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feat: add durable context compression

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Long direct-model conversations mixed provider usage with local estimates,
and Agent tool rounds could remain above the configured compression target.
Compression state and status markers also did not reliably survive restarts
or bounded history rollover.

Direct-model calls now prefer provider-reported usage, compact complete
conversation turns and Agent tool rounds within reserved payload budgets,
and persist reusable summaries with scope-specific markers. The chat meter
separates latest-call usage from estimated compressed conversation size,
while failed or cancelled calls retain the last successful measurement.

Release note: 直连模型现可在长对话和多轮工具执行中自动压缩旧上下文，并分别显示本次调用用量与压缩后对话估算；摘要会自动保存并跨重启复用，无需手动操作。
This commit is contained in:
mesalogo
2026-08-16 00:36:11 +08:00
parent b3c753fac2
commit c98fe67f1a
18 changed files with 3202 additions and 420 deletions
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src/main/agent/runtime-e2e.manual.test.ts
+356 -8
View File
@@ -165,6 +165,75 @@ class RealModelConfigToolProvider implements ModelToolProviderLike {
}
}
class RealLongAgentToolProvider implements ModelToolProviderLike {
readonly completedSteps: number[] = []
async listTools(): Promise<ModelToolDefinition[]> {
const expectedStep = this.completedSteps.length + 1
return [
{
name: 'record_progress',
displayName: 'Record progress',
description:
expectedStep <= 3
? `Record required progress step ${expectedStep}. Call exactly once with step ${expectedStep} before continuing.`
: 'All required progress is recorded. Do not call this tool again.',
inputSchema: {
type: 'object',
properties: {
step: {
type: 'integer',
const: expectedStep
}
},
required: ['step'],
additionalProperties: false
},
source: 'builtin'
}
]
}
getApproval() {
return {
scopeKey: 'real-long-agent-test',
title: 'Record test progress',
description: 'Record deterministic E2E progress',
allowPermanent: false
}
}
async callTool(
name: string,
argumentsValue: Record<string, unknown>,
signal: AbortSignal
): Promise<ModelToolResult> {
signal.throwIfAborted()
const expectedStep = this.completedSteps.length + 1
if (
name !== 'record_progress' ||
argumentsValue.step !== expectedStep ||
expectedStep > 3
) {
throw new Error(
`Unexpected progress call: ${name} ${JSON.stringify(argumentsValue)}`
)
}
this.completedSteps.push(expectedStep)
const text = [
`STEP_${expectedStep}_RECORDED`,
`evidence-${expectedStep} `.repeat(4_000)
].join('\n')
return {
parts: [{ type: 'text', text }],
contextBytes: Buffer.byteLength(text)
}
}
async releaseConversation(): Promise<void> {}
async dispose(): Promise<void> {}
}
describe.runIf(enabled)('runtime end-to-end', () => {
let workspace = ''
@@ -214,6 +283,104 @@ describe.runIf(enabled)('runtime end-to-end', () => {
120_000
)
it(
'counts a real image in provider-reported input usage',
async () => {
const runtime = new ModelAgentRuntime({
apiKey,
baseUrl,
model: modelName,
protocol,
authentication: 'api-key',
supportsImageInput: true,
maxOutputTokens: 128,
contextCompression: {
settings: {
...defaultContextCompressionSettings,
enabled: true
},
contextWindowTokens: 32_000
}
})
const baselineEvents: RuntimeEvent[] = []
const imageEvents: RuntimeEvent[] = []
const prompt =
'Return exactly this text and nothing else: IMAGE_USAGE_E2E_OK'
try {
for await (const event of runtime.run(
{
requestId: crypto.randomUUID(),
conversationId: crypto.randomUUID(),
workMode: 'ask',
prompt
},
new AbortController().signal
)) {
baselineEvents.push(event)
}
for await (const event of runtime.run(
{
requestId: crypto.randomUUID(),
conversationId: crypto.randomUUID(),
workMode: 'ask',
prompt,
images: [
{
name: 'goodbuddy-icon.png',
mediaType: 'image/png',
data: await readFile(
join(process.cwd(), 'build', 'icon.png'),
'base64'
)
}
]
},
new AbortController().signal
)) {
imageEvents.push(event)
}
} finally {
await runtime.dispose()
}
const baselineUsage = baselineEvents.find(
(
event
): event is Extract<RuntimeEvent, { type: 'model-usage' }> =>
event.type === 'model-usage'
)
const imageUsage = imageEvents.find(
(
event
): event is Extract<RuntimeEvent, { type: 'model-usage' }> =>
event.type === 'model-usage'
)
expect(baselineUsage).toBeDefined()
expect(imageUsage).toBeDefined()
expect(imageUsage!.inputTokens).toBeGreaterThan(
baselineUsage!.inputTokens
)
expect(
imageEvents.filter(
(event) => event.type === 'context-metrics'
)
).toEqual([
expect.objectContaining({
source: 'provider',
contextTokens:
imageUsage!.inputTokens +
imageUsage!.outputTokens +
(protocol === 'anthropic-messages'
? imageUsage!.cacheReadTokens +
imageUsage!.cacheWriteTokens
: 0)
})
])
},
180_000
)
it(
'compresses real direct-model history and preserves earlier and recent facts',
async () => {
@@ -247,7 +414,7 @@ describe.runIf(enabled)('runtime end-to-end', () => {
content: [
'The project codename is ORBIT-739.',
'Background notes:',
'alpha '.repeat(5_000)
'alpha '.repeat(8_000)
].join('\n')
},
{
@@ -255,7 +422,7 @@ describe.runIf(enabled)('runtime end-to-end', () => {
content: [
'I will remember the project codename.',
'Acknowledgement notes:',
'gamma '.repeat(4_000)
'gamma '.repeat(6_500)
].join('\n')
},
{
@@ -263,7 +430,7 @@ describe.runIf(enabled)('runtime end-to-end', () => {
content: [
'The deploy region is AP-SOUTH-7.',
'Recent notes:',
'beta '.repeat(3_000)
'beta '.repeat(5_000)
].join('\n')
},
{
@@ -312,6 +479,172 @@ describe.runIf(enabled)('runtime end-to-end', () => {
120_000
)
it(
'compresses context after a real completed response reaches the threshold',
async () => {
const expectedOutput = [
'POST_RESPONSE_COMPRESSION_E2E_OK_',
'SAFE'.repeat(16)
].join('')
const prompt = `Return exactly this text and nothing else: ${expectedOutput}`
const history = [
{
role: 'user' as const,
content: `baseline\n${'alpha '.repeat(8_500)}`
},
{
role: 'assistant' as const,
content: 'ack'
}
]
const runtime = new ModelAgentRuntime({
apiKey,
baseUrl,
model: modelName,
protocol,
authentication: 'api-key',
maxOutputTokens: 128,
contextCompression: {
settings: {
...defaultContextCompressionSettings,
enabled: true,
triggerTokens: 8_000,
recentRawTokens: 4_000
},
contextWindowTokens: 32_000
}
})
const events: RuntimeEvent[] = []
try {
for await (const event of runtime.run(
{
requestId: crypto.randomUUID(),
conversationId: crypto.randomUUID(),
workMode: 'ask',
prompt,
history
},
new AbortController().signal
)) {
events.push(event)
}
} finally {
await runtime.dispose()
}
const output = events
.flatMap((event) =>
event.type === 'text' ? [event.delta] : []
)
.join('')
const lastTextIndex = events.reduce(
(lastIndex, event, index) =>
event.type === 'text' ? index : lastIndex,
-1
)
const postResponseCompressionIndex = events.findIndex(
(event) =>
event.type === 'context-compression' &&
event.scope === 'conversation' &&
event.state === 'started'
)
expect(output).toContain(expectedOutput)
expect(lastTextIndex).toBeGreaterThanOrEqual(0)
expect(postResponseCompressionIndex).toBeGreaterThan(
lastTextIndex
)
expect(
events
.filter((event) => event.type === 'context-metrics')
.at(-1)
).toMatchObject({
type: 'context-metrics',
source: 'provider'
})
expect(events).not.toContainEqual(
expect.objectContaining({
type: 'context-metrics',
source: 'estimated'
})
)
expect(events.at(-1)).toMatchObject({ type: 'done' })
},
180_000
)
it(
'compacts a real multi-round Agent run and continues to completion',
async () => {
const toolProvider = new RealLongAgentToolProvider()
const runtime = new ModelAgentRuntime({
apiKey,
baseUrl,
model: modelName,
protocol,
authentication: 'api-key',
toolProvider,
contextCompression: {
settings: {
...defaultContextCompressionSettings,
enabled: true,
triggerTokens: 8_000,
recentRawTokens: 4_000
},
contextWindowTokens: 32_000
}
})
const events: RuntimeEvent[] = []
try {
for await (const event of runtime.run(
{
requestId: crypto.randomUUID(),
conversationId: crypto.randomUUID(),
workMode: 'execute',
prompt:
'Call record_progress sequentially for steps 1, 2, and 3. Wait for each result before calling the next step. After all three results, do not call tools again and reply with LONG_AGENT_COMPRESSION_E2E_OK.'
},
new AbortController().signal,
async () => 'once'
)) {
events.push(event)
}
} finally {
await runtime.dispose()
}
const output = events
.flatMap((event) =>
event.type === 'text' ? [event.delta] : []
)
.join('')
expect(toolProvider.completedSteps).toEqual([1, 2, 3])
expect(events).toContainEqual(
expect.objectContaining({
type: 'context-compression',
scope: 'agent-run',
state: 'completed'
})
)
expect(output).toContain('LONG_AGENT_COMPRESSION_E2E_OK')
expect(
events
.filter((event) => event.type === 'context-metrics')
.at(-1)
).toMatchObject({ source: 'provider' })
expect(events).not.toContainEqual(
expect.objectContaining({
type: 'context-metrics',
source: 'estimated'
})
)
expect(events.at(-1)).toMatchObject({ type: 'done' })
},
240_000
)
it(
'discovers and plans GoodBuddy configuration through a real model',
async () => {
@@ -399,13 +732,21 @@ describe.runIf(enabled)('runtime end-to-end', () => {
baseUrl,
model: modelName,
protocol,
authentication: 'api-key'
authentication: 'api-key',
contextCompression: {
settings: {
...defaultContextCompressionSettings,
enabled: true
},
contextWindowTokens: 32_000
}
})
const abortController = new AbortController()
const events: RuntimeEvent[] = []
try {
const result = collectText(
runtime.run(
const result = (async () => {
for await (const event of runtime.run(
{
requestId: crypto.randomUUID(),
conversationId: crypto.randomUUID(),
@@ -414,12 +755,19 @@ describe.runIf(enabled)('runtime end-to-end', () => {
'Write a detailed technical essay of at least 3000 words.'
},
abortController.signal
)
)
)) {
events.push(event)
}
})()
setTimeout(() => abortController.abort(), 50)
await expect(result).rejects.toMatchObject({
name: 'AbortError'
})
expect(events).not.toContainEqual(
expect.objectContaining({
type: 'context-metrics'
})
)
} finally {
await runtime.dispose()
}