feat(core): compact v2 session context (#30986)
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26 changed files with 569 additions and 296 deletions
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packages/core/src/session/compaction.ts
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packages/core/src/session/compaction.ts
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export * as SessionCompaction from "./compaction"
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import { LLM, LLMError, LLMEvent, Message, type LLMRequest, type Model } from "@opencode-ai/llm"
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import { DateTime, Effect, Stream } from "effect"
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import type { Config } from "../config"
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import type { EventV2 } from "../event"
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import { SessionEvent } from "./event"
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import { SessionMessage } from "./message"
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import { SessionSchema } from "./schema"
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import { Token } from "../util/token"
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const DEFAULT_BUFFER = 20_000
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const DEFAULT_KEEP_TOKENS = 8_000
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const TOOL_OUTPUT_MAX_CHARS = 2_000
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const SUMMARY_OUTPUT_TOKENS = 4_096
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const SUMMARY_TEMPLATE = `Output exactly the Markdown structure shown inside <template> and keep the section order unchanged. Do not include the <template> tags in your response.
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<template>
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## Goal
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- [single-sentence task summary]
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## Constraints & Preferences
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- [user constraints, preferences, specs, or "(none)"]
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## Progress
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### Done
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- [completed work or "(none)"]
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### In Progress
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- [current work or "(none)"]
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### Blocked
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- [blockers or "(none)"]
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## Key Decisions
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- [decision and why, or "(none)"]
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## Next Steps
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- [ordered next actions or "(none)"]
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## Critical Context
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- [important technical facts, errors, open questions, or "(none)"]
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## Relevant Files
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- [file or directory path: why it matters, or "(none)"]
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</template>
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Rules:
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- Keep every section, even when empty.
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- Use terse bullets, not prose paragraphs.
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- Preserve exact file paths, commands, error strings, and identifiers when known.
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- Do not mention the summary process or that context was compacted.`
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type Entry = {
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readonly seq: number
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readonly message: SessionMessage.Message
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}
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type Settings = {
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readonly auto: boolean
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readonly buffer: number
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readonly tokens: number
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}
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type Dependencies = {
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readonly events: EventV2.Interface
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readonly llm: {
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readonly stream: (request: LLMRequest) => Stream.Stream<LLMEvent, LLMError>
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}
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readonly config: readonly Config.Entry[]
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}
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const estimate = (value: unknown) => Token.estimate(JSON.stringify(value))
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const truncate = (value: string) =>
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value.length <= TOOL_OUTPUT_MAX_CHARS ? value : `${value.slice(0, TOOL_OUTPUT_MAX_CHARS)}\n[truncated]`
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const serialize = (message: SessionMessage.Message) => {
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if (message.type === "user") {
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const files = message.files?.map((file) => `[Attached ${file.mime}: ${file.name ?? file.uri}]`) ?? []
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return [`[User]: ${message.text}`, ...files].join("\n")
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}
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if (message.type === "assistant") {
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return message.content
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.flatMap((part) => {
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if (part.type === "text") return [`[Assistant]: ${part.text}`]
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if (part.type === "reasoning") return part.text ? [`[Assistant reasoning]: ${part.text}`] : []
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const input = typeof part.state.input === "string" ? part.state.input : JSON.stringify(part.state.input)
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if (part.state.status === "completed")
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return [
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`[Assistant tool call]: ${part.name}(${input})`,
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`[Tool result]: ${truncate(JSON.stringify(part.state.content))}`,
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]
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if (part.state.status === "error")
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return [`[Assistant tool call]: ${part.name}(${input})`, `[Tool error]: ${part.state.error.message}`]
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return [`[Assistant tool call]: ${part.name}(${input})`]
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})
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.join("\n")
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}
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if (message.type === "system") return `[System update]: ${message.text}`
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if (message.type === "synthetic") return `[Synthetic context]: ${message.text}`
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if (message.type === "shell") return `[Shell]: ${message.command}\n${truncate(message.output)}`
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return ""
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}
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const settings = (documents: readonly Config.Entry[]) => {
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const configured = documents
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.filter((entry): entry is Config.Document => entry.type === "document")
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.flatMap((entry) => (entry.info.compaction ? [entry.info.compaction] : []))
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return configured.reduce<Settings>(
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(result, current) => ({
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auto: current.auto ?? result.auto,
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buffer: current.buffer ?? result.buffer,
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tokens: current.keep?.tokens ?? result.tokens,
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}),
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{ auto: true, buffer: DEFAULT_BUFFER, tokens: DEFAULT_KEEP_TOKENS },
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)
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}
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const select = (
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entries: readonly Entry[],
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tokens: number,
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): { readonly head: string; readonly recent: string } | undefined => {
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const conversation = entries
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.filter((entry) => entry.message.type !== "compaction")
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.map((entry) => serialize(entry.message))
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.filter(Boolean)
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if (conversation.length === 0) return
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let total = 0
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let split = conversation.length
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let splitPrefix = ""
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let splitSuffix = ""
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for (let index = conversation.length - 1; index >= 0; index--) {
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const next = total + Token.estimate(conversation[index])
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if (next > tokens) {
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const remaining = Math.max(0, tokens - total) * 4
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if (remaining > 0) {
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splitPrefix = conversation[index].slice(0, -remaining)
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splitSuffix = conversation[index].slice(-remaining)
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split = index + 1
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}
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break
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}
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total = next
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split = index
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}
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return {
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head: [...conversation.slice(0, split), splitPrefix].filter(Boolean).join("\n\n"),
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recent: [splitSuffix, ...conversation.slice(split)].filter(Boolean).join("\n\n"),
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}
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}
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export const buildPrompt = (input: { readonly previousSummary?: string; readonly context: readonly string[] }) =>
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[
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input.previousSummary
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? `Update the anchored summary below using the conversation history above.\nPreserve still-true details, remove stale details, and merge in the new facts.\n<previous-summary>\n${input.previousSummary}\n</previous-summary>`
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: "Create a new anchored summary from the conversation history.",
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SUMMARY_TEMPLATE,
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...input.context,
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].join("\n\n")
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export const make = (dependencies: Dependencies) => {
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const config = settings(dependencies.config)
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return Effect.fn("SessionCompaction.compactIfNeeded")(function* (input: {
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readonly sessionID: SessionSchema.ID
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readonly entries: readonly Entry[]
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readonly model: Model
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readonly request: LLMRequest
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}) {
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const context = input.model.route.defaults.limits?.context
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if (!config.auto || context === undefined || context <= 0) return false
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const output = input.request.generation?.maxTokens ?? input.model.route.defaults.limits?.output ?? 0
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if (
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estimate({ system: input.request.system, messages: input.request.messages, tools: input.request.tools }) <=
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context - Math.max(output, config.buffer)
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)
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return false
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const selected = select(input.entries, config.tokens)
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const previousSummary = input.entries.find((entry) => entry.message.type === "compaction")?.message
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if (!selected || (selected.head.length === 0 && previousSummary?.type !== "compaction")) return false
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const summaryPrompt = buildPrompt({
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previousSummary: previousSummary?.type === "compaction" ? previousSummary.summary : undefined,
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context: [previousSummary?.type === "compaction" ? previousSummary.recent : "", selected.head].filter(Boolean),
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})
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const summaryOutput = Math.min(output || SUMMARY_OUTPUT_TOKENS, SUMMARY_OUTPUT_TOKENS)
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if (Token.estimate(summaryPrompt) > context - summaryOutput) return false
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const messageID = SessionMessage.ID.create()
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yield* dependencies.events.publish(SessionEvent.Compaction.Started, {
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sessionID: input.sessionID,
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messageID,
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timestamp: yield* DateTime.now,
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reason: "auto",
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})
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const chunks: string[] = []
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yield* dependencies.llm
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.stream(
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LLM.request({
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model: input.model,
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messages: [Message.user(summaryPrompt)],
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tools: [],
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generation: { maxTokens: summaryOutput },
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}),
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)
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.pipe(
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Stream.runForEach((event) => {
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if (!LLMEvent.is.textDelta(event)) return Effect.void
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chunks.push(event.text)
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return Effect.void
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}),
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)
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const summary = chunks.join("")
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if (!summary.trim()) return yield* Effect.die("Compaction returned an empty summary")
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yield* dependencies.events.publish(SessionEvent.Compaction.Ended, {
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sessionID: input.sessionID,
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messageID,
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timestamp: yield* DateTime.now,
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reason: "auto",
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text: summary,
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recent: selected.recent,
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})
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return true
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})
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}
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