feat: implement condensing feedback from GitHub comments

Author: Your Name

src/core/condense/__tests__/index.test.ts

@@ -3,12 +3,19 @@ import { ApiHandler } from "../../../api"
 import { ApiMessage } from "../../task-persistence/apiMessages"
 import { maybeRemoveImageBlocks } from "../../../api/transform/image-cleaning"
 import { summarizeConversation, getMessagesSinceLastSummary, N_MESSAGES_TO_KEEP } from "../index"
+import { telemetryService } from "../../../services/telemetry/TelemetryService"
 
 // Mock dependencies
 jest.mock("../../../api/transform/image-cleaning", () => ({
 	maybeRemoveImageBlocks: jest.fn((messages: ApiMessage[], _apiHandler: ApiHandler) => [...messages]),
 }))
 
+jest.mock("../../../services/telemetry/TelemetryService", () => ({
+	telemetryService: {
+		captureContextCondensed: jest.fn(),
+	},
+}))
+
 const taskId = "test-task-id"
 
 describe("getMessagesSinceLastSummary", () => {
@@ -302,6 +309,9 @@ describe("summarizeConversation with custom settings", () => {
 		// Reset mocks
 		jest.clearAllMocks()
 
+		// Reset telemetry mock
+		;(telemetryService.captureContextCondensed as jest.Mock).mockClear()
+
 		// Setup mock API handlers
 		mockMainApiHandler = {
 			createMessage: jest.fn().mockImplementation(() => {
@@ -487,12 +497,7 @@ describe("summarizeConversation with custom settings", () => {
 	/**
 	 * Test that telemetry is called for custom prompt usage
 	 */
-	it("should log when using custom prompt", async () => {
-		// Mock console.log to verify logging
-		const originalLog = console.log
-		const mockLog = jest.fn()
-		console.log = mockLog
-
+	it("should capture telemetry when using custom prompt", async () => {
 		await summarizeConversation(
 			sampleMessages,
 			mockMainApiHandler,
@@ -502,24 +507,19 @@ describe("summarizeConversation with custom settings", () => {
 			"Custom prompt",
 		)
 
-		// Verify logging was called
-		expect(mockLog).toHaveBeenCalledWith(
-			expect.stringContaining(`Task [${taskId}]: Using custom condensing prompt.`),
+		// Verify telemetry was called with custom prompt flag
+		expect(telemetryService.captureContextCondensed).toHaveBeenCalledWith(
+			taskId,
+			false,
+			true, // usedCustomPrompt
+			false, // usedCustomApiHandler
 		)
-
-		// Restore console.log
-		console.log = originalLog
 	})
 
 	/**
 	 * Test that telemetry is called for custom API handler usage
 	 */
-	it("should log when using custom API handler", async () => {
-		// Mock console.log to verify logging
-		const originalLog = console.log
-		const mockLog = jest.fn()
-		console.log = mockLog
-
+	it("should capture telemetry when using custom API handler", async () => {
 		await summarizeConversation(
 			sampleMessages,
 			mockMainApiHandler,
@@ -530,12 +530,35 @@ describe("summarizeConversation with custom settings", () => {
 			mockCondensingApiHandler,
 		)
 
-		// Verify logging was called
-		expect(mockLog).toHaveBeenCalledWith(
-			expect.stringContaining(`Task [${taskId}]: Using custom API handler for condensing.`),
+		// Verify telemetry was called with custom API handler flag
+		expect(telemetryService.captureContextCondensed).toHaveBeenCalledWith(
+			taskId,
+			false,
+			false, // usedCustomPrompt
+			true, // usedCustomApiHandler
+		)
+	})
+
+	/**
+	 * Test that telemetry is called with both custom prompt and API handler
+	 */
+	it("should capture telemetry when using both custom prompt and API handler", async () => {
+		await summarizeConversation(
+			sampleMessages,
+			mockMainApiHandler,
+			defaultSystemPrompt,
+			taskId,
+			true, // isAutomaticTrigger
+			"Custom prompt",
+			mockCondensingApiHandler,
 		)
 
-		// Restore console.log
-		console.log = originalLog
+		// Verify telemetry was called with both flags
+		expect(telemetryService.captureContextCondensed).toHaveBeenCalledWith(
+			taskId,
+			true, // isAutomaticTrigger
+			true, // usedCustomPrompt
+			true, // usedCustomApiHandler
+		)
 	})
 })

src/core/condense/index.ts

@@ -84,7 +84,12 @@ export async function summarizeConversation(
 	customCondensingPrompt?: string,
 	condensingApiHandler?: ApiHandler,
 ): Promise<SummarizeResponse> {
-	telemetryService.captureContextCondensed(taskId, isAutomaticTrigger ?? false)
+	telemetryService.captureContextCondensed(
+		taskId,
+		isAutomaticTrigger ?? false,
+		!!customCondensingPrompt?.trim(),
+		!!condensingApiHandler,
+	)
 	const response: SummarizeResponse = { messages, cost: 0, summary: "" }
 	const messagesToSummarize = getMessagesSinceLastSummary(messages.slice(0, -N_MESSAGES_TO_KEEP))
 	if (messagesToSummarize.length <= 1) {
@@ -131,22 +136,6 @@ export async function summarizeConversation(
 		}
 	}
 
-	// Log when using custom prompt for debugging and telemetry
-	if (customCondensingPrompt?.trim()) {
-		console.log(`Task [${taskId}]: Using custom condensing prompt.`)
-		// TODO: Add telemetry for custom condensing prompt usage
-		// This would require extending the telemetry service with a new method like:
-		// telemetryService.captureCustomCondensingPromptUsed(taskId);
-	}
-
-	// Log when using custom API handler for condensing
-	if (condensingApiHandler) {
-		console.log(`Task [${taskId}]: Using custom API handler for condensing.`)
-		// TODO: Add telemetry for custom condensing API handler usage
-		// This would require extending the telemetry service with a new method like:
-		// telemetryService.captureCustomCondensingApiUsed(taskId, condensingApiConfigId);
-	}
-
 	const stream = handlerToUse.createMessage(promptToUse, requestMessages)
 	let summary = ""
 	let cost = 0

src/core/task/Task.ts

@@ -1493,20 +1493,20 @@ export class Task extends EventEmitter<ClineEvents> {
 	}
 
 	public async *attemptApiRequest(retryAttempt: number = 0): ApiStream {
+		const state = await this.providerRef.deref()?.getState()
 		const {
 			apiConfiguration,
 			autoApprovalEnabled,
 			alwaysApproveResubmit,
 			requestDelaySeconds,
 			experiments,
 			autoCondenseContextPercent = 100,
-		} = (await this.providerRef.deref()?.getState()) ?? {}
+		} = state ?? {}
 
 		// Get condensing configuration for automatic triggers
-		const state = await this.providerRef.deref()?.getState()
-		const customCondensingPrompt = state ? (state as any).customCondensingPrompt : undefined
-		const condensingApiConfigId = state ? (state as any).condensingApiConfigId : undefined
-		const listApiConfigMeta = state ? (state as any).listApiConfigMeta : undefined
+		const customCondensingPrompt = state?.customCondensingPrompt
+		const condensingApiConfigId = state?.condensingApiConfigId
+		const listApiConfigMeta = state?.listApiConfigMeta
 
 		// Determine API handler to use for condensing
 		let condensingApiHandler: ApiHandler | undefined
@@ -1563,7 +1563,7 @@ export class Task extends EventEmitter<ClineEvents> {
 
 			const contextWindow = modelInfo.contextWindow
 
-			const autoCondenseContext = experiments?.autoCondenseContext ?? false
+			const autoCondenseContext = state?.experiments?.autoCondenseContext ?? false
 			const truncateResult = await truncateConversationIfNeeded({
 				messages: this.apiConversationHistory,
 				totalTokens: contextTokens,
@@ -1602,8 +1602,7 @@ export class Task extends EventEmitter<ClineEvents> {
 		)
 
 		// Check if we've reached the maximum number of auto-approved requests
-		const { allowedMaxRequests } = (await this.providerRef.deref()?.getState()) ?? {}
-		const maxRequests = allowedMaxRequests || Infinity
+		const maxRequests = state?.allowedMaxRequests || Infinity
 
 		// Increment the counter for each new API request
 		this.consecutiveAutoApprovedRequestsCount++
@@ -1628,7 +1627,7 @@ export class Task extends EventEmitter<ClineEvents> {
 		} catch (error) {
 			this.isWaitingForFirstChunk = false
 			// note that this api_req_failed ask is unique in that we only present this option if the api hasn't streamed any content yet (ie it fails on the first chunk due), as it would allow them to hit a retry button. However if the api failed mid-stream, it could be in any arbitrary state where some tools may have executed, so that error is handled differently and requires cancelling the task entirely.
-			if (autoApprovalEnabled && alwaysApproveResubmit) {
+			if (state?.autoApprovalEnabled && state?.alwaysApproveResubmit) {
 				let errorMsg
 
 				if (error.error?.metadata?.raw) {
@@ -1639,7 +1638,7 @@ export class Task extends EventEmitter<ClineEvents> {
 					errorMsg = "Unknown error"
 				}
 
-				const baseDelay = requestDelaySeconds || 5
+				const baseDelay = state.requestDelaySeconds || 5
 				let exponentialDelay = Math.ceil(baseDelay * Math.pow(2, retryAttempt))
 
 				// If the error is a 429, and the error details contain a retry delay, use that delay instead of exponential backoff

src/services/telemetry/TelemetryService.ts

@@ -120,8 +120,18 @@ class TelemetryService {
 		this.captureEvent(PostHogClient.EVENTS.TASK.CHECKPOINT_RESTORED, { taskId })
 	}
 
-	public captureContextCondensed(taskId: string, isAutomaticTrigger: boolean): void {
-		this.captureEvent(PostHogClient.EVENTS.TASK.CONTEXT_CONDENSED, { taskId, isAutomaticTrigger })
+	public captureContextCondensed(
+		taskId: string,
+		isAutomaticTrigger: boolean,
+		usedCustomPrompt?: boolean,
+		usedCustomApiHandler?: boolean,
+	): void {
+		this.captureEvent(PostHogClient.EVENTS.TASK.CONTEXT_CONDENSED, {
+			taskId,
+			isAutomaticTrigger,
+			...(usedCustomPrompt !== undefined && { usedCustomPrompt }),
+			...(usedCustomApiHandler !== undefined && { usedCustomApiHandler }),
+		})
 	}
 
 	public captureSlidingWindowTruncation(taskId: string): void {

webview-ui/src/components/settings/ExperimentalSettings.tsx

@@ -14,6 +14,46 @@ import { ExperimentalFeature } from "./ExperimentalFeature"
 import { Button, Select, SelectContent, SelectItem, SelectTrigger, SelectValue, Slider } from "@/components/ui/"
 import { VSCodeTextArea } from "@vscode/webview-ui-toolkit/react"
 
+const SUMMARY_PROMPT = `\
+Your task is to create a detailed summary of the conversation so far, paying close attention to the user's explicit requests and your previous actions.
+This summary should be thorough in capturing technical details, code patterns, and architectural decisions that would be essential for continuing with the conversation and supporting any continuing tasks.
+
+Your summary should be structured as follows:
+Context: The context to continue the conversation with. If applicable based on the current task, this should include:
+  1. Previous Conversation: High level details about what was discussed throughout the entire conversation with the user. This should be written to allow someone to be able to follow the general overarching conversation flow.
+  2. Current Work: Describe in detail what was being worked on prior to this request to summarize the conversation. Pay special attention to the more recent messages in the conversation.
+  3. Key Technical Concepts: List all important technical concepts, technologies, coding conventions, and frameworks discussed, which might be relevant for continuing with this work.
+  4. Relevant Files and Code: If applicable, enumerate specific files and code sections examined, modified, or created for the task continuation. Pay special attention to the most recent messages and changes.
+  5. Problem Solving: Document problems solved thus far and any ongoing troubleshooting efforts.
+  6. Pending Tasks and Next Steps: Outline all pending tasks that you have explicitly been asked to work on, as well as list the next steps you will take for all outstanding work, if applicable. Include code snippets where they add clarity. For any next steps, include direct quotes from the most recent conversation showing exactly what task you were working on and where you left off. This should be verbatim to ensure there's no information loss in context between tasks.
+
+Example summary structure:
+1. Previous Conversation:
+  [Detailed description]
+2. Current Work:
+  [Detailed description]
+3. Key Technical Concepts:
+  - [Concept 1]
+  - [Concept 2]
+  - [...]
+4. Relevant Files and Code:
+  - [File Name 1]
+    - [Summary of why this file is important]
+    - [Summary of the changes made to this file, if any]
+    - [Important Code Snippet]
+  - [File Name 2]
+    - [Important Code Snippet]
+  - [...]
+5. Problem Solving:
+  [Detailed description]
+6. Pending Tasks and Next Steps:
+  - [Task 1 details & next steps]
+  - [Task 2 details & next steps]
+  - [...]
+
+Output only the summary of the conversation so far, without any additional commentary or explanation.
+`
+
 type ExperimentalSettingsProps = HTMLAttributes<HTMLDivElement> & {
 	experiments: Record<ExperimentId, boolean>
 	setExperimentEnabled: SetExperimentEnabled
@@ -140,7 +180,7 @@ export const ExperimentalSettings = ({
 								</div>
 								<VSCodeTextArea
 									resize="vertical"
-									value={customCondensingPrompt || ""}
+									value={customCondensingPrompt || SUMMARY_PROMPT}
 									onChange={(e) => {
 										const value = (e.target as HTMLTextAreaElement).value
 										setCustomCondensingPrompt(value)
@@ -149,26 +189,22 @@ export const ExperimentalSettings = ({
 											text: value,
 										})
 									}}
-									placeholder={t("settings:experimental.customCondensingPrompt.placeholder")}
 									rows={8}
 									className="w-full font-mono text-sm"
 								/>
-								<div className="mt-2 flex justify-between items-center">
+								<div className="mt-2">
 									<Button
 										variant="secondary"
 										size="sm"
 										onClick={() => {
-											setCustomCondensingPrompt("")
+											setCustomCondensingPrompt(SUMMARY_PROMPT)
 											vscode.postMessage({
 												type: "updateCondensingPrompt",
-												text: "",
+												text: SUMMARY_PROMPT,
 											})
 										}}>
 										{t("settings:experimental.customCondensingPrompt.reset")}
 									</Button>
-									<div className="text-xs text-vscode-descriptionForeground">
-										{t("settings:experimental.customCondensingPrompt.hint")}
-									</div>
 								</div>
 							</div>
 						</div>