Simple way to make locally client Ollama available via WebSockets (github.com)

A new Rust-based client, called the ollama-wsock-connector, has been introduced to facilitate local inference for users leveraging their own Ollama instances via WebSockets. This innovative tool allows service operators to implement "bring-your-own local inference" capabilities without compromising user privacy, as prompts and completions remain on the user's machine. The connector effectively dials out to connect with a remote WebSocket service, enabling seamless communication between a user's local Ollama instance and the service backend while sidestepping the complexities of network configurations and firewalls. This advancement is significant for the AI/ML community, particularly for applications requiring rigorous data privacy, cost efficiency, and compliance with regulations. By enabling users to run AI models locally, it eliminates costs associated with cloud token payments and ensures that users can select any model they have locally, including those that cannot be legally hosted by the service providers. The connector simplifies the deployment process, requiring the user to download just two files and run a command to establish functionality, making it an accessible solution even for those without deep technical knowledge in WebSockets or Rust.