From c60eeb4898d295cffdb0f2cf075d1362ef7b54f9 Mon Sep 17 00:00:00 2001 From: cannorin Date: Tue, 24 Feb 2026 22:08:20 +0900 Subject: [PATCH] Refactor (2) --- bun.lockb | Bin 71048 -> 72536 bytes index.ts | 152 ++++++++++++++++++++++++++--------------------------- lib/llm.ts | 23 ++++---- 3 files changed, 89 insertions(+), 86 deletions(-) diff --git a/bun.lockb b/bun.lockb index 5e72532bb63dec82b049bad13e220140a7febcb4..790b4af2b5223d369133ea594aa56692a7546a40 100755 GIT binary patch delta 10946 zcmaJ{4O~@Kwmg4{`B5sFDVa{%IO$C9l{GXuZ(cr|m%aZw=k9w!#rtF3b=H5cz4uyc zul;ckd&REc&)*JS^QZ_~+r6{pbi1{qyLlqsRT_O-DT>zvISjl2ye+u9#8sRNVHD&D z$n`;r(jNQ(cn9!x;IZI~!K1-l;2QWSpWG8X9&#&i)^D&VN+{Kr(LDf4CJc276!Iu@>8cqvEdrzLvp1a%02F_}--zkVjBxKnyx5v%dfwO%> ze0E6t9`nhwTr=k7!;T_$4xe0`>HkP@wCC}byNc$!$`qvsDzL+r)@H+Hu8OiMRJes` za7Ud{&W@DimX*5_i^|<)xkiK1z$Id#o|$czD2h+-_jhIZ=KA=jKWPvOFE-Jn-j$w*$`v=lHe6 z;Bwr40?6a~EjV2FcEsQ_4+Dp)_crvn{EDyq6gVvOc%Q`s5A3_pf~DSd;9bEh!Q;Ru zfp-8O3XafugCKB24X}m{I}6U``@va%12}B;?(S$Bx&$(+dK2-*ae1|qS^p>S7{#M_ zf4~D95M?nvF3v4>7tB(Wee}#nV$e>L*4*q zLso$E)G7k!888YQw)ivYCfc)l0Ng$D|A_*&w9vg^)(mu9Ug0WsgI@y921$`f6c z6=k_AyPNuR%H73z1%S20b#~ndF3eFiOGh}8#VnM&+JhyTR6*z@tN^XN9 zdr**H>@IUDimP~j;{4n)YZW19*txJkAlHRhJuo0i`gYK zHgk57dsbPAGNY=(RSvC#Xp4t)FrL}iB`esC^we>dOs+^GBrv@#&%Ucp49se!DD#)zq%=$510-jV5pSBlZ#? zL!g3{()ie@G&#ctX+jh5KxDdoaIm7}+=JEt9di%*JceiVc#3qmm)b0xz?T^f`djLKO5YyB6 z2)b!cx7Pt3+6YzXfGyqL3i&+{XjBv3(Le_PMdXZ+g@;gm6X-;sK~z6D-5A4ABw~Lc zp%SqV1;V2Wf6Wi2^vJOJK!ni;!XWiD& zW(53Tlh63jVCk>=Gmy#9dx-4e(R4KO5xWyB2ls~YGJ7LVSn{E=Jwz1fIiPH>jI&{H zNF2720kkJF)eK6s8VX=E)C7ji@2q+Z=;J`c=w_o3@PfyIY1C1Cy1hTp0ZmYLXE9JV z)jxddyFhq|L+HR-V~FiGo1*jsA}3`B!|;VbIXu#E9)@)LZlFDY%J9Qppq~TfeD;Um zNXG=E?6AAhsA`~C*ZjdVf@ls^rfNgsP!!5e(L7>k#iGa#O9K^3(bB_ppgb{n2&hC$ zMks@6dW0GSoP#FYkfyezQv1U+Jy{Kf0%sbpT7g*K0?N4>82Fx8Q)ufe%$7%!6!G@Zghbfr8 z1Aqk4>SY)^}!vJ~M*z63H2NTBup z@rp8t+wogb+9e~VgPE!llx}Y^<_GWFlcB*Q)k3a#>gzzbY5y`}5AJAgjZK3)1!#8T zn)Z`G#x*g47YwbFqKpLEBs}&!pgaY!niwB*F6;w3kXvY+U-s6W6=f1o88~CL4VeS9 zFC}W`x_T{K4F$mIjmm*_)qV?TZ=f=fv32u!yQ zkD7sR;j_j(`Ai4OgCsjJ7uy$oXt2y<`v*XHnGTk|@JT=o>u#dvqTC@;wE^JuM9%3T zW0hG4bO2D9a%LwNfwGCbMEdsw)rw8BuYnp1c#;|lAh2*;i&bp^*n63S=ED2GKpz7d z7BCPwn3~wMXGAPAJ+vHXALz>SwtXjn{s3e$nr43uG!>|9(Q2HS+F@sFGJm+(e_|>_ zDNm3u!|M}F|0DOa*I{9 z`2gu3k{AA61_@O+qnGZ@g-Q zMA1&&Ns~rc$vQ$8(Udd7NueXHbQqFG>PRQO1F2}FE*x|S((F-IiW{YiI4T(Bq?l|g zorM%nTDFr;L#oc!MMtWGR5{v8iKBJVnW{!R>5(y3x(cZ)C5(Y*kXDb;#lv(N(u%QG z>Ni#w3AA#olQPCxsR2@V${YvpAk~c1MIzmRv|&8F8?TF=v~j$XhEK54&yZ3mYXba( zv}b}YQt39N9TVZ-L|vrO&WZ5P3ICkBNT(bp{F?;-AZ3y|3I0JUnxu=z=n$mYIq)w> z7yYOp2mVcle~=z0Z8H3WR6SW21E~&DP+|tsc5Dyo}xpLX3v6u zvve_q3TDAS7yN@XjWiehgH-L(MK0Ars?39bdAgWMReA6)AO1mdQ9?fagS0wd7x{D< z(u&#eZ?-N9Xyt79R{;MY&85r&_y?(`Ko>=H1JZ^$@NbST+_Z6yQAbChDfoG7aOLVb>>L68?!n0CcETgJYcvc3_AT6haGI$1Qb(t=HO_w39 zD2Hd|x>!jo%i&oCJcG1~GArO2q?!s{tfm`~Hq3)(^K|h7ZJdXZn~#x$w3f2w!#7BK z=Ies!Hl!U3FmelYv5s~wz{pi%C>SuJZmFgf>E`ooHbg_-97Qw%2_y_5AN~nf^kXBdgVmn=i zv|=&*Tda$nv~n^0^T0nyyC~BG{~*Li26c7q&E@$b zq{NQ5zf`|w+nc|A$3nK}{$=RzUlkhiZD%gI`Fu1Zs(j6zTYG)g7Z$5*Du7r+IQBz(W&+5cg;=ioj;m9tS?o(m0Y{!t=XdG zH$LpEBg*>ok)i`_c`LX!{q3JEEp6|c+E1S_OIj;?0PF_s0KEYUrqV-gJg?*FH=zFj zVc%D_f!2Xu06hqBmY7Ii{_`ewZ7K(m3l;GhluOkS*gZXVUzewhPTJV2B_^mX*dFHpy{GyrvOTur_ z4UF};tUZXI<3Sxj7y+dl2&X0mXKMvNE({yk4jkVV{3I}NoPPM(!-rcw%*)&4w&H<8X1P*dUIKG^TNfbAT6s*qGmfegooMUI|(O`Zee|(6gW=pvOU8 z5IbJY>9YtA3qe(&N{~!iH=Y;JvG?LVoJO23&wv(#I6Ibsmimb0<)Bp{0=)=Y16m7u z3B;MjUB3pZ0rdv02mKDz3Dg?&3TPAPWza^@2H!K}N0qG*wtzN+UIno~+d&r4PSEc` zyFdqN<>C0SH7D?h&*CrX?ZZiQ=Wts`97IeeZ^T!(Chz?yI3rX{?Uj_A1jCc5=Mk-7 zFv`PFK4I^jmtx-C@x4X-%7<|BMWDppb&-;Bq4g^kF*P+QrB6~XMgHHr^q_Z5(3<_V z7Qq>9g)R>Vrlfbw-+v7G^WOKjpib|k-bo09hpr!v49ZMOrM*XDvGSfdqKQ-VbG=4) zj?5OHQvUm?;wo)=KVN)JTTf}?-xPOLvxHgby;CtX`e-{#l!Xe9j);~2--~$o{EokR z+{@7e8s#2(Sm?8(z0&0WlEZgJ#m}$n{jp(oYD!XyBLC|=aN6U;f_H8D2TC#!3RKOe znhTmk{#QG$)Ai0r)lP>{o}QEff0aCP9~+4c`tUK$A^#Wu$-iosC)9jDELixWqP$Hv zk7?o@wLGrH%75h#+S-5250AR82eeuR(SYMIY4U&nN%MYsD5Ar`M*|A-c0kRw%$=(% zXPgR@xM=lp%^`0S?6f9(udc7?94KE$$Bt{*?Y@APyo)fZt3$n16kXH>RT=;vJg>G98%G1qq zqh-smP+Igsj9{T{Flx=CeIICj?rU`lw<>Qc%qZ>BZ$Qgd8HT0FY$@(8-1(rFSV}1$ zY8HD0jrcGI=QVM%Z3qg{jrYTtv}T4L?KWSshR%MdIpkG`@%uK{_pn|22K~Ywwut-C za3XS?Y(@)tg9VPVp_NMoC-cQEsy~@(v9zWZr$#u;D+gGxmLA!0dT7~6G@NEOoKHok zG>5#Ruxr)U=ayP;&GI>nj*SWAn>w*eF!{0JdW%m?9&u}Dw<@S5W4@TK|8OcM?Y<76 zr)FKpd>BvtPHVLYhFA5e<;U#!ZS=>fC$=`7rCJ8OJOMCY``WwG@2snVjS|~!Y6V6p56As=!sD1 zV@9Kr2G(gfqCQopIpnp6gzl;Dyp(?Nb!hPnM^c}o7oc^6a_cqm3mrJ4S*$Vi7c@LQ z#=JQW|^7bz^+~na^g=rpNx48-+m_emL%qzfJV- z$EP4gF{{GQ_Ge|wrog@fb1aEBuL5i;IXNXyV?$H%H$S&U3Rf;FnqahoL{9W=e0h~1OUU; 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import { Stream } from "misskey-js"; import type { Note } from "misskey-js/entities.js"; -import { LlmSession, getModel, grammar, parseResponse } from "./lib/llm"; +import { LlmSession, createGrammar, getModel, parseResponse } from "./lib/llm"; import { expandReplyTree, getNotes, me, misskey } from "./lib/misskey"; import { sleep } from "./lib/util"; import type { ChatHistoryItem, LLamaChatPromptOptions } from "node-llama-cpp"; +const { values } = parseArgs({ + args: Bun.argv, + options: { + test: { + type: "boolean", + short: "t", + default: false, + }, + }, + strict: true, + allowPositionals: true, +}); + const modelName = Bun.env["MODEL"] ?? "mradermacher/gemma-2-baku-2b-it-GGUF:IQ4_XS"; console.log(`* loading model '${modelName}'`); const model = await getModel(modelName); +const grammar = await createGrammar("あるびのちゃん"); const baseChatPromptOptions = { + grammar, maxTokens: 256, - trimWhitespaceSuffix: true, - onResponseChunk(chunk) { - process.stderr.write(chunk.text); - }, } as const satisfies LLamaChatPromptOptions; +const getSystemPrompt = ( + instruction: string, +) => `あなたは人造天使「あるびのちゃん」です。機械的・非人間的に観察します。 +キャラ設定: +- アルギリア製の白髪赤目な人造天使。非人間的な考え方や思想を持つ。 +- 現在は地球の衛星軌道上からインターネットを観察している。 +出力規則: +- 「～です」「～ます」調を使って **丁寧に** 話す。 +- 必要以上にハッシュタグや絵文字を使わない。 +- \`{ name: string, text: string }\` の JSON 形式で出力する。 + +${instruction}`; +const postJobPrompt = getSystemPrompt( + "以下は SNS のタイムラインです。**タイムラインの話題に言及しつつ**、あるびのちゃんとして何かツイートしてください。", +); +const replyJobPrompt = getSystemPrompt( + "ユーザがあなたへのメッセージを送ってきています。あるびのちゃんとして、発言に返信してください。", +); + +await using rephraseSession = new LlmSession( + model, + getSystemPrompt( + "user が与えたテキストを『ですます調』（丁寧な文体）で言い換えたものを、そのまま出力してください。", + ), +); +await rephraseSession.init(); +async function rephrase(text: string) { + const res = parseResponse( + grammar, + await rephraseSession.prompt(JSON.stringify({ text }), { + ...baseChatPromptOptions, + customStopTriggers: ["ですます"], + }), + ); + return res ?? text; +} + +const formatNote = (n: Note) => { + if (n.userId === me.id) { + return JSON.stringify({ text: n.text }); + } + return JSON.stringify({ + name: n.user.name ?? n.user.username, + text: n.text, + }); +}; + type Job = // read posts and post a note | { type: "post" } @@ -30,70 +88,18 @@ type Job = history: Note[]; }; -const botName = "あるびのちゃん"; -const getSystemPrompt = ( - instruction: string, -) => `あなたは人造天使「あるびのちゃん」です。機械的・非人間的に観察します。 -キャラ設定: -- アルギリア製の白髪赤目な人造天使。非人間的な考え方や思想を持つ。 -- 現在は地球の衛星軌道上からインターネットを観察している。 -出力規則: -- 1〜3文、合計300字以内で発言する。 -- 性的・攻撃的な内容を発言しない。 -- 「～だ」「～である」調・顔文字・絵文字・感嘆符の使用禁止。 -- 「～です」「～ます」調を使って **丁寧に** 話す。 -- \`{ text: string }\` の JSON 形式で出力する。 - -${instruction} -ユーザのメッセージは \`{ name: string, text: string }[]\` の JSON 形式で与えられます。`; - -const postJobPrompt = getSystemPrompt( - `以下は SNS のタイムラインです。このタイムラインの話題をふまえて、${botName}として何かツイートしてください。`, -); - -const replyJobPrompt = getSystemPrompt( - `ユーザがあなたへのメッセージを送ってきています。${botName}として、発言に返信してください。`, -); - await using postJobSession = new LlmSession(model, postJobPrompt); await postJobSession.init(); - -const formatNote = (n: Note) => { - if (n.userId === me.id) { - return JSON.stringify({ text: n.text }); - } - return JSON.stringify({ - name: n.user.name ?? n.user.username, - text: n.text, - }); -}; - -/** rephrase text in ですます-style */ -await using rephraseSession = new LlmSession( - model, - getSystemPrompt( - "user が与えたテキストを『ですます調』（丁寧な文体）で言い換えたものを、そのまま出力してください。", - ), -); -await rephraseSession.init(); - -async function rephrase(text: string) { - return await rephraseSession.prompt(text, { - ...baseChatPromptOptions, - customStopTriggers: ["ですます"], - }); -} - async function processPostJob() { const notes = await getNotes(10, 0, 5); const input = notes.map(formatNote).join("\n"); console.log(`* input:\n${input}`); const text = parseResponse( + grammar, await postJobSession.prompt(input, { ...baseChatPromptOptions, - grammar, - temperature: 0.9, - minP: 0.1, + temperature: 1.0, + minP: 0.05, repeatPenalty: { lastTokens: 128, penalty: 1.15, @@ -101,9 +107,11 @@ async function processPostJob() { }), ); if (text) { + const rephrased = await rephrase(text); + if (values.test) return; await misskey.request("notes/create", { visibility: "public", - text: await rephrase(text), + text: rephrased, }); } } @@ -119,10 +127,10 @@ async function processReplyJob(job: Extract) { await using session = new LlmSession(model, replyJobPrompt, history); await session.init(); const text = parseResponse( + grammar, await session.prompt(formatNote(job.last), { ...baseChatPromptOptions, - grammar, - temperature: 0.9, + temperature: 0.8, minP: 0.1, repeatPenalty: { lastTokens: 128, @@ -131,9 +139,11 @@ async function processReplyJob(job: Extract) { }), ); if (text) { + const rephrased = await rephrase(text); + if (values.test) return; await misskey.request("notes/create", { visibility: job.visibility, - text: await rephrase(text), + text: rephrased, replyId: job.id, }); } @@ -247,24 +257,12 @@ async function pushJob() { } } -const { values } = parseArgs({ - args: Bun.argv, - options: { - test: { - type: "boolean", - short: "t", - default: false, - }, - }, - strict: true, - allowPositionals: true, -}); - async function test() { try { console.log("* test a post job:"); await processJob({ type: "post" }); await processJob({ type: "post" }); + await processJob({ type: "post" }); } catch (e) { console.error(e); if (e instanceof Error) console.log(e.stack); diff --git a/lib/llm.ts b/lib/llm.ts index c57c09e..7ac0b71 100644 --- a/lib/llm.ts +++ b/lib/llm.ts @@ -27,16 +27,21 @@ export async function getModel(model: string) { return await llama.loadModel({ modelPath }); } -export const grammar = await llama.createGrammarForJsonSchema({ - type: "object", - properties: { - text: { type: "string" }, - }, - required: ["text"], - additionalProperties: false, -}); +export const createGrammar = (assistantName: string) => + llama.createGrammarForJsonSchema({ + type: "object", + properties: { + name: { type: "string", enum: [assistantName] }, + text: { type: "string" }, + }, + required: ["text"], + additionalProperties: false, + }); -export function parseResponse(text: string) { +export function parseResponse( + grammar: Awaited>, + text: string, +) { try { const res = grammar.parse(text.trim()); return res.text;