quivr-typechat
Version:
A TypeChatLanguageModel compatible with Quivr API to run TpeChat on your own Quivr istance with the possibility of using a private LLM
90 lines (89 loc) • 4.51 kB
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());
});
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.createQuivrLanguageModelExplicit = exports.createQuivrLanguageModel = void 0;
const typechat_1 = require("typechat");
const axios_1 = require("axios");
const axiosConfig = { validateStatus: status => true };
const defaultQuivrModelConfig = {
endpoint: "https://api.quivr.app",
model: "gpt-3.5-turbo-0613",
max_tokens: 256
};
/**
* Creates a language model encapsulation of a Quivr REST API from environnement variables.
* @param env Envirement variables
* @param additionalConfig The additionnal configuration for the QuivrLanguageModel :
* endpoint: API endpoint for Quivr. Defaults to https://api.quivr.app
* model: Model to use in the Quivr instance. Defaults to gpt-3.5-turbo-0613
* max_tokens: Maximum tokens. Defaults to 250
*/
function createQuivrLanguageModel(env, additionalConfig) {
if (env.QUIVR_API_KEY) {
if (env.QUIVR_BRAIN_ID) {
return (0, exports.createQuivrLanguageModelExplicit)(env.QUIVR_API_KEY, env.QUIVR_BRAIN, Object.assign(Object.assign({}, defaultQuivrModelConfig), (additionalConfig !== null && additionalConfig !== void 0 ? additionalConfig : {})));
}
else
throw new Error(`"Missing environment variable: QUIVR_BRAIN`);
}
else
throw new Error(`"Missing environment variable: QUIVR_API_KEY`);
}
exports.createQuivrLanguageModel = createQuivrLanguageModel;
/**
* Creates a language model encapsulation of a Quivr REST API endpoint with parameters.
* @param apiKey The Quivr API key.
* @param brain_id The brain to use for this model
* @param options The additionnal configuration for the QuivrLanguageModel :
* endpoint: API endpoint for Quivr. Defaults to https://api.quivr.app
* model: Model to use in the Quivr instance. Defaults to gpt-3.5-turbo-0613
* max_tokens: Maximum tokens. Defaults to 250
*/
const createQuivrLanguageModelExplicit = (apiKey, brain_id, options) => {
const { endpoint, model, max_tokens } = options;
const client = axios_1.default.create({
headers: {
Authorization: `Bearer ${apiKey}`,
"user-agent": "quivr-typechat",
}
});
return {
complete
};
function complete(question) {
return __awaiter(this, void 0, void 0, function* () {
console.log(`Calling Quivr instance ${endpoint} using brain_id ${brain_id}`, options);
const chatParams = {
model,
max_tokens,
temperature: 0,
question
};
const newChatName = `Typechat ${Date.now()} - ${Math.round(Math.random() * 10)}`;
const result = yield client.post(`${endpoint}/chat`, {
name: newChatName
}, axiosConfig);
if (result.status === 200) {
const chat_id = result.data.chat_id;
console.log("Created new chat on Quivr ", result.data.chat_id);
const resultChatQuestion = yield client.post(`${endpoint}/chat/${chat_id}/question?brain_id=${brain_id}`, chatParams, axiosConfig);
if (resultChatQuestion.status === 200) {
console.log("Result: ", resultChatQuestion.data.assistant);
return (0, typechat_1.success)(resultChatQuestion.data.assistant);
}
else
return (0, typechat_1.error)(`Quivr API Error on question ${resultChatQuestion.status}: ${resultChatQuestion.statusText}`);
}
return (0, typechat_1.error)(`Quivr API Error on creating chat ${result.status}: ${result.statusText}`);
});
}
};
exports.createQuivrLanguageModelExplicit = createQuivrLanguageModelExplicit;