import { generateText, type ModelMessage } from "ai" import { Session } from "." import { Identifier } from "../id/id" import { Instance } from "../project/instance" import { Provider } from "../provider/provider" import { defer } from "../util/defer" import { MessageV2 } from "./message-v2" import { SystemPrompt } from "./system" import { Bus } from "../bus" import z from "zod/v4" import type { ModelsDev } from "../provider/models" import { SessionPrompt } from "./prompt" import { Flag } from "../flag/flag" import { Token } from "../util/token" import { Log } from "../util/log" export namespace SessionCompaction { const log = Log.create({ service: "session.compaction" }) export const Event = { Compacted: Bus.event( "session.compacted", z.object({ sessionID: z.string(), }), ), } export function isOverflow(input: { tokens: MessageV2.Assistant["tokens"]; model: ModelsDev.Model }) { if (Flag.OPENCODE_DISABLE_AUTOCOMPACT) return false const context = input.model.limit.context if (context === 0) return false const count = input.tokens.input + input.tokens.cache.read + input.tokens.output const output = Math.min(input.model.limit.output, SessionPrompt.OUTPUT_TOKEN_MAX) || SessionPrompt.OUTPUT_TOKEN_MAX const usable = context - output return count > usable } export const PRUNE_MINIMUM = 20_000 export const PRUNE_PROTECT = 40_000 // goes backwards through parts until there are 40_000 tokens worth of tool // calls. then erases output of previous tool calls. idea is to throw away old // tool calls that are no longer relevant. export async function prune(input: { sessionID: string }) { if (Flag.OPENCODE_DISABLE_PRUNE) return log.info("pruning") const msgs = await Session.messages(input.sessionID) let total = 0 let pruned = 0 const toPrune = [] let turns = 0 loop: for (let msgIndex = msgs.length - 1; msgIndex >= 0; msgIndex--) { const msg = msgs[msgIndex] if (msg.info.role === "user") turns++ if (turns < 2) continue if (msg.info.role === "assistant" && msg.info.summary) break loop for (let partIndex = msg.parts.length - 1; partIndex >= 0; partIndex--) { const part = msg.parts[partIndex] if (part.type === "tool") if (part.state.status === "completed") { if (part.state.time.compacted) break loop const estimate = Token.estimate(part.state.output) total += estimate if (total > PRUNE_PROTECT) { pruned += estimate toPrune.push(part) } } } } log.info("found", { pruned, total }) if (pruned > PRUNE_MINIMUM) { for (const part of toPrune) { if (part.state.status === "completed") { part.state.time.compacted = Date.now() await Session.updatePart(part) } } log.info("pruned", { count: toPrune.length }) } } export async function run(input: { sessionID: string; providerID: string; modelID: string }) { await Session.update(input.sessionID, (draft) => { draft.time.compacting = Date.now() }) await using _ = defer(async () => { await Session.update(input.sessionID, (draft) => { draft.time.compacting = undefined }) }) const toSummarize = await Session.messages(input.sessionID).then(MessageV2.filterSummarized) const model = await Provider.getModel(input.providerID, input.modelID) const system = [ ...SystemPrompt.summarize(model.providerID), ...(await SystemPrompt.environment()), ...(await SystemPrompt.custom()), ] const msg = (await Session.updateMessage({ id: Identifier.ascending("message"), role: "assistant", sessionID: input.sessionID, system, mode: "build", path: { cwd: Instance.directory, root: Instance.worktree, }, cost: 0, tokens: { output: 0, input: 0, reasoning: 0, cache: { read: 0, write: 0 }, }, modelID: input.modelID, providerID: model.providerID, time: { created: Date.now(), }, })) as MessageV2.Assistant const generated = await generateText({ maxRetries: 10, model: model.language, messages: [ ...system.map( (x): ModelMessage => ({ role: "system", content: x, }), ), ...MessageV2.toModelMessage(toSummarize), { role: "user", content: [ { type: "text", text: "Provide a detailed but concise summary of our conversation above. Focus on information that would be helpful for continuing the conversation, including what we did, what we're doing, which files we're working on, and what we're going to do next.", }, ], }, ], }) const usage = Session.getUsage(model.info, generated.usage, generated.providerMetadata) msg.cost += usage.cost msg.tokens = usage.tokens msg.summary = true msg.time.completed = Date.now() await Session.updateMessage(msg) const part = await Session.updatePart({ type: "text", sessionID: input.sessionID, messageID: msg.id, id: Identifier.ascending("part"), text: generated.text, time: { start: Date.now(), end: Date.now(), }, }) Bus.publish(Event.Compacted, { sessionID: input.sessionID, }) return { info: msg, parts: [part], } } }