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