108 lines
4.0 KiB
TypeScript
108 lines
4.0 KiB
TypeScript
import {
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askPaper,
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annotatePaper,
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clearPaperAnnotation,
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getPaper,
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listPaperAnnotations,
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readPaperCode,
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searchPapers,
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} from "@companion-ai/alpha-hub/lib";
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import type { ExtensionAPI } from "@mariozechner/pi-coding-agent";
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import { Type } from "@sinclair/typebox";
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function formatText(value: unknown): string {
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if (typeof value === "string") return value;
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return JSON.stringify(value, null, 2);
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}
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export function registerAlphaTools(pi: ExtensionAPI): void {
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pi.registerTool({
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name: "alpha_search",
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label: "Alpha Search",
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description:
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"Search research papers through alphaXiv. Modes: semantic (default, use 2-3 sentence queries), keyword (exact terms), agentic (broad multi-turn retrieval), both, or all.",
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parameters: Type.Object({
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query: Type.String({ description: "Search query." }),
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mode: Type.Optional(
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Type.String({ description: "Search mode: semantic, keyword, both, agentic, or all." }),
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),
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}),
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async execute(_toolCallId, params) {
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const result = await searchPapers(params.query, params.mode?.trim() || "semantic");
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return { content: [{ type: "text", text: formatText(result) }], details: result };
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},
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});
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pi.registerTool({
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name: "alpha_get_paper",
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label: "Alpha Get Paper",
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description: "Fetch a paper's AI-generated report (or raw full text) plus any local annotation.",
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parameters: Type.Object({
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paper: Type.String({ description: "arXiv ID, arXiv URL, or alphaXiv URL." }),
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fullText: Type.Optional(Type.Boolean({ description: "Return raw full text instead of AI report." })),
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}),
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async execute(_toolCallId, params) {
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const result = await getPaper(params.paper, { fullText: params.fullText });
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return { content: [{ type: "text", text: formatText(result) }], details: result };
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},
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});
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pi.registerTool({
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name: "alpha_ask_paper",
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label: "Alpha Ask Paper",
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description: "Ask a targeted question about a paper. Uses AI to analyze the PDF and answer.",
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parameters: Type.Object({
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paper: Type.String({ description: "arXiv ID, arXiv URL, or alphaXiv URL." }),
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question: Type.String({ description: "Question about the paper." }),
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}),
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async execute(_toolCallId, params) {
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const result = await askPaper(params.paper, params.question);
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return { content: [{ type: "text", text: formatText(result) }], details: result };
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},
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});
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pi.registerTool({
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name: "alpha_annotate_paper",
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label: "Alpha Annotate Paper",
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description: "Write or clear a persistent local annotation for a paper.",
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parameters: Type.Object({
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paper: Type.String({ description: "Paper ID (arXiv ID or URL)." }),
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note: Type.Optional(Type.String({ description: "Annotation text. Omit when clear=true." })),
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clear: Type.Optional(Type.Boolean({ description: "Clear the existing annotation." })),
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}),
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async execute(_toolCallId, params) {
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const result = params.clear
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? await clearPaperAnnotation(params.paper)
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: params.note
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? await annotatePaper(params.paper, params.note)
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: (() => { throw new Error("Provide either note or clear=true."); })();
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return { content: [{ type: "text", text: formatText(result) }], details: result };
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},
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});
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pi.registerTool({
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name: "alpha_list_annotations",
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label: "Alpha List Annotations",
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description: "List all persistent local paper annotations.",
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parameters: Type.Object({}),
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async execute() {
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const result = await listPaperAnnotations();
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return { content: [{ type: "text", text: formatText(result) }], details: result };
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},
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});
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pi.registerTool({
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name: "alpha_read_code",
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label: "Alpha Read Code",
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description: "Read files from a paper's GitHub repository. Use '/' for repo overview.",
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parameters: Type.Object({
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githubUrl: Type.String({ description: "GitHub repository URL." }),
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path: Type.Optional(Type.String({ description: "File or directory path. Default: '/'" })),
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}),
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async execute(_toolCallId, params) {
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const result = await readPaperCode(params.githubUrl, params.path?.trim() || "/");
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return { content: [{ type: "text", text: formatText(result) }], details: result };
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},
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});
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}
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