associated with the request.
*
* This should be a uuid, hash value, or other opaque identifier. Anthropic may use
* this id to help detect abuse. Do not include any identifying information such as
* name, email address, or phone number.
*/
user_id?: string | null;
}
}
export declare namespace Messages {
export import ContentBlock = MessagesAPI.ContentBlock;
export import ContentBlockDeltaEvent = MessagesAPI.ContentBlockDeltaEvent;
export import ContentBlockStartEvent = MessagesAPI.ContentBlockStartEvent;
export import ContentBlockStopEvent = MessagesAPI.ContentBlockStopEvent;
export import ImageBlockParam = MessagesAPI.ImageBlockParam;
export import Message = MessagesAPI.Message;
export import MessageDeltaEvent = MessagesAPI.MessageDeltaEvent;
export import MessageDeltaUsage = MessagesAPI.MessageDeltaUsage;
export import MessageParam = MessagesAPI.MessageParam;
export import MessageStartEvent = MessagesAPI.MessageStartEvent;
export import MessageStopEvent = MessagesAPI.MessageStopEvent;
export import MessageStreamEvent = MessagesAPI.MessageStreamEvent;
export import TextBlock = MessagesAPI.TextBlock;
export import TextDelta = MessagesAPI.TextDelta;
export import Usage = MessagesAPI.Usage;
export import MessageCreateParams = MessagesAPI.MessageCreateParams;
export import MessageCreateParamsNonStreaming = MessagesAPI.MessageCreateParamsNonStreaming;
export import MessageCreateParamsStreaming = MessagesAPI.MessageCreateParamsStreaming;
export import MessageStreamParams = MessagesAPI.MessageStreamParams;
}
//# sourceMappingURL=messages.d.ts.map
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