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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,176 @@ | ||
| import * as vscode from "vscode"; | ||
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| const ECLAGENT_NAMES_COMMAND_ID = "eclagent.doSomething"; | ||
| const ECLAGENT_PARTICIPANT_ID = "chat-ecl.eclagent"; | ||
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| interface IECLChatResult extends vscode.ChatResult { | ||
| metadata: { | ||
| command: string; | ||
| } | ||
| } | ||
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| const LANGUAGE_MODEL_ID = "copilot-gpt-3.5-turbo"; // Use faster model. Alternative is 'copilot-gpt-4', which is slower but more powerful | ||
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| export function activate(context: vscode.ExtensionContext) { | ||
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| // Define an ECL chat handler. | ||
| const handler: vscode.ChatRequestHandler = async (request: vscode.ChatRequest, context: vscode.ChatContext, stream: vscode.ChatResponseStream, token: vscode.CancellationToken): Promise<IECLChatResult> => { | ||
| // To talk to an LLM in your subcommand handler implementation, your | ||
| // extension can use VS Code's `requestChatAccess` API to access the Copilot API. | ||
| // The GitHub Copilot Chat extension implements this provider. | ||
| if (request.command == "teach") { | ||
| stream.progress("Picking the right topic to teach..."); | ||
| const topic = getTopic(context.history); | ||
| const messages = [ | ||
| new vscode.LanguageModelChatSystemMessage("You are an ECL expert! Your job is to explain ECL concepts. Always start your response by stating what concept you are explaining. Always include code samples."), | ||
| new vscode.LanguageModelChatUserMessage(topic) | ||
| ]; | ||
| const chatResponse = await vscode.lm.sendChatRequest(LANGUAGE_MODEL_ID, messages, {}, token); | ||
| for await (const fragment of chatResponse.stream) { | ||
| stream.markdown(fragment); | ||
| } | ||
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| stream.button({ | ||
| command: ECLAGENT_NAMES_COMMAND_ID, | ||
| title: vscode.l10n.t("Do something"), | ||
| }); | ||
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| return { metadata: { command: "teach" } }; | ||
| } else if (request.command == "play") { | ||
| stream.progress("Preparing to look at some ECL code..."); | ||
| const messages = [ | ||
| new vscode.LanguageModelChatSystemMessage("You are an ECL expert! You are also very knowledgable about HPCC."), | ||
| new vscode.LanguageModelChatUserMessage("Give small random ECL code samples. " + request.prompt) | ||
| ]; | ||
| const chatResponse = await vscode.lm.sendChatRequest(LANGUAGE_MODEL_ID, messages, {}, token); | ||
| for await (const fragment of chatResponse.stream) { | ||
| stream.markdown(fragment); | ||
| } | ||
| return { metadata: { command: "play" } }; | ||
| } else { | ||
| const messages = [ | ||
| new vscode.LanguageModelChatSystemMessage(`You are an ECL expert! Think carefully and step by step like an expert who is good at explaining something. | ||
| Your job is to explain computer science concepts in fun and entertaining way. Always start your response by stating what concept you are explaining. Always include code samples.`), | ||
| new vscode.LanguageModelChatUserMessage(request.prompt) | ||
| ]; | ||
| const chatResponse = await vscode.lm.sendChatRequest(LANGUAGE_MODEL_ID, messages, {}, token); | ||
| for await (const fragment of chatResponse.stream) { | ||
| // Process the output from the language model | ||
| stream.markdown(fragment); | ||
| } | ||
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| return { metadata: { command: "" } }; | ||
| } | ||
| }; | ||
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| // Chat participants appear as top-level options in the chat input | ||
| // when you type `@`, and can contribute sub-commands in the chat input | ||
| // that appear when you type `/`. | ||
| const eclagent = vscode.chat.createChatParticipant(ECLAGENT_PARTICIPANT_ID, handler); | ||
| eclagent.iconPath = vscode.Uri.joinPath(context.extensionUri, "resources/hpcc-icon.png"); | ||
| eclagent.followupProvider = { | ||
| provideFollowups(result: IECLChatResult, context: vscode.ChatContext, token: vscode.CancellationToken) { | ||
| return [{ | ||
| prompt: "let us learn", | ||
| label: vscode.l10n.t("Play with ECL Code"), | ||
| command: "play" | ||
| } satisfies vscode.ChatFollowup]; | ||
| } | ||
| }; | ||
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| vscode.chat.registerChatVariableResolver("ECLAGENT_context", "Describes the state of mind and version of the ECL agent", { | ||
| resolve: (name, context, token) => { | ||
| if (name == "ECLAGENT_context") { | ||
| const mood = Math.random() > 0.5 ? "happy" : "grumpy"; | ||
| return [ | ||
| { | ||
| level: vscode.ChatVariableLevel.Short, | ||
| value: "version 1.3 " + mood | ||
| }, | ||
| { | ||
| level: vscode.ChatVariableLevel.Medium, | ||
| value: "I am the ECL agent, version 1.3, and I am " + mood | ||
| }, | ||
| { | ||
| level: vscode.ChatVariableLevel.Full, | ||
| value: "I am the ECL agent, version 1.3, and I am " + mood | ||
| } | ||
| ]; | ||
| } | ||
| } | ||
| }); | ||
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| context.subscriptions.push( | ||
| eclagent, | ||
| // Register the command handler for the do something followup | ||
| vscode.commands.registerTextEditorCommand(ECLAGENT_NAMES_COMMAND_ID, async (textEditor: vscode.TextEditor) => { | ||
| const text = textEditor.document.getText(); | ||
| const messages = [ | ||
| new vscode.LanguageModelChatSystemMessage(`You are an ECL expert! Think carefully and step by step. | ||
| Your job is to be as clear as possible and be encouraging. Be creative. IMPORTANT respond just with code. Do not use markdown!`), | ||
| new vscode.LanguageModelChatUserMessage(text) | ||
| ]; | ||
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| let chatResponse: vscode.LanguageModelChatResponse | undefined; | ||
| try { | ||
| chatResponse = await vscode.lm.sendChatRequest(LANGUAGE_MODEL_ID, messages, {}, new vscode.CancellationTokenSource().token); | ||
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| } catch (err) { | ||
| // making the chat request might fail because | ||
| // - model does not exist | ||
| // - user consent not given | ||
| // - quote limits exceeded | ||
| if (err instanceof vscode.LanguageModelError) { | ||
| console.log(err.message, err.code, err.cause); | ||
| } | ||
| return; | ||
| } | ||
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| // Clear the editor content before inserting new content | ||
| await textEditor.edit(edit => { | ||
| const start = new vscode.Position(0, 0); | ||
| const end = new vscode.Position(textEditor.document.lineCount - 1, textEditor.document.lineAt(textEditor.document.lineCount - 1).text.length); | ||
| edit.delete(new vscode.Range(start, end)); | ||
| }); | ||
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| // Stream the code into the editor as it is coming in from the Language Model | ||
| try { | ||
| for await (const fragment of chatResponse.stream) { | ||
| await textEditor.edit(edit => { | ||
| const lastLine = textEditor.document.lineAt(textEditor.document.lineCount - 1); | ||
| const position = new vscode.Position(lastLine.lineNumber, lastLine.text.length); | ||
| edit.insert(position, fragment); | ||
| }); | ||
| } | ||
| } catch (err) { | ||
| // async response stream may fail, e.g network interruption or server side error | ||
| await textEditor.edit(edit => { | ||
| const lastLine = textEditor.document.lineAt(textEditor.document.lineCount - 1); | ||
| const position = new vscode.Position(lastLine.lineNumber, lastLine.text.length); | ||
| edit.insert(position, (<Error>err).message); | ||
| }); | ||
| } | ||
| }), | ||
| ); | ||
| } | ||
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| // Get a random topic that the ECL agent has not taught in the chat history yet | ||
| function getTopic(history: ReadonlyArray<vscode.ChatRequestTurn | vscode.ChatResponseTurn>): string { | ||
| const topics = ["import", "modules", "functions", "transforms", "strings"]; | ||
| // Filter the chat history to get only the responses from the ecl agent | ||
| const previousEclAgentResponses = history.filter(h => { | ||
| return h instanceof vscode.ChatResponseTurn && h.participant == ECLAGENT_PARTICIPANT_ID; | ||
| }) as vscode.ChatResponseTurn[]; | ||
| // Filter the topics to get only the topics that have not been taught by the ecl agent yet | ||
| const topicsNoRepetition = topics.filter(topic => { | ||
| return !previousEclAgentResponses.some(eclAgentResponse => { | ||
| return eclAgentResponse.response.some(r => { | ||
| return r instanceof vscode.ChatResponseMarkdownPart && r.value.value.includes(topic); | ||
| }); | ||
| }); | ||
| }); | ||
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| return topicsNoRepetition[Math.floor(Math.random() * topicsNoRepetition.length)] || "I have taught you everything I know."; | ||
| } | ||
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| export function deactivate() { } |
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