{"repo":"farshed/sage","free":true,"listed":false,"github":"https://github.com/farshed/sage","clone":"git clone https://github.com/farshed/sage.git","description":"Self-hosted voice chat with LLMs","language":"Rust","stars":466,"topics":[],"license":"MIT","category":"self-hosted-apps","readme_excerpt":"Sage Converse with large language models using speech. DEMO - Open : Powered by state-of-the-art open-source speech processing models. - Efficient : Light enough to run on consumer hardware, with low latency. - Self-hosted : Entire pipeline runs offline, limited only by compute power. - Modular : Switching LLM providers is as simple as changing an environment variable. How it works Run 1. For text generation, you can either self-host an LLM using Ollama, or opt for a third-party provider. This can be configured using a .env file in the project root. - If you're using Ollama , add the OLLAMA MODEL variable to the .env file to specify the model you'd like to use. (Example: OLLAMA MODEL=deepseek-r1:7b ) - Among the third-party providers , Sage supports the following out of the box: 1. Deepseek 2. OpenAI 3. Anthropic 4. Together.ai - To use a provider, add a API KEY variable to the .env file. (Example: OPENAI API KEY=xxxxxxxxxxxxxxxxxxxxxxx ) - To choose which model should be used for a given provider, use the MODEL variable. (Example: DEEPSEEK MODEL=deepseek-chat ) 2. Next, you have two choices: Run Sage as a Docker container (the easy way) or natively (the hard way). Note that running it with Docker may have a performance penalty (Inference with whisper is 4-5x slower compared to native). - With Docker : Install Docker and start the daemon. Download the following files and place them inside a models directory at the project root. - kokoro-v0 19.onnx - voices.json - ggml-large-v","default_branch":null,"files":null,"tree":[],"storefront":"/r/farshed","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/farshed/sage/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}