mirror of
https://github.com/pacnpal/Roo-Code.git
synced 2025-12-20 04:11:10 -05:00
Spacing adjustments
This commit is contained in:
Matt Rubens
@@ -15,43 +15,40 @@ import { VsCodeLmHandler } from "./providers/vscode-lm"
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import { ApiStream } from "./transform/stream"
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export interface SingleCompletionHandler {
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completePrompt(prompt: string): Promise<string>
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completePrompt(prompt: string): Promise<string>
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}
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export interface ApiHandler {
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createMessage(systemPrompt: string, messages: Anthropic.Messages.MessageParam[]): ApiStream
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getModel(): { id: string; info: ModelInfo }
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createMessage(systemPrompt: string, messages: Anthropic.Messages.MessageParam[]): ApiStream
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getModel(): { id: string; info: ModelInfo }
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}
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export function buildApiHandler(configuration: ApiConfiguration): ApiHandler {
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const { apiProvider, ...options } = configuration
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switch (apiProvider) {
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case "anthropic":
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return new AnthropicHandler(options)
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case "glama":
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return new GlamaHandler(options)
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case "openrouter":
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return new OpenRouterHandler(options)
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case "bedrock":
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return new AwsBedrockHandler(options)
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case "vertex":
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return new VertexHandler(options)
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case "openai":
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return new OpenAiHandler(options)
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case "ollama":
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return new OllamaHandler(options)
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case "lmstudio":
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return new LmStudioHandler(options)
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case "gemini":
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return new GeminiHandler(options)
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case "openai-native":
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return new OpenAiNativeHandler(options)
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case "deepseek":
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return new DeepSeekHandler(options)
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case "vscode-lm":
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return new VsCodeLmHandler(options)
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default:
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return new AnthropicHandler(options)
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}
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const { apiProvider, ...options } = configuration
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switch (apiProvider) {
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case "anthropic":
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return new AnthropicHandler(options)
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case "glama":
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return new GlamaHandler(options)
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case "openrouter":
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return new OpenRouterHandler(options)
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case "bedrock":
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return new AwsBedrockHandler(options)
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case "vertex":
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return new VertexHandler(options)
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case "openai":
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return new OpenAiHandler(options)
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case "ollama":
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return new OllamaHandler(options)
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case "lmstudio":
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return new LmStudioHandler(options)
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case "gemini":
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return new GeminiHandler(options)
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case "openai-native":
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return new OpenAiNativeHandler(options)
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case "deepseek":
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return new DeepSeekHandler(options)
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default:
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return new AnthropicHandler(options)
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}
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}
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File diff suppressed because it is too large
Load Diff
@@ -5,205 +5,205 @@ import * as vscode from 'vscode';
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* Safely converts a value into a plain object.
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*/
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function asObjectSafe(value: any): object {
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// Handle null/undefined
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if (!value) {
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return {};
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}
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// Handle null/undefined
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if (!value) {
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return {};
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}
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try {
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// Handle strings that might be JSON
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if (typeof value === 'string') {
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return JSON.parse(value);
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}
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try {
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// Handle strings that might be JSON
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if (typeof value === 'string') {
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return JSON.parse(value);
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}
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// Handle pre-existing objects
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if (typeof value === 'object') {
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return Object.assign({}, value);
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}
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// Handle pre-existing objects
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if (typeof value === 'object') {
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return Object.assign({}, value);
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}
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return {};
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}
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catch (error) {
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console.warn('Cline <Language Model API>: Failed to parse object:', error);
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return {};
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}
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return {};
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}
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catch (error) {
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console.warn('Cline <Language Model API>: Failed to parse object:', error);
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return {};
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}
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}
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export function convertToVsCodeLmMessages(anthropicMessages: Anthropic.Messages.MessageParam[]): vscode.LanguageModelChatMessage[] {
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const vsCodeLmMessages: vscode.LanguageModelChatMessage[] = [];
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const vsCodeLmMessages: vscode.LanguageModelChatMessage[] = [];
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for (const anthropicMessage of anthropicMessages) {
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// Handle simple string messages
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if (typeof anthropicMessage.content === "string") {
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vsCodeLmMessages.push(
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anthropicMessage.role === "assistant"
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? vscode.LanguageModelChatMessage.Assistant(anthropicMessage.content)
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: vscode.LanguageModelChatMessage.User(anthropicMessage.content)
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);
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continue;
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}
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for (const anthropicMessage of anthropicMessages) {
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// Handle simple string messages
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if (typeof anthropicMessage.content === "string") {
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vsCodeLmMessages.push(
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anthropicMessage.role === "assistant"
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? vscode.LanguageModelChatMessage.Assistant(anthropicMessage.content)
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: vscode.LanguageModelChatMessage.User(anthropicMessage.content)
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);
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continue;
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}
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// Handle complex message structures
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switch (anthropicMessage.role) {
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case "user": {
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const { nonToolMessages, toolMessages } = anthropicMessage.content.reduce<{
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nonToolMessages: (Anthropic.TextBlockParam | Anthropic.ImageBlockParam)[];
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toolMessages: Anthropic.ToolResultBlockParam[];
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}>(
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(acc, part) => {
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if (part.type === "tool_result") {
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acc.toolMessages.push(part);
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}
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else if (part.type === "text" || part.type === "image") {
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acc.nonToolMessages.push(part);
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}
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return acc;
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},
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{ nonToolMessages: [], toolMessages: [] },
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);
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// Handle complex message structures
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switch (anthropicMessage.role) {
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case "user": {
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const { nonToolMessages, toolMessages } = anthropicMessage.content.reduce<{
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nonToolMessages: (Anthropic.TextBlockParam | Anthropic.ImageBlockParam)[];
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toolMessages: Anthropic.ToolResultBlockParam[];
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}>(
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(acc, part) => {
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if (part.type === "tool_result") {
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acc.toolMessages.push(part);
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}
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else if (part.type === "text" || part.type === "image") {
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acc.nonToolMessages.push(part);
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}
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return acc;
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},
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{ nonToolMessages: [], toolMessages: [] },
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);
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// Process tool messages first then non-tool messages
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const contentParts = [
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// Convert tool messages to ToolResultParts
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...toolMessages.map((toolMessage) => {
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// Process tool result content into TextParts
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const toolContentParts: vscode.LanguageModelTextPart[] = (
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typeof toolMessage.content === "string"
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? [new vscode.LanguageModelTextPart(toolMessage.content)]
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: (
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toolMessage.content?.map((part) => {
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if (part.type === "image") {
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return new vscode.LanguageModelTextPart(
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`[Image (${part.source?.type || 'Unknown source-type'}): ${part.source?.media_type || 'unknown media-type'} not supported by VSCode LM API]`
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);
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}
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return new vscode.LanguageModelTextPart(part.text);
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})
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?? [new vscode.LanguageModelTextPart("")]
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)
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);
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// Process tool messages first then non-tool messages
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const contentParts = [
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// Convert tool messages to ToolResultParts
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...toolMessages.map((toolMessage) => {
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// Process tool result content into TextParts
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const toolContentParts: vscode.LanguageModelTextPart[] = (
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typeof toolMessage.content === "string"
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? [new vscode.LanguageModelTextPart(toolMessage.content)]
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: (
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toolMessage.content?.map((part) => {
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if (part.type === "image") {
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return new vscode.LanguageModelTextPart(
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`[Image (${part.source?.type || 'Unknown source-type'}): ${part.source?.media_type || 'unknown media-type'} not supported by VSCode LM API]`
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);
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}
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return new vscode.LanguageModelTextPart(part.text);
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})
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?? [new vscode.LanguageModelTextPart("")]
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)
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);
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return new vscode.LanguageModelToolResultPart(
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toolMessage.tool_use_id,
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toolContentParts
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);
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}),
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return new vscode.LanguageModelToolResultPart(
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toolMessage.tool_use_id,
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toolContentParts
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);
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}),
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// Convert non-tool messages to TextParts after tool messages
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...nonToolMessages.map((part) => {
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if (part.type === "image") {
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return new vscode.LanguageModelTextPart(
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`[Image (${part.source?.type || 'Unknown source-type'}): ${part.source?.media_type || 'unknown media-type'} not supported by VSCode LM API]`
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);
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}
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return new vscode.LanguageModelTextPart(part.text);
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})
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];
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// Convert non-tool messages to TextParts after tool messages
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...nonToolMessages.map((part) => {
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if (part.type === "image") {
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return new vscode.LanguageModelTextPart(
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`[Image (${part.source?.type || 'Unknown source-type'}): ${part.source?.media_type || 'unknown media-type'} not supported by VSCode LM API]`
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);
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}
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return new vscode.LanguageModelTextPart(part.text);
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})
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];
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// Add single user message with all content parts
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vsCodeLmMessages.push(vscode.LanguageModelChatMessage.User(contentParts));
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break;
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}
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// Add single user message with all content parts
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vsCodeLmMessages.push(vscode.LanguageModelChatMessage.User(contentParts));
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break;
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}
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case "assistant": {
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const { nonToolMessages, toolMessages } = anthropicMessage.content.reduce<{
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nonToolMessages: (Anthropic.TextBlockParam | Anthropic.ImageBlockParam)[];
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toolMessages: Anthropic.ToolUseBlockParam[];
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}>(
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(acc, part) => {
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if (part.type === "tool_use") {
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acc.toolMessages.push(part);
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}
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else if (part.type === "text" || part.type === "image") {
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acc.nonToolMessages.push(part);
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}
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return acc;
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},
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{ nonToolMessages: [], toolMessages: [] },
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);
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case "assistant": {
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const { nonToolMessages, toolMessages } = anthropicMessage.content.reduce<{
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nonToolMessages: (Anthropic.TextBlockParam | Anthropic.ImageBlockParam)[];
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toolMessages: Anthropic.ToolUseBlockParam[];
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}>(
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(acc, part) => {
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if (part.type === "tool_use") {
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acc.toolMessages.push(part);
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}
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else if (part.type === "text" || part.type === "image") {
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acc.nonToolMessages.push(part);
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}
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return acc;
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},
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{ nonToolMessages: [], toolMessages: [] },
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);
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// Process tool messages first then non-tool messages
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const contentParts = [
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// Convert tool messages to ToolCallParts first
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...toolMessages.map((toolMessage) =>
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new vscode.LanguageModelToolCallPart(
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toolMessage.id,
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toolMessage.name,
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asObjectSafe(toolMessage.input)
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)
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),
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// Process tool messages first then non-tool messages
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const contentParts = [
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// Convert tool messages to ToolCallParts first
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...toolMessages.map((toolMessage) =>
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new vscode.LanguageModelToolCallPart(
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toolMessage.id,
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toolMessage.name,
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asObjectSafe(toolMessage.input)
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)
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),
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// Convert non-tool messages to TextParts after tool messages
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...nonToolMessages.map((part) => {
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if (part.type === "image") {
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return new vscode.LanguageModelTextPart("[Image generation not supported by VSCode LM API]");
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}
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return new vscode.LanguageModelTextPart(part.text);
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})
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];
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// Convert non-tool messages to TextParts after tool messages
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...nonToolMessages.map((part) => {
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if (part.type === "image") {
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return new vscode.LanguageModelTextPart("[Image generation not supported by VSCode LM API]");
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}
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return new vscode.LanguageModelTextPart(part.text);
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})
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];
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// Add the assistant message to the list of messages
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vsCodeLmMessages.push(vscode.LanguageModelChatMessage.Assistant(contentParts));
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break;
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}
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}
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}
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// Add the assistant message to the list of messages
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vsCodeLmMessages.push(vscode.LanguageModelChatMessage.Assistant(contentParts));
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break;
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}
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}
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}
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return vsCodeLmMessages;
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return vsCodeLmMessages;
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}
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export function convertToAnthropicRole(vsCodeLmMessageRole: vscode.LanguageModelChatMessageRole): string | null {
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switch (vsCodeLmMessageRole) {
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case vscode.LanguageModelChatMessageRole.Assistant:
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return "assistant";
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case vscode.LanguageModelChatMessageRole.User:
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return "user";
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default:
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return null;
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}
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switch (vsCodeLmMessageRole) {
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case vscode.LanguageModelChatMessageRole.Assistant:
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return "assistant";
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case vscode.LanguageModelChatMessageRole.User:
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return "user";
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default:
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return null;
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}
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}
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export async function convertToAnthropicMessage(vsCodeLmMessage: vscode.LanguageModelChatMessage): Promise<Anthropic.Messages.Message> {
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const anthropicRole: string | null = convertToAnthropicRole(vsCodeLmMessage.role);
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if (anthropicRole !== "assistant") {
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throw new Error("Cline <Language Model API>: Only assistant messages are supported.");
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}
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const anthropicRole: string | null = convertToAnthropicRole(vsCodeLmMessage.role);
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if (anthropicRole !== "assistant") {
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throw new Error("Cline <Language Model API>: Only assistant messages are supported.");
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}
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return {
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id: crypto.randomUUID(),
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type: "message",
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model: "vscode-lm",
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role: anthropicRole,
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content: (
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vsCodeLmMessage.content
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.map((part): Anthropic.ContentBlock | null => {
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if (part instanceof vscode.LanguageModelTextPart) {
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return {
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type: "text",
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text: part.value
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};
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}
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return {
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id: crypto.randomUUID(),
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type: "message",
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model: "vscode-lm",
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role: anthropicRole,
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content: (
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vsCodeLmMessage.content
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.map((part): Anthropic.ContentBlock | null => {
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if (part instanceof vscode.LanguageModelTextPart) {
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return {
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type: "text",
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text: part.value
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};
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}
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if (part instanceof vscode.LanguageModelToolCallPart) {
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return {
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type: "tool_use",
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id: part.callId || crypto.randomUUID(),
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name: part.name,
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input: asObjectSafe(part.input)
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};
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}
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if (part instanceof vscode.LanguageModelToolCallPart) {
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return {
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type: "tool_use",
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id: part.callId || crypto.randomUUID(),
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name: part.name,
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input: asObjectSafe(part.input)
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};
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}
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return null;
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})
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.filter(
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(part): part is Anthropic.ContentBlock => part !== null
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)
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),
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stop_reason: null,
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stop_sequence: null,
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usage: {
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input_tokens: 0,
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output_tokens: 0,
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}
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};
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return null;
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})
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.filter(
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(part): part is Anthropic.ContentBlock => part !== null
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)
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),
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stop_reason: null,
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stop_sequence: null,
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usage: {
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input_tokens: 0,
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output_tokens: 0,
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}
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};
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}
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Reference in New Issue
Block a user