Santhosh Janardhanan
a12afb792e
- SvelteKit project scaffolded with TypeScript - Type definitions for Style, StyleCategory, ConversionRequest, ConversionResponse, LLMConfig - Style definitions with 6 categories and 25 sub-styles - Intensity mapping (1-5) with prompt modifier placeholders - LLM client using OpenAI-compatible API (Ollama default) - POST /api/convert endpoint with input validation - Animated loading modal with per-letter animations - Main page UI with category/style selectors, intensity slider - Copy to clipboard, collapsible prompt display - Vitest tests for styles, LLM prompt building, and API validation - Environment configuration for LLM settings
77 lines
2.1 KiB
TypeScript
77 lines
2.1 KiB
TypeScript
import { env } from '$env/dynamic/private';
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import type { LLMConfig } from './types';
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const DEFAULT_CONFIG: LLMConfig = {
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baseUrl: 'http://localhost:11434/v1',
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apiKey: 'ollama',
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model: 'llama3'
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};
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function getConfig(): LLMConfig {
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return {
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baseUrl: env.OPENAI_BASE_URL || DEFAULT_CONFIG.baseUrl,
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apiKey: env.OPENAI_API_KEY || DEFAULT_CONFIG.apiKey,
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model: env.OPENAI_MODEL || DEFAULT_CONFIG.model
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};
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}
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export interface ConvertResult {
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converted: string;
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systemPrompt: string;
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userMessage: string;
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}
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export function buildSystemPrompt(styleModifier: string, intensityInstruction: string): string {
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const intensityFilled = intensityInstruction.replace('{style}', styleModifier);
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return `You are an expert English style converter.
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${intensityFilled}.
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${styleModifier}
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Preserve the core meaning but fully transform the voice and tone.
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Output ONLY the converted text — no explanations, no labels, no quotes.`;
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}
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export function buildUserMessage(text: string): string {
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return text;
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}
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export async function convertText(
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text: string,
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styleModifier: string,
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intensityInstruction: string,
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overrides?: Partial<LLMConfig>
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): Promise<ConvertResult> {
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const merged: LLMConfig = { ...DEFAULT_CONFIG, ...getConfig(), ...overrides };
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const systemPrompt = buildSystemPrompt(styleModifier, intensityInstruction);
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const userMessage = buildUserMessage(text);
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const response = await fetch(`${merged.baseUrl}/chat/completions`, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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Authorization: `Bearer ${merged.apiKey}`
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},
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body: JSON.stringify({
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model: merged.model,
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messages: [
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{ role: 'system', content: systemPrompt },
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{ role: 'user', content: userMessage }
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],
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temperature: 0.8
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})
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});
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if (!response.ok) {
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const errorText = await response.text().catch(() => 'Unknown error');
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throw new Error(`LLM request failed (${response.status}): ${errorText}`);
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}
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const data = await response.json();
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const converted = data.choices?.[0]?.message?.content?.trim();
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if (!converted) {
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throw new Error('LLM returned empty response');
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}
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return { converted, systemPrompt, userMessage };
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} |