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web.ts
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import { SignatureV4 } from "@smithy/signature-v4";
import { HttpRequest } from "@smithy/protocol-http";
import { EventStreamCodec } from "@smithy/eventstream-codec";
import { fromUtf8, toUtf8 } from "@smithy/util-utf8";
import { Sha256 } from "@aws-crypto/sha256-js";
import { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager";
import {
type BaseChatModelParams,
BaseChatModel,
} from "@langchain/core/language_models/chat_models";
import { getEnvironmentVariable } from "@langchain/core/utils/env";
import {
AIMessageChunk,
BaseMessage,
AIMessage,
ChatMessage,
} from "@langchain/core/messages";
import {
ChatGeneration,
ChatGenerationChunk,
ChatResult,
} from "@langchain/core/outputs";
import {
BaseBedrockInput,
BedrockLLMInputOutputAdapter,
type CredentialType,
} from "../../utils/bedrock.js";
import type { SerializedFields } from "../../load/map_keys.js";
const PRELUDE_TOTAL_LENGTH_BYTES = 4;
function convertOneMessageToText(
message: BaseMessage,
humanPrompt: string,
aiPrompt: string
): string {
if (message._getType() === "human") {
return `${humanPrompt} ${message.content}`;
} else if (message._getType() === "ai") {
return `${aiPrompt} ${message.content}`;
} else if (message._getType() === "system") {
return `${humanPrompt} <admin>${message.content}</admin>`;
} else if (message._getType() === "function") {
return `${humanPrompt} ${message.content}`;
} else if (ChatMessage.isInstance(message)) {
return `\n\n${
message.role[0].toUpperCase() + message.role.slice(1)
}: {message.content}`;
}
throw new Error(`Unknown role: ${message._getType()}`);
}
export function convertMessagesToPromptAnthropic(
messages: BaseMessage[],
humanPrompt = "\n\nHuman:",
aiPrompt = "\n\nAssistant:"
): string {
const messagesCopy = [...messages];
if (
messagesCopy.length === 0 ||
messagesCopy[messagesCopy.length - 1]._getType() !== "ai"
) {
messagesCopy.push(new AIMessage({ content: "" }));
}
return messagesCopy
.map((message) => convertOneMessageToText(message, humanPrompt, aiPrompt))
.join("");
}
/**
* Function that converts an array of messages into a single string prompt
* that can be used as input for a chat model. It delegates the conversion
* logic to the appropriate provider-specific function.
* @param messages Array of messages to be converted.
* @param options Options to be used during the conversion.
* @returns A string prompt that can be used as input for a chat model.
*/
export function convertMessagesToPrompt(
messages: BaseMessage[],
provider: string
): string {
if (provider === "anthropic") {
return convertMessagesToPromptAnthropic(messages);
}
throw new Error(`Provider ${provider} does not support chat.`);
}
/**
* A type of Large Language Model (LLM) that interacts with the Bedrock
* service. It extends the base `LLM` class and implements the
* `BaseBedrockInput` interface. The class is designed to authenticate and
* interact with the Bedrock service, which is a part of Amazon Web
* Services (AWS). It uses AWS credentials for authentication and can be
* configured with various parameters such as the model to use, the AWS
* region, and the maximum number of tokens to generate.
* @example
* ```typescript
* const model = new BedrockChat({
* model: "anthropic.claude-v2",
* region: "us-east-1",
* });
* const res = await model.invoke([{ content: "Tell me a joke" }]);
* console.log(res);
* ```
*/
export class BedrockChat extends BaseChatModel implements BaseBedrockInput {
model = "amazon.titan-tg1-large";
region: string;
credentials: CredentialType;
temperature?: number | undefined = undefined;
maxTokens?: number | undefined = undefined;
fetchFn: typeof fetch;
endpointHost?: string;
/** @deprecated Use as a call option using .bind() instead. */
stopSequences?: string[];
modelKwargs?: Record<string, unknown>;
codec: EventStreamCodec = new EventStreamCodec(toUtf8, fromUtf8);
streaming = false;
usesMessagesApi = false;
lc_serializable = true;
get lc_aliases(): Record<string, string> {
return {
model: "model_id",
region: "region_name",
};
}
get lc_secrets(): { [key: string]: string } | undefined {
return {
"credentials.accessKeyId": "BEDROCK_AWS_ACCESS_KEY_ID",
"credentials.secretAccessKey": "BEDROCK_AWS_SECRET_ACCESS_KEY",
};
}
get lc_attributes(): SerializedFields | undefined {
return { region: this.region };
}
_identifyingParams(): Record<string, string> {
return {
model: this.model,
};
}
_llmType() {
return "bedrock";
}
static lc_name() {
return "BedrockChat";
}
constructor(fields?: Partial<BaseBedrockInput> & BaseChatModelParams) {
super(fields ?? {});
this.model = fields?.model ?? this.model;
const allowedModels = [
"ai21",
"anthropic",
"amazon",
"cohere",
"meta",
"mistral",
];
if (!allowedModels.includes(this.model.split(".")[0])) {
throw new Error(
`Unknown model: '${this.model}', only these are supported: ${allowedModels}`
);
}
const region =
fields?.region ?? getEnvironmentVariable("AWS_DEFAULT_REGION");
if (!region) {
throw new Error(
"Please set the AWS_DEFAULT_REGION environment variable or pass it to the constructor as the region field."
);
}
this.region = region;
const credentials = fields?.credentials;
if (!credentials) {
throw new Error(
"Please set the AWS credentials in the 'credentials' field."
);
}
this.credentials = credentials;
this.temperature = fields?.temperature ?? this.temperature;
this.maxTokens = fields?.maxTokens ?? this.maxTokens;
this.fetchFn = fields?.fetchFn ?? fetch.bind(globalThis);
this.endpointHost = fields?.endpointHost ?? fields?.endpointUrl;
this.stopSequences = fields?.stopSequences;
this.modelKwargs = fields?.modelKwargs;
this.streaming = fields?.streaming ?? this.streaming;
this.usesMessagesApi =
this.model.split(".")[0] === "anthropic" &&
!this.model.includes("claude-v2") &&
!this.model.includes("claude-instant-v1");
}
async _generate(
messages: BaseMessage[],
options: this["ParsedCallOptions"],
runManager?: CallbackManagerForLLMRun
): Promise<ChatResult> {
const service = "bedrock-runtime";
const endpointHost =
this.endpointHost ?? `${service}.${this.region}.amazonaws.com`;
const provider = this.model.split(".")[0];
if (this.streaming) {
const stream = this._streamResponseChunks(messages, options, runManager);
let finalResult: ChatGenerationChunk | undefined;
for await (const chunk of stream) {
if (finalResult === undefined) {
finalResult = chunk;
} else {
finalResult = finalResult.concat(chunk);
}
}
if (finalResult === undefined) {
throw new Error(
"Could not parse final output from Bedrock streaming call."
);
}
return {
generations: [finalResult],
llmOutput: finalResult.generationInfo,
};
}
const response = await this._signedFetch(messages, options, {
bedrockMethod: "invoke",
endpointHost,
provider,
});
const json = await response.json();
if (!response.ok) {
throw new Error(
`Error ${response.status}: ${json.message ?? JSON.stringify(json)}`
);
}
if (this.usesMessagesApi) {
const outputGeneration =
BedrockLLMInputOutputAdapter.prepareMessagesOutput(provider, json);
if (outputGeneration === undefined) {
throw new Error("Failed to parse output generation.");
}
return {
generations: [outputGeneration],
llmOutput: outputGeneration.generationInfo,
};
} else {
const text = BedrockLLMInputOutputAdapter.prepareOutput(provider, json);
return { generations: [{ text, message: new AIMessage(text) }] };
}
}
async _signedFetch(
messages: BaseMessage[],
options: this["ParsedCallOptions"],
fields: {
bedrockMethod: "invoke" | "invoke-with-response-stream";
endpointHost: string;
provider: string;
}
) {
const { bedrockMethod, endpointHost, provider } = fields;
const inputBody = this.usesMessagesApi
? BedrockLLMInputOutputAdapter.prepareMessagesInput(
provider,
messages,
this.maxTokens,
this.temperature,
options.stop ?? this.stopSequences,
this.modelKwargs
)
: BedrockLLMInputOutputAdapter.prepareInput(
provider,
convertMessagesToPromptAnthropic(messages),
this.maxTokens,
this.temperature,
options.stop ?? this.stopSequences,
this.modelKwargs,
fields.bedrockMethod
);
const url = new URL(
`https://${endpointHost}/model/${this.model}/${bedrockMethod}`
);
const request = new HttpRequest({
hostname: url.hostname,
path: url.pathname,
protocol: url.protocol,
method: "POST", // method must be uppercase
body: JSON.stringify(inputBody),
query: Object.fromEntries(url.searchParams.entries()),
headers: {
// host is required by AWS Signature V4: https://docs.aws.amazon.com/general/latest/gr/sigv4-create-canonical-request.html
host: url.host,
accept: "application/json",
"content-type": "application/json",
},
});
const signer = new SignatureV4({
credentials: this.credentials,
service: "bedrock",
region: this.region,
sha256: Sha256,
});
const signedRequest = await signer.sign(request);
// Send request to AWS using the low-level fetch API
const response = await this.caller.callWithOptions(
{ signal: options.signal },
async () =>
this.fetchFn(url, {
headers: signedRequest.headers,
body: signedRequest.body,
method: signedRequest.method,
})
);
return response;
}
async *_streamResponseChunks(
messages: BaseMessage[],
options: this["ParsedCallOptions"],
runManager?: CallbackManagerForLLMRun
): AsyncGenerator<ChatGenerationChunk> {
const provider = this.model.split(".")[0];
const service = "bedrock-runtime";
const endpointHost =
this.endpointHost ?? `${service}.${this.region}.amazonaws.com`;
const bedrockMethod =
provider === "anthropic" ||
provider === "cohere" ||
provider === "meta" ||
provider === "mistral"
? "invoke-with-response-stream"
: "invoke";
const response = await this._signedFetch(messages, options, {
bedrockMethod,
endpointHost,
provider,
});
if (response.status < 200 || response.status >= 300) {
throw Error(
`Failed to access underlying url '${endpointHost}': got ${
response.status
} ${response.statusText}: ${await response.text()}`
);
}
if (
provider === "anthropic" ||
provider === "cohere" ||
provider === "meta" ||
provider === "mistral"
) {
const reader = response.body?.getReader();
const decoder = new TextDecoder();
for await (const chunk of this._readChunks(reader)) {
const event = this.codec.decode(chunk);
if (
(event.headers[":event-type"] !== undefined &&
event.headers[":event-type"].value !== "chunk") ||
event.headers[":content-type"].value !== "application/json"
) {
throw Error(`Failed to get event chunk: got ${chunk}`);
}
const body = JSON.parse(decoder.decode(event.body));
if (body.message) {
throw new Error(body.message);
}
if (body.bytes !== undefined) {
const chunkResult = JSON.parse(
decoder.decode(
Uint8Array.from(atob(body.bytes), (m) => m.codePointAt(0) ?? 0)
)
);
if (this.usesMessagesApi) {
const chunk = BedrockLLMInputOutputAdapter.prepareMessagesOutput(
provider,
chunkResult
);
if (chunk === undefined) {
continue;
}
if (isChatGenerationChunk(chunk)) {
yield chunk;
}
// eslint-disable-next-line no-void
void runManager?.handleLLMNewToken(chunk.text);
} else {
const text = BedrockLLMInputOutputAdapter.prepareOutput(
provider,
chunkResult
);
yield new ChatGenerationChunk({
text,
message: new AIMessageChunk({ content: text }),
});
// eslint-disable-next-line no-void
void runManager?.handleLLMNewToken(text);
}
}
}
} else {
const json = await response.json();
const text = BedrockLLMInputOutputAdapter.prepareOutput(provider, json);
yield new ChatGenerationChunk({
text,
message: new AIMessageChunk({ content: text }),
});
// eslint-disable-next-line no-void
void runManager?.handleLLMNewToken(text);
}
}
// eslint-disable-next-line @typescript-eslint/no-explicit-any
_readChunks(reader: any) {
function _concatChunks(a: Uint8Array, b: Uint8Array) {
const newBuffer = new Uint8Array(a.length + b.length);
newBuffer.set(a);
newBuffer.set(b, a.length);
return newBuffer;
}
function getMessageLength(buffer: Uint8Array) {
if (buffer.byteLength < PRELUDE_TOTAL_LENGTH_BYTES) return 0;
const view = new DataView(
buffer.buffer,
buffer.byteOffset,
buffer.byteLength
);
return view.getUint32(0, false);
}
return {
async *[Symbol.asyncIterator]() {
let readResult = await reader.read();
let buffer: Uint8Array = new Uint8Array(0);
while (!readResult.done) {
const chunk: Uint8Array = readResult.value;
buffer = _concatChunks(buffer, chunk);
let messageLength = getMessageLength(buffer);
while (
buffer.byteLength >= PRELUDE_TOTAL_LENGTH_BYTES &&
buffer.byteLength >= messageLength
) {
yield buffer.slice(0, messageLength);
buffer = buffer.slice(messageLength);
messageLength = getMessageLength(buffer);
}
readResult = await reader.read();
}
},
};
}
_combineLLMOutput() {
return {};
}
}
function isChatGenerationChunk(
x?: ChatGenerationChunk | ChatGeneration
): x is ChatGenerationChunk {
return (
x !== undefined && typeof (x as ChatGenerationChunk).concat === "function"
);
}
/**
* @deprecated Use `BedrockChat` instead.
*/
export const ChatBedrock = BedrockChat;