2024-07-24 01:35:37 +02:00
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const Provider = require("./ai-provider.js");
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const InheritMultiple = require("./helpers/classes.js");
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const UnTooled = require("./helpers/untooled.js");
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const { ChatBedrockConverse } = require("@langchain/aws");
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const {
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HumanMessage,
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SystemMessage,
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AIMessage,
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} = require("@langchain/core/messages");
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/**
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* The agent provider for the AWS Bedrock provider.
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*/
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class AWSBedrockProvider extends InheritMultiple([Provider, UnTooled]) {
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model;
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constructor(_config = {}) {
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super();
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const model = process.env.AWS_BEDROCK_LLM_MODEL_PREFERENCE ?? null;
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const client = new ChatBedrockConverse({
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region: process.env.AWS_BEDROCK_LLM_REGION,
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credentials: {
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accessKeyId: process.env.AWS_BEDROCK_LLM_ACCESS_KEY_ID,
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secretAccessKey: process.env.AWS_BEDROCK_LLM_ACCESS_KEY,
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2024-10-30 00:34:52 +01:00
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// If we're using a session token, we need to pass it in as a credential
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// otherwise we must omit it so it does not conflict if using IAM auth
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...(this.authMethod === "sessionToken"
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? { sessionToken: process.env.AWS_BEDROCK_LLM_SESSION_TOKEN }
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: {}),
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2024-07-24 01:35:37 +02:00
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},
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model,
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});
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this._client = client;
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this.model = model;
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this.verbose = true;
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}
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2024-10-30 00:34:52 +01:00
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/**
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* Get the authentication method for the AWS Bedrock LLM.
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* There are only two valid values for this setting - anything else will default to "iam".
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* @returns {"iam"|"sessionToken"}
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*/
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get authMethod() {
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const method = process.env.AWS_BEDROCK_LLM_CONNECTION_METHOD || "iam";
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if (!["iam", "sessionToken"].includes(method)) return "iam";
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return method;
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}
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2024-07-24 01:35:37 +02:00
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get client() {
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return this._client;
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}
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// For streaming we use Langchain's wrapper to handle weird chunks
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// or otherwise absorb headaches that can arise from Ollama models
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#convertToLangchainPrototypes(chats = []) {
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const langchainChats = [];
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const roleToMessageMap = {
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system: SystemMessage,
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user: HumanMessage,
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assistant: AIMessage,
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};
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for (const chat of chats) {
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if (!roleToMessageMap.hasOwnProperty(chat.role)) continue;
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const MessageClass = roleToMessageMap[chat.role];
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langchainChats.push(new MessageClass({ content: chat.content }));
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}
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return langchainChats;
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}
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async #handleFunctionCallChat({ messages = [] }) {
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const response = await this.client
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.invoke(this.#convertToLangchainPrototypes(messages))
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.then((res) => res)
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.catch((e) => {
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console.error(e);
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return null;
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});
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return response?.content;
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}
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/**
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* Create a completion based on the received messages.
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*
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* @param messages A list of messages to send to the API.
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* @param functions
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* @returns The completion.
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*/
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async complete(messages, functions = null) {
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try {
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let completion;
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if (functions.length > 0) {
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const { toolCall, text } = await this.functionCall(
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messages,
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functions,
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this.#handleFunctionCallChat.bind(this)
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);
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if (toolCall !== null) {
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this.providerLog(`Valid tool call found - running ${toolCall.name}.`);
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this.deduplicator.trackRun(toolCall.name, toolCall.arguments);
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return {
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result: null,
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functionCall: {
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name: toolCall.name,
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arguments: toolCall.arguments,
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},
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cost: 0,
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};
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}
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completion = { content: text };
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}
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if (!completion?.content) {
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this.providerLog(
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"Will assume chat completion without tool call inputs."
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);
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const response = await this.client.invoke(
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this.#convertToLangchainPrototypes(this.cleanMsgs(messages))
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);
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completion = response;
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}
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// The UnTooled class inherited Deduplicator is mostly useful to prevent the agent
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// from calling the exact same function over and over in a loop within a single chat exchange
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// _but_ we should enable it to call previously used tools in a new chat interaction.
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this.deduplicator.reset("runs");
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return {
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result: completion.content,
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cost: 0,
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};
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} catch (error) {
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throw error;
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}
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}
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/**
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* Get the cost of the completion.
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*
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* @param _usage The completion to get the cost for.
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* @returns The cost of the completion.
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* Stubbed since KoboldCPP has no cost basis.
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*/
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getCost(_usage) {
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return 0;
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}
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}
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module.exports = AWSBedrockProvider;
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