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import { ok } from 'assert';
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import * as vscode from 'vscode';
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import commentPrefix from './comments.json';
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// llama.cpp server response format
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type llamaData = {
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content: string,
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generation_settings: JSON,
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model: string,
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prompt: string,
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stopped_eos: boolean,
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stopped_limit: boolean,
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stopped_word: boolean,
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stopping_word: string,
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timings: {
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predicted_ms: number,
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predicted_n: number,
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predicted_per_second: number,
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predicted_per_token_ms: number,
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prompt_ms: number,
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prompt_n: number,
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prompt_per_second: number,
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prompt_per_token_ms: number
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},
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tokens_cached: number,
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tokens_evaluated: number,
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tokens_predicted: number,
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truncated: boolean
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};
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type llamaCompletionRequest = {
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n_predict: number,
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mirostat: number,
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repeat_penalty: number,
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frequency_penalty: number,
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presence_penalty: number,
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repeat_last_n: number,
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temperature: number,
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top_p: number,
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top_k: number,
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typical_p: number,
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tfs_z: number,
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seed: number,
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stream: boolean,
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prompt: string,
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};
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type llamaFillRequest = {
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n_predict: number,
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mirostat: number,
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repeat_penalty: number,
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frequency_penalty: number,
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presence_penalty: number,
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repeat_last_n: number,
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temperature: number,
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top_p: number,
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top_k: number,
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typical_p: number,
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tfs_z: number,
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seed: number,
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stream: boolean,
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input_prefix: string,
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input_suffix: string,
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};
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const llama_ctxsize = 2048;
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const llama_maxtokens = -1;
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const llama_mirostat = 0;
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const llama_repeat_penalty = 1.11;
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const llama_frequency_penalty = 0.0;
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const llama_presence_penalty = 0.0;
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const llama_repeat_ctx = 256;
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const llama_temperature = 0.25;
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const llama_top_p = 0.95;
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const llama_top_k = 40;
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const llama_typical_p = 0.95;
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const llama_tailfree_z = 0.5;
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const llama_session_seed = -1;
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const llama_host = "http://0.0.0.0:8080";
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// clean up the document
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function clean_text(txt: string): string {
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// these are already done by JSON.stringify()
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//txt = txt.replace(/(\r\n|\n|\r)/gm, "\\n");
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//txt = txt.replace((/\t/gm, "\\t"));
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// FIXME: I don't know if this penalizes some results since most people indent with spaces
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//txt = txt.replace(/\s+/gm, " ");
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return txt;
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}
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export function activate(context: vscode.ExtensionContext) {
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console.log('dumbpilot is now active');
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const config = vscode.workspace.getConfiguration("dumbpilot");
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var completion_enabled: boolean = config.get("completionEnabled") as boolean;
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// TODO: work with local configurations
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let disposable = vscode.commands.registerCommand("dumbpilot.enableCompletion", () => {
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completion_enabled = true;
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config.update("completionEnabled", true);
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});
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context.subscriptions.push(disposable);
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disposable = vscode.commands.registerCommand("dumbpilot.disableCompletion", () => {
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completion_enabled = false;
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config.update("completionEnabled", false);
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});
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// Register a new provider of inline completions, this does not decide how it is invoked
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// only what the completion should be
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// https://github.com/microsoft/vscode-extension-samples/blob/main/inline-completions/src/extension.ts
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const provider: vscode.InlineCompletionItemProvider = {
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async provideInlineCompletionItems(document, position, context, token) {
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if (completion_enabled === false) {
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return null;
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}
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// Since for every completion we want to query the server, we want to filter out
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// automatic completion invokes
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if (context.triggerKind === vscode.InlineCompletionTriggerKind.Automatic) {
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return null;
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}
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// FIXME: I don't know if this works
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token.onCancellationRequested(() => {
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console.log("dumbpilot: operation cancelled, may still be running on the server");
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return null;
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});
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//console.log('dumbpilot: completion invoked at position: line=' + position.line + ' char=' + position.character);
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const result: vscode.InlineCompletionList = {
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items: []
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};
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// Get the document's text and position to send to the model
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const doc_text = document.getText();
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const doc_off = document.offsetAt(position);
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var doc_before = doc_text.substring(0, doc_off);
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var doc_after = doc_text.substring(doc_off);
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// make it cleaner in hope to reduce the number of tokens
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doc_before = clean_text(doc_before);
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doc_after = clean_text(doc_after);
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// TODO: prune text up to a maximum context length
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// Prefix the filename in a comment
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var pfx: string, sfx: string;
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const lang = document.languageId;
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const prefixes = commentPrefix;
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pfx = (prefixes as any)[lang][0] as string;
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sfx = (prefixes as any)[lang][1] as string;
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// FIXME: is there a more efficient way?
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doc_before = pfx + ' ' + document.fileName + sfx + '\n' + doc_before;
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// server request object
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const request: llamaCompletionRequest = {
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n_predict: llama_maxtokens,
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mirostat: llama_mirostat,
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repeat_penalty: llama_repeat_penalty,
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frequency_penalty: llama_frequency_penalty,
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presence_penalty: llama_presence_penalty,
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repeat_last_n: llama_repeat_ctx,
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temperature: llama_temperature,
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top_p: llama_top_p,
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top_k: llama_top_k,
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typical_p: llama_typical_p,
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tfs_z: llama_tailfree_z,
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seed: llama_session_seed,
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stream: false,
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prompt: doc_before,
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};
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var data: llamaData;
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// try to send the request to the running server
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try {
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const response = await fetch(
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llama_host.concat('/completion'),
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{
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method: 'POST',
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headers: {
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'content-type': 'application/json; charset=UTF-8'
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},
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body: JSON.stringify(request)
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}
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);
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if (response.ok === false) {
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throw new Error("llama server request is not ok??");
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}
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data = await response.json() as llamaData;
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} catch (e: any) {
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console.log('dumbpilot: ' + e.message);
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return null;
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};
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result.items.push({insertText: data.content, range: new vscode.Range(position, position)});
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return result;
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},
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};
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vscode.languages.registerInlineCompletionItemProvider({pattern: '**'}, provider);
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}
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// This method is called when your extension is deactivated
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export function deactivate() {}
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