2022-04-26T21:38:43,893 Created temporary directory: /tmp/pip-ephem-wheel-cache-ywb2q3_z 2022-04-26T21:38:43,900 Created temporary directory: /tmp/pip-req-tracker-u4sd56kh 2022-04-26T21:38:43,900 Initialized build tracking at /tmp/pip-req-tracker-u4sd56kh 2022-04-26T21:38:43,901 Created build tracker: /tmp/pip-req-tracker-u4sd56kh 2022-04-26T21:38:43,901 Entered build tracker: /tmp/pip-req-tracker-u4sd56kh 2022-04-26T21:38:43,903 Created temporary directory: /tmp/pip-wheel-j3i6lblr 2022-04-26T21:38:43,963 Looking in indexes: https://pypi.org/simple, https://www.piwheels.org/simple 2022-04-26T21:38:43,966 2 location(s) to search for versions of gradio: 2022-04-26T21:38:43,966 * https://pypi.org/simple/gradio/ 2022-04-26T21:38:43,966 * https://www.piwheels.org/simple/gradio/ 2022-04-26T21:38:43,967 Fetching project page and analyzing links: https://pypi.org/simple/gradio/ 2022-04-26T21:38:43,969 Getting page https://pypi.org/simple/gradio/ 2022-04-26T21:38:43,973 Found index url 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https://www.piwheels.org/simple/gradio/gradio-2.9.4-py3-none-any.whl#sha256=1624d4970001d2daebebd0c9b601e3809498c6cad64e9a6a116c5971e122a37a (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,853 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-2.9.3-py3-none-any.whl#sha256=4d1ea221b2c91ee98c8447fae9d8aa5374f73afb35f8426b066394415000b014 (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,854 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-2.9.2-py3-none-any.whl#sha256=c048025761fa94fc83db71726bb8de1339ba05e4080b4de340d10c3fe27a85ef (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,855 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-2.9.1-py3-none-any.whl#sha256=f2411ebd1487e3c279c49b7191558cfdf502534a83aafe059d7566a3ef116845 (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,856 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-2.9.0-py3-none-any.whl#sha256=c840d44d712c9d89597ac77b46cd3dd93ac5c3821b862ca1f91628257a210ef6 (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,856 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-2.9.0b8-py3-none-any.whl#sha256=bc7d87725d38e73738f59224fb478a20592e2bb8ab9fd2c691b0602e5d86ae18 (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,857 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-2.9.0b7-py3-none-any.whl#sha256=a2c743f83ec3a0f3482d4541df095925806fc9b9870861c0e8177cbad1fe06f5 (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,858 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-2.9.0b6-py3-none-any.whl#sha256=da2b5b41964a4c0ee6d135c64a5f94c060b0143496d57fbf95204724672a1991 (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,858 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-2.9.0b5-py3-none-any.whl#sha256=9fa8fd2534558cd2132b80124a7ef009339ae4d79ad6248dc76bb9b6338a631a (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,859 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-2.9.0b3-py3-none-any.whl#sha256=a3bb4657afec508ff9c1f2ef494a1b0c046425d770aeb8f484a6c67fd47dbfdf (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,860 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-2.9.0b2-py3-none-any.whl#sha256=2f7ecdae18ffd1db161bbd44b9aee8327967fda64cb850bc17daa2decc3f5fac (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,860 Skipping link: No binaries permitted for gradio: 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Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-2.8.12-py3-none-any.whl#sha256=f40a1003d1ab5f8efec85df0aa59ec677d9d113bf2596c058f099af720f52e67 (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,863 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-2.8.11-py3-none-any.whl#sha256=d5219018992fe3a04cf21835a0d3dd477cff5023c07335caac5537842f3708b7 (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,864 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-2.8.10-py3-none-any.whl#sha256=58de00eee1ff76b070b93e66feb21442c1fb7c669594979c2588fa073fcb2fce (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,865 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-2.8.9-py3-none-any.whl#sha256=239d0362c8e9a9d99cf849616c4af86196ac63e8955d932fb165804274e947de (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,865 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-2.8.8-py3-none-any.whl#sha256=f7ba2c257ddcb342b6f15b279ed9355e01a8d0b784fc15b9a67ad3f9be828b9b (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,866 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-2.8.7-py3-none-any.whl#sha256=bdf3955dfd0c5df1765e9ec4953f98922c1d785f39046182820c53b3f0d27df9 (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,867 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-2.8.6-py3-none-any.whl#sha256=09a06a0d72e3270434e44997365041e51bcfd8bda790d6b9e0861c2efa18191f (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,867 Skipping link: No binaries permitted for gradio: 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Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-0.1.6-py3-none-any.whl#sha256=7745f52712bbc2ac081a1b48564079fa87ac9decc2cf2e97c0ee33a6be783ff2 (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,997 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-0.1.5-py3-none-any.whl#sha256=5a44bee2fafd7f5f3561313588192bcb807e2fb72a95958d737084ed40dd307f (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,998 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-0.1.4-py3-none-any.whl#sha256=0024c140c0e9bf5260595aa592bcc95386d320f785f88b1a9edd8854092367d7 (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,998 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-0.1.3-py3-none-any.whl#sha256=66e45a0b3b52da07388200881141c1ebef6eda1d46a4c8e31cfd97a6db7a7787 (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,999 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-0.1.2-py3-none-any.whl#sha256=519b1ebc472eda5365cc74b21effb4f95aa07d0d7457ad059e8ebe5073ad1371 (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:45,1000 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-0.1.1-py3-none-any.whl#sha256=ba37ee7576f5110f5c42640932feb6738846eeb02eb143a67385dd151469bda5 (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:46,000 Skipping link: No binaries permitted for gradio: https://www.piwheels.org/simple/gradio/gradio-0.1.0-py3-none-any.whl#sha256=cf7e28b9f9c51bf31363f38a6f58046dcd4e1ab5c3426b262164fd8fa919bf25 (from https://www.piwheels.org/simple/gradio/) 2022-04-26T21:38:46,138 Given no hashes to check 1 links for project 'gradio': discarding no candidates 2022-04-26T21:38:46,181 Collecting gradio==2.9.0b9 2022-04-26T21:38:46,184 Created temporary directory: /tmp/pip-unpack-_oo0cbv2 2022-04-26T21:38:47,111 Downloading gradio-2.9.0b9.tar.gz (3.0 MB) 2022-04-26T21:38:50,083 Added gradio==2.9.0b9 from https://files.pythonhosted.org/packages/6c/6d/6d27f2737e1873b6e4eb0469f9618ab04e5689af89fb3f91a90bfa05c1fc/gradio-2.9.0b9.tar.gz#sha256=d7095c8b9f31cd63be8ff64cfb629d60fe17e5706aef0919420624a8ffb4a69e to build tracker '/tmp/pip-req-tracker-u4sd56kh' 2022-04-26T21:38:50,085 Running setup.py (path:/tmp/pip-wheel-j3i6lblr/gradio_7cb2db11246741818da3aa2beedbe62d/setup.py) egg_info for package gradio 2022-04-26T21:38:50,087 Created temporary directory: /tmp/pip-pip-egg-info-m4jcrqcc 2022-04-26T21:38:50,088 Running command python setup.py egg_info 2022-04-26T21:38:51,924 [](https://circleci.com/gh/gradio-app/gradio) [](https://badge.fury.io/py/gradio) [](https://codecov.io/gh/gradio-app/gradio) [](https://pypi.org/project/gradio/) [](https://twitter.com/gradio) 2022-04-26T21:38:51,926 # Welcome to Gradio 2022-04-26T21:38:51,927 Quickly create beautiful user interfaces around your machine learning models. Gradio (pronounced GRAY-dee-oh) makes it easy for you to demo your model in your browser or let people "try it out" by dragging-and-dropping in their own images, pasting text, recording their own voice, etc. and seeing what the model outputs. 2022-04-26T21:38:51,928  2022-04-26T21:38:51,929 Gradio is useful for: 2022-04-26T21:38:51,930 * **Demoing** your machine learning models for clients / collaborators / users / students 2022-04-26T21:38:51,931 * **Deploying** your models quickly with automatic shareable links and getting feedback on model performance 2022-04-26T21:38:51,933 * **Debugging** your model interactively during development using built-in manipulation and interpretation tools 2022-04-26T21:38:51,934 **You can find an interactive version of the following Getting Started at [https://gradio.app/getting_started](https://gradio.app/getting_started).** 2022-04-26T21:38:51,936 ## Getting Started 2022-04-26T21:38:51,937 **Prerequisite**: Python 3.7+ and that's it! 2022-04-26T21:38:51,938 ### Quick Start 2022-04-26T21:38:51,939 To get Gradio running with a simple "Hello, World" example, follow these three steps: 2022-04-26T21:38:51,940 1. Install Gradio from pip. 2022-04-26T21:38:51,942 ```bash 2022-04-26T21:38:51,942 pip install gradio 2022-04-26T21:38:51,943 ``` 2022-04-26T21:38:51,944 2. Run the code below as a Python script or in a Python notebook (or in a [colab notebook](https://colab.research.google.com/drive/18ODkJvyxHutTN0P5APWyGFO_xwNcgHDZ?usp=sharing)). 2022-04-26T21:38:51,945 ```python 2022-04-26T21:38:51,946 import gradio as gr 2022-04-26T21:38:51,948 def greet(name): 2022-04-26T21:38:51,948 return "Hello " + name + "!!" 2022-04-26T21:38:51,950 iface = gr.Interface(fn=greet, inputs="text", outputs="text") 2022-04-26T21:38:51,951 iface.launch() 2022-04-26T21:38:51,952 ``` 2022-04-26T21:38:51,953 3. The interface below will appear automatically within the Python notebook, or pop in a browser on [http://localhost:7860](http://localhost:7860/) if running from a script. 2022-04-26T21:38:51,954  2022-04-26T21:38:51,955 ### Understanding the `Interface` class 2022-04-26T21:38:51,957 Gradio can wrap almost any Python function with an easy-to-use user interface. In the example above, we saw a simple text-based function. But the function could be anything from image enhancer to a tax calculator to (most commonly) the prediction function of a pretrained machine learning model. 2022-04-26T21:38:51,958 The core `Interface` class is initialized with three parameters: 2022-04-26T21:38:51,959 - `fn`: the function to wrap 2022-04-26T21:38:51,960 - `inputs`: the input component type(s), e.g. `"image"` or `"audio"` ([see docs for complete list](/docs)) 2022-04-26T21:38:51,960 - `outputs`: the output component type(s) e.g. `"image"` or `"label"` ([see docs for complete list](/docs)) 2022-04-26T21:38:51,962 With these three arguments, we can quickly create interfaces and `launch()` them. But what if you want to change how the UI components look or behave? 2022-04-26T21:38:51,963 ### Customizable Components 2022-04-26T21:38:51,964 Let's say we want to customize the input text field - for example, we wanted it to be larger and have a text hint. If we use the actual input class for `Textbox` instead of using the string shortcut, we have access to much more customizability. To see a list of all the components we support and how you can customize them, check out the [Docs](https://gradio.app/docs). 2022-04-26T21:38:51,965 ```python 2022-04-26T21:38:51,966 import gradio as gr 2022-04-26T21:38:51,968 def greet(name): 2022-04-26T21:38:51,968 return "Hello " + name + "!" 2022-04-26T21:38:51,970 iface = gr.Interface( 2022-04-26T21:38:51,971 fn=greet, 2022-04-26T21:38:51,971 inputs=gr.inputs.Textbox(lines=2, placeholder="Name Here..."), 2022-04-26T21:38:51,972 outputs="text", 2022-04-26T21:38:51,972 ) 2022-04-26T21:38:51,973 iface.launch() 2022-04-26T21:38:51,974 ``` 2022-04-26T21:38:51,975  2022-04-26T21:38:51,976 ### Multiple Inputs and Outputs 2022-04-26T21:38:51,977 Let's say we had a much more complex function, with multiple inputs and outputs. In the example below, we have a function that takes a string, boolean, and number, and returns a string and number. Take a look how we pass a list of input and output components. 2022-04-26T21:38:51,978 ```python 2022-04-26T21:38:51,978 import gradio as gr 2022-04-26T21:38:51,980 def greet(name, is_morning, temperature): 2022-04-26T21:38:51,980 salutation = "Good morning" if is_morning else "Good evening" 2022-04-26T21:38:51,981 greeting = "%s %s. It is %s degrees today" % (salutation, name, temperature) 2022-04-26T21:38:51,982 celsius = (temperature - 32) * 5 / 9 2022-04-26T21:38:51,982 return greeting, round(celsius, 2) 2022-04-26T21:38:51,984 iface = gr.Interface( 2022-04-26T21:38:51,984 fn=greet, 2022-04-26T21:38:51,985 inputs=["text", "checkbox", gr.inputs.Slider(0, 100)], 2022-04-26T21:38:51,985 outputs=["text", "number"], 2022-04-26T21:38:51,986 ) 2022-04-26T21:38:51,987 iface.launch() 2022-04-26T21:38:51,988 ``` 2022-04-26T21:38:51,988  2022-04-26T21:38:51,990 We simply wrap the components in a list. Each component in the `inputs` list corresponds to one of the parameters of the function, in order. Each component in the `outputs` list corresponds to one of the values returned by the function, again in order. 2022-04-26T21:38:51,991 ### Working with Images 2022-04-26T21:38:51,992 Let's try an image-to-image function. When using the `Image` component, your function will receive a numpy array of your specified size, with the shape `(width, height, 3)`, where the last dimension represents the RGB values. We'll return an image as well in the form of a numpy array. 2022-04-26T21:38:51,993 ```python 2022-04-26T21:38:51,994 import numpy as np 2022-04-26T21:38:51,995 import gradio as gr 2022-04-26T21:38:51,996 def sepia(input_img): 2022-04-26T21:38:51,997 sepia_filter = np.array( 2022-04-26T21:38:51,998 [[0.393, 0.769, 0.189], [0.349, 0.686, 0.168], [0.272, 0.534, 0.131]] 2022-04-26T21:38:51,998 ) 2022-04-26T21:38:51,999 sepia_img = input_img.dot(sepia_filter.T) 2022-04-26T21:38:51,1000 sepia_img /= sepia_img.max() 2022-04-26T21:38:52,000 return sepia_img 2022-04-26T21:38:52,002 iface = gr.Interface(sepia, gr.inputs.Image(shape=(200, 200)), "image") 2022-04-26T21:38:52,003 iface.launch() 2022-04-26T21:38:52,004 ``` 2022-04-26T21:38:52,005  2022-04-26T21:38:52,006 Additionally, our `Image` input interface comes with an 'edit' button which opens tools for cropping, flipping, rotating, drawing over, and applying filters to images. We've found that manipulating images in this way will often reveal hidden flaws in a model. 2022-04-26T21:38:52,007 In addition to images, Gradio supports other media input types, such as audio or video uploads, as well as many output components. Read about these in the [Docs](https://gradio.app/docs). 2022-04-26T21:38:52,008 ### Working with DataFrames and Graphs 2022-04-26T21:38:52,010 You can use Gradio to support inputs and outputs from your typical data libraries, such as numpy arrays, pandas dataframes, and plotly graphs. Take a look at the demo below (ignore the complicated data manipulation in the function!) 2022-04-26T21:38:52,011 ```python 2022-04-26T21:38:52,011 import matplotlib.pyplot as plt 2022-04-26T21:38:52,012 import numpy as np 2022-04-26T21:38:52,013 import pandas as pd 2022-04-26T21:38:52,014 import gradio as gr 2022-04-26T21:38:52,016 def sales_projections(employee_data): 2022-04-26T21:38:52,016 sales_data = employee_data.iloc[:, 1:4].astype("int").to_numpy() 2022-04-26T21:38:52,017 regression_values = np.apply_along_axis( 2022-04-26T21:38:52,017 lambda row: np.array(np.poly1d(np.polyfit([0, 1, 2], row, 2))), 0, sales_data 2022-04-26T21:38:52,018 ) 2022-04-26T21:38:52,019 projected_months = np.repeat( 2022-04-26T21:38:52,019 np.expand_dims(np.arange(3, 12), 0), len(sales_data), axis=0 2022-04-26T21:38:52,020 ) 2022-04-26T21:38:52,020 projected_values = np.array( 2022-04-26T21:38:52,021 [ 2022-04-26T21:38:52,022 month * month * regression[0] + month * regression[1] + regression[2] 2022-04-26T21:38:52,022 for month, regression in zip(projected_months, regression_values) 2022-04-26T21:38:52,023 ] 2022-04-26T21:38:52,023 ) 2022-04-26T21:38:52,024 plt.plot(projected_values.T) 2022-04-26T21:38:52,024 plt.legend(employee_data["Name"]) 2022-04-26T21:38:52,025 return employee_data, plt.gcf(), regression_values 2022-04-26T21:38:52,027 iface = gr.Interface( 2022-04-26T21:38:52,027 sales_projections, 2022-04-26T21:38:52,028 gr.inputs.Dataframe( 2022-04-26T21:38:52,028 headers=["Name", "Jan Sales", "Feb Sales", "Mar Sales"], 2022-04-26T21:38:52,029 default=[["Jon", 12, 14, 18], ["Alice", 14, 17, 2], ["Sana", 8, 9.5, 12]], 2022-04-26T21:38:52,030 ), 2022-04-26T21:38:52,030 ["dataframe", "plot", "numpy"], 2022-04-26T21:38:52,031 description="Enter sales figures for employees to predict sales trajectory over year.", 2022-04-26T21:38:52,031 ) 2022-04-26T21:38:52,032 iface.launch() 2022-04-26T21:38:52,033 ``` 2022-04-26T21:38:52,034  2022-04-26T21:38:52,035 ### Example Inputs 2022-04-26T21:38:52,036 You can provide example data that a user can easily load into the model. This can be helpful to demonstrate the types of inputs the model expects, as well as to provide a way to explore your dataset in conjunction with your model. To load example data, you provide a **nested list** to the `examples=` keyword argument of the Interface constructor. Each sublist within the outer list represents a data sample, and each element within the sublist represents an input for each input component. The format of example data for each component is specified in the [Docs](https://gradio.app/docs). 2022-04-26T21:38:52,037 ```python 2022-04-26T21:38:52,038 import gradio as gr 2022-04-26T21:38:52,039 def calculator(num1, operation, num2): 2022-04-26T21:38:52,040 if operation == "add": 2022-04-26T21:38:52,040 return num1 + num2 2022-04-26T21:38:52,041 elif operation == "subtract": 2022-04-26T21:38:52,041 return num1 - num2 2022-04-26T21:38:52,042 elif operation == "multiply": 2022-04-26T21:38:52,043 return num1 * num2 2022-04-26T21:38:52,043 elif operation == "divide": 2022-04-26T21:38:52,044 return num1 / num2 2022-04-26T21:38:52,045 iface = gr.Interface( 2022-04-26T21:38:52,045 calculator, 2022-04-26T21:38:52,046 ["number", gr.inputs.Radio(["add", "subtract", "multiply", "divide"]), "number"], 2022-04-26T21:38:52,046 "number", 2022-04-26T21:38:52,047 examples=[ 2022-04-26T21:38:52,047 [5, "add", 3], 2022-04-26T21:38:52,048 [4, "divide", 2], 2022-04-26T21:38:52,048 [-4, "multiply", 2.5], 2022-04-26T21:38:52,049 [0, "subtract", 1.2], 2022-04-26T21:38:52,049 ], 2022-04-26T21:38:52,049 title="test calculator", 2022-04-26T21:38:52,050 description="heres a sample toy calculator. enjoy!", 2022-04-26T21:38:52,051 flagging_options=["this", "or", "that"], 2022-04-26T21:38:52,051 ) 2022-04-26T21:38:52,052 iface.launch() 2022-04-26T21:38:52,053 ``` 2022-04-26T21:38:52,054  2022-04-26T21:38:52,055 You can load a large dataset into the examples to browse and interact with the dataset through Gradio. The examples will be automatically paginated (you can configure this through the `examples_per_page` argument of Interface) and you can use CTRL + arrow keys to navigate through the examples quickly. 2022-04-26T21:38:52,056 ### Live Interfaces 2022-04-26T21:38:52,057 You can make interfaces automatically refresh by setting `live=True` in the interface. Now the interface will recalculate as soon as the user input changes. 2022-04-26T21:38:52,058 ```python 2022-04-26T21:38:52,058 import gradio as gr 2022-04-26T21:38:52,060 def calculator(num1, operation, num2): 2022-04-26T21:38:52,061 if operation == "add": 2022-04-26T21:38:52,061 return num1 + num2 2022-04-26T21:38:52,062 elif operation == "subtract": 2022-04-26T21:38:52,062 return num1 - num2 2022-04-26T21:38:52,063 elif operation == "multiply": 2022-04-26T21:38:52,063 return num1 * num2 2022-04-26T21:38:52,064 elif operation == "divide": 2022-04-26T21:38:52,064 return num1 / num2 2022-04-26T21:38:52,066 iface = gr.Interface( 2022-04-26T21:38:52,066 calculator, 2022-04-26T21:38:52,067 ["number", gr.inputs.Radio(["add", "subtract", "multiply", "divide"]), "number"], 2022-04-26T21:38:52,068 "number", 2022-04-26T21:38:52,068 live=True, 2022-04-26T21:38:52,069 ) 2022-04-26T21:38:52,070 iface.launch() 2022-04-26T21:38:52,071 ``` 2022-04-26T21:38:52,072  2022-04-26T21:38:52,073 Note there is no submit button, because the interface resubmits automatically on change. 2022-04-26T21:38:52,074 ### Using State 2022-04-26T21:38:52,075 Your function may use data that persists beyond a single function call. If the data is something accessible to all function calls and all users, you can create a global variable outside the function call and access it inside the function. For example, you may load a large model outside the function and use it inside the function so that every function call does not need to reload the model. 2022-04-26T21:38:52,076 Another type of data persistence Gradio supports is session **state**, where data persists across multiple submits within a page load. However, data is *not* shared between different users of your model. To store data in a session state, you need to do three things: (1) Pass in an extra parameter into your function, which represents the state of the interface. (2) At the end of the function, return the updated value of the state as an extra return value (3) Add the `'state'` input and `'state'` output components when creating your `Interface`. See the chatbot example below: 2022-04-26T21:38:52,077 ```python 2022-04-26T21:38:52,078 import random 2022-04-26T21:38:52,079 import gradio as gr 2022-04-26T21:38:52,080 def chat(message, history): 2022-04-26T21:38:52,081 history = history or [] 2022-04-26T21:38:52,081 if message.startswith("How many"): 2022-04-26T21:38:52,082 response = random.randint(1, 10) 2022-04-26T21:38:52,082 elif message.startswith("How"): 2022-04-26T21:38:52,083 response = random.choice(["Great", "Good", "Okay", "Bad"]) 2022-04-26T21:38:52,083 elif message.startswith("Where"): 2022-04-26T21:38:52,084 response = random.choice(["Here", "There", "Somewhere"]) 2022-04-26T21:38:52,084 else: 2022-04-26T21:38:52,085 response = "I don't know" 2022-04-26T21:38:52,085 history.append((message, response)) 2022-04-26T21:38:52,086 html = "