mirror of
https://github.com/larsbaunwall/vscode-copilot-bridge.git
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Add copilot instructions
This commit is contained in:
Lars Baunwall
parent
6b20e60f5b
commit
e4a24785bb
4 changed files with 324 additions and 40 deletions
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@ -2,11 +2,51 @@ import * as vscode from 'vscode';
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import type { IncomingMessage, ServerResponse } from 'http';
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import { state } from '../../state';
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import { getBridgeConfig } from '../../config';
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import { isChatCompletionRequest, normalizeMessagesLM } from '../../messages';
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import { isChatCompletionRequest, normalizeMessagesLM, convertOpenAIToolsToLM, convertFunctionsToTools } from '../../messages';
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import { getModel, hasLMApi } from '../../models';
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import { readJson, writeErrorResponse, writeJson } from '../utils';
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import { verbose } from '../../log';
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// OpenAI response interfaces for better typing
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interface OpenAIToolCall {
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id: string;
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type: 'function';
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function: {
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name: string;
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arguments: string;
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};
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}
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interface OpenAIMessage {
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role: 'assistant';
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content: string | null;
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tool_calls?: OpenAIToolCall[];
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function_call?: {
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name: string;
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arguments: string;
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};
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}
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interface OpenAIChoice {
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index: number;
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message?: OpenAIMessage;
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delta?: Partial<OpenAIMessage>;
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finish_reason: 'stop' | 'length' | 'tool_calls' | 'content_filter' | 'function_call' | null;
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}
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interface OpenAIResponse {
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id: string;
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object: 'chat.completion' | 'chat.completion.chunk';
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created: number;
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model: string;
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choices: OpenAIChoice[];
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usage?: {
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prompt_tokens: number;
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completion_tokens: number;
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total_tokens: number;
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};
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}
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export const handleChatCompletion = async (req: IncomingMessage, res: ServerResponse): Promise<void> => {
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const config = getBridgeConfig();
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state.activeRequests++;
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@ -20,6 +60,14 @@ export const handleChatCompletion = async (req: IncomingMessage, res: ServerResp
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const requestedModel = body.model;
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const stream = body.stream !== false; // default true
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// Handle tools and deprecated functions
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let tools = body.tools || [];
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if (body.functions) {
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// Convert deprecated functions to tools format
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tools = [...tools, ...convertFunctionsToTools(body.functions)];
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}
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const model = await getModel(false, requestedModel);
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if (!model) {
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@ -33,11 +81,19 @@ export const handleChatCompletion = async (req: IncomingMessage, res: ServerResp
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}
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const lmMessages = normalizeMessagesLM(body.messages, config.historyWindow) as vscode.LanguageModelChatMessage[];
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verbose(`LM request via API model=${model.family || model.id || model.name || 'unknown'}`);
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const lmTools = convertOpenAIToolsToLM(tools);
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// Prepare request options for Language Model API
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const requestOptions: any = {};
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if (lmTools.length > 0) {
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requestOptions.tools = lmTools;
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}
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verbose(`LM request via API model=${model.family || model.id || model.name || 'unknown'} tools=${lmTools.length}`);
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const cts = new vscode.CancellationTokenSource();
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const response = await model.sendRequest(lmMessages, {}, cts.token);
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await sendResponse(res, response, stream);
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const response = await model.sendRequest(lmMessages, requestOptions, cts.token);
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await sendResponse(res, response, stream, body, tools);
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} catch (e) {
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const msg = e instanceof Error ? e.message : String(e);
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writeErrorResponse(res, 500, msg || 'internal_error', 'server_error', 'internal_error');
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@ -47,40 +103,157 @@ export const handleChatCompletion = async (req: IncomingMessage, res: ServerResp
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}
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};
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const sendResponse = async (res: ServerResponse, response: vscode.LanguageModelChatResponse, stream: boolean): Promise<void> => {
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const sendResponse = async (
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res: ServerResponse,
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response: vscode.LanguageModelChatResponse,
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stream: boolean,
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requestBody?: any,
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tools?: any[]
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): Promise<void> => {
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const modelName = requestBody?.model || 'copilot';
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const responseId = `chatcmpl-${Math.random().toString(36).slice(2)}`;
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const created = Math.floor(Date.now() / 1000);
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if (stream) {
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res.writeHead(200, {
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'Content-Type': 'text/event-stream',
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'Cache-Control': 'no-cache',
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'Connection': 'keep-alive',
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});
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const id = `cmp_${Math.random().toString(36).slice(2)}`;
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verbose(`SSE start id=${id}`);
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for await (const fragment of response.text) {
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res.write(`data: ${JSON.stringify({
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id,
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object: 'chat.completion.chunk',
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choices: [{ index: 0, delta: { content: fragment } }],
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})}\n\n`);
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verbose(`SSE start id=${responseId}`);
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let toolCalls: OpenAIToolCall[] = [];
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for await (const part of response.stream) {
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// Check if this part is a LanguageModelToolCallPart
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if (part && typeof part === 'object' && 'callId' in part && 'name' in part && 'input' in part) {
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const toolCallPart = part as vscode.LanguageModelToolCallPart;
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const toolCall: OpenAIToolCall = {
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id: toolCallPart.callId,
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type: 'function',
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function: {
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name: toolCallPart.name,
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arguments: JSON.stringify(toolCallPart.input)
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}
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};
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toolCalls.push(toolCall);
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// Send tool call in streaming format
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const chunkResponse: OpenAIResponse = {
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id: responseId,
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object: 'chat.completion.chunk',
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created,
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model: modelName,
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choices: [{
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index: 0,
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delta: {
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tool_calls: [toolCall]
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},
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finish_reason: null
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}]
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};
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res.write(`data: ${JSON.stringify(chunkResponse)}\n\n`);
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} else if (typeof part === 'string' || (part && typeof part === 'object' && 'value' in part)) {
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// Handle text content
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const content = typeof part === 'string' ? part : (part as any).value || '';
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if (content) {
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const chunkResponse: OpenAIResponse = {
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id: responseId,
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object: 'chat.completion.chunk',
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created,
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model: modelName,
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choices: [{
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index: 0,
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delta: { content },
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finish_reason: null
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}]
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};
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res.write(`data: ${JSON.stringify(chunkResponse)}\n\n`);
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}
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}
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}
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verbose(`SSE end id=${id}`);
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// Send final chunk
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const finishReason: OpenAIChoice['finish_reason'] = toolCalls.length > 0 ? 'tool_calls' : 'stop';
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const finalChunkResponse: OpenAIResponse = {
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id: responseId,
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object: 'chat.completion.chunk',
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created,
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model: modelName,
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choices: [{
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index: 0,
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delta: {},
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finish_reason: finishReason
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}]
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};
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res.write(`data: ${JSON.stringify(finalChunkResponse)}\n\n`);
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verbose(`SSE end id=${responseId}`);
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res.write('data: [DONE]\n\n');
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res.end();
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return;
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}
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// Non-streaming response
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let content = '';
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for await (const fragment of response.text) content += fragment;
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verbose(`Non-stream complete len=${content.length}`);
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writeJson(res, 200, {
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id: `cmpl_${Math.random().toString(36).slice(2)}`,
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let toolCalls: OpenAIToolCall[] = [];
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for await (const part of response.stream) {
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if (part && typeof part === 'object' && 'callId' in part && 'name' in part && 'input' in part) {
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// Handle VS Code LanguageModelToolCallPart
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const toolCallPart = part as vscode.LanguageModelToolCallPart;
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const toolCall: OpenAIToolCall = {
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id: toolCallPart.callId,
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type: 'function',
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function: {
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name: toolCallPart.name,
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arguments: JSON.stringify(toolCallPart.input)
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}
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};
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toolCalls.push(toolCall);
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} else if (typeof part === 'string' || (part && typeof part === 'object' && 'value' in part)) {
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// Handle text content
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content += typeof part === 'string' ? part : (part as any).value || '';
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}
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}
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verbose(`Non-stream complete len=${content.length} tool_calls=${toolCalls.length}`);
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const message: OpenAIMessage = {
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role: 'assistant',
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content: toolCalls.length > 0 ? null : content,
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};
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// Add tool_calls if present
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if (toolCalls.length > 0) {
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message.tool_calls = toolCalls;
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// For backward compatibility, also add function_call if there's exactly one tool call
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if (toolCalls.length === 1 && requestBody?.function_call !== undefined) {
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message.function_call = {
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name: toolCalls[0].function.name,
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arguments: toolCalls[0].function.arguments
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};
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}
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}
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const responseObj: OpenAIResponse = {
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id: responseId,
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object: 'chat.completion',
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choices: [
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{
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index: 0,
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message: { role: 'assistant', content },
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finish_reason: 'stop',
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},
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],
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});
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created,
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model: modelName,
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choices: [{
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index: 0,
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message,
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finish_reason: toolCalls.length > 0 ? 'tool_calls' : 'stop',
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}],
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usage: {
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prompt_tokens: 0, // VS Code API doesn't provide token counts
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completion_tokens: 0,
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total_tokens: 0
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}
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};
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writeJson(res, 200, responseObj);
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};
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@ -14,10 +14,21 @@ export const handleHealthCheck = async (res: ServerResponse, v: boolean): Promis
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const unavailableReason = state.modelCache
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? undefined
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: (!hasLM ? 'missing_language_model_api' : (state.lastReason || 'copilot_model_unavailable'));
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writeJson(res, 200, {
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ok: true,
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status: 'operational',
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copilot: state.modelCache ? 'ok' : 'unavailable',
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reason: unavailableReason,
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version: vscode.version,
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features: {
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chat_completions: true,
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streaming: true,
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tool_calling: true,
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function_calling: true, // deprecated but supported
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models_list: true
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},
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active_requests: state.activeRequests,
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model_attempted: state.modelAttempted
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});
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};
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@ -4,17 +4,29 @@ import type { ServerResponse } from 'http';
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export const handleModelsRequest = async (res: ServerResponse): Promise<void> => {
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try {
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const models = await listCopilotModels();
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const modelIds = await listCopilotModels();
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const models = modelIds.map((id: string) => ({
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id,
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object: 'model',
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created: Math.floor(Date.now() / 1000),
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owned_by: 'copilot',
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permission: [],
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root: id,
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parent: null,
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}));
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writeJson(res, 200, {
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data: models.map((id: string) => ({
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id,
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object: 'model',
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owned_by: 'vscode-bridge',
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})),
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object: 'list',
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data: models,
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});
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} catch {
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writeJson(res, 200, {
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data: [],
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} catch (e) {
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const msg = e instanceof Error ? e.message : String(e);
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writeJson(res, 500, {
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error: {
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message: msg || 'Failed to list models',
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type: 'server_error',
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code: 'internal_error'
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}
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});
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}
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};
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@ -1,8 +1,12 @@
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import * as vscode from 'vscode';
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export interface ChatMessage {
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readonly role: 'system' | 'user' | 'assistant';
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readonly content: string | MessageContent[];
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readonly role: 'system' | 'user' | 'assistant' | 'tool';
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readonly content?: string | MessageContent[] | null;
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readonly name?: string;
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readonly tool_calls?: ToolCall[];
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readonly tool_call_id?: string;
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readonly function_call?: FunctionCall;
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}
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export interface MessageContent {
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@ -11,22 +15,87 @@ export interface MessageContent {
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readonly [key: string]: unknown;
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}
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export interface ToolCall {
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readonly id: string;
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readonly type: 'function';
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readonly function: FunctionCall;
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}
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export interface FunctionCall {
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readonly name: string;
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readonly arguments: string;
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}
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export interface Tool {
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readonly type: 'function';
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readonly function: ToolFunction;
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}
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export interface ToolFunction {
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readonly name: string;
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readonly description?: string;
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readonly parameters?: object;
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}
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export interface ChatCompletionRequest {
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readonly model?: string;
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readonly messages: ChatMessage[];
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readonly stream?: boolean;
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readonly tools?: Tool[];
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readonly tool_choice?: 'none' | 'auto' | 'required' | { type: 'function'; function: { name: string } };
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readonly parallel_tool_calls?: boolean;
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readonly functions?: ToolFunction[]; // Deprecated, use tools instead
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readonly function_call?: 'none' | 'auto' | { name: string }; // Deprecated, use tool_choice instead
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readonly temperature?: number;
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readonly top_p?: number;
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readonly n?: number;
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readonly stop?: string | string[];
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readonly max_tokens?: number;
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readonly max_completion_tokens?: number;
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readonly presence_penalty?: number;
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readonly frequency_penalty?: number;
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readonly logit_bias?: Record<string, number>;
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readonly logprobs?: boolean;
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readonly top_logprobs?: number;
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readonly user?: string;
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readonly seed?: number;
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readonly response_format?: {
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readonly type: 'text' | 'json_object' | 'json_schema';
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readonly json_schema?: {
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readonly name: string;
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readonly schema: object;
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readonly strict?: boolean;
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};
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};
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readonly [key: string]: unknown;
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}
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const VALID_ROLES = ['system', 'user', 'assistant'] as const;
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const VALID_ROLES = ['system', 'user', 'assistant', 'tool'] as const;
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type Role = typeof VALID_ROLES[number];
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const isValidRole = (role: unknown): role is Role => typeof role === 'string' && VALID_ROLES.includes(role as Role);
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export const isChatMessage = (msg: unknown): msg is ChatMessage => {
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if (typeof msg !== 'object' || msg === null) return false;
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const candidate = msg as Record<string, unknown>;
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if (!('role' in candidate) || !('content' in candidate)) return false;
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return isValidRole(candidate.role) && candidate.content !== undefined && candidate.content !== null;
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if (!('role' in candidate)) return false;
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if (!isValidRole(candidate.role)) return false;
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// Tool messages require tool_call_id and content
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if (candidate.role === 'tool') {
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return typeof candidate.tool_call_id === 'string' &&
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(typeof candidate.content === 'string' || candidate.content === null);
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}
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// Assistant messages can have content and/or tool_calls/function_call
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if (candidate.role === 'assistant') {
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const hasContent = candidate.content !== undefined;
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const hasToolCalls = Array.isArray(candidate.tool_calls);
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const hasFunctionCall = typeof candidate.function_call === 'object' && candidate.function_call !== null;
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return hasContent || hasToolCalls || hasFunctionCall;
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}
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// System and user messages must have content
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return candidate.content !== undefined && candidate.content !== null;
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};
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export const isChatCompletionRequest = (body: unknown): body is ChatCompletionRequest => {
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@ -37,6 +106,25 @@ export const isChatCompletionRequest = (body: unknown): body is ChatCompletionRe
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return Array.isArray(messages) && messages.length > 0 && messages.every(isChatMessage);
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};
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// Convert OpenAI tools to VS Code Language Model tools
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export const convertOpenAIToolsToLM = (tools?: Tool[]): vscode.LanguageModelChatTool[] => {
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if (!tools) return [];
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return tools.map(tool => ({
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name: tool.function.name,
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description: tool.function.description || '',
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inputSchema: tool.function.parameters
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}));
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};
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// Convert deprecated functions to tools format
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export const convertFunctionsToTools = (functions?: ToolFunction[]): Tool[] => {
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if (!functions) return [];
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return functions.map(func => ({
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type: 'function' as const,
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function: func
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}));
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};
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const toText = (content: unknown): string => {
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if (typeof content === 'string') return content;
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if (Array.isArray(content)) return content.map(toText).join('\n');
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