mirror of
https://github.com/pacnpal/Roo-Code.git
synced 2025-12-20 04:11:10 -05:00
Prettier backfill
This commit is contained in:
Matt Rubens
@@ -1,31 +1,31 @@
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import { Anthropic } from "@anthropic-ai/sdk";
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import * as vscode from 'vscode';
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import { ApiHandler, SingleCompletionHandler } from "../";
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import { calculateApiCost } from "../../utils/cost";
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import { ApiStream } from "../transform/stream";
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import { convertToVsCodeLmMessages } from "../transform/vscode-lm-format";
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import { SELECTOR_SEPARATOR, stringifyVsCodeLmModelSelector } from "../../shared/vsCodeSelectorUtils";
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import { ApiHandlerOptions, ModelInfo, openAiModelInfoSaneDefaults } from "../../shared/api";
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import { Anthropic } from "@anthropic-ai/sdk"
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import * as vscode from "vscode"
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import { ApiHandler, SingleCompletionHandler } from "../"
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import { calculateApiCost } from "../../utils/cost"
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import { ApiStream } from "../transform/stream"
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import { convertToVsCodeLmMessages } from "../transform/vscode-lm-format"
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import { SELECTOR_SEPARATOR, stringifyVsCodeLmModelSelector } from "../../shared/vsCodeSelectorUtils"
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import { ApiHandlerOptions, ModelInfo, openAiModelInfoSaneDefaults } from "../../shared/api"
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/**
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* Handles interaction with VS Code's Language Model API for chat-based operations.
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* This handler implements the ApiHandler interface to provide VS Code LM specific functionality.
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*
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*
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* @implements {ApiHandler}
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*
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*
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* @remarks
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* The handler manages a VS Code language model chat client and provides methods to:
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* - Create and manage chat client instances
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* - Stream messages using VS Code's Language Model API
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* - Retrieve model information
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*
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*
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* @example
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* ```typescript
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* const options = {
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* vsCodeLmModelSelector: { vendor: "copilot", family: "gpt-4" }
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* };
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* const handler = new VsCodeLmHandler(options);
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*
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*
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* // Stream a conversation
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* const systemPrompt = "You are a helpful assistant";
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* const messages = [{ role: "user", content: "Hello!" }];
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@@ -35,39 +35,36 @@ import { ApiHandlerOptions, ModelInfo, openAiModelInfoSaneDefaults } from "../..
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* ```
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*/
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export class VsCodeLmHandler implements ApiHandler, SingleCompletionHandler {
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private options: ApiHandlerOptions;
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private client: vscode.LanguageModelChat | null;
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private disposable: vscode.Disposable | null;
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private currentRequestCancellation: vscode.CancellationTokenSource | null;
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private options: ApiHandlerOptions
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private client: vscode.LanguageModelChat | null
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private disposable: vscode.Disposable | null
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private currentRequestCancellation: vscode.CancellationTokenSource | null
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constructor(options: ApiHandlerOptions) {
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this.options = options;
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this.client = null;
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this.disposable = null;
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this.currentRequestCancellation = null;
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this.options = options
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this.client = null
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this.disposable = null
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this.currentRequestCancellation = null
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try {
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// Listen for model changes and reset client
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this.disposable = vscode.workspace.onDidChangeConfiguration(event => {
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if (event.affectsConfiguration('lm')) {
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this.disposable = vscode.workspace.onDidChangeConfiguration((event) => {
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if (event.affectsConfiguration("lm")) {
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try {
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this.client = null;
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this.ensureCleanState();
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}
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catch (error) {
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console.error('Error during configuration change cleanup:', error);
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this.client = null
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this.ensureCleanState()
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} catch (error) {
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console.error("Error during configuration change cleanup:", error)
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}
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}
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});
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}
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catch (error) {
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})
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} catch (error) {
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// Ensure cleanup if constructor fails
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this.dispose();
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this.dispose()
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throw new Error(
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`Cline <Language Model API>: Failed to initialize handler: ${error instanceof Error ? error.message : 'Unknown error'}`
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);
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`Cline <Language Model API>: Failed to initialize handler: ${error instanceof Error ? error.message : "Unknown error"}`,
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)
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}
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}
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@@ -77,46 +74,46 @@ export class VsCodeLmHandler implements ApiHandler, SingleCompletionHandler {
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* @param selector - Selector criteria to filter language model chat instances
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* @returns Promise resolving to the first matching language model chat instance
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* @throws Error when no matching models are found with the given selector
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*
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*
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* @example
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* const selector = { vendor: "copilot", family: "gpt-4o" };
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* const chatClient = await createClient(selector);
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*/
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async createClient(selector: vscode.LanguageModelChatSelector): Promise<vscode.LanguageModelChat> {
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try {
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const models = await vscode.lm.selectChatModels(selector);
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const models = await vscode.lm.selectChatModels(selector)
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// Use first available model or create a minimal model object
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if (models && Array.isArray(models) && models.length > 0) {
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return models[0];
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return models[0]
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}
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// Create a minimal model if no models are available
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return {
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id: 'default-lm',
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name: 'Default Language Model',
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vendor: 'vscode',
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family: 'lm',
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version: '1.0',
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id: "default-lm",
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name: "Default Language Model",
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vendor: "vscode",
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family: "lm",
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version: "1.0",
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maxInputTokens: 8192,
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sendRequest: async (messages, options, token) => {
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// Provide a minimal implementation
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return {
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stream: (async function* () {
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yield new vscode.LanguageModelTextPart(
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"Language model functionality is limited. Please check VS Code configuration."
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);
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"Language model functionality is limited. Please check VS Code configuration.",
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)
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})(),
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text: (async function* () {
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yield "Language model functionality is limited. Please check VS Code configuration.";
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})()
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};
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yield "Language model functionality is limited. Please check VS Code configuration."
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})(),
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}
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},
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countTokens: async () => 0
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};
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countTokens: async () => 0,
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}
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} catch (error) {
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const errorMessage = error instanceof Error ? error.message : 'Unknown error';
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throw new Error(`Cline <Language Model API>: Failed to select model: ${errorMessage}`);
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const errorMessage = error instanceof Error ? error.message : "Unknown error"
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throw new Error(`Cline <Language Model API>: Failed to select model: ${errorMessage}`)
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}
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}
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@@ -125,242 +122,234 @@ export class VsCodeLmHandler implements ApiHandler, SingleCompletionHandler {
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*
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* @param systemPrompt - The system prompt to initialize the conversation context
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* @param messages - An array of message parameters following the Anthropic message format
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*
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*
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* @yields {ApiStream} An async generator that yields either text chunks or tool calls from the model response
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*
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*
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* @throws {Error} When vsCodeLmModelSelector option is not provided
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* @throws {Error} When the response stream encounters an error
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*
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*
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* @remarks
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* This method handles the initialization of the VS Code LM client if not already created,
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* converts the messages to VS Code LM format, and streams the response chunks.
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* Tool calls handling is currently a work in progress.
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*/
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dispose(): void {
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if (this.disposable) {
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this.disposable.dispose();
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this.disposable.dispose()
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}
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if (this.currentRequestCancellation) {
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this.currentRequestCancellation.cancel();
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this.currentRequestCancellation.dispose();
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this.currentRequestCancellation.cancel()
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this.currentRequestCancellation.dispose()
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}
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}
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private async countTokens(text: string | vscode.LanguageModelChatMessage): Promise<number> {
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// Check for required dependencies
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if (!this.client) {
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console.warn('Cline <Language Model API>: No client available for token counting');
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return 0;
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console.warn("Cline <Language Model API>: No client available for token counting")
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return 0
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}
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if (!this.currentRequestCancellation) {
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console.warn('Cline <Language Model API>: No cancellation token available for token counting');
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return 0;
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console.warn("Cline <Language Model API>: No cancellation token available for token counting")
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return 0
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}
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// Validate input
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if (!text) {
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console.debug('Cline <Language Model API>: Empty text provided for token counting');
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return 0;
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console.debug("Cline <Language Model API>: Empty text provided for token counting")
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return 0
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}
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try {
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// Handle different input types
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let tokenCount: number;
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let tokenCount: number
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if (typeof text === 'string') {
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tokenCount = await this.client.countTokens(text, this.currentRequestCancellation.token);
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if (typeof text === "string") {
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tokenCount = await this.client.countTokens(text, this.currentRequestCancellation.token)
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} else if (text instanceof vscode.LanguageModelChatMessage) {
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// For chat messages, ensure we have content
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if (!text.content || (Array.isArray(text.content) && text.content.length === 0)) {
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console.debug('Cline <Language Model API>: Empty chat message content');
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return 0;
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console.debug("Cline <Language Model API>: Empty chat message content")
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return 0
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}
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tokenCount = await this.client.countTokens(text, this.currentRequestCancellation.token);
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tokenCount = await this.client.countTokens(text, this.currentRequestCancellation.token)
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} else {
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console.warn('Cline <Language Model API>: Invalid input type for token counting');
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return 0;
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console.warn("Cline <Language Model API>: Invalid input type for token counting")
|
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return 0
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||||
}
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|
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// Validate the result
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if (typeof tokenCount !== 'number') {
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console.warn('Cline <Language Model API>: Non-numeric token count received:', tokenCount);
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return 0;
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if (typeof tokenCount !== "number") {
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console.warn("Cline <Language Model API>: Non-numeric token count received:", tokenCount)
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return 0
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}
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if (tokenCount < 0) {
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console.warn('Cline <Language Model API>: Negative token count received:', tokenCount);
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return 0;
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console.warn("Cline <Language Model API>: Negative token count received:", tokenCount)
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return 0
|
||||
}
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||||
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return tokenCount;
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||||
}
|
||||
catch (error) {
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return tokenCount
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} catch (error) {
|
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// Handle specific error types
|
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if (error instanceof vscode.CancellationError) {
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console.debug('Cline <Language Model API>: Token counting cancelled by user');
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return 0;
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console.debug("Cline <Language Model API>: Token counting cancelled by user")
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return 0
|
||||
}
|
||||
|
||||
const errorMessage = error instanceof Error ? error.message : 'Unknown error';
|
||||
console.warn('Cline <Language Model API>: Token counting failed:', errorMessage);
|
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const errorMessage = error instanceof Error ? error.message : "Unknown error"
|
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console.warn("Cline <Language Model API>: Token counting failed:", errorMessage)
|
||||
|
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// Log additional error details if available
|
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if (error instanceof Error && error.stack) {
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console.debug('Token counting error stack:', error.stack);
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console.debug("Token counting error stack:", error.stack)
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}
|
||||
|
||||
return 0; // Fallback to prevent stream interruption
|
||||
return 0 // Fallback to prevent stream interruption
|
||||
}
|
||||
}
|
||||
|
||||
private async calculateTotalInputTokens(systemPrompt: string, vsCodeLmMessages: vscode.LanguageModelChatMessage[]): Promise<number> {
|
||||
private async calculateTotalInputTokens(
|
||||
systemPrompt: string,
|
||||
vsCodeLmMessages: vscode.LanguageModelChatMessage[],
|
||||
): Promise<number> {
|
||||
const systemTokens: number = await this.countTokens(systemPrompt)
|
||||
|
||||
const systemTokens: number = await this.countTokens(systemPrompt);
|
||||
const messageTokens: number[] = await Promise.all(vsCodeLmMessages.map((msg) => this.countTokens(msg)))
|
||||
|
||||
const messageTokens: number[] = await Promise.all(
|
||||
vsCodeLmMessages.map(msg => this.countTokens(msg))
|
||||
);
|
||||
|
||||
return systemTokens + messageTokens.reduce(
|
||||
(sum: number, tokens: number): number => sum + tokens, 0
|
||||
);
|
||||
return systemTokens + messageTokens.reduce((sum: number, tokens: number): number => sum + tokens, 0)
|
||||
}
|
||||
|
||||
private ensureCleanState(): void {
|
||||
|
||||
if (this.currentRequestCancellation) {
|
||||
|
||||
this.currentRequestCancellation.cancel();
|
||||
this.currentRequestCancellation.dispose();
|
||||
this.currentRequestCancellation = null;
|
||||
this.currentRequestCancellation.cancel()
|
||||
this.currentRequestCancellation.dispose()
|
||||
this.currentRequestCancellation = null
|
||||
}
|
||||
}
|
||||
|
||||
private async getClient(): Promise<vscode.LanguageModelChat> {
|
||||
if (!this.client) {
|
||||
console.debug('Cline <Language Model API>: Getting client with options:', {
|
||||
console.debug("Cline <Language Model API>: Getting client with options:", {
|
||||
vsCodeLmModelSelector: this.options.vsCodeLmModelSelector,
|
||||
hasOptions: !!this.options,
|
||||
selectorKeys: this.options.vsCodeLmModelSelector ? Object.keys(this.options.vsCodeLmModelSelector) : []
|
||||
});
|
||||
selectorKeys: this.options.vsCodeLmModelSelector ? Object.keys(this.options.vsCodeLmModelSelector) : [],
|
||||
})
|
||||
|
||||
try {
|
||||
// Use default empty selector if none provided to get all available models
|
||||
const selector = this.options?.vsCodeLmModelSelector || {};
|
||||
console.debug('Cline <Language Model API>: Creating client with selector:', selector);
|
||||
this.client = await this.createClient(selector);
|
||||
const selector = this.options?.vsCodeLmModelSelector || {}
|
||||
console.debug("Cline <Language Model API>: Creating client with selector:", selector)
|
||||
this.client = await this.createClient(selector)
|
||||
} catch (error) {
|
||||
const message = error instanceof Error ? error.message : 'Unknown error';
|
||||
console.error('Cline <Language Model API>: Client creation failed:', message);
|
||||
throw new Error(`Cline <Language Model API>: Failed to create client: ${message}`);
|
||||
const message = error instanceof Error ? error.message : "Unknown error"
|
||||
console.error("Cline <Language Model API>: Client creation failed:", message)
|
||||
throw new Error(`Cline <Language Model API>: Failed to create client: ${message}`)
|
||||
}
|
||||
}
|
||||
|
||||
return this.client;
|
||||
return this.client
|
||||
}
|
||||
|
||||
private cleanTerminalOutput(text: string): string {
|
||||
if (!text) {
|
||||
return '';
|
||||
return ""
|
||||
}
|
||||
|
||||
return text
|
||||
// Нормализуем переносы строк
|
||||
.replace(/\r\n/g, '\n')
|
||||
.replace(/\r/g, '\n')
|
||||
return (
|
||||
text
|
||||
// Нормализуем переносы строк
|
||||
.replace(/\r\n/g, "\n")
|
||||
.replace(/\r/g, "\n")
|
||||
|
||||
// Удаляем ANSI escape sequences
|
||||
.replace(/\x1B(?:[@-Z\\-_]|\[[0-?]*[ -/]*[@-~])/g, '') // Полный набор ANSI sequences
|
||||
.replace(/\x9B[0-?]*[ -/]*[@-~]/g, '') // CSI sequences
|
||||
// Удаляем ANSI escape sequences
|
||||
.replace(/\x1B(?:[@-Z\\-_]|\[[0-?]*[ -/]*[@-~])/g, "") // Полный набор ANSI sequences
|
||||
.replace(/\x9B[0-?]*[ -/]*[@-~]/g, "") // CSI sequences
|
||||
|
||||
// Удаляем последовательности установки заголовка терминала и прочие OSC sequences
|
||||
.replace(/\x1B\][0-9;]*(?:\x07|\x1B\\)/g, '')
|
||||
// Удаляем последовательности установки заголовка терминала и прочие OSC sequences
|
||||
.replace(/\x1B\][0-9;]*(?:\x07|\x1B\\)/g, "")
|
||||
|
||||
// Удаляем управляющие символы
|
||||
.replace(/[\x00-\x09\x0B-\x0C\x0E-\x1F\x7F]/g, '')
|
||||
// Удаляем управляющие символы
|
||||
.replace(/[\x00-\x09\x0B-\x0C\x0E-\x1F\x7F]/g, "")
|
||||
|
||||
// Удаляем escape-последовательности VS Code
|
||||
.replace(/\x1B[PD].*?\x1B\\/g, '') // DCS sequences
|
||||
.replace(/\x1B_.*?\x1B\\/g, '') // APC sequences
|
||||
.replace(/\x1B\^.*?\x1B\\/g, '') // PM sequences
|
||||
.replace(/\x1B\[[\d;]*[HfABCDEFGJKST]/g, '') // Cursor movement and clear screen
|
||||
// Удаляем escape-последовательности VS Code
|
||||
.replace(/\x1B[PD].*?\x1B\\/g, "") // DCS sequences
|
||||
.replace(/\x1B_.*?\x1B\\/g, "") // APC sequences
|
||||
.replace(/\x1B\^.*?\x1B\\/g, "") // PM sequences
|
||||
.replace(/\x1B\[[\d;]*[HfABCDEFGJKST]/g, "") // Cursor movement and clear screen
|
||||
|
||||
// Удаляем пути Windows и служебную информацию
|
||||
.replace(/^(?:PS )?[A-Z]:\\[^\n]*$/mg, '')
|
||||
.replace(/^;?Cwd=.*$/mg, '')
|
||||
// Удаляем пути Windows и служебную информацию
|
||||
.replace(/^(?:PS )?[A-Z]:\\[^\n]*$/gm, "")
|
||||
.replace(/^;?Cwd=.*$/gm, "")
|
||||
|
||||
// Очищаем экранированные последовательности
|
||||
.replace(/\\x[0-9a-fA-F]{2}/g, '')
|
||||
.replace(/\\u[0-9a-fA-F]{4}/g, '')
|
||||
// Очищаем экранированные последовательности
|
||||
.replace(/\\x[0-9a-fA-F]{2}/g, "")
|
||||
.replace(/\\u[0-9a-fA-F]{4}/g, "")
|
||||
|
||||
// Финальная очистка
|
||||
.replace(/\n{3,}/g, '\n\n') // Убираем множественные пустые строки
|
||||
.trim();
|
||||
// Финальная очистка
|
||||
.replace(/\n{3,}/g, "\n\n") // Убираем множественные пустые строки
|
||||
.trim()
|
||||
)
|
||||
}
|
||||
|
||||
private cleanMessageContent(content: any): any {
|
||||
if (!content) {
|
||||
return content;
|
||||
return content
|
||||
}
|
||||
|
||||
if (typeof content === 'string') {
|
||||
return this.cleanTerminalOutput(content);
|
||||
if (typeof content === "string") {
|
||||
return this.cleanTerminalOutput(content)
|
||||
}
|
||||
|
||||
if (Array.isArray(content)) {
|
||||
return content.map(item => this.cleanMessageContent(item));
|
||||
return content.map((item) => this.cleanMessageContent(item))
|
||||
}
|
||||
|
||||
if (typeof content === 'object') {
|
||||
const cleaned: any = {};
|
||||
if (typeof content === "object") {
|
||||
const cleaned: any = {}
|
||||
for (const [key, value] of Object.entries(content)) {
|
||||
cleaned[key] = this.cleanMessageContent(value);
|
||||
cleaned[key] = this.cleanMessageContent(value)
|
||||
}
|
||||
return cleaned;
|
||||
return cleaned
|
||||
}
|
||||
|
||||
return content;
|
||||
return content
|
||||
}
|
||||
|
||||
async *createMessage(systemPrompt: string, messages: Anthropic.Messages.MessageParam[]): ApiStream {
|
||||
|
||||
// Ensure clean state before starting a new request
|
||||
this.ensureCleanState();
|
||||
const client: vscode.LanguageModelChat = await this.getClient();
|
||||
this.ensureCleanState()
|
||||
const client: vscode.LanguageModelChat = await this.getClient()
|
||||
|
||||
// Clean system prompt and messages
|
||||
const cleanedSystemPrompt = this.cleanTerminalOutput(systemPrompt);
|
||||
const cleanedMessages = messages.map(msg => ({
|
||||
const cleanedSystemPrompt = this.cleanTerminalOutput(systemPrompt)
|
||||
const cleanedMessages = messages.map((msg) => ({
|
||||
...msg,
|
||||
content: this.cleanMessageContent(msg.content)
|
||||
}));
|
||||
content: this.cleanMessageContent(msg.content),
|
||||
}))
|
||||
|
||||
// Convert Anthropic messages to VS Code LM messages
|
||||
const vsCodeLmMessages: vscode.LanguageModelChatMessage[] = [
|
||||
vscode.LanguageModelChatMessage.Assistant(cleanedSystemPrompt),
|
||||
...convertToVsCodeLmMessages(cleanedMessages),
|
||||
];
|
||||
]
|
||||
|
||||
// Initialize cancellation token for the request
|
||||
this.currentRequestCancellation = new vscode.CancellationTokenSource();
|
||||
this.currentRequestCancellation = new vscode.CancellationTokenSource()
|
||||
|
||||
// Calculate input tokens before starting the stream
|
||||
const totalInputTokens: number = await this.calculateTotalInputTokens(systemPrompt, vsCodeLmMessages);
|
||||
const totalInputTokens: number = await this.calculateTotalInputTokens(systemPrompt, vsCodeLmMessages)
|
||||
|
||||
// Accumulate the text and count at the end of the stream to reduce token counting overhead.
|
||||
let accumulatedText: string = '';
|
||||
let accumulatedText: string = ""
|
||||
|
||||
try {
|
||||
|
||||
// Create the response stream with minimal required options
|
||||
const requestOptions: vscode.LanguageModelChatRequestOptions = {
|
||||
justification: `Cline would like to use '${client.name}' from '${client.vendor}', Click 'Allow' to proceed.`
|
||||
};
|
||||
justification: `Cline would like to use '${client.name}' from '${client.vendor}', Click 'Allow' to proceed.`,
|
||||
}
|
||||
|
||||
// Note: Tool support is currently provided by the VSCode Language Model API directly
|
||||
// Extensions can register tools using vscode.lm.registerTool()
|
||||
@@ -368,40 +357,40 @@ export class VsCodeLmHandler implements ApiHandler, SingleCompletionHandler {
|
||||
const response: vscode.LanguageModelChatResponse = await client.sendRequest(
|
||||
vsCodeLmMessages,
|
||||
requestOptions,
|
||||
this.currentRequestCancellation.token
|
||||
);
|
||||
this.currentRequestCancellation.token,
|
||||
)
|
||||
|
||||
// Consume the stream and handle both text and tool call chunks
|
||||
for await (const chunk of response.stream) {
|
||||
if (chunk instanceof vscode.LanguageModelTextPart) {
|
||||
// Validate text part value
|
||||
if (typeof chunk.value !== 'string') {
|
||||
console.warn('Cline <Language Model API>: Invalid text part value received:', chunk.value);
|
||||
continue;
|
||||
if (typeof chunk.value !== "string") {
|
||||
console.warn("Cline <Language Model API>: Invalid text part value received:", chunk.value)
|
||||
continue
|
||||
}
|
||||
|
||||
accumulatedText += chunk.value;
|
||||
accumulatedText += chunk.value
|
||||
yield {
|
||||
type: "text",
|
||||
text: chunk.value,
|
||||
};
|
||||
}
|
||||
} else if (chunk instanceof vscode.LanguageModelToolCallPart) {
|
||||
try {
|
||||
// Validate tool call parameters
|
||||
if (!chunk.name || typeof chunk.name !== 'string') {
|
||||
console.warn('Cline <Language Model API>: Invalid tool name received:', chunk.name);
|
||||
continue;
|
||||
if (!chunk.name || typeof chunk.name !== "string") {
|
||||
console.warn("Cline <Language Model API>: Invalid tool name received:", chunk.name)
|
||||
continue
|
||||
}
|
||||
|
||||
if (!chunk.callId || typeof chunk.callId !== 'string') {
|
||||
console.warn('Cline <Language Model API>: Invalid tool callId received:', chunk.callId);
|
||||
continue;
|
||||
if (!chunk.callId || typeof chunk.callId !== "string") {
|
||||
console.warn("Cline <Language Model API>: Invalid tool callId received:", chunk.callId)
|
||||
continue
|
||||
}
|
||||
|
||||
// Ensure input is a valid object
|
||||
if (!chunk.input || typeof chunk.input !== 'object') {
|
||||
console.warn('Cline <Language Model API>: Invalid tool input received:', chunk.input);
|
||||
continue;
|
||||
if (!chunk.input || typeof chunk.input !== "object") {
|
||||
console.warn("Cline <Language Model API>: Invalid tool input received:", chunk.input)
|
||||
continue
|
||||
}
|
||||
|
||||
// Convert tool calls to text format with proper error handling
|
||||
@@ -409,82 +398,75 @@ export class VsCodeLmHandler implements ApiHandler, SingleCompletionHandler {
|
||||
type: "tool_call",
|
||||
name: chunk.name,
|
||||
arguments: chunk.input,
|
||||
callId: chunk.callId
|
||||
};
|
||||
callId: chunk.callId,
|
||||
}
|
||||
|
||||
const toolCallText = JSON.stringify(toolCall);
|
||||
accumulatedText += toolCallText;
|
||||
const toolCallText = JSON.stringify(toolCall)
|
||||
accumulatedText += toolCallText
|
||||
|
||||
// Log tool call for debugging
|
||||
console.debug('Cline <Language Model API>: Processing tool call:', {
|
||||
console.debug("Cline <Language Model API>: Processing tool call:", {
|
||||
name: chunk.name,
|
||||
callId: chunk.callId,
|
||||
inputSize: JSON.stringify(chunk.input).length
|
||||
});
|
||||
inputSize: JSON.stringify(chunk.input).length,
|
||||
})
|
||||
|
||||
yield {
|
||||
type: "text",
|
||||
text: toolCallText,
|
||||
};
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Cline <Language Model API>: Failed to process tool call:', error);
|
||||
console.error("Cline <Language Model API>: Failed to process tool call:", error)
|
||||
// Continue processing other chunks even if one fails
|
||||
continue;
|
||||
continue
|
||||
}
|
||||
} else {
|
||||
console.warn('Cline <Language Model API>: Unknown chunk type received:', chunk);
|
||||
console.warn("Cline <Language Model API>: Unknown chunk type received:", chunk)
|
||||
}
|
||||
}
|
||||
|
||||
// Count tokens in the accumulated text after stream completion
|
||||
const totalOutputTokens: number = await this.countTokens(accumulatedText);
|
||||
const totalOutputTokens: number = await this.countTokens(accumulatedText)
|
||||
|
||||
// Report final usage after stream completion
|
||||
yield {
|
||||
type: "usage",
|
||||
inputTokens: totalInputTokens,
|
||||
outputTokens: totalOutputTokens,
|
||||
totalCost: calculateApiCost(
|
||||
this.getModel().info,
|
||||
totalInputTokens,
|
||||
totalOutputTokens
|
||||
)
|
||||
};
|
||||
}
|
||||
catch (error: unknown) {
|
||||
|
||||
this.ensureCleanState();
|
||||
totalCost: calculateApiCost(this.getModel().info, totalInputTokens, totalOutputTokens),
|
||||
}
|
||||
} catch (error: unknown) {
|
||||
this.ensureCleanState()
|
||||
|
||||
if (error instanceof vscode.CancellationError) {
|
||||
|
||||
throw new Error("Cline <Language Model API>: Request cancelled by user");
|
||||
throw new Error("Cline <Language Model API>: Request cancelled by user")
|
||||
}
|
||||
|
||||
if (error instanceof Error) {
|
||||
console.error('Cline <Language Model API>: Stream error details:', {
|
||||
console.error("Cline <Language Model API>: Stream error details:", {
|
||||
message: error.message,
|
||||
stack: error.stack,
|
||||
name: error.name
|
||||
});
|
||||
name: error.name,
|
||||
})
|
||||
|
||||
// Return original error if it's already an Error instance
|
||||
throw error;
|
||||
} else if (typeof error === 'object' && error !== null) {
|
||||
throw error
|
||||
} else if (typeof error === "object" && error !== null) {
|
||||
// Handle error-like objects
|
||||
const errorDetails = JSON.stringify(error, null, 2);
|
||||
console.error('Cline <Language Model API>: Stream error object:', errorDetails);
|
||||
throw new Error(`Cline <Language Model API>: Response stream error: ${errorDetails}`);
|
||||
const errorDetails = JSON.stringify(error, null, 2)
|
||||
console.error("Cline <Language Model API>: Stream error object:", errorDetails)
|
||||
throw new Error(`Cline <Language Model API>: Response stream error: ${errorDetails}`)
|
||||
} else {
|
||||
// Fallback for unknown error types
|
||||
const errorMessage = String(error);
|
||||
console.error('Cline <Language Model API>: Unknown stream error:', errorMessage);
|
||||
throw new Error(`Cline <Language Model API>: Response stream error: ${errorMessage}`);
|
||||
const errorMessage = String(error)
|
||||
console.error("Cline <Language Model API>: Unknown stream error:", errorMessage)
|
||||
throw new Error(`Cline <Language Model API>: Response stream error: ${errorMessage}`)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Return model information based on the current client state
|
||||
getModel(): { id: string; info: ModelInfo; } {
|
||||
getModel(): { id: string; info: ModelInfo } {
|
||||
if (this.client) {
|
||||
// Validate client properties
|
||||
const requiredProps = {
|
||||
@@ -492,68 +474,69 @@ export class VsCodeLmHandler implements ApiHandler, SingleCompletionHandler {
|
||||
vendor: this.client.vendor,
|
||||
family: this.client.family,
|
||||
version: this.client.version,
|
||||
maxInputTokens: this.client.maxInputTokens
|
||||
};
|
||||
maxInputTokens: this.client.maxInputTokens,
|
||||
}
|
||||
|
||||
// Log any missing properties for debugging
|
||||
for (const [prop, value] of Object.entries(requiredProps)) {
|
||||
if (!value && value !== 0) {
|
||||
console.warn(`Cline <Language Model API>: Client missing ${prop} property`);
|
||||
console.warn(`Cline <Language Model API>: Client missing ${prop} property`)
|
||||
}
|
||||
}
|
||||
|
||||
// Construct model ID using available information
|
||||
const modelParts = [
|
||||
this.client.vendor,
|
||||
this.client.family,
|
||||
this.client.version
|
||||
].filter(Boolean);
|
||||
const modelParts = [this.client.vendor, this.client.family, this.client.version].filter(Boolean)
|
||||
|
||||
const modelId = this.client.id || modelParts.join(SELECTOR_SEPARATOR);
|
||||
const modelId = this.client.id || modelParts.join(SELECTOR_SEPARATOR)
|
||||
|
||||
// Build model info with conservative defaults for missing values
|
||||
const modelInfo: ModelInfo = {
|
||||
maxTokens: -1, // Unlimited tokens by default
|
||||
contextWindow: typeof this.client.maxInputTokens === 'number'
|
||||
? Math.max(0, this.client.maxInputTokens)
|
||||
: openAiModelInfoSaneDefaults.contextWindow,
|
||||
contextWindow:
|
||||
typeof this.client.maxInputTokens === "number"
|
||||
? Math.max(0, this.client.maxInputTokens)
|
||||
: openAiModelInfoSaneDefaults.contextWindow,
|
||||
supportsImages: false, // VSCode Language Model API currently doesn't support image inputs
|
||||
supportsPromptCache: true,
|
||||
inputPrice: 0,
|
||||
outputPrice: 0,
|
||||
description: `VSCode Language Model: ${modelId}`
|
||||
};
|
||||
description: `VSCode Language Model: ${modelId}`,
|
||||
}
|
||||
|
||||
return { id: modelId, info: modelInfo };
|
||||
return { id: modelId, info: modelInfo }
|
||||
}
|
||||
|
||||
// Fallback when no client is available
|
||||
const fallbackId = this.options.vsCodeLmModelSelector
|
||||
? stringifyVsCodeLmModelSelector(this.options.vsCodeLmModelSelector)
|
||||
: "vscode-lm";
|
||||
: "vscode-lm"
|
||||
|
||||
console.debug('Cline <Language Model API>: No client available, using fallback model info');
|
||||
console.debug("Cline <Language Model API>: No client available, using fallback model info")
|
||||
|
||||
return {
|
||||
id: fallbackId,
|
||||
info: {
|
||||
...openAiModelInfoSaneDefaults,
|
||||
description: `VSCode Language Model (Fallback): ${fallbackId}`
|
||||
}
|
||||
};
|
||||
description: `VSCode Language Model (Fallback): ${fallbackId}`,
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
async completePrompt(prompt: string): Promise<string> {
|
||||
try {
|
||||
const client = await this.getClient();
|
||||
const response = await client.sendRequest([vscode.LanguageModelChatMessage.User(prompt)], {}, new vscode.CancellationTokenSource().token);
|
||||
let result = "";
|
||||
const client = await this.getClient()
|
||||
const response = await client.sendRequest(
|
||||
[vscode.LanguageModelChatMessage.User(prompt)],
|
||||
{},
|
||||
new vscode.CancellationTokenSource().token,
|
||||
)
|
||||
let result = ""
|
||||
for await (const chunk of response.stream) {
|
||||
if (chunk instanceof vscode.LanguageModelTextPart) {
|
||||
result += chunk.value;
|
||||
result += chunk.value
|
||||
}
|
||||
}
|
||||
return result;
|
||||
return result
|
||||
} catch (error) {
|
||||
if (error instanceof Error) {
|
||||
throw new Error(`VSCode LM completion error: ${error.message}`)
|
||||
|
||||
Reference in New Issue
Block a user