39 lines
1.3 KiB
JavaScript
39 lines
1.3 KiB
JavaScript
const fs = require("fs");
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const path = "D:\\q\\Bailongma\\orchestrator-v2\\debate\\llm.js";
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const content = `// ============================================================
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// LLM 调用工具 — 独立于 agent-worker，直接 fetch API
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// ============================================================
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const BASE_URL = (process.env.LLM_BASE_URL || process.env.OPENAI_BASE_URL || "https://api.openai.com/v1").replace(/\\/+$/, "");
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const MODEL = process.env.LLM_MODEL || process.env.OPENAI_MODEL || "gpt-4o";
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const API_KEY = process.env.LLM_API_KEY || process.env.OPENAI_API_KEY || "";
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async function callLLM({ messages, model, maxTokens, temperature }) {
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const url = BASE_URL + "/chat/completions";
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const body = {
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model: model || MODEL,
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messages: messages,
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max_tokens: maxTokens || 2048,
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temperature: temperature ?? 0.7
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};
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const resp = await fetch(url, {
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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 " + API_KEY
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},
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body: JSON.stringify(body)
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});
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if (!resp.ok) {
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const errText = await resp.text().catch(() => "");
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throw new Error("LLM " + resp.status + ": " + errText.slice(0, 200));
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}
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return await resp.json();
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}
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module.exports = { callLLM };
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`;
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fs.writeFileSync(path, content.trim(), "utf8");
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console.log("llm.js written, bytes: " + content.length);
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