4 dépôts
Execution of services as independent host-managed processes.
Explore 4 awesome GitHub repositories matching operating systems & systems programming · Subprocess-Based Isolation. Refine with filters or upvote what's useful.
The Model Context Protocol is a standardized communication framework designed to connect language models to external data sources, functional tools, and interactive user interfaces. It provides a vendor-neutral interface layer that enables AI hosts to discover and execute capabilities across heterogeneous service environments, using a JSON-RPC based messaging standard to facilitate bidirectional communication between clients and servers. The protocol distinguishes itself through a robust capability-based handshake that negotiates feature sets during session initialization, ensuring compatibil
Executes service instances as independent host-managed processes to enforce security boundaries and resource management.
Wasmer is a high-performance runtime engine designed to execute sandboxed WebAssembly modules across server-side, edge, and browser environments. It functions as a comprehensive platform for building, distributing, and running isolated applications, providing a secure and portable execution layer that maintains consistency across diverse hardware architectures and operating systems. The platform distinguishes itself through a robust toolchain that enables cross-language interoperability and the transformation of code into portable binary packages. It supports ahead-of-time binary generation t
Enables secure inter-process communication and process spawning within an isolated environment using dedicated pipes.
Cog is a machine learning packaging tool and containerized model wrapper that bundles models and their dependencies into standardized Docker containers. It functions as an environment manager and inference server, ensuring consistent model execution across different hardware systems by resolving GPU drivers, system libraries, and Python dependencies. The project distinguishes itself by automatically generating RESTful HTTP servers and OpenAPI schemas based on defined model input and output types. It manages large model weights as external fixtures to optimize image size and utilizes a slot-ba
Executes model inferences in separate subprocesses to isolate the main server from memory leaks or crashes.
rlm is an LLM code execution engine and orchestration framework designed to coordinate multiple language model calls and recursive sub-tasks through a programmable environment. It provides a sandboxed REPL environment and a recursive context processor to handle inputs that exceed standard token limits by programmatically decomposing prompts. The project differentiates itself through a reinforcement learning training harness used to teach models how to utilize recursive calls and code execution. It includes a reasoning visualization system that records and renders execution trajectories to ana
Runs generated code in separate subprocesses to ensure namespace isolation and strictly enforce execution timeouts.