tprompter/dist/llm/LLMService.js

```bash $ ask anything ```

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        step((generator = generator.apply(thisArg, _arguments || [])).next());
    });
};
var LLMService_1;
import { AppConfig } from '../config/AppConfig.js';
import { OpenAIService } from './OpenAIService.js';
import { countTokens } from 'gpt-tokenizer';
import { PromptTooLongError } from './errors/PromptTooLongError.js';
import { Service } from 'typedi';
import { EnvironmentInfo } from '../config/EnvironmentInfo.js';
import { InjectLogger } from '../logger/logger.decorator.js';
let LLMService = LLMService_1 = class LLMService {
    constructor(openAI, config, env, logger) {
        this.openAI = openAI;
        this.config = config;
        this.env = env;
        this.logger = logger;
    }
    getCompletion(prompt, opts) {
        return __awaiter(this, void 0, void 0, function* () {
            var _a, _b;
            this.checkPromptLength(prompt, opts);
            const timeoutId = setTimeout(() => {
                this.logger.info('Request to LLM takes a little bit too long...');
            }, LLMService_1.WARN_DELAY);
            try {
                return yield this.openAI.getCompletion(prompt, {
                    model: (_b = (_a = opts === null || opts === void 0 ? void 0 : opts.model) !== null && _a !== void 0 ? _a : this.config.getConfig().agentDefaultModel) !== null && _b !== void 0 ? _b : 'gpt-4o-mini',
                    developerMessages: opts === null || opts === void 0 ? void 0 : opts.developerMessages,
                });
            }
            finally {
                clearTimeout(timeoutId);
            }
        });
    }
    agent(prompt, mbModel) {
        return __awaiter(this, void 0, void 0, function* () {
            const model = mbModel !== null && mbModel !== void 0 ? mbModel : this.config.getConfig().agentDefaultModel;
            return this.getCompletion(prompt, { model });
        });
    }
    question(prompt, input, model) {
        return __awaiter(this, void 0, void 0, function* () {
            const config = this.config.getConfig();
            const userMessages = [];
            if (input) {
                userMessages.push(`<input from="pipe">${input}</input>`);
            }
            userMessages.push(`<question>${prompt}</question>`);
            return this.getCompletion(userMessages, {
                developerMessages: [
                    'You are helpful CLI tool, that works in a user shell. Be brief, clear and provide a highly structured responses. Your users are skilled developers, who is looking for a quick solution to a problem.',
                    `Your environment: Platform: ${this.env.platform} ${this.env.machine}; Shell: ${this.env.shell}`,
                    `To access the text from the <input> section provided below you can suggest to a user to run \`${config.appName} archive last\` in the shell. Example, \`${config.appName} archive last input | grep "some text"\``,
                ],
                model,
            });
        });
    }
    checkPromptLength(userMessages, opts) {
        var _a, _b;
        let fullMessage = Array.isArray(userMessages) ? userMessages.join(' ') : userMessages;
        fullMessage += (_b = (_a = opts === null || opts === void 0 ? void 0 : opts.developerMessages) === null || _a === void 0 ? void 0 : _a.join(' ').length) !== null && _b !== void 0 ? _b : '';
        const config = this.config.getConfig();
        if (config.agentMaxTokens) {
            const tokenLength = countTokens(fullMessage);
            if (tokenLength > config.agentMaxTokens) {
                throw new PromptTooLongError(tokenLength, config.agentMaxTokens);
            }
        }
    }
    listModels() {
        return __awaiter(this, void 0, void 0, function* () {
            return this.openAI.getSupportedModels();
        });
    }
};
LLMService.WARN_DELAY = 5000;
LLMService = LLMService_1 = __decorate([
    Service(),
    __param(3, InjectLogger()),
    __metadata("design:paramtypes", [OpenAIService,
        AppConfig,
        EnvironmentInfo, Object])
], LLMService);
export { LLMService };