77 lines
2.4 KiB
TypeScript
77 lines
2.4 KiB
TypeScript
import type { ChatMessage } from "../llm/types";
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/** Detect messages that already embed full paper dumps (should not be in UI history). */
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export function isPaperDump(content: string): boolean {
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return (
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content.includes("【论文正文】") ||
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content.includes("【论文 1】") ||
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content.startsWith("【论文元数据】") ||
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content.startsWith("已收到论文内容") ||
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content.includes("【说明】以上为本次会话的论文材料")
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);
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}
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/**
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* Keep short Q&A turns for the model. Truncate very long assistant replies
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* so paper context + latest question are less likely to be dropped.
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*/
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export function sanitizeChatHistory(
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history: ChatMessage[],
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options?: { maxMessages?: number; maxAssistantChars?: number },
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): ChatMessage[] {
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const maxMessages = options?.maxMessages ?? 10;
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const maxAssistantChars = options?.maxAssistantChars ?? 5000;
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const cleaned = history
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.filter((m) => m.role === "user" || m.role === "assistant")
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.filter((m) => !isPaperDump(m.content))
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.map((m) => {
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if (
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m.role === "assistant" &&
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m.content &&
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m.content.length > maxAssistantChars
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) {
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return {
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...m,
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content:
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m.content.slice(0, maxAssistantChars) +
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"\n\n…（为保留论文上下文，历史回复已截断）",
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};
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}
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return m;
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});
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return cleaned.slice(-maxMessages);
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}
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/**
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* Pin paper corpus near the start of the request, then prior Q&A, then the
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* current task. Avoids stuffing full papers only into the latest message
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* (which providers often truncate under context pressure on turn 2+).
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*/
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export function assemblePaperChatMessages(options: {
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system: string;
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paperBlock: string;
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taskBlock: string;
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history: ChatMessage[];
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}): ChatMessage[] {
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const messages: ChatMessage[] = [
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{ role: "system", content: options.system },
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{
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role: "user",
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content: `${options.paperBlock}
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【说明】以上为本次会话的论文材料。后续所有问题与分析任务均基于这些论文；无需用户再次提供全文或文本。`,
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},
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{
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role: "assistant",
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content:
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"已收到并理解以上论文材料。请继续提问或下达分析任务，我将基于这些论文作答，不会要求你再次提供全文。",
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},
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];
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messages.push(...sanitizeChatHistory(options.history));
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messages.push({ role: "user", content: options.taskBlock });
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return messages;
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}
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