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Because
- LLM runtimes are rapidly evolving, and mainstream tools like
`Transformers`, `vLLM`, and `MLC LLM` now support advanced LLM features.
This commit
- refactored CLI codebase
- unified Dockerfile for multi-platform build current supporting CPU for
both `amd64` and `arm64` and GPU for only `amd66`
- added unit testing for CLI commands
> **This SDK tool is under active development**<br>
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> For any bug found or featur request, feel free to open any issue regarding this SDK in our [instill-core](https://github.com/instill-ai/instill-core/issues) repo.
> For any bug found or feature request, feel free to open any issue regarding this SDK in our [instill-core](https://github.com/instill-ai/instill-core/issues) repo.
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## Overview
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Welcome to Instill Python SDK, where the world of AI-first application comes alive in the form of Python.
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## Setup
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> [!NOTE]<br>
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> [!NOTE]
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> For setting up development environment, please refer to [Contributing](#contributing)
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### Requirements
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- Python 3.8 - 3.11
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- Python 3.9 - 3.12
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- CUDA 12.2 - 12.8 (if you want to build a model with GPU support)
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### Installation
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> [!WARNING]<br>
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> If your host machine is on arm64 architecture(including Apple silicon machines, equipped with m1/m2 processors), there are some issues when installing `grpcio` within `conda` environment. You will have to manually build and install it like below. Read more about this issue [here](https://github.com/grpc/grpc/issues/33714).
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> [!WARNING]
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> If your host machine is on arm64 architecture(including Apple silicon machines, equipped with m1/m2 processors), there are some issues when installing `grpcio` within `conda` environment. You will have to manually build and install it like below. Read more about this issue in the [gRPC GitHub issue](https://github.com/grpc/grpc/issues/33714).
Install it directly into an activated virtual environment:
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```text
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$ pip install instill-sdk
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```shell
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pip install instill-sdk
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```
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or add it to your [Poetry](https://poetry.eustace.io/) project:
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```text
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$ poetry add instill-sdk
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```shell
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poetry add instill-sdk
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```
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### Check import
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After installation, you can check if it has been installed correctly:
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```text
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$ python
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```shell
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python
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>>> import instill
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>>> instill.__version__
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```
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### Config `Instill Core` or `Instill Cloud` instance
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### Config `Instill Core` or `Managed Instill Core` instance
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Before we can start using this SDK, you will need to properly config your target instance. We support two ways to setup the configs, which are
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#### Config file
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create a config file under this path `${HOME}/.config/instill/sdk/python/config.yml`, and within that path you will need to fill in some basic parameters for your desired host.[^1]
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[^1]: You can obtain an `api_token` by simply going to Settings > API Tokens page from the console, no matter it is `Instill Core` or `Instill Cloud`.
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[^1]: You can obtain an `api_token` by simply going to Settings > API Tokens page from the console, no matter it is `Instill Core` or `Managed Instill Core`.
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Within the config file, you can define multiple instances with the `alias` of your liking, later in the SDK you can refer to this `alias` to switch between instances.[^2]
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# ...
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```
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Please find more usages for this sdk at [here](https://www.instill-ai.dev/docs/sdk/python#usage)
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Please find more usages for this SDK in our [documentation](https://www.instill-ai.dev/docs/sdk/python#usage)
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**You can also find some notebook examples [here](https://github.com/instill-ai/python-sdk/tree/main/notebooks)**
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**You can also find some notebook examples in our [notebooks directory](https://github.com/instill-ai/python-sdk/tree/main/notebooks)**
`Instill Model` is an advanced MLOps/LLMOps platform that was specifically crafted to facilitate the efficient management and orchestration of model deployments for unstructured data ETL. With `Instill Model`, you can easily create, manage, and deploy your own custom models with ease in `Instill Core` or on the cloud with `Instill Cloud`.
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Follow the instructions [here](https://www.instill-ai.dev/docs/model/create) to build and deploy your model.
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Follow the [model creation guide](https://www.instill-ai.dev/docs/model/create) to build and deploy your model.
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