"BentoML provides our research teams a streamlined way to quickly iterate on their POCs and when ready, deploy their AI services at scale. In addition, the flexible architecture allows us to showcase and deploy many different types of models and workflows from Computer Vision to …

BentoML is a Unified Inference Platform for deploying and scaling AI models with production-grade reliability, all without the complexity of managing infrastructure. It enables your developers to build AI systems 10x faster with custom models, scale efficiently in your cloud, and maintain complete control over security and compliance .

In BentoML, you use the bentoml.monitor context manager to log data related to model inference. It allows you to specify a monitoring session where you can log various data types. This ensures that logging is structured and organized, making it easier to analyze the data later.

Log in to BentoCloud using the BentoML CLI¶ CLI login requires an API token with Developer Operations Access. Run the bentoml cloud login command.

A collection of example projects for learning BentoML and building your own solutions.

Jan 3, 2020 · BentoML allows you to specify the desired version and install a package from a custom PyPI source or from a GitHub repository. If a package lacks a specific version, BentoML will lock the versions of all Python packages for the current platform and Python when building a …

Adaptive batching is a dispatching mechanism in BentoML, which adjusts both the batch window and size based on traffic patterns. This mechanism minimizes latency and optimizes resource usage by con...

Import a bento model exported with bentoml.models.export_model. To import a model saved with a framework, see the save function under the relevant framework, e.g. bentoml.sklearn.save. Examples:

With BentoML tasks, you can send prompts first and then asynchronously get the results. Here is the general workflow of using BentoML tasks: Define a task endpoint ¶

BentoML supports streaming responses for various applications, such as large language model (LLM) output and audio synthesis. LLM output¶ In BentoML, you can stream LLM output using Python generators. Here’s an example using OpenAI’s API: