v1.0.0

# 🚀 Added

## 💪 `inference 1.0.0` just landed 🔥 

We are excited to announce the official 1.0.0 release of Inference - which was announced 2 weeks ago with [1.0.0rc1 preview release](https://github.com/roboflow/inference/releases/tag/v1.0.0rc1).

Over the past years, Inference has evolved from a lightweight prediction server into a widely adopted runtime powering local deployments, Docker workloads, edge devices, and production systems. After hundreds of releases, the project has matured — and so has the need for **something faster, more modular, and more future-proof.**

`inference 1.0.0` closes one chapter and opens another. This release introduces a new prediction engine that will serve as the foundation for future development.

### ⚡ New prediction engine: `inference-models`

We are introducing inference-models, a redesigned engine to run models focused on:
* faster model loading and inference
* improved resource utilization
* better modularity and extensibility
* cleaner separation between serving and model runtime
* support from different backends - **including TensorRT**

> [!IMPORTANT]  
> With `inference 1.0.0` we released also first stable build of `inference-models 0.19.0`. You can use the engine in `inference` - just set env variable `USE_INFERENCE_MODELS=True`

> [!CAUTION]  
> The new `inference-models` engine is wrapped with adapters - to serve as **dropdown replacement** for old engine. We are making it default engine on Roboflow platform, but clients **running `inference` locally have the `USE_INFERENCE_MODELS` set to `False` by default.** We would like all clients to test the new engine - when the flag is not set, `inference` works as usually.
> In approximately 2 weeks, with `inference 1.1.0` release - we will **make `inference-models` default engine for everyone.**

> [!CAUTION]  
> `inference-models` is completely new backend, we've fixed a lot of problems and bugs. As a result - predictions from your model may be **different** - but according to our tests, quality-wise they are better. That being said, we still may have introduced some minor bugs - please report us any problems - we will do our best to fix problems 🙏 

### 🛣️ Roadmap
Todays release is just a start for broader changes in `inference` - the plan for the future is the following:
* shortly after release, we will complete our work around Roboflow platform - including migration of **small fraction of models not onboarded into new registry used by `inference-models`** and adjusting automations on the platform - until finished, clients who very recently uploaded or renamed models may be impacted by HTTP 404 - **contact us to receive support in such cases.** 
* there will be consecutive hot-fixes (if needed) - released as `1.0.x` versions.
* clients running `inference` locally should test `inference-models` backend now, as in approximately 2 weeks, `inference-models` will become default engine
* We have still some work to do in `1.x.x` - mainly to provide patches - **but we start a march towards 2.0**, which should bring new quality for other components of `inference` - **stay tuned for updates**.
* You should expect that new contributions to `inference` will be based on `inference-models` engine and may **not work if you don't migrate**.

> [!CAUTION]  
> One of the problem we have not addressed in `1.0.0` is models cache purge - new `inference-models` engine uses different structure of the local cache than old engine. As a result - `inference` server with `USE_INFERENCE_MODELS=True` does not perform clean-up on volume with models pulled from the platform. If you run locally, generally that should not be an issue, since we expect clients only use limited number of different models in their deployments. 
> If you use large amount of models or when your disk space is tight, running new inference you should perform periodic clean-ups of `/tmp/cache`. This issue will be addressed before `1.1.0` release.

## 🎨 Semantic Segmentation in `inference`
<img width="3314" height="1688" alt="image" src="https://github.com/user-attachments/assets/e6b4791e-ca13-4ee7-88e7-c8dea6463e04" />

Thanks to @leeclemnet, DeepLabV3Plus segmentation model was onboarded to `inference` and can be used by clients.

## 📐 Area Measurement block 🤝 Workflows

Thanks to @jeku46  we can now measure area size with Workflows.

# 🚧 Maintanence
* add missing ffmpeg package for dev by @rafel-roboflow in https://github.com/roboflow/inference/pull/2009
* fix expose sam3 with proper envs by @rafel-roboflow in https://github.com/roboflow/inference/pull/2011
* Detections Class Replacement support for strings by @Erol444 in https://github.com/roboflow/inference/pull/2000
* fix: Send termination_reason via data channel on WebRTC stream timeout by @balthazur in https://github.com/roboflow/inference/pull/2008
* Remove content length validation to allow for chunked responses by @dkosowski87 in https://github.com/roboflow/inference/pull/2015
* added `processing_timeout` support to webrtc's `StreamConfig` dataclass by @Erol444 in https://github.com/roboflow/inference/pull/2017
* fix: Return 400 instead of 500 for raw bytes sent as base64 image by @bigbitbus in https://github.com/roboflow/inference/pull/2016
* Added claude sonnet 4.6 by @Erol444 in https://github.com/roboflow/inference/pull/2014
* Fix mkdocs-macros Jinja2 syntax errors in generated block docs by @yeldarby in https://github.com/roboflow/inference/pull/2012
* Add remote GPU processing time collection and forwarding by @hansent in https://github.com/roboflow/inference/pull/2007
* Add semantic-segmentation endpoints + deep_lab_v3_plus by @leeclemnet in https://github.com/roboflow/inference/pull/2018
* Update CODEOWNERS: Add dkosowski87 and reorganize team assignments by @hansent in https://github.com/roboflow/inference/pull/2021
* Add support for gemini 3.1 pro in gemini block by @Erol444 in https://github.com/roboflow/inference/pull/2024
* Add area_measurement workflow block by @jeku46 in https://github.com/roboflow/inference/pull/2013
* Auto-detect Jetson JetPack version in CLI server start by @alexnorell in https://github.com/roboflow/inference/pull/1958
* Ged rid of unstable assertions on predictions in e2e tests by @PawelPeczek-Roboflow in https://github.com/roboflow/inference/pull/2026
* ENT-884: Add `workflow_version_id` support to inference pipeline by @NVergunst-ROBO in https://github.com/roboflow/inference/pull/2022
* Add JetPack 7.1 support for NVIDIA Thor by @alexnorell in https://github.com/roboflow/inference/pull/1935

# 🏅  New Contributors
* @dkosowski87 made their first contribution in https://github.com/roboflow/inference/pull/2015
* @leeclemnet made their first contribution in https://github.com/roboflow/inference/pull/2018

**Full Changelog**: https://github.com/roboflow/inference/compare/v0.64.8...v1.0.0