Vinv is an autonomous open-source swarm that finds bugs, dead code, and performance issues in your codebase and fixes them through a closed-loop reinforcement loop paired with the coding agent you already pay for. Nine parallel oracles drive a real run of your code with inputs no one wrote, adversarial-but-legal shapes at every dependency boundary, concurrent schedules, and every symbol no test coverage ever executed, then hand findings to your editor and verify every fix against acceptance tests written before the change that the agent never sees. A speedup only lands when behaviour replays byte-identical and the statistics clear the bar; otherwise the change is reverted automatically. Vinv is Python-first (services and plain libraries), with TypeScript and Go next, runs fully on your machine under Apache-2.0 with no account, no API keys, and no telemetry, and is distributed via Open VSX. It matters now because AI agents claim success they cannot prove, and Vinv turns judgment from the agent's word into what the code actually did.
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Ollama is a local AI platform for running, managing, and sharing open models on your own machine or private infrastructure. It makes it easy to pull models, serve them through an API, and integrate local inference into developer workflows without relying on a fully managed cloud stack. Teams use Ollama for privacy-sensitive assistants, internal tools, offline experimentation, and rapid testing of open-weight models across laptops, workstations, and servers. It is especially useful for developers, operators, and AI builders who want quick setup with less operational overhead. What makes Ollama distinctive is how approachable it is: it packages model runtime, distribution, and deployment into a streamlined experience that helps people get productive with local AI in minutes instead of spending days on configuration.
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