inference-client


Nameinference-client JSON
Version 0.0.8 PyPI version JSON
download
home_pagehttps://inference-api.jina.ai
SummaryPython Client for Jina Inference API
upload_time2023-07-12 04:28:05
maintainer
docs_urlNone
authorJina AI
requires_python>=3.8,<4.0.0
licenseApache-2.0
keywords jina inference api client
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            <p align="center">
<br>
<a href="https://cloud.jina.ai/user/inference"><img src="https://github.com/jina-ai/inference-client/blob/main/.github/README-img/inference_client.svg?raw=true" alt="" width="360px"></a>
<br>
</p>

[![PyPI](https://img.shields.io/pypi/v/inference-client)](https://pypi.org/project/inference-client/)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/inference-client)](https://pypi.org/project/inference-client/)
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Inference-Client is a Python library that allows you to interact with the [Jina AI Inference](https://cloud.jina.ai/user/inference). 
It provides a simple and intuitive API to perform various tasks such as image captioning, encoding, ranking, visual 
question answering (VQA), and image upscaling.

The current version of Inference Client includes methods to call the following tasks:

📷 **Caption**: Generate captions for images 

📈 **Encode**: Encode data into embeddings using various models 

🔍 **Rank**: Re-rank cross-modal matches according to their joint likelihood

🆙 **Upscale**: Increasing the resolution while preserving the quality and details

🤔 **VQA**: Answer questions related to images 


## Installation

Inference Client is available on PyPI and can be installed using pip:

```bash
pip install inference-client
```

## Getting Started

Before using the Inference-Client, please create an inference on [Jina AI Cloud](https://cloud.jina.ai/user/inference).

After the inference is created and the status is "Serving", you can use the Inference-Client to connect to it.
This could take a few minutes, depending on the model you selected.

### Client Initialization

To use the Inference-Client, you first need to import the `Client` class and create a new instance of it. 

```python
from inference_client import Client

client = Client(token='<your auth token>')
```

You will need to provide your access token when creating the client. The token can be generated at the [Jina AI Cloud](https://cloud.jina.ai/settings/tokens), or via CLI as described in [this guide](https://docs.jina.ai/jina-ai-cloud/login/#create-a-new-pat):
```bash
jina auth token create <name of PAT> -e <expiration days>
```

You can then use the `get_model` method of the `Client` object to get a specific model.

```python
model = client.get_model('<model of your selection>')
```
You can connect to as many inference models as you want once they have been created on Jina AI Cloud, and you can use them for multiple tasks.

## Performing tasks

Now that you have connected to the models, you can use them to perform the tasks they support.

### Image Captioning

The `caption` method of the `Model` object takes an image as input and returns a caption as output.

```python
image = 'path/to/image.jpg'
caption = model.caption(image=image)
```

### Encoding

The `encode` method of the `Model` object takes text or image data as input and returns an embedding as output.

```python
text = 'a sentence describing the beautiful nature'
embedding = model.encode(text=text)

# OR
image = 'path/to/image.jpg'
embedding = model.encode(image=image)
```

### Ranking

The `rank` method of the `Model` object takes a text or image data as query and a list of candidates as input and returns a list of reordered candidates as well as their scores as output.

```python
candidates = [
    'an image about dogs',
    'an image about cats',
    'an image about birds',
]
image = 'path/to/image.jpg'
result = model.rank(image=image, candidates=candidates)
```

### Image Upscaling

The `upscale` method of the `Model` object takes an image and optional configurations as input, and returns the upscaled image bytes as output.

```python
image = 'path/to/image.jpg'
result = model.upscale(image=image, output_path='upscaled_image.png', scale='800:600')
```

### Visual Question Answering (VQA)

The `vqa` method of the `Model` object takes an image and a question as input and returns an answer as output.

```python
image = 'path/to/image.jpg'
question = 'Question: What is the name of this place? Answer:'
answer = model.vqa(image=image, question=question)
```

## Advanced Usage

In addition to the basic usage, the Inference-Client also supports advanced features such as handling DocumentArray inputs, customizing the task parameters, and more. 
Please refer to the [official documentation](https://jina.readme.io/docs/inference) for more details.

## Support

- Join our [Discord community](https://discord.jina.ai) and chat with other community members about ideas.
- Watch our [Engineering All Hands](https://youtube.com/playlist?list=PL3UBBWOUVhFYRUa_gpYYKBqEAkO4sxmne) to learn Jina's new features and stay up-to-date with the latest AI techniques.
- Subscribe to the latest video tutorials on our [YouTube channel](https://youtube.com/c/jina-ai)

## License

Inference-Client is backed by [Jina AI](https://jina.ai) and licensed under [Apache-2.0](./LICENSE). 
                                 Apache License
                           Version 2.0, January 2004
                        http://www.apache.org/licenses/

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Raw data

            {
    "_id": null,
    "home_page": "https://inference-api.jina.ai",
    "name": "inference-client",
    "maintainer": "",
    "docs_url": null,
    "requires_python": ">=3.8,<4.0.0",
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    "keywords": "jina,inference,api,client",
    "author": "Jina AI",
    "author_email": "hello@jina.ai",
    "download_url": "https://files.pythonhosted.org/packages/7e/b8/df7d646f08514406eab854a1bf8f5eb4bad8e7b1ec3f40ddc302ed729db2/inference_client-0.0.8.tar.gz",
    "platform": null,
    "description": "<p align=\"center\">\n<br>\n<a href=\"https://cloud.jina.ai/user/inference\"><img src=\"https://github.com/jina-ai/inference-client/blob/main/.github/README-img/inference_client.svg?raw=true\" alt=\"\" width=\"360px\"></a>\n<br>\n</p>\n\n[![PyPI](https://img.shields.io/pypi/v/inference-client)](https://pypi.org/project/inference-client/)\n[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/inference-client)](https://pypi.org/project/inference-client/)\n[![PyPI - License](https://img.shields.io/pypi/l/inference-client)](https://pypi.org/project/inference-client/)\n\nInference-Client is a Python library that allows you to interact with the [Jina AI Inference](https://cloud.jina.ai/user/inference). \nIt provides a simple and intuitive API to perform various tasks such as image captioning, encoding, ranking, visual \nquestion answering (VQA), and image upscaling.\n\nThe current version of Inference Client includes methods to call the following tasks:\n\n\ud83d\udcf7 **Caption**: Generate captions for images \n\n\ud83d\udcc8 **Encode**: Encode data into embeddings using various models \n\n\ud83d\udd0d **Rank**: Re-rank cross-modal matches according to their joint likelihood\n\n\ud83c\udd99 **Upscale**: Increasing the resolution while preserving the quality and details\n\n\ud83e\udd14 **VQA**: Answer questions related to images \n\n\n## Installation\n\nInference Client is available on PyPI and can be installed using pip:\n\n```bash\npip install inference-client\n```\n\n## Getting Started\n\nBefore using the Inference-Client, please create an inference on [Jina AI Cloud](https://cloud.jina.ai/user/inference).\n\nAfter the inference is created and the status is \"Serving\", you can use the Inference-Client to connect to it.\nThis could take a few minutes, depending on the model you selected.\n\n### Client Initialization\n\nTo use the Inference-Client, you first need to import the `Client` class and create a new instance of it. \n\n```python\nfrom inference_client import Client\n\nclient = Client(token='<your auth token>')\n```\n\nYou will need to provide your access token when creating the client. The token can be generated at the [Jina AI Cloud](https://cloud.jina.ai/settings/tokens), or via CLI as described in [this guide](https://docs.jina.ai/jina-ai-cloud/login/#create-a-new-pat):\n```bash\njina auth token create <name of PAT> -e <expiration days>\n```\n\nYou can then use the `get_model` method of the `Client` object to get a specific model.\n\n```python\nmodel = client.get_model('<model of your selection>')\n```\nYou can connect to as many inference models as you want once they have been created on Jina AI Cloud, and you can use them for multiple tasks.\n\n## Performing tasks\n\nNow that you have connected to the models, you can use them to perform the tasks they support.\n\n### Image Captioning\n\nThe `caption` method of the `Model` object takes an image as input and returns a caption as output.\n\n```python\nimage = 'path/to/image.jpg'\ncaption = model.caption(image=image)\n```\n\n### Encoding\n\nThe `encode` method of the `Model` object takes text or image data as input and returns an embedding as output.\n\n```python\ntext = 'a sentence describing the beautiful nature'\nembedding = model.encode(text=text)\n\n# OR\nimage = 'path/to/image.jpg'\nembedding = model.encode(image=image)\n```\n\n### Ranking\n\nThe `rank` method of the `Model` object takes a text or image data as query and a list of candidates as input and returns a list of reordered candidates as well as their scores as output.\n\n```python\ncandidates = [\n    'an image about dogs',\n    'an image about cats',\n    'an image about birds',\n]\nimage = 'path/to/image.jpg'\nresult = model.rank(image=image, candidates=candidates)\n```\n\n### Image Upscaling\n\nThe `upscale` method of the `Model` object takes an image and optional configurations as input, and returns the upscaled image bytes as output.\n\n```python\nimage = 'path/to/image.jpg'\nresult = model.upscale(image=image, output_path='upscaled_image.png', scale='800:600')\n```\n\n### Visual Question Answering (VQA)\n\nThe `vqa` method of the `Model` object takes an image and a question as input and returns an answer as output.\n\n```python\nimage = 'path/to/image.jpg'\nquestion = 'Question: What is the name of this place? Answer:'\nanswer = model.vqa(image=image, question=question)\n```\n\n## Advanced Usage\n\nIn addition to the basic usage, the Inference-Client also supports advanced features such as handling DocumentArray inputs, customizing the task parameters, and more. \nPlease refer to the [official documentation](https://jina.readme.io/docs/inference) for more details.\n\n## Support\n\n- Join our [Discord community](https://discord.jina.ai) and chat with other community members about ideas.\n- Watch our [Engineering All Hands](https://youtube.com/playlist?list=PL3UBBWOUVhFYRUa_gpYYKBqEAkO4sxmne) to learn Jina's new features and stay up-to-date with the latest AI techniques.\n- Subscribe to the latest video tutorials on our [YouTube channel](https://youtube.com/c/jina-ai)\n\n## License\n\nInference-Client is backed by [Jina AI](https://jina.ai) and licensed under [Apache-2.0](./LICENSE). \n                                 Apache License\n                           Version 2.0, January 2004\n                        http://www.apache.org/licenses/\n\n   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION\n\n   1. Definitions.\n\n      \"License\" shall mean the terms and conditions for use, reproduction,\n      and distribution as defined by Sections 1 through 9 of this document.\n\n      \"Licensor\" shall mean the copyright owner or entity authorized by\n      the copyright owner that is granting the License.\n\n      \"Legal Entity\" shall mean the union of the acting entity and all\n      other entities that control, are controlled by, or are under common\n      control with that entity. For the purposes of this definition,\n      \"control\" means (i) the power, direct or indirect, to cause the\n      direction or management of such entity, whether by contract or\n      otherwise, or (ii) ownership of fifty percent (50%) or more of the\n      outstanding shares, or (iii) beneficial ownership of such entity.\n\n      \"You\" (or \"Your\") shall mean an individual or Legal Entity\n      exercising permissions granted by this License.\n\n      \"Source\" form shall mean the preferred form for making modifications,\n      including but not limited to software source code, documentation\n      source, and configuration files.\n\n      \"Object\" form shall mean any form resulting from mechanical\n      transformation or translation of a Source form, including but\n      not limited to compiled object code, generated documentation,\n      and conversions to other media types.\n\n      \"Work\" shall mean the work of authorship, whether in Source or\n      Object form, made available under the License, as indicated by a\n      copyright notice that is included in or attached to the work\n      (an example is provided in the Appendix below).\n\n      \"Derivative Works\" shall mean any work, whether in Source or Object\n      form, that is based on (or derived from) the Work and for which the\n      editorial revisions, annotations, elaborations, or other modifications\n      represent, as a whole, an original work of authorship. For the purposes\n      of this License, Derivative Works shall not include works that remain\n      separable from, or merely link (or bind by name) to the interfaces of,\n      the Work and Derivative Works thereof.\n\n      \"Contribution\" shall mean any work of authorship, including\n      the original version of the Work and any modifications or additions\n      to that Work or Derivative Works thereof, that is intentionally\n      submitted to Licensor for inclusion in the Work by the copyright owner\n      or by an individual or Legal Entity authorized to submit on behalf of\n      the copyright owner. For the purposes of this definition, \"submitted\"\n      means any form of electronic, verbal, or written communication sent\n      to the Licensor or its representatives, including but not limited to\n      communication on electronic mailing lists, source code control systems,\n      and issue tracking systems that are managed by, or on behalf of, the\n      Licensor for the purpose of discussing and improving the Work, but\n      excluding communication that is conspicuously marked or otherwise\n      designated in writing by the copyright owner as \"Not a Contribution.\"\n\n      \"Contributor\" shall mean Licensor and any individual or Legal Entity\n      on behalf of whom a Contribution has been received by Licensor and\n      subsequently incorporated within the Work.\n\n   2. Grant of Copyright License. Subject to the terms and conditions of\n      this License, each Contributor hereby grants to You a perpetual,\n      worldwide, non-exclusive, no-charge, royalty-free, irrevocable\n      copyright license to reproduce, prepare Derivative Works of,\n      publicly display, publicly perform, sublicense, and distribute the\n      Work and such Derivative Works in Source or Object form.\n\n   3. Grant of Patent License. Subject to the terms and conditions of\n      this License, each Contributor hereby grants to You a perpetual,\n      worldwide, non-exclusive, no-charge, royalty-free, irrevocable\n      (except as stated in this section) patent license to make, have made,\n      use, offer to sell, sell, import, and otherwise transfer the Work,\n      where such license applies only to those patent claims licensable\n      by such Contributor that are necessarily infringed by their\n      Contribution(s) alone or by combination of their Contribution(s)\n      with the Work to which such Contribution(s) was submitted. If You\n      institute patent litigation against any entity (including a\n      cross-claim or counterclaim in a lawsuit) alleging that the Work\n      or a Contribution incorporated within the Work constitutes direct\n      or contributory patent infringement, then any patent licenses\n      granted to You under this License for that Work shall terminate\n      as of the date such litigation is filed.\n\n   4. Redistribution. You may reproduce and distribute copies of the\n      Work or Derivative Works thereof in any medium, with or without\n      modifications, and in Source or Object form, provided that You\n      meet the following conditions:\n\n      (a) You must give any other recipients of the Work or\n          Derivative Works a copy of this License; and\n\n      (b) You must cause any modified files to carry prominent notices\n          stating that You changed the files; and\n\n      (c) You must retain, in the Source form of any Derivative Works\n          that You distribute, all copyright, patent, trademark, and\n          attribution notices from the Source form of the Work,\n          excluding those notices that do not pertain to any part of\n          the Derivative Works; and\n\n      (d) If the Work includes a \"NOTICE\" text file as part of its\n          distribution, then any Derivative Works that You distribute must\n          include a readable copy of the attribution notices contained\n          within such NOTICE file, excluding those notices that do not\n          pertain to any part of the Derivative Works, in at least one\n          of the following places: within a NOTICE text file distributed\n          as part of the Derivative Works; within the Source form or\n          documentation, if provided along with the Derivative Works; or,\n          within a display generated by the Derivative Works, if and\n          wherever such third-party notices normally appear. The contents\n          of the NOTICE file are for informational purposes only and\n          do not modify the License. You may add Your own attribution\n          notices within Derivative Works that You distribute, alongside\n          or as an addendum to the NOTICE text from the Work, provided\n          that such additional attribution notices cannot be construed\n          as modifying the License.\n\n      You may add Your own copyright statement to Your modifications and\n      may provide additional or different license terms and conditions\n      for use, reproduction, or distribution of Your modifications, or\n      for any such Derivative Works as a whole, provided Your use,\n      reproduction, and distribution of the Work otherwise complies with\n      the conditions stated in this License.\n\n   5. Submission of Contributions. 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