Sliding window fix

src/core/sliding-window/__tests__/sliding-window.test.ts

@@ -0,0 +1,130 @@
+// npx jest src/core/sliding-window/__tests__/sliding-window.test.ts
+
+import { Anthropic } from "@anthropic-ai/sdk"
+
+import { ModelInfo } from "../../../shared/api"
+import { truncateConversation, truncateConversationIfNeeded } from "../index"
+
+describe("truncateConversation", () => {
+	it("should retain the first message", () => {
+		const messages: Anthropic.Messages.MessageParam[] = [
+			{ role: "user", content: "First message" },
+			{ role: "assistant", content: "Second message" },
+			{ role: "user", content: "Third message" },
+		]
+
+		const result = truncateConversation(messages, 0.5)
+
+		// With 2 messages after the first, 0.5 fraction means remove 1 message
+		// But 1 is odd, so it rounds down to 0 (to make it even)
+		expect(result.length).toBe(3) // First message + 2 remaining messages
+		expect(result[0]).toEqual(messages[0])
+		expect(result[1]).toEqual(messages[1])
+		expect(result[2]).toEqual(messages[2])
+	})
+
+	it("should remove the specified fraction of messages (rounded to even number)", () => {
+		const messages: Anthropic.Messages.MessageParam[] = [
+			{ role: "user", content: "First message" },
+			{ role: "assistant", content: "Second message" },
+			{ role: "user", content: "Third message" },
+			{ role: "assistant", content: "Fourth message" },
+			{ role: "user", content: "Fifth message" },
+		]
+
+		// 4 messages excluding first, 0.5 fraction = 2 messages to remove
+		// 2 is already even, so no rounding needed
+		const result = truncateConversation(messages, 0.5)
+
+		expect(result.length).toBe(3)
+		expect(result[0]).toEqual(messages[0])
+		expect(result[1]).toEqual(messages[3])
+		expect(result[2]).toEqual(messages[4])
+	})
+
+	it("should round to an even number of messages to remove", () => {
+		const messages: Anthropic.Messages.MessageParam[] = [
+			{ role: "user", content: "First message" },
+			{ role: "assistant", content: "Second message" },
+			{ role: "user", content: "Third message" },
+			{ role: "assistant", content: "Fourth message" },
+			{ role: "user", content: "Fifth message" },
+			{ role: "assistant", content: "Sixth message" },
+			{ role: "user", content: "Seventh message" },
+		]
+
+		// 6 messages excluding first, 0.3 fraction = 1.8 messages to remove
+		// 1.8 rounds down to 1, then to 0 to make it even
+		const result = truncateConversation(messages, 0.3)
+
+		expect(result.length).toBe(7) // No messages removed
+		expect(result).toEqual(messages)
+	})
+
+	it("should handle edge case with fracToRemove = 0", () => {
+		const messages: Anthropic.Messages.MessageParam[] = [
+			{ role: "user", content: "First message" },
+			{ role: "assistant", content: "Second message" },
+			{ role: "user", content: "Third message" },
+		]
+
+		const result = truncateConversation(messages, 0)
+
+		expect(result).toEqual(messages)
+	})
+
+	it("should handle edge case with fracToRemove = 1", () => {
+		const messages: Anthropic.Messages.MessageParam[] = [
+			{ role: "user", content: "First message" },
+			{ role: "assistant", content: "Second message" },
+			{ role: "user", content: "Third message" },
+			{ role: "assistant", content: "Fourth message" },
+		]
+
+		// 3 messages excluding first, 1.0 fraction = 3 messages to remove
+		// But 3 is odd, so it rounds down to 2 to make it even
+		const result = truncateConversation(messages, 1)
+
+		expect(result.length).toBe(2)
+		expect(result[0]).toEqual(messages[0])
+		expect(result[1]).toEqual(messages[3])
+	})
+})
+
+describe("truncateConversationIfNeeded", () => {
+	const createModelInfo = (contextWindow: number, supportsPromptCache: boolean, maxTokens?: number): ModelInfo => ({
+		contextWindow,
+		supportsPromptCache,
+		maxTokens,
+	})
+
+	const messages: Anthropic.Messages.MessageParam[] = [
+		{ role: "user", content: "First message" },
+		{ role: "assistant", content: "Second message" },
+		{ role: "user", content: "Third message" },
+		{ role: "assistant", content: "Fourth message" },
+		{ role: "user", content: "Fifth message" },
+	]
+
+	it("should not truncate if tokens are below threshold for prompt caching models", () => {
+		const modelInfo = createModelInfo(200000, true, 50000)
+		const totalTokens = 100000 // Below threshold
+		const result = truncateConversationIfNeeded(messages, totalTokens, modelInfo)
+		expect(result).toEqual(messages)
+	})
+
+	it("should not truncate if tokens are below threshold for non-prompt caching models", () => {
+		const modelInfo = createModelInfo(200000, false)
+		const totalTokens = 100000 // Below threshold
+		const result = truncateConversationIfNeeded(messages, totalTokens, modelInfo)
+		expect(result).toEqual(messages)
+	})
+
+	it("should use 80% of context window as threshold if it's greater than (contextWindow - buffer)", () => {
+		const modelInfo = createModelInfo(50000, true) // Small context window
+		const totalTokens = 40001 // Above 80% threshold (40000)
+		const mockResult = [messages[0], messages[3], messages[4]]
+		const result = truncateConversationIfNeeded(messages, totalTokens, modelInfo)
+		expect(result).toEqual(mockResult)
+	})
+})

src/core/sliding-window/index.ts

@@ -1,4 +1,5 @@
 import { Anthropic } from "@anthropic-ai/sdk"
+
 import { ModelInfo } from "../../shared/api"
 
 /**
@@ -55,13 +56,15 @@ export function truncateConversationIfNeeded(
 /**
  * Calculates the maximum allowed tokens for models that support prompt caching.
  *
- * The maximum is computed as the greater of (contextWindow - 40000) and 80% of the contextWindow.
+ * The maximum is computed as the greater of (contextWindow - buffer) and 80% of the contextWindow.
  *
  * @param {ModelInfo} modelInfo - The model information containing the context window size.
  * @returns {number} The maximum number of tokens allowed for prompt caching models.
  */
 function getMaxTokensForPromptCachingModels(modelInfo: ModelInfo): number {
-	return Math.max(modelInfo.contextWindow - 40_000, modelInfo.contextWindow * 0.8)
+	// The buffer needs to be at least as large as `modelInfo.maxTokens`.
+	const buffer = modelInfo.maxTokens ? Math.max(40_000, modelInfo.maxTokens) : 40_000
+	return Math.max(modelInfo.contextWindow - buffer, modelInfo.contextWindow * 0.8)
 }
 
 /**
@@ -83,7 +86,9 @@ function getTruncFractionForPromptCachingModels(modelInfo: ModelInfo): number {
  * @returns {number} The maximum number of tokens allowed for non-prompt caching models.
  */
 function getMaxTokensForNonPromptCachingModels(modelInfo: ModelInfo): number {
-	return Math.max(modelInfo.contextWindow - 40_000, modelInfo.contextWindow * 0.8)
+	// The buffer needs to be at least as large as `modelInfo.maxTokens`.
+	const buffer = modelInfo.maxTokens ? Math.max(40_000, modelInfo.maxTokens) : 40_000
+	return Math.max(modelInfo.contextWindow - buffer, modelInfo.contextWindow * 0.8)
 }
 
 /**

src/core/webview/ClineProvider.ts

@@ -2126,6 +2126,7 @@ export class ClineProvider implements vscode.WebviewViewProvider {
 
 					switch (rawModel.id) {
 						case "anthropic/claude-3.7-sonnet":
+						case "anthropic/claude-3.7-sonnet:beta":
 						case "anthropic/claude-3.5-sonnet":
 						case "anthropic/claude-3.5-sonnet:beta":
 							// NOTE: this needs to be synced with api.ts/openrouter default model info.