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Local voice chatbot for engaging conversations, powered by Ollama, Hugging Face Transformers, and Coqui TTS Toolkit
| Date | Stars |
|---|---|
| 2026-07-24 | 787 |
| 2026-07-25 | 787 |
| 2026-07-28 | 788 |
| 2026-07-30 | 788 |
| 2026-08-06 | 788 |
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# june
## Local Voice Chatbot: Ollama + HF Transformers + Coqui TTS Toolkit
- [OVERVIEW](#overview)
- [INSTALLATION](#installation)
- [USAGE](#usage)
- [CUSTOMIZATION](#customization)
- [FAQ](#frequently-asked-questions)
## OVERVIEW
[**june**](https://github.com/mezbaul-h/june) is a local voice chatbot that combines the power of Ollama (for language model capabilities), Hugging Face Transformers (for speech recognition), and the Coqui TTS Toolkit (for text-to-speech synthesis). It provides a flexible, privacy-focused solution for voice-assisted interactions on your local machine, ensuring that no data is sent to external servers.
### Interaction Modes
- **Text Input/Output:** Provide text inputs to the assistant and receive text responses.
- **Voice Input/Text Output:** Use your microphone to give voice inputs, and receive text responses from the assistant.
- **Text Input/Audio Output:** Provide text inputs and receive both text and synthesised audio responses from the assistant.
- **Voice Input/Audio Output (Default):** Use your microphone for voice inputs, and receive responses in both text and synthesised audio form.
## INSTALLATION
### Pre-requisites
- [**Ollama**](https://github.com/ollama/ollama)
- [**Python**](https://www.python.org/downloads/) 3.10 or greater (with _pip_)
- **Python** development package (e.g. `apt install python3-dev` for Debian) — **only for GNU/Linux**
- **PortAudio** development package (e.g. `apt install portaudio19-dev` for Debian) — **only for GNU/Linux**
- **PortAudio** (e.g. `brew install portaudio` using Homebrew) — **only for macOS**
- [**Microsoft Visual C++**](https://visualstudio.microsoft.com/visual-cpp-build-tools/) 14.0 or greater — **only for Windows**
### From Source
#### Method 1: Direct Installation
To install **june** directly from the GitHub repository:
```shell
pip install git+https://github.com/mezbaul-h/june.git@master
```
#### Method 2: Clone and Install
Alternatively, you can clone the repository and install it locally:
```shell
git clone https://github.com/mezbaul-h/june.git
cd june
pip install .
```
## USAGE
Pull the language model (default is `llama3.1:8b-instruct-q4_0`) with Ollama first, if you haven't already:
```shell
ollama pull llama3.1:8b-instruct-q4_0
```
Next, run the program (with default configuration):
```shell
june-va
```
This will use [llama3.1:8b-instruct-q4_0](https://ollama.com/library/llama3.1:8b-instruct-q4_0) for LLM capabilities, [openai/whisper-small.en](https://huggingface.co/openai/whisper-small.en) for speech recognition, and `tts_models/en/ljspeech/glow-tts` for audio synthesis.
You can also customize behaviour of the program with a json configuration file:
```shell
june-va --config path/to/config.json
```
> [!NOTE]
> The configuration file is optional. To learn more about the structure of the config file, see the [Customization](#customization) section.
## CUSTOMIZATION
The application can be customised using a configuration file. The config file must be a JSON file. The default configuration is as follows:
```json
{
"llm": {
"disable_chat_history": false,
"model": "llama3.1:8b-instruct-q4_0"
},
"stt": {
"device": "torch device identifier (`cuda` if available; otherwise `cpu`",
"generation_args": {
"batch_size": 8
},
"model": "openai/whisper-small.en"
},
"tts": {
"device": "torch device identifier (`cuda` if available; otherwise `cpu`",
"model": "tts_models/en/ljspeech/glow-tts"
}
}
```
When you use a configuration file, it overrides the default configuration but does not overwrite it. So you can partially modify the configuration if you desire. For instance, if you do not wish to use speech recognition and only want to provide prompts through text, you can disable that by using a config file with the following configuration:
```json
{
"stt": null
}
```
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matched fp:a5aea545747f1f45, topic:speech-recognition, topic:text-to-speech, topic:whisper
matched fp:a5aea545747f1f45, topic:large-language-models, topic:llm