General
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github_checks:
annotations: false
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General
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Security Policy
BentoML is currently under active development and releases a new version
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<picture>
<source media="(prefers-color-scheme: dark)" srcset="https://github.com/bentoml/BentoML/assets/489344/d3e6c95d-d224-49a5-9cff-0789f094e127">
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General
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Developer Guide
Before getting started, check out the `#bentoml-contributors` channel in the [BentoML community slack](https://l.bentoml.com/join-slack).
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Contributor Covenant Code of Conduct
We as members, contributors, and leaders pledge to make participation in our
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.yamllint.yml
---
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See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
version: 2
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Contributing to BentoML
[BentoML](https://github.com/bentoml/BentoML) is an open and community-driven project. Everyone is welcome to contribute.
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grpc-client/java/src/main/java/com/bentoml
grpc-client/kotlin/src/main/kotlin/com/bentoml
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ci:
autoupdate_schedule: monthly
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Byte-compiled / optimized / DLL files
__pycache__/
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.python Version Default
3.11
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typings/**/*.pyi linguist-generated=true
*_pb2*.py linguist-generated=true
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load bazelrc from the legacy location as recommended
import %workspace%/tools/bazel.rc
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Deploying the Phospho Platform with Docker
Welcome! This guide will help you deploy the Phospho Platform using Docker Compose. Phospho is an advanced backoffice for managing your LLM apps, with tools like clustering, data labeling, and user analytics. This deployment guide is designed to provide easy-to-follow steps, allowing you to set up P
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Contribution guide
We welcome contributions from every respectful contributor!
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limit.maxIDLength:
- value: 255
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services:
platform:
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Deploy with Docker
This guide describes how to deploy the Argilla Server with docker compose. This is useful if you want to deploy Argilla locally, and/or have full control over the configuration the server, database, and search engine (Elasticsearch).
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General
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The LLM app backoffice for busy builders
<div align="center">
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.DS_Store
.vscode/
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LangKit
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LangKit is an open-source text metrics toolkit for monitoring language models. It offers an array of methods for extracting relevant signals from the input and/or output text, which are compatible wit
> 💡 Want to experience LangKit? Go to this [notebook](https://github.com/whylabs/langkit/blob/main/langkit/examples/Intro_to_Langkit.ipynb)!
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!__init__.py
.mypy_cache
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