simple-voice-chat 3.3.0

A simple voice chat interface using configurable LLM, STT, and TTS providers.

Simple Voice Chat

This project provides a flexible voice chat interface that connects to various Speech-to-Text (STT), Large Language Model (LLM), and Text-to-Speech (TTS) services.

Acknowledgement: This project heavily relies on the fantastic fastrtc library, which simplifies real-time audio streaming over WebRTC, making this application possible.

Motivation

The primary motivation for creating this project was the high cost associated with OpenAI's real-time voice API. This application allows you to leverage potentially more cost-effective or self-hosted alternatives for STT, LLM, and TTS, while still providing a near real-time voice interaction experience.

Features

• 🔌 Modular Architecture: Easily connect to various STT, LLM, and TTS services.
  • 🗣️ STT: Supports OpenAI Whisper API or self-hosted engines like Speaches (Faster Whisper).
  • 🧠 LLM: Integrates with LiteLLM, enabling connections to OpenAI, Anthropic, Google, Mistral, Cohere, Azure, local models (via LiteLLM proxy, vLLM, Ollama), and more.
  • 🔊 TTS: Supports OpenAI TTS API or alternatives like Kokoro-FastAPI.
• ⚙️ Highly Configurable: Adjust STT/LLM/TTS hosts, ports, models, API keys, STT confidence thresholds, TTS voice/speed, system messages, and more via CLI arguments or .env file.
• 🌐 Web Interface: Simple and responsive UI built with HTML, CSS, and JavaScript.
• 📊 Cost Tracking: Real-time cost estimation for OpenAI LLM and TTS usage.
• ⚡ Real-time Interaction: Low-latency voice communication powered by fastrtc (WebRTC).
• 👂 STT Confidence Filtering: Automatically reject low-confidence transcriptions based on configurable thresholds (no speech probability, average log probability, minimum word count).
• 🎤 Dynamic Voice/Model Selection: Change LLM model, TTS voice, TTS speed, and STT language on-the-fly through the UI without restarting.
• 🔍 Fuzzy Search: Quickly find models and voices using fuzzy search in the UI dropdowns.
• 💬 System Message Support: Define a custom system message to guide the LLM's behavior.
• 📝 Chat History Logging: Automatically saves conversation history to timestamped JSON files.
• 🔄 TTS Audio Replay: Replay the audio for any assistant message directly from the chat interface.
• ⌨️ Keyboard Shortcuts: Control mute (M), clear chat (Ctrl+R), and toggle options (Shift+S) using keyboard shortcuts.
• 💓 Connection Monitoring: Uses a heartbeat mechanism to detect disconnected clients and potentially shut down the server.
• 🖥️ Cross-Platform GUI: Runs as a standalone desktop application using pywebview (default) or in a standard web browser (--browser flag). The application explicitly uses the QT backend for pywebview as the GTK backend lacks necessary WebRTC support.

Installation

1. Clone the repository:

   git clone https://github.com/thiswillbeyourgithub/simple_voice_chat
   
   cd simple_voice_chat
   

2. Install the Python packages:

   uv pip install -e .
   

3. (Optional) Configure services using environment variables. You can create a .env file based on the available options (see --help or utils/env.py).

Usage

Run the main script using Python:

simple-voice-chat --help

The application will start a web server and attempt to open the interface in a dedicated window (or browser tab if --browser is specified).

For a detailed list of all configuration options (STT/LLM/TTS hosts, ports, models, API keys, etc.), please use the --help flag:

simple-voice-chat --help

This will provide the most up-to-date information on available arguments and their corresponding environment variables.

Command-Line Options (--help)

usage: simple-voice-chat [-h] [--host HOST] [--port PORT] [-v] [--browser] [--system-message SYSTEM_MESSAGE] [--llm-host LLM_HOST]
                         [--llm-port LLM_PORT] [--llm-model LLM_MODEL] [--llm-api-key LLM_API_KEY] [--stt-host STT_HOST]
                         [--stt-port STT_PORT] [--stt-model STT_MODEL] [--stt-language STT_LANGUAGE] [--stt-api-key STT_API_KEY]
                         [--stt-no-speech-prob-threshold STT_NO_SPEECH_PROB_THRESHOLD]
                         [--stt-avg-logprob-threshold STT_AVG_LOGPROB_THRESHOLD] [--stt-min-words-threshold STT_MIN_WORDS_THRESHOLD]
                         [--tts-host TTS_HOST] [--tts-port TTS_PORT] [--tts-model TTS_MODEL] [--tts-voice TTS_VOICE]
                         [--tts-api-key TTS_API_KEY] [--tts-speed TTS_SPEED] [--tts-acronym-preserve-list TTS_ACRONYM_PRESERVE_LIST]
Run a simple voice chat interface using a configurable LLM provider, STT server, and TTS.
options:
-h, --help            show this help message and exit
--host HOST           Host address to bind the FastAPI server to. Default: 127.0.0.1
--port PORT           Preferred port to run the FastAPI server on. Default: 7860. (Env: APP_PORT)
-v, --verbose         Enable verbose logging (DEBUG level)
--browser             Launch the application in the default web browser instead of a dedicated GUI window. Default: False
--system-message SYSTEM_MESSAGE
System message to prepend to the chat history. Default: (from SYSTEM_MESSAGE env var, empty if unset).
--llm-host LLM_HOST   Host address of the LLM proxy server (optional). Default: None. (Env: LLM_HOST)
--llm-port LLM_PORT   Port of the LLM proxy server (optional). Default: None. (Env: LLM_PORT)
--llm-model LLM_MODEL
Default LLM model to use (e.g., 'gpt-4o', 'litellm_proxy/claude-3-opus'). Default:
'openrouter/google/gemini-2.5-pro-preview-03-25'. (Env: LLM_MODEL)
--llm-api-key LLM_API_KEY
API key for the LLM provider/proxy (optional, depends on setup). Default: None. (Env: LLM_API_KEY)
--stt-host STT_HOST   Host address of the STT server (e.g., 'api.openai.com' or 'localhost'). Default: 'api.openai.com'. (Env:
STT_HOST)
--stt-port STT_PORT   Port of the STT server (e.g., 443 for OpenAI, 8002 for local). Default: '443'. (Env: STT_PORT)
--stt-model STT_MODEL
STT model to use (e.g., 'whisper-1' for OpenAI, 'deepdml/faster-whisper-large-v3-turbo-ct2' for local).
Default: 'whisper-1'. (Env: STT_MODEL)
--stt-language STT_LANGUAGE
Language code for STT (e.g., 'en', 'fr'). If unset (empty string or not provided), Whisper usually auto-
detects. Default: None. (Env: STT_LANGUAGE)
--stt-api-key STT_API_KEY
API key for the STT server (REQUIRED for OpenAI STT). Default: None. (Env: STT_API_KEY)
--stt-no-speech-prob-threshold STT_NO_SPEECH_PROB_THRESHOLD
STT confidence threshold: Reject if no_speech_prob is higher than this. Default: 0.6. (Env:
STT_NO_SPEECH_PROB_THRESHOLD)
--stt-avg-logprob-threshold STT_AVG_LOGPROB_THRESHOLD
STT confidence threshold: Reject if avg_logprob is lower than this. Default: -0.7. (Env:
STT_AVG_LOGPROB_THRESHOLD)
--stt-min-words-threshold STT_MIN_WORDS_THRESHOLD
STT confidence threshold: Reject if the number of words is less than this. Default: 5. (Env:
STT_MIN_WORDS_THRESHOLD)
--tts-host TTS_HOST   Host address of the TTS server (e.g., 'api.openai.com' or 'localhost'). Default: 'api.openai.com'. (Env:
TTS_HOST)
--tts-port TTS_PORT   Port of the TTS server (e.g., 443 for OpenAI, 8880 for local). Default: '443'. (Env: TTS_PORT)
--tts-model TTS_MODEL
TTS model to use (e.g., 'tts-1', 'tts-1-hd' for OpenAI, 'kokoro' for local). Default: 'tts-1'. (Env:
TTS_MODEL)
--tts-voice TTS_VOICE
Default TTS voice to use (e.g., 'alloy', 'ash', 'echo' for OpenAI, 'ff_siwis' for local). Default: 'ash'.
(Env: TTS_VOICE)
--tts-api-key TTS_API_KEY
API key for the TTS server (REQUIRED for OpenAI TTS). Default: None. (Env: TTS_API_KEY)
--tts-speed TTS_SPEED
Default TTS speed multiplier. Default: 1.0. (Env: TTS_SPEED)
--tts-acronym-preserve-list TTS_ACRONYM_PRESERVE_LIST
Comma-separated list of acronyms to preserve during TTS (currently only used for Kokoro TTS). Default: ''.
(Env: TTS_ACRONYM_PRESERVE_LIST)

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This README was generated with assistance from aider.chat.