Llama-swap is a lightweight, transparent proxy server designed to automate model swapping for llama.cpp's server. It allows users to run multiple large language models (LLMs) locally and switch between them dynamically without restarting applications.
Key Features:
Automatic model switching based on API requests
Compatibility with any OpenAI-compatible local server (llama.cpp, vllm, tabbyAPI)
Real-time web UI for monitoring model activity and logs
Support for Docker and Podman containerization
Zero external dependencies
Ideal for developers and machine learning enthusiasts who want to experiment with different models or provide flexible LLM capabilities in their applications.
README
llama-swap
Run multiple LLM models on your machine and hot-swap between them as needed. llama-swap works with any OpenAI API-compatible server, giving you the flexibility to switch models without restarting your applications.
Built in Go for performance and simplicity, llama-swap has zero dependencies and is incredibly easy to set up. Get started in minutes - just one binary and one configuration file.
Features:
✅ Easy to deploy and configure: one binary, one configuration file. no external dependencies
✅ On-demand model switching
✅ Use any local OpenAI compatible server (llama.cpp, vllm, tabbyAPI, etc)
future proof, upgrade your inference servers at any time.
When a request is made to an OpenAI compatible endpoint, llama-swap will extract the model value and load the appropriate server configuration to serve it. If the wrong upstream server is running, it will be replaced with the correct one. This is where the "swap" part comes in. The upstream server is automatically swapped to handle the request correctly.
In the most basic configuration llama-swap handles one model at a time. For more advanced use cases, the groups feature allows multiple models to be loaded at the same time. You have complete control over how your system resources are used.
Reverse Proxy Configuration (nginx)
If you deploy llama-swap behind nginx, disable response buffering for streaming endpoints. By default, nginx buffers responses which breaks Server‑Sent Events (SSE) and streaming chat completion. (#236)
As a safeguard, llama-swap also sets X-Accel-Buffering: no on SSE responses. However, explicitly disabling proxy_buffering at your reverse proxy is still recommended for reliable streaming behavior.
Monitoring Logs on the CLI
# sends up to the last 10KB of logs
curl http://host/logs'
# streams combined logs
curl -Ns 'http://host/logs/stream'
# just llama-swap's logs
curl -Ns 'http://host/logs/stream/proxy'
# just upstream's logs
curl -Ns 'http://host/logs/stream/upstream'
# stream and filter logs with linux pipes
curl -Ns http://host/logs/stream | grep 'eval time'
# skips history and just streams new log entries
curl -Ns 'http://host/logs/stream?no-history'
Do I need to use llama.cpp's server (llama-server)?
Any OpenAI compatible server would work. llama-swap was originally designed for llama-server and it is the best supported.
For Python based inference servers like vllm or tabbyAPI it is recommended to run them via podman or docker. This provides clean environment isolation as well as responding correctly to SIGTERM signals for proper shutdown.
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