LM TTS (LM Studio + Kokoro)

Small Flask app that lets you chat with an LM Studio model and hear the replies via Kokoro text-to-speech. The web/ frontend talks to two endpoints: /api/chat for combined text + audio replies and /api/tts for on-demand speech.

Requirements

• Python 3.10+ with pip
• LM Studio running locally with a chat model loaded and the API server enabled (defaults to http://127.0.0.1:1234/v1 and key lm-studio)

Quickstart

• Windows (simplest): double-click run_server.bat — it will create/activate .venv, install requirements, and start the server.
• Mac/Linux (or manual):

python -m venv .venv
source .venv/bin/activate
pip install --upgrade pip
pip install -r requirements.txt

# Start LM Studio separately, then run the app:
python server.py

Then open http://localhost:5000 in your browser to use the chat UI.

Config (environment variables)

• LMSTUDIO_BASE_URL – Base URL for the LM Studio API (default http://127.0.0.1:1234/v1)
• LMSTUDIO_API_KEY – API key for LM Studio (default lm-studio)
• LMSTUDIO_MODEL_NAME – Force a specific model ID; omit to auto-pick the first loaded model
• KOKORO_REPO_ID – Hugging Face repo for Kokoro weights (default hexgrad/Kokoro-82M)
• KOKORO_LANG – Default language code used when parsing VOICES.md (single letter, default a)
• KOKORO_VOICE – Default voice name; must exist in VOICES.md
• KOKORO_SAMPLE_RATE – Output sample rate (default 24000)
• PORT – Server port (default 5000)

Voice catalog

Available voices are read from VOICES.md. Each entry exposes a name and lang_code to the frontend dropdown. Update that file to add or remove voices without touching code.

How it works

• /api/models proxies LM Studio to list available model IDs.
• /api/chat sends the conversation to LM Studio, gets a text reply, and immediately synthesizes audio for the selected voice.
• /api/voices returns the Kokoro voices parsed from VOICES.md.
• /api/tts runs Kokoro TTS for arbitrary text (used by the “Speak” buttons).

Local chat history, selected model, voice, and temperature are cached in localStorage so your settings persist between refreshes.