56 lines
3.6 KiB
TypeScript
56 lines
3.6 KiB
TypeScript
import { register } from "../engine/registry";
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import { RuntimeError } from "../engine/types";
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import { chatCompletion, requireAiConfig } from "./ai-service";
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function inputText(args: Record<string, unknown>, nodeId: string): string {
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for (const key of ["input", "text", "content", "sentence", "prompt", "sourceFilePath", "filePath", "source", "document"]) {
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const v = String(args[key] ?? "").trim();
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if (v) return v;
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}
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throw new RuntimeError("validation_error", "输入文本为空", { nodeId, componentId: nodeId });
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}
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async function readMaybeFile(value: string): Promise<string> {
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const looksLikeFile = /\.(txt|md|csv|json|log)$/i.test(value) && value.length < 260 && !value.includes("\n");
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if (!looksLikeFile) return value;
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try {
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const fs = await import("node:fs/promises");
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const stat = await fs.stat(value);
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if (stat.isFile()) return await fs.readFile(value, "utf8");
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} catch { /* treat the value as literal text */ }
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return value;
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}
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async function complete(prompt: string, input: string, temperature = 0.3): Promise<string> {
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requireAiConfig();
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return chatCompletion([
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{ role: "system", content: prompt },
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{ role: "user", content: input }
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], { temperature });
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}
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const TEXT_TASKS: Array<{ ids: string[]; system: string; task: string }> = [
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{ ids: ["DataService_AIGenTxt"], system: "你是写作助手，根据用户要求生成高质量中文内容。", task: "AI 生成文本" },
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{ ids: ["DataService_LargeModel", "DataService_ZBrain", "DataService_AgentCall", "NLP_XunFei_NLPBaseServer"], system: "你是智能助手，尽力完成用户的任务。", task: "通用模型调用" },
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{ ids: ["DataService_ChatBot"], system: "你是对话机器人，用中文自然对话。", task: "对话机器人" },
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{ ids: ["DataService_KeyWord", "NLP_KeyWordsAnalysis", "NLP_SplitText"], system: "从文本中提取关键词，输出 JSON 数组（字符串列表），不要输出其他内容。", task: "关键词抽取" },
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{ ids: ["DataService_Correct"], system: "修正文本中的错别字与语病，直接输出修正后的全文。", task: "文本纠错" },
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{ ids: ["DataService_Review"], system: '审核文本内容是否合规，输出 JSON：{\"pass\":true/false,\"reason\":\"原因\"}。', task: "文本审核" },
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{ ids: ["DataService_TextComparison", "Scenario_TextComparison"], system: "比较两段文本差异，输出简明差异摘要。", task: "文档比对" },
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{ ids: ["NLP_SplitWords"], system: '对文本分词，输出 JSON 数组（字符串列表）。', task: "分词" },
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{ ids: ["NLP_EmotionalAnalysis"], system: '分析文本情感倾向，输出 JSON：{\"label\":\"正面/负面/中性\",\"score\":0.99}。', task: "情感分析" },
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{ ids: ["NLP_SemanticSimilarity"], system: '判断两段文本语义相似度，输出 JSON：{\"score\":0.99}（0-1）。输入格式：文本1\n---\n文本2。', task: "语义相似度" },
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{ ids: ["NLP_PerspectiveAnalysis"], system: '分析文本中的观点与立场，输出 JSON：{\"perspectives\":[{\"view\":\"...\",\"stance\":\"支持/反对/中立\"}]}。', task: "观点分析" },
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{ ids: ["NLP_AnalyseProductReview", "NLP_BatchAnalyseProductReview"], system: '分析商品评论，输出 JSON：{\"summary\":\"...\",\"sentiment\":\"...\",\"issues\":[]}。', task: "商品评论分析" },
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];
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for (const task of TEXT_TASKS) {
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register(task.ids, async (ctx, node, args) => {
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const rawInput = inputText(args, node.id);
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const input = await readMaybeFile(rawInput);
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const result = await complete(task.system, input);
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ctx.log(task.task + "完成", "info", node.id);
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return result;
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});
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}
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