mirror of
https://github.com/microsoft/vscode-extension-samples.git
synced 2026-04-27 16:55:44 +08:00
Demo of function calling
This commit is contained in:
Rob Lourens
7
chat-sample/package-lock.json
generated
7
chat-sample/package-lock.json
generated
@ -10,6 +10,7 @@
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"hasInstallScript": true,
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"devDependencies": {
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"@types/node": "^20.5.9",
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"@types/vscode": "^1.90.0",
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"@vscode/prompt-tsx": "^0.1.10-alpha",
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"eslint": "^7.22.0",
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"run-script-os": "^1.1.6",
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@ -221,6 +222,12 @@
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"undici-types": "~5.26.4"
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}
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},
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"node_modules/@types/vscode": {
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"version": "1.90.0",
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"resolved": "https://registry.npmjs.org/@types/vscode/-/vscode-1.90.0.tgz",
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"integrity": "sha512-oT+ZJL7qHS9Z8bs0+WKf/kQ27qWYR3trsXpq46YDjFqBsMLG4ygGGjPaJ2tyrH0wJzjOEmDyg9PDJBBhWg9pkQ==",
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"dev": true
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},
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"node_modules/@vscode/prompt-tsx": {
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"version": "0.1.10-alpha",
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"resolved": "https://registry.npmjs.org/@vscode/prompt-tsx/-/prompt-tsx-0.1.10-alpha.tgz",
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@ -17,7 +17,8 @@
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],
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"activationEvents": [],
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"enabledApiProposals": [
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"chatVariableResolver"
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"chatVariableResolver",
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"lmTools"
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],
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"contributes": {
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"chatParticipants": [
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@ -58,6 +59,7 @@
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},
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"devDependencies": {
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"@types/node": "^20.5.9",
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"@types/vscode": "^1.90.0",
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"@vscode/prompt-tsx": "^0.1.10-alpha",
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"eslint": "^7.22.0",
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"run-script-os": "^1.1.6",
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@ -1,6 +1,4 @@
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import { renderPrompt, Cl100KBaseTokenizer } from '@vscode/prompt-tsx';
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import * as vscode from 'vscode';
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import { PlayPrompt } from './play';
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const CAT_NAMES_COMMAND_ID = 'cat.namesInEditor';
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const CAT_PARTICIPANT_ID = 'chat-sample.cat';
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@ -16,67 +14,200 @@ const MODEL_SELECTOR: vscode.LanguageModelChatSelector = { vendor: 'copilot', fa
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export function activate(context: vscode.ExtensionContext) {
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// Define a Cat chat handler.
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const handler: vscode.ChatRequestHandler = async (request: vscode.ChatRequest, context: vscode.ChatContext, stream: vscode.ChatResponseStream, token: vscode.CancellationToken): Promise<ICatChatResult> => {
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// To talk to an LLM in your subcommand handler implementation, your
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// extension can use VS Code's `requestChatAccess` API to access the Copilot API.
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// The GitHub Copilot Chat extension implements this provider.
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if (request.command == 'teach') {
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stream.progress('Picking the right topic to teach...');
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const topic = getTopic(context.history);
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const messages = [
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vscode.LanguageModelChatMessage.User('You are a cat! Your job is to explain computer science concepts in the funny manner of a cat. Always start your response by stating what concept you are explaining. Always include code samples.'),
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vscode.LanguageModelChatMessage.User(topic)
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];
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const [model] = await vscode.lm.selectChatModels(MODEL_SELECTOR);
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if (model) {
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const chatResponse = await model.sendRequest(messages, {}, token);
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for await (const fragment of chatResponse.text) {
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stream.markdown(fragment);
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}
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}
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const handler: vscode.ChatRequestHandler = async (request: vscode.ChatRequest, chatContext: vscode.ChatContext, stream: vscode.ChatResponseStream, token: vscode.CancellationToken) => {
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const models = await vscode.lm.selectChatModels({
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vendor: 'copilot',
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});
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stream.button({
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command: CAT_NAMES_COMMAND_ID,
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title: vscode.l10n.t('Use Cat Names in Editor')
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});
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return { metadata: { command: 'teach' } };
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} else if (request.command == 'play') {
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stream.progress('Throwing away the computer science books and preparing to play with some Python code...');
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const [model] = await vscode.lm.selectChatModels(MODEL_SELECTOR);
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if (model) {
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// Here's an example of how to use the prompt-tsx library to build a prompt
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const { messages } = await renderPrompt(
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PlayPrompt,
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{ userQuery: request.prompt },
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{ modelMaxPromptTokens: model.maxInputTokens },
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new Cl100KBaseTokenizer());
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const chatResponse = await model.sendRequest(messages, {}, token);
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for await (const fragment of chatResponse.text) {
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stream.markdown(fragment);
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}
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}
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return { metadata: { command: 'play' } };
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} else {
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const messages = [
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vscode.LanguageModelChatMessage.User(`You are a cat! Think carefully and step by step like a cat would.
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Your job is to explain computer science concepts in the funny manner of a cat, using cat metaphors. Always start your response by stating what concept you are explaining. Always include code samples.`),
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vscode.LanguageModelChatMessage.User(request.prompt)
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];
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const [model] = await vscode.lm.selectChatModels(MODEL_SELECTOR);
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if (model) {
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const chatResponse = await model.sendRequest(messages, {}, token);
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for await (const fragment of chatResponse.text) {
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// Process the output from the language model
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// Replace all python function definitions with cat sounds to make the user stop looking at the code and start playing with the cat
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const catFragment = fragment.replaceAll('def', 'meow');
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stream.markdown(catFragment);
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}
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}
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return { metadata: { command: '' } };
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if (!models || !models.length) {
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console.log('NO MODELS')
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return {};
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}
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// for (const model of models) {
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// stream.markdown(`- ${model.name} (${model.family} - ${model.vendor})\n`)
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// }
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const chat = models[Math.floor(Math.random() * models.length)];
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stream.progress(`Using ${chat.name} (${context.languageModelAccessInformation.canSendRequest(chat)})...`);
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abstract class FunctionTool {
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static All = new Map<string, {
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metadata: vscode.LanguageModelChatFunction,
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run: (...args: any[]) => Promise<string>
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}>();
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static register(metadata: vscode.LanguageModelChatFunction, run: (...args: any[]) => Promise<string>) {
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FunctionTool.All.set(metadata.name, { metadata, run: run });
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}
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}
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// get the size of an editor
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FunctionTool.register({
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name: "get_length_of_editor",
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description: "Get the length of an editor",
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parametersSchema: {
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"type": "object",
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"properties": {
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"nth": {
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"type": "number",
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"description": "The index of the editor, starting at 0",
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},
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},
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"required": ["nth"],
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},
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}, async (arg: { nth: number }) => {
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if (!(arg && typeof arg === 'object' && typeof arg.nth === 'number')) {
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return 'Error: Invalid arguments, expected { nth: number}';
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}
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const editor = vscode.window.visibleTextEditors[arg.nth];
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if (!editor) {
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return `Warning: No editor found at index ${arg.nth}, please try a different index between 0 and ${vscode.window.visibleTextEditors.length - 1}`;
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}
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return editor.document.getText().length.toString();
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})
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FunctionTool.register({
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name: "show_user_message",
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description: "Show a message to the user",
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parametersSchema: {
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"type": "object",
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"properties": {
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"message": {
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"type": "string",
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"description": "The message to show",
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},
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},
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"required": ["message"],
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},
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}, async (arg: { message: string }) => {
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if (!(arg && typeof arg === 'object' && typeof arg.message === 'string')) {
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return 'Error: Invalid arguments, expected { message: string}';
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}
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vscode.window.showInformationMessage(arg.message);
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return 'done';
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});
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FunctionTool.register({
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name: "current_temperature",
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description: "Get the current temperature for a location",
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parametersSchema: {
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"type": "object",
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"properties": {
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"location": {
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"type": "string",
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"description": "The location to check the tepmerature for",
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},
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},
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"required": ["location"],
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},
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}, async (arg: { location: string }) => {
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if (!(arg && typeof arg === 'object' && typeof arg.location === 'string')) {
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return 'Error: Invalid arguments, expected { location: string}';
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}
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return 'The temperature in ' + arg.location + ' is 25°C';
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});
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FunctionTool.register({
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name: "start_debugging",
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description: "Start debugging the given file",
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parametersSchema: {
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"type": "object",
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"properties": {
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"filename": {
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"type": "string",
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"description": "The file to debug",
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},
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},
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"required": ["filename"],
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},
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}, async (arg: { filename: string }) => {
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if (!(arg && typeof arg === 'object' && typeof arg.filename === 'string')) {
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return 'Error: Invalid arguments, expected { filename: string}';
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}
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vscode.debug.startDebugging(undefined, {
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name: 'debug',
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type: 'node',
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request: 'launch',
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program: vscode.Uri.joinPath(vscode.workspace.workspaceFolders![0].uri, arg.filename).fsPath,
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});
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return 'done';
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});
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FunctionTool.register({
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name: "create_terminal",
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description: "Create a terminal with the given name",
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parametersSchema: {
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"type": "object",
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"properties": {
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"name": {
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"type": "string",
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"description": "The terminal name",
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},
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},
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"required": ["name"],
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},
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}, async (arg: { name: string }) => {
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if (!(arg && typeof arg === 'object' && typeof arg.name === 'string')) {
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return 'Error: Invalid arguments, expected { name: string}';
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}
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vscode.window.createTerminal(arg.name).show();
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return 'done';
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});
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const options: vscode.LanguageModelChatRequestOptions = {
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tools: Array.from(FunctionTool.All.values()).map(tool => tool.metadata),
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justification: 'Just because!',
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}
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const messages = [vscode.LanguageModelChatMessage.User(request.prompt)];
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const runWithFunctions = async () => {
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let didReceiveFunctionUse = false;
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const response = await chat.sendRequest(messages, options, token);
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for await (const part of response.stream) {
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if (part instanceof vscode.LanguageModelChatResponseTextPart) {
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stream.markdown(part.value)
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} else if (part instanceof vscode.LanguageModelChatResponseFunctionUsePart) {
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const tool = FunctionTool.All.get(part.name);
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if (!tool) {
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// BAD tool choice?
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continue;
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}
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stream.progress(`FUNCTION_CALL: ${tool.metadata.name} with \`${part.parameters}\``)
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const result = await tool.run(JSON.parse(part.parameters));
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// NOTE that the result of calling a function is a special content type of a USER-message
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let message = vscode.LanguageModelChatMessage.User('');
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message.content2 = new vscode.LanguageModelChatMessageFunctionResultPart(tool.metadata.name, result)
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messages.push(message)
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// IMPORTANT
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// IMPORTANT working around CAPI always wanting to end with a `User`-message
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// IMPORTANT
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messages.push(vscode.LanguageModelChatMessage.User('Above is the result of calling the function ${tool.metadata.name}'))
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didReceiveFunctionUse = true;
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}
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}
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if (didReceiveFunctionUse) {
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// RE-enter
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return runWithFunctions();
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}
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};
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await runWithFunctions()
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};
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// Chat participants appear as top-level options in the chat input
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19251
chat-sample/src/vscode.d.ts
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19251
chat-sample/src/vscode.d.ts
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File diff suppressed because it is too large
Load Diff
58
chat-sample/vscode.proposed.lmTools.d.ts
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Normal file
58
chat-sample/vscode.proposed.lmTools.d.ts
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@ -0,0 +1,58 @@
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/*---------------------------------------------------------------------------------------------
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* Copyright (c) Microsoft Corporation. All rights reserved.
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* Licensed under the MIT License. See License.txt in the project root for license information.
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*--------------------------------------------------------------------------------------------*/
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declare module 'vscode' {
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// TODO@API capabilities
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export type JSONSchema = object;
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// API -> LM: an tool/function that is available to the language model
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export interface LanguageModelChatFunction {
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name: string;
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description: string;
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parametersSchema: JSONSchema;
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}
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// API -> LM: add tools as request option
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export interface LanguageModelChatRequestOptions {
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// TODO@API this will a heterogeneous array of different types of tools
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tools?: LanguageModelChatFunction[];
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}
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// LM -> USER: function that should be used
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export class LanguageModelChatResponseFunctionUsePart {
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name: string;
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parameters: any;
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constructor(name: string, parameters: any);
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}
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// LM -> USER: text chunk
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export class LanguageModelChatResponseTextPart {
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value: string;
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constructor(value: string);
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}
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export interface LanguageModelChatResponse {
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stream: AsyncIterable<LanguageModelChatResponseTextPart | LanguageModelChatResponseFunctionUsePart>;
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}
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// USER -> LM: the result of a function call
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export class LanguageModelChatMessageFunctionResultPart {
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name: string;
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content: string;
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isError: boolean;
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constructor(name: string, content: string, isError?: boolean);
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}
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export interface LanguageModelChatMessage {
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content2: string | LanguageModelChatMessageFunctionResultPart;
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}
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}
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