Metadata-Version: 2.1
Name: jina-now
Version: 0.0.27
Summary: Jina NOW - get your neural search case up and running in minutes.
Home-page: https://github.com/jina-ai/now/
Author: Jina AI
Author-email: hello@jina.ai
License: Apache 2.0
Download-URL: https://github.com/jina-ai/now/tags
Project-URL: Documentation, https://docs.jina.ai
Project-URL: Source, https://github.com/jina-ai/now
Project-URL: Tracker, https://github.com/jina-ai/now/issues
Description: <p align="center">
        
        <img src="https://github.com/jina-ai/now/blob/main/docs/_static/logo-light.svg?raw=true" alt="Jina NOW logo: The data structure for unstructured data" width="300px">  
        
        
        <br>
        One command to host them all. Bring your search case into the cloud in minutes. <br>
        Tell us what you think: <a href="https://10sw1tcpld4.typeform.com/to/VTAyYRpR?utm_source=cli">Survey</a>
        </p>
        
        <p align=center>
        <a href="https://pypi.org/project/jina-now/"><img src="https://github.com/jina-ai/jina/blob/master/.github/badges/python-badge.svg?raw=true" alt="Python 3.7 3.8 3.9 3.10" title="Jina NOW supports Python 3.7 and above"></a>
        <a href="https://pypi.org/project/jina-now/"><img src="https://img.shields.io/pypi/v/jina-now?color=%23099cec&amp;label=PyPI&amp;logo=pypi&amp;logoColor=white" alt="PyPI"></a>
        </p>
        
        <!-- start elevator-pitch -->
        
        <p align="center">
        <img src="https://user-images.githubusercontent.com/11627845/164569398-5ef22a41-e2e1-438a-88a5-2ac43ad9426d.gif" alt="Jina NOW logo: The data structure for unstructured data" width="600px">
        
        
        NOW gives the world access to neural image search in just one command execution.
        Main features
        - ⛅ **Cloud**: We take care of the deployment and maintenance
        - 🐥 **Easy**: Minimal effort required to set up your search case
        - 🐎 **Fast**: Set up your search case within minutes
        - 🌈 **Quality**: If you provide labels to your documents, Jina NOW fine-tunes a model for you
        - ✨ **Nocode**: Deployment can be done by non-technical people
        
        
        ### Installation
        
        ```bash
        pip install jina-now
        ```
        
        In case you need sudo for running Docker, install and use jina-now using sudo as well.
        
        #### Mac M1
        
        For the Mac M1 it is generally recommended using a conda environment as outlined in the [Jina documentation](https://docs.jina.ai/get-started/install/troubleshooting/#on-mac-m1).
        In a new conda environment first execute `conda install grpcio tokenizers protobuf`. Then run `pip install jina-now`.
        
        ### Usage
        You can use the following command to start Jina NOW.
        ```bash
        jina now start
        ```
        First, you will get asked what search case you would like to deploy. 
        
        
        ### Quick Start
        ```bash
        jina now start
        ```
        First, you will be prompted to choose an app. As for now, we support images or text searches. But in the future, we will add many more options here.
        
        <img width="613" alt="Screenshot 2022-05-31 at 01 08 25" src="https://user-images.githubusercontent.com/11627845/171066876-b01bb76d-80f0-4f7c-8e5b-f329ef59e147.png">
        
        In the next step, you get asked to select the dataset for your search app. You could either choose one of our existing datasets or select `custom` to index your own data.
        
        <img width="422" alt="question-ds" src="https://user-images.githubusercontent.com/11627845/170263852-46776391-a906-417c-8528-e1fb7058c33a.png">
        
        When choosing `custom`, you can decide in what format you provide your data. The recommended way, is to push a document array described [here](https://docarray.jina.ai/fundamentals/documentarray/serialization/#from-to-cloud).
        Alternatively, you can specify a URL where a document array can be downloaded from.
        Also, it is possible to provide a local folder where the Images are located. In case of text search it would be a local text file.
        
        <img width="724" alt="question-custom" src="https://user-images.githubusercontent.com/11627845/170256031-b868058b-dec6-46aa-b2cf-afac4b33d996.png">
        
        If you chose `docarray.pull`, you will be asked to insert your docarray id. 
        Likewise, if you chose docarray URL, you will be prompted to enter the URL.
        In case you selected local path, `jina-now` will ask you to enter the local path of the data folder as shown bellow.
        
        <img width="506" alt="question-local-path" src="https://user-images.githubusercontent.com/11627845/170256044-67e82e86-6439-4a3e-98f1-dbdf1940de67.png">
        
        The search app can be deployed in different qualities. Have in mind that a better quality leads to a larger ai model being deployed and therefore inference will be a bit slower.
        
        <img width="497" alt="question-quality" src="https://user-images.githubusercontent.com/11627845/170256049-18add461-f666-48f4-9dfe-52be9404a73d.png">
        
        Currently, we provide two deployment options. We recommend using the cloud deployment. This will run your search app on our servers.
        Alternatively, you can select the local deployment option.
        
        <img width="547" alt="question-deployment" src="https://user-images.githubusercontent.com/11627845/170256038-8c44a5b8-985a-4fe7-af5d-16df0244f4bb.png">
        
        In case of local deployment, you will be asked where you want to deploy it. Jina NOW reads your local .kube/config and lists all kubernetes clusters you have access to. 
        If you don't want to use an existing cluster, you can create a new one locally.
        
        <img width="643" alt="question-cluster" src="https://user-images.githubusercontent.com/11627845/170256027-99798fae-3ec4-42dc-8737-843f4a23f941.png">
        
        After the program execution is finished, two links will be shown to you. The first one brings you to a playground where you can run example queries and experiment with the search case.
        The second URL leads you to the swagger UI which is useful for Frontend integration.
        
        <img width="709" alt="Screenshot 2022-05-26 at 16 34 56" src="https://user-images.githubusercontent.com/11627845/170511632-c741a418-1246-4c23-aadd-cfd74d783f6b.png">
        
        Example of the playground.
        
        <img width="350" alt="Screenshot 2022-05-26 at 16 36 49" src="https://user-images.githubusercontent.com/11627845/170511607-3fb810f7-a5aa-47cd-9f70-e6034a96b9fd.png">
        
        Example of the swagger ui.
        
        <img width="350" alt="Screenshot 2022-05-26 at 16 36 06" src="https://user-images.githubusercontent.com/11627845/170511580-230d1e41-5e14-4623-adb6-3d4b2d400dc9.png">
        
        
          
        ### Use CLI Parameters
        Instead of answering the questions manually, you can also provide command-line arguments when starting Jina NOW like shown here.
        ```bash
        jina now start --quality medium --data /local/img/folder
        ```
          
        ### Use API
        You can now send requests to the API using the jina client. This case shows a local deployment.
        ```bash
        from jina import Client    
        client = Client(
                host='localhost',
                port=31080,
        ) 
        response = client.search(
                Document(text=search_text), # or in case you send an image: Document(url=image_path),
                parameters={"limit": 9, "filter": {}},
        )
        ```
          
        ### Cleanup
        ```bash
        jina now stop
        ```
        
        ### Requirements
        - `Linux` or `Mac`
        - `Python 3.7`, `3.8`, `3.9` or `3.10`
        #### Local execution
        - `Docker` installation
        - 10 GB assigned to docker
        - User must be permitted to run docker containers
        
        
        ## Supported apps (more will be added)
        
        - [x] Text to Image search 📝 ▶ 🏞 
        - [x] Image to Text search 🏞 ▶ 📝 
        - [x] Image to Image search 🏞 ▶ 🏞
        - [x] Text to Text search 📝 ▶ 📝
        - [x] Music to Music search 🥁 ▶ 🥁 
        - [x] Text to Video search 📝 ▶ 🎥 (only gif at the moment)
        - [ ] Text to 3D Mesh search 📝 ▶ 🧊
        - [ ] ...
        
        [![IMAGE ALT TEXT HERE](https://user-images.githubusercontent.com/11627845/164571632-0e6a6c39-0137-413b-8287-21fc34785665.png)](https://www.youtube.com/watch?v=fdIaLP0ctpo)
        </p>
        <br>
          
        ## Examples
        
        <details><summary>👕 Fashion</summary>
        <img width="400" alt="image" src="https://user-images.githubusercontent.com/11627845/157079335-8f36fc73-d826-4c0a-b1f3-ed5d650a1af1.png">
        </details>
        
        <details><summary>☢️ Chest X-Ray</summary>
        <img src="https://user-images.githubusercontent.com/11627845/157067695-59851a77-5c43-4f68-80c4-403fec850776.png" width="400">
        </details>
          
        <details><summary>💰 NFT - bored apes</summary>
        <img src="https://user-images.githubusercontent.com/11627845/157019002-573cc101-e23b-4020-825c-f37ec66c6ccf.jpeg" width="400">
        </details>
          
        <details><summary>🖼 Art</summary>
        <img width="400" alt="image" src="https://user-images.githubusercontent.com/11627845/157074453-721c0f2d-3f7d-4839-b6ff-bbccbdba2e5f.png">
        </details>
          
        <details><summary>🚗 Cars</summary>
        <img width="400" alt="image" src="https://user-images.githubusercontent.com/11627845/157081047-792df6bd-544d-420c-b180-df824c802e73.png">
        </details>
          
        <details><summary>🏞 Street view</summary>
        <img width="400" alt="image" src="https://user-images.githubusercontent.com/11627845/157087532-46ae36a2-c97f-45d7-9c3e-c624dcf6dc46.png">
        </details>
        
        <details><summary>🦆 Birds</summary>
        <img width="400" alt="image" src="https://user-images.githubusercontent.com/11627845/157069954-615a5cb6-dda0-4a2f-9442-ea807ad4a8d5.png">
        </details>
        
        
        ### Now use your custom data :)
        <!-- end elevator-pitch -->
        
Keywords: jina neural-search neural-network deep-learning now private data democratization
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Environment :: Console
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Description-Content-Type: text/markdown
Provides-Extra: test
