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Meta AI has released the first stable version of Llama Stack, a unified platform designed to simplify the complexities of building and deploying AI solutions.
Some of the key features and benefits of Llama Stack 0.1.0 include:
Backward-compatible upgrades to ensure seamless integration with future API versions without modifying existing implementations. Automated provider verification to enable faster and error-free integration with supported providers. Modular architecture that sets the stage for creating scalable and production-ready applications. One-stop solution for building production-grade applications, supporting APIs covering inference, Retrieval-Augmented Generation (RAG), agents, safety, and telemetry. Ability to operate uniformly across local, cloud, and edge environments, making it a standout in AI development. SDKs for Python, Node.js, Swift, and Kotlin to support developers with tools and templates to streamline the integration process. Interactive demos and evaluation tools to guide development and benchmark model performance in the Playground environment.
This folder contains some example client scripts using our Python SDK for connecting with Llama Stack Distros. Instructions are provided for setting up dependencies and running demo scripts and apps.
Llama Stack v0.1.0 introduces a stable API release enabling developers to build RAG applications and agents, integrate with various tools, and use telemetry for monitoring and evaluation. This release provides a comprehensive interface, rich provider ecosystem, and multiple developer interfaces, along with sample applications for Python, iOS, and Android.
Meta has launched Llama-Stack 0.1.0, a development platform designed to simplify the process of building AI applications using Llama models. The platform offers standardized building blocks and flexible deployment options, including remote and local hosting. It features a plugin system for various API providers and supports multiple programming environments with its CLI tools and SDKs. Meta aims to address common challenges faced by AI developers, such as integrating tools and managing data sources.
This repository contains the Llama Stack API specifications as well as API Providers and Llama Stack Distributions. The Llama Stack aims to standardize the building blocks needed for generative AI applications across various development stages.
It includes API specifications and providers for the Llama Stack, which aims to standardize components needed for developing generative AI applications. The stack includes APIs for Inference, Safety, Memory, Agentic System, Evaluation, Post Training, Synthetic Data Generation, and Reward Scoring. Providers offer actual implementations for these APIs, either through open-source libraries or remote REST services.
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