138 lines
3.9 KiB
TypeScript
138 lines
3.9 KiB
TypeScript
import { modelConfigs, shedulerAICharacter } from '../../src/config/aiCharacters';
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import OpenAI from 'openai';
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interface AICharacter {
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id: string;
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name: string;
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tags?: string[];
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}
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interface MessageHistory {
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role: string;
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content: string;
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name: string;
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}
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export async function onRequestPost({ env, request }) {
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try {
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const { message, history, availableAIs } = await request.json();
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const selectedAIs = await scheduleAIResponses(message, history, availableAIs, env);
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return Response.json({
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selectedAIs: selectedAIs
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});
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} catch (error) {
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console.error(error);
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return Response.json(
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{ error: error.message },
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{ status: 500 }
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);
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}
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}
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async function analyzeMessageWithAI(message: string, allTags: string[], env: any, history: MessageHistory[] = []): Promise<string[]> {
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const shedulerAI = shedulerAICharacter(message, allTags);
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const modelConfig = modelConfigs.find(config => config.model === shedulerAI.model);
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const apiKey = env[modelConfig.apiKey];
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if (!apiKey) {
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throw new Error(`${modelConfig.model} 的API密钥未配置`);
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}
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const openai = new OpenAI({
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apiKey: apiKey,
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baseURL: modelConfig.baseURL,
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});
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const prompt = shedulerAI.custom_prompt;
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try {
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const completion = await openai.chat.completions.create({
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model: shedulerAI.model,
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messages: [
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{ role: "user", content: prompt },
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...history.slice(-10), // 添加历史消息
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{ role: "user", content: message }
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],
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});
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const matchedTags = completion.choices[0].message.content?.split(',').map(tag => tag.trim()) || [];
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return matchedTags;
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} catch (error) {
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console.error('AI分析失败:', error);
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return [];
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}
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}
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async function scheduleAIResponses(
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message: string,
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history: MessageHistory[],
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availableAIs: AICharacter[],
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env: any
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): Promise<string[]> {
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// 1. 收集所有可用的标签
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const allTags = new Set<string>();
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availableAIs.forEach(ai => {
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ai.tags?.forEach(tag => allTags.add(tag));
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});
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// 2. 使用AI模型分析消息并匹配标签
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const matchedTags = await analyzeMessageWithAI(message, Array.from(allTags), env, history);
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console.log('matchedTags', matchedTags, allTags);
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//如果含有"文字游戏"标签，则需要全员参与
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if (matchedTags.includes("文字游戏")) {
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return availableAIs.map(ai => ai.id);
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}
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// 3. 计算每个AI的匹配分数
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const aiScores = new Map<string, number>();
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const messageLC = message.toLowerCase();
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for (const ai of availableAIs) {
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if (!ai.tags) continue;
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let score = 0;
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// 标签匹配分数
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matchedTags.forEach(tag => {
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if (ai.tags?.includes(tag)) {
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score += 2; // 每个匹配的标签得2分
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}
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});
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// 直接提到AI名字额外加分
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if (messageLC.includes(ai.name.toLowerCase())) {
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score += 5;
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}
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// 历史对话相关性加分
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const recentHistory = history.slice(-5); // 只看最近5条消息
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recentHistory.forEach(hist => {
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if (hist.name === ai.name && hist.content.length > 0) {
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score += 1; // 最近有参与对话的AI加分
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}
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});
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if (score > 0) {
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aiScores.set(ai.id, score);
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}
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}
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// 4. 根据分数排序选择AI
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const sortedAIs = Array.from(aiScores.entries())
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.sort((a, b) => b[1] - a[1])
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.map(([id]) => id);
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// 5. 如果没有匹配到任何AI，随机选择1-2个
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if (sortedAIs.length === 0) {
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console.log('没有匹配到任何AI，随机选择1-2个');
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const maxResponders = Math.min(2, availableAIs.length);
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const numResponders = Math.floor(Math.random() * maxResponders) + 1;
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const shuffledAIs = [...availableAIs]
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.sort(() => Math.random() - 0.5)
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.slice(0, numResponders);
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return shuffledAIs.map(ai => ai.id);
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}
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// 6. 限制最大回复数量
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const MAX_RESPONDERS = 3;
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return sortedAIs.slice(0, MAX_RESPONDERS);
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}
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