lume-ai
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A powerful yet simple library to build your own AI applications.
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JavaScript
;
var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
return new (P || (P = Promise))(function (resolve, reject) {
function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
step((generator = generator.apply(thisArg, _arguments || [])).next());
});
};
var __await = (this && this.__await) || function (v) { return this instanceof __await ? (this.v = v, this) : new __await(v); }
var __asyncValues = (this && this.__asyncValues) || function (o) {
if (!Symbol.asyncIterator) throw new TypeError("Symbol.asyncIterator is not defined.");
var m = o[Symbol.asyncIterator], i;
return m ? m.call(o) : (o = typeof __values === "function" ? __values(o) : o[Symbol.iterator](), i = {}, verb("next"), verb("throw"), verb("return"), i[Symbol.asyncIterator] = function () { return this; }, i);
function verb(n) { i[n] = o[n] && function (v) { return new Promise(function (resolve, reject) { v = o[n](v), settle(resolve, reject, v.done, v.value); }); }; }
function settle(resolve, reject, d, v) { Promise.resolve(v).then(function(v) { resolve({ value: v, done: d }); }, reject); }
};
var __asyncGenerator = (this && this.__asyncGenerator) || function (thisArg, _arguments, generator) {
if (!Symbol.asyncIterator) throw new TypeError("Symbol.asyncIterator is not defined.");
var g = generator.apply(thisArg, _arguments || []), i, q = [];
return i = Object.create((typeof AsyncIterator === "function" ? AsyncIterator : Object).prototype), verb("next"), verb("throw"), verb("return", awaitReturn), i[Symbol.asyncIterator] = function () { return this; }, i;
function awaitReturn(f) { return function (v) { return Promise.resolve(v).then(f, reject); }; }
function verb(n, f) { if (g[n]) { i[n] = function (v) { return new Promise(function (a, b) { q.push([n, v, a, b]) > 1 || resume(n, v); }); }; if (f) i[n] = f(i[n]); } }
function resume(n, v) { try { step(g[n](v)); } catch (e) { settle(q[0][3], e); } }
function step(r) { r.value instanceof __await ? Promise.resolve(r.value.v).then(fulfill, reject) : settle(q[0][2], r); }
function fulfill(value) { resume("next", value); }
function reject(value) { resume("throw", value); }
function settle(f, v) { if (f(v), q.shift(), q.length) resume(q[0][0], q[0][1]); }
};
var __importDefault = (this && this.__importDefault) || function (mod) {
return (mod && mod.__esModule) ? mod : { "default": mod };
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.Anthropic = void 0;
// ===============================
// SECTION | IMPORTS
// ===============================
const sdk_1 = __importDefault(require("@anthropic-ai/sdk"));
const interfaces_1 = require("../interfaces");
const voyageai_1 = require("voyageai");
// ===============================
// ===============================
// SECTION | Anthropic
// ===============================
/**
* Implementation of the LLM interface for Anthropic's Claude models.
* Handles message formatting and API interaction for Anthropic.
*/
class Anthropic extends interfaces_1.LLM {
/**
* Constructs a new Anthropic LLM instance.
* @param apiKey - The API key for authenticating with Anthropic.
* @param debug - Optional flag to enable debug logging.
*/
constructor(apiKey, debug = false) {
super();
if (!apiKey || typeof apiKey !== 'string') {
throw new Error('Anthropic: apiKey must be a non-empty string');
}
this.llm = new sdk_1.default({ apiKey });
this.voyage = new voyageai_1.VoyageAIClient({ apiKey });
this.debug = debug;
}
logDebug(message, ...args) {
if (this.debug) {
// eslint-disable-next-line no-console
console.debug(`[Anthropic DEBUG] ${message}`, ...args);
}
}
/**
* Gets a response from the Anthropic Claude model based on the provided text and options.
* @param text - The user's input message.
* @param options - Optional parameters including message history and tags for context.
* @returns A promise that resolves to the model's response as a string.
*/
getResponse(text, options) {
return __awaiter(this, void 0, void 0, function* () {
var _a, _b;
if (!text || typeof text !== 'string') {
throw new Error('Anthropic.getResponse: text must be a non-empty string');
}
if (!options || typeof options !== 'object') {
throw new Error('Anthropic.getResponse: options must be provided as an object');
}
if (!options.llmOptions || typeof options.llmOptions !== 'object') {
throw new Error('Anthropic.getResponse: llmOptions must be provided');
}
try {
this.logDebug('Requesting response', { text, options });
const response = yield this.llm.messages.create({
model: options.llmOptions.model || 'claude-3-5-sonnet-latest',
max_tokens: options.llmOptions.maxTokens || 1000,
system: options.llmOptions.systemPrompt,
messages: [
...(options.history || []),
{ role: 'user', content: text },
// --> Tool calls
...(options.toolCallId && options.toolCall
? [
{ role: 'assistant', content: options.toolCall },
{
role: 'user',
content: [
{
tool_use_id: options.toolCallId,
content: options.toolResult,
type: 'tool_result',
},
],
},
]
: []),
],
temperature: options.llmOptions.temperature || 0.5,
top_p: options.llmOptions.topP || 1,
tools: (_a = options.tools) === null || _a === void 0 ? void 0 : _a.map((tool) => this.parseTool(tool)),
});
this.logDebug('Received response', response);
// Defensive: check response structure
if (!response || typeof response !== 'object') {
throw new Error('Anthropic.getResponse: Invalid response from API');
}
// --> Process tools
if (response.stop_reason === 'pause_turn') {
this.logDebug('stop_reason: pause_turn, retrying...');
return yield this.getResponse(text, Object.assign({}, options));
}
else if (response.stop_reason === 'tool_use') {
const toolCall = response.content;
if (!Array.isArray(toolCall)) {
throw new Error('Anthropic.getResponse: toolCall is not an array');
}
const toolCallContent = toolCall.find((c) => c && c.type === 'tool_use');
if (toolCallContent) {
const tool = (_b = options.tools) === null || _b === void 0 ? void 0 : _b.find((t) => { var _a; return ((_a = t === null || t === void 0 ? void 0 : t.metadata) === null || _a === void 0 ? void 0 : _a.name) === (toolCallContent === null || toolCallContent === void 0 ? void 0 : toolCallContent.name); });
if (!tool) {
this.logDebug('Tool not found for tool_call', toolCallContent);
return 'Tool not found';
}
let result;
try {
result = yield tool.execute(toolCallContent.input);
}
catch (err) {
this.logDebug('Error executing tool', err);
return `Error executing tool: ${err instanceof Error ? err.message : String(err)}`;
}
return yield this.getResponse(text, Object.assign(Object.assign({}, options), { toolCallId: toolCallContent.id, toolCall, toolCallDepth: options.toolCallDepth || 0, toolResult: result }));
}
}
// Defensive: check content structure
if (!Array.isArray(response.content) || response.content.length === 0) {
this.logDebug('No content in response');
return 'No response from the model';
}
if ('text' in response.content[0]) {
return response.content[0].text;
}
this.logDebug('No text in response content');
return 'No response from the model';
}
catch (err) {
this.logDebug('Error in getResponse', err);
return `Anthropic.getResponse error: ${err instanceof Error ? err.message : String(err)}`;
}
});
}
/**
* Streams a response from the Anthropic Claude model based on the provided text and options.
* @param text - The user's input message.
* @param options - Optional parameters including message history and tags for context.
* @returns A promise that resolves to the model's response as a string.
*/
streamResponse(text, options) {
return __asyncGenerator(this, arguments, function* streamResponse_1() {
var _a, e_1, _b, _c;
if (!text || typeof text !== 'string') {
throw new Error('Anthropic.streamResponse: text must be a non-empty string');
}
if (!options || typeof options !== 'object') {
throw new Error('Anthropic.streamResponse: options must be provided as an object');
}
if (!options.llmOptions || typeof options.llmOptions !== 'object') {
throw new Error('Anthropic.streamResponse: llmOptions must be provided');
}
try {
this.logDebug('Requesting stream response', { text, options });
const response = yield __await(this.llm.messages.create({
model: options.llmOptions.model || 'claude-3-5-sonnet-latest',
max_tokens: options.llmOptions.maxTokens || 1000,
system: options.llmOptions.systemPrompt,
messages: [...(options.history || []), { role: 'user', content: text }],
temperature: options.llmOptions.temperature || 0.5,
top_p: options.llmOptions.topP || 1,
stream: true,
}));
try {
for (var _d = true, response_1 = __asyncValues(response), response_1_1; response_1_1 = yield __await(response_1.next()), _a = response_1_1.done, !_a; _d = true) {
_c = response_1_1.value;
_d = false;
const chunk = _c;
if (chunk && typeof chunk === 'object') {
if ('delta' in chunk && chunk.delta && 'text' in chunk.delta) {
yield yield __await(chunk.delta.text);
}
else if ('text' in chunk) {
yield yield __await(chunk.text);
}
}
}
}
catch (e_1_1) { e_1 = { error: e_1_1 }; }
finally {
try {
if (!_d && !_a && (_b = response_1.return)) yield __await(_b.call(response_1));
}
finally { if (e_1) throw e_1.error; }
}
}
catch (err) {
this.logDebug('Error in streamResponse', err);
yield yield __await(`Anthropic.streamResponse error: ${err instanceof Error ? err.message : String(err)}`);
}
});
}
/**
* Gets an embedding from the Anthropic Claude model based on the provided text.
* @param text - The input text to get an embedding for.
* @returns A promise that resolves to the model's embedding as an array of numbers.
*/
getEmbedding(text) {
return __awaiter(this, void 0, void 0, function* () {
var _a, _b;
if (!text || typeof text !== 'string') {
throw new Error('Anthropic.getEmbedding: text must be a non-empty string');
}
try {
this.logDebug('Requesting embedding', { text });
const response = yield this.voyage.embed({
input: text,
model: 'voyage-3',
});
if (!response ||
typeof response !== 'object' ||
!Array.isArray(response.data)) {
throw new Error('Anthropic.getEmbedding: Invalid response from VoyageAI');
}
return ((_b = (_a = response.data) === null || _a === void 0 ? void 0 : _a[0]) === null || _b === void 0 ? void 0 : _b.embedding) || [];
}
catch (err) {
this.logDebug('Error in getEmbedding', err);
return [];
}
});
}
/**
* Parses a tool into an object.
* @param tool - The tool to parse.
* @returns An object representing the tool compatible with the LLM.
*/
parseTool(tool) {
if (!tool || typeof tool !== 'object' || !tool.metadata) {
throw new Error('Anthropic.parseTool: tool must be a valid Tool object');
}
const meta = tool.metadata;
if (!meta.name || !meta.parameters) {
throw new Error('Anthropic.parseTool: tool metadata must have name and parameters');
}
const properties = {};
const required = [];
for (const param of meta.parameters) {
properties[param.name] = {
type: param.type,
description: param.description,
};
if (param.required)
required.push(param.name);
}
return {
name: meta.name,
description: meta.description,
input_schema: {
type: 'object',
properties,
required,
},
};
}
}
exports.Anthropic = Anthropic;
// ===============================