Remove unnecessary variable, add JSDocs

src/core/sliding-window/index.ts

@@ -1,6 +1,16 @@
 import { Anthropic } from "@anthropic-ai/sdk"
 import { ModelInfo } from "../../shared/api"
 
+/**
+ * Truncates a conversation by removing a fraction of the messages.
+ *
+ * The first message is always retained, and a specified fraction (rounded to an even number)
+ * of messages from the beginning (excluding the first) is removed.
+ *
+ * @param {Anthropic.Messages.MessageParam[]} messages - The conversation messages.
+ * @param {number} fracToRemove - The fraction (between 0 and 1) of messages (excluding the first) to remove.
+ * @returns {Anthropic.Messages.MessageParam[]} The truncated conversation messages.
+ */
 export function truncateConversation(
 	messages: Anthropic.Messages.MessageParam[],
 	fracToRemove: number,
@@ -14,6 +24,18 @@ export function truncateConversation(
 	return truncatedMessages
 }
 
+/**
+ * Conditionally truncates the conversation messages if the total token count exceeds the model's limit.
+ *
+ * Depending on whether the model supports prompt caching, different maximum token thresholds
+ * and truncation fractions are used. If the current total tokens exceed the threshold,
+ * the conversation is truncated using the appropriate fraction.
+ *
+ * @param {Anthropic.Messages.MessageParam[]} messages - The conversation messages.
+ * @param {number} totalTokens - The total number of tokens in the conversation.
+ * @param {ModelInfo} modelInfo - Model metadata including context window size and prompt cache support.
+ * @returns {Anthropic.Messages.MessageParam[]} The original or truncated conversation messages.
+ */
 export function truncateConversationIfNeeded(
 	messages: Anthropic.Messages.MessageParam[],
 	totalTokens: number,
@@ -24,25 +46,52 @@ export function truncateConversationIfNeeded(
 			? messages
 			: truncateConversation(messages, getTruncFractionForPromptCachingModels(modelInfo))
 	} else {
-		const thresh = getMaxTokensForNonPromptCachingModels(modelInfo)
-		return totalTokens < thresh
+		return totalTokens < getMaxTokensForNonPromptCachingModels(modelInfo)
 			? messages
 			: truncateConversation(messages, getTruncFractionForNonPromptCachingModels(modelInfo))
 	}
 }
 
+/**
+ * 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.
+ *
+ * @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)
 }
 
+/**
+ * Provides the fraction of messages to remove for models that support prompt caching.
+ *
+ * @param {ModelInfo} modelInfo - The model information (unused in current implementation).
+ * @returns {number} The truncation fraction for prompt caching models (fixed at 0.5).
+ */
 function getTruncFractionForPromptCachingModels(modelInfo: ModelInfo): number {
-	return Math.min(80_000, modelInfo.contextWindow * 0.4)
+	return 0.5
 }
 
+/**
+ * Calculates the maximum allowed tokens for models that do not support prompt caching.
+ *
+ * The maximum is computed as the greater of (contextWindow - 40000) 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 non-prompt caching models.
+ */
 function getMaxTokensForNonPromptCachingModels(modelInfo: ModelInfo): number {
 	return Math.max(modelInfo.contextWindow - 40_000, modelInfo.contextWindow * 0.8)
 }
 
+/**
+ * Provides the fraction of messages to remove for models that do not support prompt caching.
+ *
+ * @param {ModelInfo} modelInfo - The model information (unused in current implementation).
+ * @returns {number} The truncation fraction for non-prompt caching models (fixed at 0.1).
+ */
 function getTruncFractionForNonPromptCachingModels(modelInfo: ModelInfo): number {
-	return Math.min(80_000, modelInfo.contextWindow * 0.4)
+	return 0.1
 }