llama-flow
Version:
The Typescript-first prompt engineering toolkit for working with chat based LLMs.
37 lines (36 loc) • 1.8 kB
JavaScript
;
var __importDefault = (this && this.__importDefault) || function (mod) {
return (mod && mod.__esModule) ? mod : { "default": mod };
};
Object.defineProperty(exports, "__esModule", { value: true });
const lodash_1 = require("lodash");
const zod_1 = require("zod");
const json_1 = __importDefault(require("./json"));
function buildRawPrompt(prompt) {
const arraySchema = zod_1.z.array(prompt.length
? zod_1.z
.string()
.max(prompt.length, `Each bullet point should be less than ${prompt.length} characters, including white spaces.`)
: zod_1.z.string());
const formatMessages = (0, lodash_1.compact)([
"Respond to the prompt below in bullet points, where each bullet point starts with the - character. Don't include any other text other than the bullet points.",
prompt.length
? `Each bullet point should be less than ${prompt.length} characters long, including white spaces.`
: undefined,
prompt.amount
? `There should be exactly ${prompt.amount} bullet points, no more or less.`
: undefined,
]);
return (0, json_1.default)({
message: `${formatMessages.join(' ')}\n\n${prompt.message}`,
parseResponse: (res) => res
.split('\n')
.filter((s) => s.includes('-'))
.map((s) => s.replace('-', '').trim()),
schema: prompt.amount
? arraySchema.length(prompt.amount, `There should be exactly ${prompt.amount} bullet points, no more or less.`)
: arraySchema,
retryMessage: "Respond to the prompt above in bullet points, where each bullet point starts with the - character. Don't include any other text other than the bullet points.",
});
}
exports.default = buildRawPrompt;