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2 changes: 1 addition & 1 deletion LICENSE
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Expand Up @@ -6,7 +6,7 @@ The license for a piece of source code is defined with the following prioritized
3. First LICENSE file found in the parent directories up to the top level
4. By default to the Elastic License 2.0 (ELv2)

If you have any question regarding licenses, just visit our [License](https://www.instill.tech/docs/license) or [contact us](mailto:[email protected]).
If you have any question regarding licenses, please [contact us](mailto:[email protected]).

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Elastic License 2.0 (ELv2)
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129 changes: 14 additions & 115 deletions README.md
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<h1 align="center">
<img src="https://raw.githubusercontent.com/instill-ai/.github/main/img/vdp.svg" alt="Versatile Data Pipeline: unstructured data ETL">
</h1>

<h4 align="center">
<a href="https://www.instill.tech/career?utm_source=github&utm_medium=banner&utm_campaign=vdp_readme">We're hiring 🚀</a>
</h4>

<h4 align="center">
<a href="https://www.instill.tech/docs?utm_source=github&utm_medium=banner&utm_campaign=vdp_readme">Doc</a> |
<a href="https://www.instill.tech/?utm_source=github&utm_medium=banner&utm_campaign=vdp_readme">Website</a> |
<a href="https://discord.gg/sevxWsqpGh">Community</a> |
<a href="https://blog.instill.tech/?utm_source=github&utm_medium=banner&utm_campaign=vdp_readme">Blog</a>
</h4>

---

# Instill VDP &nbsp; [![Twitter URL](https://img.shields.io/twitter/url?logo=twitter&style=social&url=https%3A%2F%2Fgithub.com%2Finstill-ai%2Fvdp)](https://twitter.com/intent/tweet?url=https%3A%2F%2Fgithub.com%2Finstill-ai%2Fvdp&via=instill_tech&text=Build%20end-to-end%20unstructured%20data%20processing%20pipelines%20with%20VDP%2C%2010x%20faster.&hashtags=ETL%2Cvdp%2Cdata%2Cai%2Cml%2Copensource)
# Instill VDP

[![GitHub release (latest SemVer including pre-releases)](https://img.shields.io/github/v/release/instill-ai/vdp?&label=Release&color=blue&include_prereleases&logo=data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMjQiIGhlaWdodD0iMjQiIHZpZXdCb3g9IjAgMCAyNCAyNCIgZmlsbD0ibm9uZSIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KPHBhdGggZD0iTTQgOEg3VjRIMjNWMTdIMjFDMjEgMTguNjYgMTkuNjYgMjAgMTggMjBDMTYuMzQgMjAgMTUgMTguNjYgMTUgMTdIOUM5IDE4LjY2IDcuNjYgMjAgNiAyMEM0LjM0IDIwIDMgMTguNjYgMyAxN0gxVjEyTDQgOFpNMTggMThDMTguNTUgMTggMTkgMTcuNTUgMTkgMTdDMTkgMTYuNDUgMTguNTUgMTYgMTggMTZDMTcuNDUgMTYgMTcgMTYuNDUgMTcgMTdDMTcgMTcuNTUgMTcuNDUgMTggMTggMThaTTQuNSA5LjVMMi41NCAxMkg3VjkuNUg0LjVaTTYgMThDNi41NSAxOCA3IDE3LjU1IDcgMTdDNyAxNi40NSA2LjU1IDE2IDYgMTZDNS40NSAxNiA1IDE2LjQ1IDUgMTdDNSAxNy41NSA1LjQ1IDE4IDYgMThaIiBmaWxsPSJ3aGl0ZSIvPgo8L3N2Zz4K)](https://github.com/instill-ai/vdp/releases)
[![Artifact Hub](https://img.shields.io/endpoint?url=https://artifacthub.io/badge/repository/instill-ai)](https://artifacthub.io/packages/helm/instill-ai/vdp)
Expand All @@ -26,46 +9,31 @@
[![License ELv2](https://img.shields.io/badge/License-ELv2%20-blue)](https://github.com/instill-ai/vdp/blob/main/LICENSE)


**Versatile Data Pipeline (VDP)** is a source available unstructured data ETL tool to streamline the end-to-end unstructured data processing pipeline:

- **Extract** unstructured data from pre-built data sources such as cloud/on-prem storage, or IoT devices

- **Transform** it into analysable or meaningful data representations by AI models
💧 **Instill VDP (Versatile Data Pipeline)** is a source available unstructured data ETL tool to streamline the end-to-end unstructured data processing pipeline.

- **Load** the transformed data into warehouses, applications, or other destinations

![VDP Concept](https://artifacts.instill.tech/imgs/vdp-concept.png?id=1)
☁️ **Instill Cloud** offers fully managed Instill VDP. Please [sign up](https://console.instill.tech) to try out for free.

## Highlights

- 🚀 **[The fastest way to build end-to-end unstructured data pipelines](https://www.instill.tech/docs/core-concepts/pipeline)** - building a pipeline is like assembling LEGO blocks

- ⚡️ **[High-performing backends](https://www.instill.tech/docs/prepare-models/overview)** implemented in Go with Triton Inference Server for unleashing the full power of NVIDIA GPU architecture (e.g., concurrency, scheduler, batcher) supporting TensorRT, PyTorch, TensorFlow, ONNX, Python and more.

- 🖱️ **[One-click import & deploy ML/DL models](https://www.instill.tech/docs/import-models/overview)** from GitHub, Hugging Face or cloud storage managed by version control tools like DVC or ArtiVC

- 📦 **[Standardised AI Task](https://www.instill.tech/docs/core-concepts/ai-task)** output formats to streamline data integration or analysis

- 🔌 **[Pre-built ETL data connectors](https://www.instill.tech/docs/core-concepts/connector)** for extensive data access integrated with Airbyte
- 🧬 **[The backbone for all your AI needs](https://www.instill.tech/docs/core-concepts/pipeline)** - production-ready AI-first applications built with LLM, Diffusion Models and more

- 🪢 **[Build pipelines for diverse scenarios](https://www.instill.tech/docs/core-concepts/pipeline#mode)** - **SYNC** mode for real-time inference and **ASYNC** mode for on-demand workload
- 🚀 **[The fastest way to build unstructured data pipelines](https://www.instill.tech/docs/core-concepts/pipeline)** - building a pipeline is like assembling LEGO blocks

- 🧁 **[Scalable API-first microservice design for great developer experience](https://www.instill.tech/docs/start-here/faq#tech)** - seamless integration to modern data stack at any scale
- ⚡️ **[High-performing backends](https://www.instill.tech/docs/prepare-models/overview)** implemented in Go

- 🤠 **[Built for every AI and Data practitioner](https://www.instill.tech/docs/start-here/faq#essentials)** - The no-/low-code interface helps take off your AI Researcher/AI Engineer/Data Engineer/Data Scientist hat and *put on the all-rounder hat* to deliver more with VDP
- 🔌 **[Pre-built miscellaneous connectors](https://www.instill.tech/docs/core-concepts/connector)** for extensive data and AI access

## Demo playground
- 🪢 **[Build pipelines for diverse scenarios](https://www.instill.tech/docs/core-concepts/pipeline#mode)** - **SYNC** mode for real-time inference, and **ASYNC** or **PULL/PUSH** mode for on-demand workload

An online demo VDP instance has been provisioned, in which you can directly play around the basic features in its Console via https://demo.instill.tech.
- 🧁 **[Scalable API-first platform](https://www.instill.tech/docs/start-here/faq#tech)** - seamless integration to modern data stack at any scale

Want to showcase your ML/DL models? We offer fully-managed VDP on Instill Cloud. Please [sign up the form](https://www.instill.tech/get-access/?utm_source=github&utm_medium=banner&utm_campaign=vdp_readme) and we will reach out to you.
- 🤠 **[Built for every AI and Data practitioner](https://www.instill.tech/docs/start-here/faq#essentials)** - The no-/low-code interface helps take off your AI Researcher, AI Engineer, Data Engineer, Data Scientist, designer, marketer and content creator hat and *put on the all-rounder hat* to deliver more with VDP

## Prerequisites

- **macOS or Linux** - VDP works on macOS or Linux, but does not support Windows yet.

- **Docker and Docker Compose** - VDP uses Docker Compose (specifically, `Compose V2` and `Compose specification`) to run all services at local. Please install the latest stable [Docker](https://docs.docker.com/get-docker/) and [Docker Compose](https://docs.docker.com/compose/install/) before using VDP.
- `yq` > `v4.x`. Please follow the installation [guide](https://github.com/mikefarah/yq/#install).
- **(Optional) NVIDIA Container Toolkit** - To enable GPU support in VDP, please refer to [NVIDIA Cloud Native Documentation](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html) to install NVIDIA Container Toolkit. If you'd like to specifically allot GPUs to VDP, you can set the environment variable `NVIDIA_VISIBLE_DEVICES`. For example, `NVIDIA_VISIBLE_DEVICES=0,1` will make the `triton-server` consume GPU device id `0` and `1` specifically. By default `NVIDIA_VISIBLE_DEVICES` is set to `all` to use all available GPUs on the machine.

## Quick start
Expand All @@ -81,99 +49,30 @@ $ make all

🚀 That's it! Once all the services are up with health status, the UI is ready to go at http://localhost:3000!

![VDO Console](https://artifacts.instill.tech/imgs/vdp-console.png?)

Jump right in [VDP 101: Create your first pipeline on VDP](https://www.instill.tech/tutorials/vdp-101-3-create-your-first-pipeline/?utm_source=github&utm_medium=banner&utm_campaign=vdp_readme) and explore other [VDP tutorials](https://www.instill.tech/tutorials/?utm_source=github&utm_medium=banner&utm_campaign=vdp_readme).

> **Note**
>
> The image of model-backend (~2GB) and Triton Inference Server (~23GB) can take a while to pull, but this should be an one-time effort at the first setup.
**Shut down VDP**

To shut down all running services:
```
$ make down
```
### Guidance philosophy
VDP is built with open heart and we expect VDP to be exposed to more MLOps integrations. It is implemented with microservice and API-first design principle. Instead of building all components from scratch, we've decided to adopt sophisticated open-source tools:

- [Triton Inference Server](https://github.com/triton-inference-server/server) for high-performance model serving

- [Temporal](https://github.com/temporalio/temporal) for a reliable, durable and scalable workflow engine

- [Airbyte](https://github.com/airbytehq/airbyte) for abundant destination connectors

We hope VDP can also enrich the open-source communities in a way to bring more practical use cases in unstructured data processing.
> **Note**
> Code in the main branch tracks under-development progress towards the next release and may not work as expected. If you are looking for a stable alpha version, please use [latest release](https://github.com/instill-ai/vdp/releases).
## Documentation

📔 **Documentation**


Check out the [documentation & tutorials](https://www.instill.tech/docs?utm_source=github&utm_medium=banner&utm_campaign=vdp_readme) to learn VDP!
Please check out the [documentation](https://www.instill.tech/docs?utm_source=github&utm_medium=banner&utm_campaign=vdp_readme) website.

📘 **API Reference**

The gRPC protocols in [protobufs](https://github.com/instill-ai/protobufs) provide the single source of truth for the VDP APIs. The genuine protobuf documentation can be found in our [Buf Scheme Registry (BSR)](https://buf.build/instill-ai/protobufs).

For the OpenAPI documentation, access http://localhost:3001 after `make all`, or simply run `make doc`.

## Model Hub

We curate a list of ready-to-use models for VDP. These models are from different sources and have been tested by our team. Want to contribute a new model? Please create an issue, we are happy to test and add it to the list 👐.

| Model | Task | Sources | Framework | CPU | GPU |
| --------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ----------------- | --- | --- |
| [MobileNet v2](https://github.com/onnx/models/tree/main/vision/classification/mobilenet) | Image Classification | [GitHub-DVC](https://github.com/instill-ai/model-mobilenetv2-dvc) | ONNX | ✅ | ✅ |
| [Vision Transformer (ViT)](https://huggingface.co/google/vit-base-patch16-224) | Image Classification | [Hugging Face](https://huggingface.co/google/vit-base-patch16-224) | ONNX | ✅ | ❌ |
| [YOLOv4](https://github.com/AlexeyAB/darknet) | Object Detection | [GitHub-DVC](https://github.com/instill-ai/model-yolov4-dvc) | ONNX | ✅ | ✅ |
| [YOLOv7](https://github.com/WongKinYiu/yolov7) | Object Detection | [GitHub-DVC](https://github.com/instill-ai/model-yolov7-dvc) | ONNX | ✅ | ✅ |
| [YOLOv7 W6 Pose](https://github.com/WongKinYiu/yolov7) | Keypoint Detection | [GitHub-DVC](https://github.com/instill-ai/model-yolov7-pose-dvc) | ONNX | ✅ | ✅ |
| [PSNet](https://github.com/open-mmlab/mmocr/tree/main/configs/textdet/psenet) + [EasyOCR](https://github.com/JaidedAI/EasyOCR) | Optical Character Recognition (OCR) | [GitHub-DVC](https://github.com/instill-ai/model-ocr-dvc) | ONNX | ✅ | ✅ |
| [Mask RCNN](https://github.com/onnx/models/blob/main/vision/object_detection_segmentation/mask-rcnn/model/MaskRCNN-10.onnx) | Instance Segmentation | [GitHub-DVC](https://github.com/instill-ai/model-instance-segmentation-dvc) | PyTorch | ✅ | ✅ |
| [Lite R-ASPP based on MobileNetV3](https://github.com/open-mmlab/mmsegmentation/tree/98dfa1749bac0b5281502f4bb3832379da8feb8c/configs/mobilenet_v3) | Semantic Segmentation | [GitHub-DVC](https://github.com/instill-ai/model-semantic-segmentation-dvc) | ONNX | ✅ | ✅ |
| [Stable Diffusion](https://huggingface.co/runwayml/stable-diffusion-v1-5) | Text to Image | [GitHub-DVC](https://github.com/instill-ai/model-diffusion-dvc), [Local-CPU](https://artifacts.instill.tech/vdp/sample-models/stable-diffusion-1-5-cpu.zip), [Local-GPU](https://artifacts.instill.tech/vdp/sample-models/stable-diffusion-1-5-fp16-gpu.zip) | ONNX | ✅ | ✅ | |
| [Megatron GPT2](https://catalog.ngc.nvidia.com/orgs/nvidia/models/megatron_lm_345m) | Text Generation | [GitHub-DVC](https://github.com/instill-ai/model-gpt2-megatron-dvc) | FasterTransformer | ❌ | ✅ |


Note: The `GitHub-DVC` source in the table means importing a model into VDP from a GitHub repository that uses [DVC](https://dvc.org) to manage large files.

## Community support

For general help using VDP, you can use one of these channels:

- [GitHub](https://github.com/instill-ai/vdp) - bug reports, feature requests, project discussions and contributions

- [Discord](https://discord.gg/sevxWsqpGh) - live discussion with the community and our team

- [Newsletter](https://www.instill.tech/newsletter/?utm_source=github&utm_medium=banner&utm_campaign=vdp_readme) & [Twitter](https://twitter.com/instill_tech) - get the latest updates

If you are interested in hosting service of VDP, we've started signing up users to our private alpha. [Get early access](https://www.instill.tech/get-access/?utm_source=github&utm_medium=banner&utm_campaign=vdp_readme) and we'll contact you when we're ready.

## Contributing

We love contribution to VDP in any forms:

- Please refer to the [guideline](https://www.instill.tech/docs/development/setup-local-development/?utm_source=github&utm_medium=banner&utm_campaign=vdp_readme) for local development.

- Please open a topic in the repository [Discussions](https://github.com/instill-ai/vdp/discussions) for any feature requests.

- Please open issues for bug report in the repository

- [vdp](https://github.com/instill-ai/vdp) for general issues;

- [pipeline-backend](https://github.com/instill-ai/pipeline-backend), [connector-backend](https://github.com/instill-ai/connector-backend), [model-backend](https://github.com/instill-ai/model-backend), [console](https://github.com/instill-ai/console), etc., for specific issues.

- Please refer to the [VDP project board](https://github.com/orgs/instill-ai/projects/5) to track progress.

> **Note**
> Code in the main branch tracks under-development progress towards the next release and may not work as expected. If you are looking for a stable alpha version, please use [latest release](https://github.com/instill-ai/vdp/releases).
Please refer to the [community](https://github.com/instill-ai/community) repository.

## License

See the [LICENSE](./LICENSE) file for licensing information.

## We're hiring 🚀

Interested in building VDP with us? Join our remote team and build the future for unstructured data ETL. Check out [our open roles](https://www.instill.tech/career?utm_source=github&utm_medium=banner&utm_campaign=vdp_readme).

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