feat: per-model max output tokens and a conversation-time thinking level backed by agent settings (#28)
Co-authored-by: Alice <alice@prismshadow.com> Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
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/**
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* Session title generation: an **out-of-band, one-off request** that generates
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* a short title from the first-turn conversation text (used by `Session.generateTitle`
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* for assembly, not exported wholesale via the barrel).
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*
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* Called by `session.generateTitle()`: sends one request using the bare LLM for the session's
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* Model (no tools, no system prompt, thinking off), without writing history or Trace. Material
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* defaults to what the Session self-captures during run (see session.ts); this module is only
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* responsible for the prompt format, driving the one-off request, and sanitizing the result —
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* when to generate a title and where to store it is decided by the host (Web server / CLI).
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* The narrow public surface — `SessionTitleResult` (part of `Session.generateTitle`'s
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* signature) and the sanitation helpers the host's title fallback builds on — is re-exported
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* by the barrel; the prompt/request internals are not.
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*/
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import { userText } from "../omnimessage/index.js";
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import type {
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OmniMessage,
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TextPayload,
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TokenCounts,
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TokenUsagePayload,
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} from "../omnimessage/index.js";
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import type { LLMInterface } from "../interfaces.js";
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/** Cap on conversation text spliced into the title request (user/model each truncated separately, to control cost). */
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const EXCERPT_MAX_CHARS = 2000;
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/** Cap on title length (fallback truncation for when the model occasionally ignores the constraint). */
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const TITLE_MAX_CHARS = 30;
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/**
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* Special message markers that must never leak into a title. These are machine-inserted
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* XML-ish blocks (a skill invocation wraps the body in `<use_skills>…</use_skills>`, a
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* subagent handoff / scheduled task prepend their own blocks) — meaningful to the runtime,
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* noise in a title. The list is a fixed allowlist so ordinary angle-bracket text (e.g. a
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* user pasting `<div>`) is left untouched.
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*/
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const MARKER_TAGS = ["use_skills", "handoff_from", "scheduled_task"];
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/**
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* Strips machine-inserted marker blocks (see MARKER_TAGS) from conversation text so titles are
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* built from the human-meaningful body only — both the material sent to the model and the
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* fallback derived from the raw first message. Removes the paired `<tag>…</tag>` block (any
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* inner content, across lines) and any stray unpaired `<tag>` / `</tag>` left behind.
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*/
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export function stripConversationMarkers(text: string): string {
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let out = text;
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for (const tag of MARKER_TAGS) {
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out = out
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.replace(new RegExp(`<${tag}>[\\s\\S]*?</${tag}>`, "g"), "")
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.replace(new RegExp(`</?${tag}>`, "g"), "");
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}
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return out.trim();
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}
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export interface SessionTitleResult {
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/** The sanitized title; null when material is insufficient, the request fails, or the output is empty. */
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title: string | null;
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/** Token consumption for this request (accumulated token_usage.request); null if no request occurred or there's no usage. */
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usage: TokenCounts | null;
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}
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/**
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* Assembles the title-generation Prompt (exported for host/test assertion use). Uses English
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* instructions to avoid polluting the title's language, and requires the **title to be in the
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* same language as the conversation** (English conversation gets an English title, Chinese
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* conversation gets a Chinese title); when assistant material is empty, it relies on the user
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* request alone.
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*/
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export function buildTitlePrompt(userExcerpt: string, assistantExcerpt: string): string {
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const clip = (s: string) => (s.length > EXCERPT_MAX_CHARS ? s.slice(0, EXCERPT_MAX_CHARS) : s);
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const lines = [
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"Generate a concise title for the conversation below.",
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"Rules:",
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"- Write the title in the SAME language the user is using.",
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"- Keep it short: at most 6 words, or ~16 characters for CJK.",
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"- Output ONLY the title text — no quotes, no trailing punctuation, no explanation.",
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"- Answer immediately — do not think aloud or produce chain-of-thought.",
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"",
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"[User]",
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clip(userExcerpt),
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];
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if (assistantExcerpt.trim()) {
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lines.push("", "[Assistant]", clip(assistantExcerpt));
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}
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// The trailing empty think block makes many reasoning models treat their thinking phase
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// as already closed, so the one-off request spends its budget on the title itself.
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lines.push("", "<think></think>");
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return lines.join("\n");
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}
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/** Sanitizes model output into a title: strips any leaked marker blocks and leading/trailing quotes/brackets and trailing punctuation (until stable), collapses whitespace, and truncates if too long; returns null for an empty result. */
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export function sanitizeTitle(raw: string): string | null {
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let t = stripConversationMarkers(raw).replace(/\s+/g, " ").trim();
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// Stripping quotes can expose more punctuation underneath (or vice versa), so strip repeatedly until stable.
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for (let prev = ""; prev !== t;) {
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prev = t;
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t = t
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.replace(/^["'“”‘’「」『』《》〈〉【】()()\s]+/, "")
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.replace(/["'“”‘’「」『』《》〈〉【】()()\s]+$/, "")
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.replace(/[。..!!??;;,,、::]+$/, "")
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.trim();
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}
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if (!t) return null;
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return t.length > TITLE_MAX_CHARS ? t.slice(0, TITLE_MAX_CHARS) : t;
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}
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/**
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* Drives a single title-generation request: collects model text and token_usage, and resolves
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* based on the outcome. Generation only requires user material (assistant material may be
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* empty — a pure tool-only turn can still get a title); no request is sent if user material is
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* empty; `title` is null if the request doesn't complete (any usage already produced is still
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* returned).
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*/
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export async function generateTitleWithLLM(
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llm: LLMInterface,
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args: { userText: string; assistantText: string; signal?: AbortSignal },
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): Promise<SessionTitleResult> {
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// Strip machine markers before the model ever sees the material, so a skill-invocation
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// block (or handoff / scheduled-task marker) can't bleed into the generated title.
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const userMaterial = stripConversationMarkers(args.userText);
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const assistantMaterial = stripConversationMarkers(args.assistantText);
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if (!userMaterial.trim()) {
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return { title: null, usage: null };
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}
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const prompt = buildTitlePrompt(userMaterial, assistantMaterial);
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const gen = llm.streamGenerate({
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newMessages: [userText(prompt)],
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...(args.signal ? { signal: args.signal } : {}),
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});
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let collected = "";
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let usage: TokenCounts | null = null;
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for (;;) {
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const step = await gen.next();
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if (step.done) {
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if (step.value.status !== "completed") return { title: null, usage };
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break;
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}
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const msg = step.value;
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if (isAssistantText(msg)) collected += msg.payload.text;
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if (isTokenUsage(msg)) {
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const r = msg.payload.request;
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usage = usage
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? {
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cache_read: usage.cache_read + r.cache_read,
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cache_write: usage.cache_write + r.cache_write,
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output: usage.output + r.output,
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total: usage.total + r.total,
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}
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: { ...r };
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}
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}
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return { title: sanitizeTitle(collected), usage };
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}
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function isAssistantText(msg: OmniMessage): msg is OmniMessage<TextPayload> {
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const payload = msg.payload as { type?: string; role?: string };
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return msg.type === "model_msg" && payload.type === "text" && payload.role === "assistant";
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}
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function isTokenUsage(msg: OmniMessage): msg is OmniMessage<TokenUsagePayload> {
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return msg.type === "event_msg" && (msg.payload as { type?: string }).type === "token_usage";
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}
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