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Ollama Voice Chat — A Local, Talking AI Assistant for Windows

 

Ollama Voice Chat — A Local, Talking AI Assistant for Windows

I’m excited to share my latest open-source project: Ollama Voice Chat — a simple but powerful local voice chat assistant that runs fully on your machine using open-source AI tools. It lets you talk to a Large Language Model (LLM) and hear its responses spoken back out loud — no cloud APIs, no monthly fees, and full control of your data.

👉 GitHub repository:
https://github.com/error0327/ollama-voice-chat

🚀 What Is It?

Ollama Voice Chat is an interactive client for Windows that connects to a locally running LLM (via Ollama), converts user speech to text, sends it to the model, and uses Coqui TTS to speak the replies. It includes an automated setup script to streamline installation and configuration.

Instead of typing, you can talk to your AI assistant and get spoken answers — great for hands-free use cases, prototyping voice UIs, or just having a more natural interaction with your models.

🧠 Why This Matters

Most AI voice assistants today rely on cloud APIs (and associated costs). With recent advances in local LLM engines like Ollama (which hosts open models locally), you can now build an offline, privacy-focused voice assistant. This project sits right in that ecosystem, inspired by similar community efforts that combine speech-to-text + LLM + text-to-speech locally.

🛠️ Key Features

✔️ Automated Setup — One script prepares your Windows machine with all needed tools: Ollama, firewall rules, Python environment, and voice model dependencies.
✔️ Ollama Integration — Connects to a local Ollama server and pulls models like DeepSeek-R1:7B for conversational AI.
✔️ Coqui TTS Support — Generates spoken replies for each AI response.
✔️ Remote LAN Access — Configured to allow local network clients to connect if desired.
✔️ CLI Chat Loop — Simple command-line interface that continuously listens and replies.

📦 Requirements

To use this project, you’ll need:

  • Windows 11 + Administrator rights

  • winget available in your PATH (standard on modern Windows)

  • Python 3.10+ installed

  • ~15 GB free disk space for models & voice assets

  • Speakers or headphones for audio output

🧩 Setup & Start

In essence:

  1. Open an elevated PowerShell in the repo folder.

  2. Run the automated setup script:

    Set-ExecutionPolicy -Scope Process Bypass
    ./setup.ps1

    This will install Ollama, set up environment variables, open necessary ports, and download models.

  3. Activate the Python virtual environment and start the voice chat:

    ./.venv/Scripts/Activate.ps1
    python src/ollama_voice.py --model deepseek-r1:7b

Once running, you can speak and the assistant will reply out loud — just like talking to your own local AI “Jarvis.” (There’s no cloud dependency involved.)

🤖 The Technology Stack

This project brings together:

  • Ollama — A local LLM serving framework that lets you run open models on your machine.

  • Coqui TTS — Flexible text-to-speech engine for natural voice responses.

  • Python — Orchestrates the audio pipeline and connection to Ollama.

This combo enables a fully offline voice AI experience — the same architecture other advanced voice chat feats are using in larger projects.

🧠 What’s Next

This is the first version of the project, and there’s a lot of room for exploration:

  • Add real-time voice input with VAD (voice activity detection).

  • Support additional languages and TTS voices.

  • Build a GUI or browser-based frontend.

  • Integrate other local STT engines (e.g., Whisper).

If you’re building local voice UIs or privacy-centric assistants, this project can act as a solid base you can customize. Explore it on GitHub and let me know what you create! 

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