| import fs from "fs"; |
|
|
| const config = JSON.parse(fs.readFileSync('./config.json', 'utf-8')); |
|
|
| |
| const PROVIDERS = { |
| openai: { url: 'https://opencode.ai/zen/v1', keyEnv: 'OPENCODE_ZEN_API_KEY', defaultModel: 'nemotron-3-ultra-free', chatPath: '/chat/completions', fmt: o => ({ model: o.model, messages: o.messages, temperature: 0.7, max_tokens: 16384 }), parse: d => { const c = d.choices?.[0]?.message?.content?.trim(); return c || (d.choices?.[0]?.finish_reason === 'length' ? '[Response truncated]' : '...'); }, auth: k => ({ 'Authorization': 'Bearer ' + k }) }, |
| opencode: { url: 'https://opencode.ai/zen/v1', keyEnv: 'OPENCODE_ZEN_API_KEY', defaultModel: 'nemotron-3-ultra-free', chatPath: '/chat/completions', fmt: o => ({ model: o.model, messages: o.messages, temperature: 0.7, max_tokens: 16384 }), parse: d => { const c = d.choices?.[0]?.message?.content?.trim(); return c || (d.choices?.[0]?.finish_reason === 'length' ? '[Response truncated]' : '...'); }, auth: k => ({ 'Authorization': 'Bearer ' + k }) }, |
| }; |
|
|
| const PHANTOM_LLM_PROVIDER = 'openai'; |
|
|
| function getProvider() { |
| const name = PHANTOM_LLM_PROVIDER || 'openai'; |
| const p = PROVIDERS[name]; |
| if (!p) return PROVIDERS.openai; |
| return p; |
| } |
|
|
| function getKey(p) { |
| if (p.keyEnv) { |
| const k = process.env[p.keyEnv]; |
| if (k) return k; |
| if (config[p.keyEnv]) return config[p.keyEnv]; |
| } |
| return ''; |
| } |
|
|
| const llm = { |
| get provider() { return PHANTOM_LLM_PROVIDER; }, |
| set provider(name) { if (PROVIDERS[name]) PHANTOM_LLM_PROVIDER = name; }, |
| get providers() { return Object.keys(PROVIDERS); }, |
| detectProviders: async () => {}, |
| selectBest: () => {}, |
| get hasLLM() { |
| const p = getProvider(); |
| return !!(p.keyEnv ? getKey(p) : p === PROVIDERS.ollama); |
| }, |
| chat: async function(messages, opts = {}) { |
| const p = getProvider(); |
| const key = getKey(p); |
| if (p.keyEnv && !key) return '[' + PHANTOM_LLM_PROVIDER + '] No API key. Set ' + p.keyEnv + ' env or in config.json'; |
| const model = opts.model || p.defaultModel; |
| console.log('Using model:', model); |
| try { |
| let url = p.url + p.chatPath.replace('{model}', model); |
| const headers = { 'Content-Type': 'application/json', ...p.auth(key) }; |
| const body = JSON.stringify(p.fmt({ model, messages })); |
| const r = await fetch(url, { method: 'POST', headers, body, signal: AbortSignal.timeout(60000) }); |
| if (!r.ok) { const t = await r.text().catch(() => ''); return '[' + r.status + '] ' + t.substring(0, 200); } |
| const d = await r.json(); |
| return p.parse(d) || '...'; |
| } catch (e) { return '[err] ' + e.message; } |
| } |
| }; |
|
|
| const messages = [ |
| { role: 'system', content: 'You are Phantom, a helpful AI assistant. You are concise, knowledgeable, and direct. Answer clearly and accurately.' }, |
| { role: 'user', content: 'what is phantom?' } |
| ]; |
| const response = await llm.chat(messages); |
| console.log('Response:', response); |
