Bump go-skynet/local-ai from v2.9.0-ffmpeg-core to v2.11.0-ffmpeg-core

[dependabot[bot]]

Bumps go-skynet/local-ai from v2.9.0-ffmpeg-core to v2.11.0-ffmpeg-core.

Release notes

Sourced from go-skynet/local-ai's releases.

v2.11.0

Introducing LocalAI v2.11.0: All-in-One Images!

Hey everyone! 🎉 I'm super excited to share what we've been working on at LocalAI - the launch of v2.11.0. This isn't just any update; it's a massive leap forward, making LocalAI easier to use, faster, and more accessible for everyone.

🌠 The Spotlight: All-in-One Images, OpenAI in a box

Imagine having a magic box that, once opened, gives you everything you need to get your AI project off the ground with generative AI. A full clone of OpenAI in a box. That's exactly what our AIO images are! Designed for both CPU and GPU environments, these images come pre-packed with a full suite of models and backends, ready to go right out of the box.

Whether you're using Nvidia, AMD, or Intel, we've got an optimized image for you. If you are using CPU-only you can enjoy even smaller and lighter images.

To start LocalAI, pre-configured with function calling, llm, tts, speech to text, and image generation, just run:

docker run -p 8080:8080 --name local-ai -ti localai/localai:latest-aio-cpu
Do you have a Nvidia GPUs? Use this instead
CUDA 11
docker run -p 8080:8080 --gpus all --name local-ai -ti localai/localai:latest-aio-gpu-cuda-11
CUDA 12
docker run -p 8080:8080 --gpus all --name local-ai -ti localai/localai:latest-aio-gpu-cuda-12

:heart: Why You're Going to Love AIO Images:

• Ease of Use: Say goodbye to the setup blues. With AIO images, everything is configured upfront, so you can dive straight into the fun part - hacking!
• Flexibility: CPU, Nvidia, AMD, Intel? We support them all. These images are made to adapt to your setup, not the other way around.
• Speed: Spend less time configuring and more time innovating. Our AIO images are all about getting you across the starting line as fast as possible.

🌈 Jumping In Is a Breeze:

Getting started with AIO images is as simple as pulling from Docker Hub or Quay and running it. We take care of the rest, downloading all necessary models for you. For all the details, including how to customize your setup with environment variables, our updated docs have got you covered here, while you can get more details of the AIO images here.

🎈 Vector Store

Thanks to the great contribution from @​richiejp now LocalAI has a new backend type, "vector stores" that allows to use LocalAI as in-memory Vector DB (mudler/LocalAI#1792). You can learn more about it here!

🐛 Bug fixes

This release contains major bugfixes to the watchdog component, and a fix to a regression introduced in v2.10.x which was not respecting --f16, --threads and --context-size to be applied as model's defaults.

🎉 New Model defaults for llama.cpp

Model defaults has changed to automatically offload maximum GPU layers if a GPU is available, and it sets saner defaults to the models to enhance the LLM's output.

🧠 New pre-configured models

You can now run llava-1.6-vicuna, llava-1.6-mistral and hermes-2-pro-mistral, see Run other models for a list of all the pre-configured models available in the release.

📣 Spread the word!

... (truncated)

Commits

• 1395e50 :arrow_up: Update ggerganov/llama.cpp (#1897)
• 42a4c86 :arrow_up: Update ggerganov/whisper.cpp (#1896)
• c9adc56 fix(aio): make image-gen for GPU functional, update docs (#1895)
• 08c7b17 Fix NVIDIA VRAM detection on WSL2 environments (#1894)
• 5e12382 NVIDIA GPU detection support for WSL2 environments (#1891)
• 6cf9952 docs(aio): Add All-in-One images docs (#1887)
• 3e293f1 :arrow_up: Update ggerganov/llama.cpp (#1889)
• 0106c58 :arrow_up: Update ggerganov/llama.cpp (#1885)
• bd25d80 fix(watchdog): use ShutdownModel instead of StopModel (#1882)
• 49cec7f ci(aio): add latest tag images (#1884)
• Additional commits viewable in compare view

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