English Speaking Training VS Code Extension

Standalone VS Code speaking-practice cockpit for EnglishSpeakingTraining materials.

The extension no longer depends on Hermes or Telegram for the main practice loop. It reads local prebuilt/ package files, records inside a VS Code webview, stores API keys in VS Code SecretStorage, and writes session artifacts locally.

Bring Your Own Materials

The extension does not ship lessons. You point it at a local prebuilt/ directory of your own, and it walks every YYYY-MM-DD subdirectory it finds. There is no required curriculum length: 7 lessons or 365 lessons both work.

First-run path (no lessons yet):

1. Open the English Training sidebar. The Quick Setup card lists what's missing.
2. Click Pick local folder or run English Training: Configure Local Materials Folder.
3. Click Create your first lesson → pick a folder; the extension creates prebuilt/ and progress/ inside it and writes a starter prebuilt/<today>/english-training.json you can edit.
4. Click Add your first AI key → pick a provider (MiMo recommended for the default coach + STT + TTS combo).
5. Press the red record button.

For the field-by-field schema, run English Training: Open Materials Guide from the command palette.

Local Materials Source

• Local: auto-detects a workspace or parent folder containing prebuilt/.
• Fixed local path: set englishTraining.localMaterialsRoot to a directory containing prebuilt/ so the sidebar works from any VS Code workspace.
• Picker: run English Training: Configure Local Materials Folder, or click Source -> Local Folder in the sidebar.

Source Diagnostics and Learner Profile

The Practice sidebar shows Source Diagnostics so you can verify what it actually loaded: local root, lesson count, current package date, and the exact english-training.json path.

To personalize coaching, add one of these files to your materials root:

• profile/learner-profile.md
• profile/learner-profile.json

When found, the sidebar shows Profile loaded and the coach receives that profile with every practice turn. If no profile exists, the sidebar shows the expected path.

Provider Defaults

• Speech input: OpenAI gpt-4o-transcribe by default, with Gemini gemini-2.5-flash and MiMo mimo-v2.5 as options
• Coach: Xiaomi MiMo mimo-v2.5, with MiniMax MiniMax-M2.7-highspeed and Gemini gemini-2.5-flash, Kimi Code kimi-for-coding, and DeepSeek deepseek-v4-pro as language-model options
• Speech output: MiniMax speech-2.8-hd with English_expressive_narrator by default, with OpenAI gpt-4o-mini-tts, Gemini gemini-2.5-flash-preview-tts, and MiMo mimo-v2.5-tts as options

Features

• English Training Activity Bar container with a Practice webview.
• Direct Record / Stop microphone flow inside the sidebar.
• Transcript, native-speaker version, concrete problems, repeat instruction, and follow-up question returned in the same sidebar.
• On-demand Example audio: click Generate Example to synthesize only the lesson example text (clean_tts_text, audio_text, or demo_line) with your configured speech-output provider. Scenario and goal background are not read aloud.
• Generated native-version audio saved locally and played in VS Code.
• API key commands:
  • English Training: Configure OpenAI API Key
  • English Training: Configure Gemini API Key
  • English Training: Configure MiniMax API Key
  • English Training: Configure MiMo API Key
  • English Training: Configure Kimi API Key
  • English Training: Configure DeepSeek API Key
• Local actions:
  • English Training: Complete Current Package Locally
  • English Training: Open Current Task Card
  • English Training: Open Local Session Folder
  • English Training: Configure Local Materials Folder

Development

cd vscode-extension
npm install
npm run compile
npx @vscode/vsce package --allow-missing-repository

Open this folder in VS Code and press F5 to run an Extension Development Host. Open the EnglishSpeakingTraining project folder in that host to activate the extension.

Notes

The recorder defaults to englishTraining.recorderBackend = macLocal on macOS. That path records through ffmpeg AVFoundation, auto-selects a local Mac microphone such as iMac Microphone, and avoids device names matching englishTraining.blockedMicrophoneNamePattern such as iPhone/Continuity inputs. Set englishTraining.preferredMicrophoneName if you want to pin a specific local microphone.