From c9c72ecf0acf68ff940203a399a5d677c6ff026a Mon Sep 17 00:00:00 2001 From: Chiara Pullem Date: Fri, 10 Nov 2023 14:58:53 +0100 Subject: [PATCH 1/8] update starting page --- vizro-ai/docs/index.md | 14 +++++++++++++- 1 file changed, 13 insertions(+), 1 deletion(-) diff --git a/vizro-ai/docs/index.md b/vizro-ai/docs/index.md index db302cbd1..10deabd6a 100644 --- a/vizro-ai/docs/index.md +++ b/vizro-ai/docs/index.md @@ -1,6 +1,18 @@ # Vizro-AI -Vizro-AI is a tool for generating data visualizations. +Vizro-AI is a tool designed for generating data visualizations. It serves as an extension to Vizro, leveraging natural language capabilities to empower users in creating charts effortlessly. + +## Why Vizro-AI? + +### Easy-to-use +One of the key strengths of Vizro-AI lies in its natural language capabilities, making it accessible to coding novices. Vizro-AI provides a user-friendly interface that allows to create interactive charts while offering detailed explanations about the data and the generated code. + +### Visually-optimized +Vizro-AI also caters data scientist who often spend more time on formatting than creating a visualization. Vizro-AI enables the user to speed up the formatting process and create a visually appealing chart, also leveraging the design library of Vizro. + +### Dashboard-ready +Vizro-AI focuses currently on plotly and is used to create interactive chart. Thus, it is primarily aimed at dashboards, ensuring that the generated charts are well-suited for dashboard applications. + !!! notice "Notice" Please review this [disclaimer](pages/explanation/disclaimer.md) before using the `vizro-ai` package. From ca97832509c5fcdb76fb4a107bfaa558476b9fad Mon Sep 17 00:00:00 2001 From: Chiara Pullem Date: Fri, 10 Nov 2023 14:59:46 +0100 Subject: [PATCH 2/8] update installation guide --- vizro-ai/docs/pages/user_guides/install.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/vizro-ai/docs/pages/user_guides/install.md b/vizro-ai/docs/pages/user_guides/install.md index a2bd7aec3..5eb8a24c3 100644 --- a/vizro-ai/docs/pages/user_guides/install.md +++ b/vizro-ai/docs/pages/user_guides/install.md @@ -28,7 +28,7 @@ More details can be found in the [environment setup guide](../user_guides/api_se To install Vizro-AI from the Python Package Index (PyPI), utilize [`pip`](https://pip.pypa.io/en/stable/) in your terminal with the following command: ```bash -pip install vizro-ai +pip install vizro_ai ``` While you can execute code from the tutorials and user guides using a Python script, using a Jupyter notebook is often considered more convenient. You can install `jupyter` with the following command: @@ -50,9 +50,9 @@ pip install jupyter After successfully installing Vizro-AI, to verify the version or confirm the installation, you can run the following code from a Python script or a Jupyter notebook cell: ```py -import vizro-ai +import vizro_ai -print(vizro-ai.__version__) +print(vizro_ai.__version__) ``` You should see a return output of the current version. @@ -61,7 +61,7 @@ You should see a return output of the current version. If you want to upgrade Vizro-AI to a different version later on, you can do so by running the following command: ``` -pip install vizro-ai -U +pip install vizro_ai -U ``` The best way to safely upgrade is to check the [release notes]() for any notable breaking changes before migrating an From 84f4955f0c99e48f1e62b5ae4b2a473dd7e956e1 Mon Sep 17 00:00:00 2001 From: Chiara Pullem Date: Fri, 10 Nov 2023 15:09:35 +0100 Subject: [PATCH 3/8] update examples and quickstart --- .../tutorials/chart/GDP_Composition_Bar.png | Bin 125286 -> 161196 bytes .../bar_chart_gdp_per_continent.png | Bin 54630 -> 94501 bytes vizro-ai/docs/pages/tutorials/quickstart.md | 17 +++++++++++------ .../docs/pages/user_guides/run_vizro_ai.md | 8 ++++---- 4 files changed, 15 insertions(+), 10 deletions(-) diff --git a/vizro-ai/docs/assets/tutorials/chart/GDP_Composition_Bar.png b/vizro-ai/docs/assets/tutorials/chart/GDP_Composition_Bar.png index 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.../docs/pages/tutorials/explore_vizro_ai.md | 99 +++++++++++++++++++ 2 files changed, 147 insertions(+) create mode 100644 vizro-ai/changelog.d/20231110_151408_chiara_pullem_update.md create mode 100644 vizro-ai/docs/pages/tutorials/explore_vizro_ai.md diff --git a/vizro-ai/changelog.d/20231110_151408_chiara_pullem_update.md b/vizro-ai/changelog.d/20231110_151408_chiara_pullem_update.md new file mode 100644 index 000000000..f1f65e73c --- /dev/null +++ b/vizro-ai/changelog.d/20231110_151408_chiara_pullem_update.md @@ -0,0 +1,48 @@ + + + + + + + + + diff --git a/vizro-ai/docs/pages/tutorials/explore_vizro_ai.md b/vizro-ai/docs/pages/tutorials/explore_vizro_ai.md new file mode 100644 index 000000000..ba5a43bbe --- /dev/null +++ b/vizro-ai/docs/pages/tutorials/explore_vizro_ai.md @@ -0,0 +1,99 @@ +# Get started with Vizro-AI +This tutorial serves as an introduction to Vizro-AI. +It is a step-by-step guide to help you experiment and create your initial Vizro chart using Vizro-AI, our English-to-visualization package. The goal is to provide you with the necessary knowledge to explore further into our documentation. + +## Let's get started! +### 1. Install vizro-ai and its dependencies +If you haven't already installed `vizro_ai` package, follow the [installation guide](../user_guides/install.md) +to do so inside a virtual environment. + +??? tip "Beginners/Code novices" + If you consider yourself a beginner to python and/or virtual environments, there is also a section in the [installation guide](../user_guides/install.md) that avoids any use of terminals and relies only upon a graphical user interface. + +### 2. Set up jupyter notebook +A good way to initially explore Vizro-AI is from a Jupyter notebook. +Activate your previously created virtual environment and install Jupyter using the following command: + +```console +pip install jupyter +``` + +Next, you can start your jupyter notebook in your activated environment by: + +```console +jupyter notebook +``` +This opens a browser tab, and you can navigate to your preferred folder for this new project. Create a new notebook Python 3 (ipykernel) notebook from the "New" dropdown. Make sure that you select your environment as kernel. + +??? tip "Beginners/Code novices" + If you followed the beginners steps in the [installation guide](../user_guides/install.md), you should already be set, and you can continue below. + +Confirm that vizro-ai is installed by typing the following into a jupyter cell in your notebook and running it. + +```py +import vizro_ai +print(vizro_ai.__version__) +``` + +You should see a return output of the version. + +### 3. Large Language Model (LLM) API KEY + +A prerequisite to use Vizro-AI is access to one of the supported LLMs. Refer to the [user guide](../user_guides/api_setup.md) on how to set up the API. + +After successful setup, your API key is loaded in Jupyter with the following two lines: + +```py +from dotenv import load_dotenv +load_dotenv() +``` + +### 4. Ask your first question using vizro-ai + +For your first visualization, we will create a chart illustrating the GDP of various continents while including a reference line for the average. + +Let's go through the code step-by-step to understand how to use Vizro-AI. First, we create `pandas` DataFrame using the gapminder data from `plotly express`. Next, we instantiate `VizroAI` to call the `plot()` method to generate your visualization. + +By passing your prepared data and your written visualization request to this method, Vizro-AI takes care of the processing. It generates the necessary code for data manipulation and chart creation, and then it proceeds to render the chart by executing the generated code. + +!!! example "Vizro AI Syntax" + === "Code for the cell" + ```py + from vizro_ai import VizroAI + import vizro.plotly.express as px + + from dotenv import load_dotenv + load_dotenv() + + df = px.data.gapminder() + vizro_ai = VizroAI() + vizro_ai.plot(df, "describe the composition of gdp in continent and color by continent, and add a horizontal line for avg gdp") + ``` + === "Result" + [![BarChart]][BarChart] + + [BarChart]: ../../assets/tutorials/chart/GDP_Composition_Bar.png + +The created chart is interactive, and you can hover over the data for additional information. + +### 5. Get an explanation with your chart + +By passing `explain=True` to the `plot()` method will provide additional insights in addition to the rendered chart. + +Let's create another example and read through the additional information. + +!!! example "Specify `explain=True`" + === "Code for the cell" + ```py + vizro_ai.plot(df, "show me the geo distribution of life expectancy", explain=True) + ``` + === "Result" + [![GeoDistribution]][GeoDistribution] + + [GeoDistribution]: ../../assets/tutorials/chart/GeoDistribution.png + +### 6. Explore further + +Now, you have created your first charts with Vizro-AI and are ready to explore the documentation further. + +A good place to start would be to go through the [model configuration](../user_guides/model_config.md) or different [run options](../user_guides/run_vizro_ai.md) including application integration. 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z+P@d9{k5t5{=V7YLSA#day@Zx@9&&`E_2-jEYlhK^tkrBZTZfb8<2bUR;l2##km4^ zCn`3-UG@9ROJhO3!!8^5Ry=s|f8vAJ6<_LkIhEP>e$Y;nI(f}ubG5%HXYzaI?bG+k zY@Iu|T~13IxHfmv+uP+Vc}E?mP1bkk6|hNUTFK5QGX*%vReZ+n)6eY1xB6!+e_H={ ztIeTxk83U6C*?NH?nzFtD=NM6VC7}zIqB>6J*(E6KOuhluK#wse*-7!N`;*l$Z{UI z<8p=t%LwWQCdJ0HeRnX&G8tKHKx^Q-K42ctEWoh=I4sG~JPGqK8ifa-`KI8O>sW?( z8-V7qNKAQy#V&u~2VE@6oPjr2R7gslul^4tgDy6wlB zhqAGR`T@{DIFDBuW+*i*2af+^EIR!)FsvLyW_phGrXT2D<{9 literal 0 HcmV?d00001 diff --git a/vizro-ai/docs/pages/tutorials/explore_vizro_ai.md b/vizro-ai/docs/pages/tutorials/explore_vizro_ai.md index ba5a43bbe..18c9db503 100644 --- a/vizro-ai/docs/pages/tutorials/explore_vizro_ai.md +++ b/vizro-ai/docs/pages/tutorials/explore_vizro_ai.md @@ -1,62 +1,73 @@ -# Get started with Vizro-AI -This tutorial serves as an introduction to Vizro-AI. -It is a step-by-step guide to help you experiment and create your initial Vizro chart using Vizro-AI, our English-to-visualization package. The goal is to provide you with the necessary knowledge to explore further into our documentation. +# Explore Vizro-AI +This tutorial serves as an exploration of the extended applications offered by Vizro-AI beyond the initial [quickstart guide](../tutorials/quickstart.md). + +By the end of this tutorial, you will have gained an understanding of different language options and leveraging Vizro-AI to enhance the formatting your visualizations. ## Let's get started! -### 1. Install vizro-ai and its dependencies -If you haven't already installed `vizro_ai` package, follow the [installation guide](../user_guides/install.md) -to do so inside a virtual environment. +### 1. Install vizro-ai and get ready to run your code +Before proceeding, ensure the installation of the `vizro_ai` package by following the steps outlined in the [installation guide](../user_guides/install.md). Once installed, you can execute your code either by pasting it into a Jupyter notebook cell or running it from a Python script. -??? tip "Beginners/Code novices" - If you consider yourself a beginner to python and/or virtual environments, there is also a section in the [installation guide](../user_guides/install.md) that avoids any use of terminals and relies only upon a graphical user interface. -### 2. Set up jupyter notebook -A good way to initially explore Vizro-AI is from a Jupyter notebook. -Activate your previously created virtual environment and install Jupyter using the following command: +??? tip "Beginners/Code novices" + For those new to Python or virtual environments, a user-friendly alternative is available in the [installation guide](../user_guides/install.md), offering a graphical user interface without the need for terminal commands. -```console -pip install jupyter -``` +A prerequisite for this tutorial is access to one of the supported large language models. Please refer to the [api setup](../user_guides/api_setup.md) for instructions on setting up the API. -Next, you can start your jupyter notebook in your activated environment by: +Upon successful setup, load your API key with the following two lines: -```console -jupyter notebook +```py +from dotenv import load_dotenv +load_dotenv() ``` -This opens a browser tab, and you can navigate to your preferred folder for this new project. Create a new notebook Python 3 (ipykernel) notebook from the "New" dropdown. Make sure that you select your environment as kernel. -??? tip "Beginners/Code novices" - If you followed the beginners steps in the [installation guide](../user_guides/install.md), you should already be set, and you can continue below. +### 2. Create your visualization using different languages -Confirm that vizro-ai is installed by typing the following into a jupyter cell in your notebook and running it. +Vizro-AI is versatile, supporting prompts and chart visualizations in multiple languages. Let's explore this capability with two examples, starting with Chinese where we inquire about visualizing the GDP per capita over time. -```py -import vizro_ai -print(vizro_ai.__version__) -``` +!!! example "Vizro-AI Chinese" + === "Code for the cell" + ```py + from vizro_ai import VizroAI + import vizro.plotly.express as px -You should see a return output of the version. + from dotenv import load_dotenv + load_dotenv() -### 3. Large Language Model (LLM) API KEY + df = px.data.gapminder() + vizro_ai = VizroAI() + vizro_ai.plot(df, "请画一个世界年均GDP的趋势图") + ``` + === "Result" + [![ChineseChart]][ChineseChart] -A prerequisite to use Vizro-AI is access to one of the supported LLMs. Refer to the [user guide](../user_guides/api_setup.md) on how to set up the API. + [ChineseChart]: ../../assets/tutorials/chart/ChineseExample.png -After successful setup, your API key is loaded in Jupyter with the following two lines: +Subsequently, we'll switch to German and prompt the visualization of life expectancy in the United States over time, comparing it to the global life expectancy trend. For this example, we'll include `explain=True` to obtain comprehensive insights into both the data and the generated code. -```py -from dotenv import load_dotenv -load_dotenv() -``` +!!! example "Vizro-AI German" + === "Code for the cell" + ```py + from vizro_ai import VizroAI + import vizro.plotly.express as px -### 4. Ask your first question using vizro-ai + from dotenv import load_dotenv + load_dotenv() -For your first visualization, we will create a chart illustrating the GDP of various continents while including a reference line for the average. + df = px.data.gapminder() + vizro_ai = VizroAI() + vizro_ai.plot(df, "Visualiere den Trend von der Lebenserwartung in USA über die Jahre im Vergleich zur Veränderung der weltweiten Lebenserwartung über die Jahre und kreiere eine deutsche Visualisierung", explain=True) + ``` + === "Result" + [![GermanChart]][GermanChart] -Let's go through the code step-by-step to understand how to use Vizro-AI. First, we create `pandas` DataFrame using the gapminder data from `plotly express`. Next, we instantiate `VizroAI` to call the `plot()` method to generate your visualization. + [GermanChart]: ../../assets/tutorials/chart/GermanExample.png -By passing your prepared data and your written visualization request to this method, Vizro-AI takes care of the processing. It generates the necessary code for data manipulation and chart creation, and then it proceeds to render the chart by executing the generated code. +### 3. Create advanced charts and formatting +Now, let's explore more advanced visualizations and leverage Vizro-AI for enhanced formatting. -!!! example "Vizro AI Syntax" +To begin, we'll create an animated bar chart illustrating the population development of each continent over time. Let's run the code below and look at the result. + +!!! example "Vizro-AI animated chart" === "Code for the cell" ```py from vizro_ai import VizroAI @@ -67,33 +78,54 @@ By passing your prepared data and your written visualization request to this met df = px.data.gapminder() vizro_ai = VizroAI() - vizro_ai.plot(df, "describe the composition of gdp in continent and color by continent, and add a horizontal line for avg gdp") + vizro_ai.plot(df, "The chart should be an animated stacked bar chart with popoluation on the y axis and continent on the x axis with all respective countries, allowing you to observe changes in the population over consecutive years.") ``` === "Result" - [![BarChart]][BarChart] + [![AnimatedChart1]][AnimatedChart1] - [BarChart]: ../../assets/tutorials/chart/GDP_Composition_Bar.png + [AnimatedChart1]: ../../assets/tutorials/chart/animated_bar_chart_1.png -The created chart is interactive, and you can hover over the data for additional information. +Having unveiled our animated bar chart showcasing population development per country, it's apparent that crucial details are overshadowed by the legend. Next, we will try to tweak our prompt to group the countries into continents and improve the overall layout. -### 5. Get an explanation with your chart +!!! example "Vizro-AI animated chart" + === "Code for the cell" + ```py + from vizro_ai import VizroAI + import vizro.plotly.express as px -By passing `explain=True` to the `plot()` method will provide additional insights in addition to the rendered chart. + from dotenv import load_dotenv + load_dotenv() -Let's create another example and read through the additional information. + df = px.data.gapminder() + vizro_ai = VizroAI() + vizro_ai.plot(df, "The chart should be an animated stacked bar chart with popoluation on the y axis and continent on the x axis with all respective countries, allowing you to observe changes in the population over consecutive years. Please improve layout.") + ``` + === "Result" + [![AnimatedChart2]][AnimatedChart2] -!!! example "Specify `explain=True`" + [AnimatedChart2]: ../../assets/tutorials/chart/animated_bar_chart_2.png + + +Great, by incorporating the directive `Please improve layout`, we've successfully refined our animation and are now able to better interpret our result. + +Now, upon closer inspection, two challenges emerge. Firstly, the legend overlaps the x-axis. Secondly, the y-axis range is insufficient to capture the full spectrum of Asia's population development. Let's run the code below and see how we can improve and finalize our chart. + +!!! example "Vizro-AI animated chart" === "Code for the cell" ```py - vizro_ai.plot(df, "show me the geo distribution of life expectancy", explain=True) - ``` - === "Result" - [![GeoDistribution]][GeoDistribution] + from vizro_ai import VizroAI + import vizro.plotly.express as px - [GeoDistribution]: ../../assets/tutorials/chart/GeoDistribution.png + from dotenv import load_dotenv + load_dotenv() -### 6. Explore further + df = px.data.gapminder() + vizro_ai = VizroAI() + vizro_ai.plot(df, "The chart should be an animated stacked bar chart with population on the y axis and continent on the x axis with all respective countries, allowing you to observe changes in the population over consecutive years. Make sure that y axis range fits entire data. Please improve layout and optimize layout of legend.") + ``` + === "Result" + [![AnimatedChart3]][AnimatedChart3] -Now, you have created your first charts with Vizro-AI and are ready to explore the documentation further. + [AnimatedChart3]: ../../assets/tutorials/chart/animated_bar_chart_3.png -A good place to start would be to go through the [model configuration](../user_guides/model_config.md) or different [run options](../user_guides/run_vizro_ai.md) including application integration. +Congratulations! You've now gained insights into harnessing the power of Vizro-AI for crafting advanced charts and elevating formatting. Don't forget, enabling `explain=True` is a good way of learning more about how a chart can be further improved and formatted. \ No newline at end of file From daa5f8d1e2ec418a183b23439d290a2e25b73e16 Mon Sep 17 00:00:00 2001 From: Chiara Pullem Date: Fri, 10 Nov 2023 17:25:31 +0100 Subject: [PATCH 6/8] add explore vizro-ai to nav --- vizro-ai/mkdocs.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/vizro-ai/mkdocs.yml b/vizro-ai/mkdocs.yml index f67dd0cd0..9e58cc5ac 100644 --- a/vizro-ai/mkdocs.yml +++ b/vizro-ai/mkdocs.yml @@ -4,6 +4,7 @@ nav: - Vizro-AI: index.md - Get started: - Quickstart: pages/tutorials/quickstart.md + - Explore Vizro-AI: pages/tutorials/explore_vizro_ai.md - User Guides: - Fundamentals: - Installation: pages/user_guides/install.md From 8121fbc8d1cd30ca2cc988f7e2dda671e59b942d Mon Sep 17 00:00:00 2001 From: Chiara Pullem Date: Mon, 13 Nov 2023 11:51:11 +0100 Subject: [PATCH 7/8] linting --- vizro-ai/docs/index.md | 2 +- vizro-ai/docs/pages/tutorials/explore_vizro_ai.md | 6 +++--- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/vizro-ai/docs/index.md b/vizro-ai/docs/index.md index 10deabd6a..606a4764e 100644 --- a/vizro-ai/docs/index.md +++ b/vizro-ai/docs/index.md @@ -1,6 +1,6 @@ # Vizro-AI -Vizro-AI is a tool designed for generating data visualizations. It serves as an extension to Vizro, leveraging natural language capabilities to empower users in creating charts effortlessly. +Vizro-AI is a tool designed for generating data visualizations. It serves as an extension to Vizro, leveraging natural language capabilities to empower users in creating charts effortlessly. ## Why Vizro-AI? diff --git a/vizro-ai/docs/pages/tutorials/explore_vizro_ai.md b/vizro-ai/docs/pages/tutorials/explore_vizro_ai.md index 18c9db503..7a11d0c4e 100644 --- a/vizro-ai/docs/pages/tutorials/explore_vizro_ai.md +++ b/vizro-ai/docs/pages/tutorials/explore_vizro_ai.md @@ -22,7 +22,7 @@ load_dotenv() ### 2. Create your visualization using different languages -Vizro-AI is versatile, supporting prompts and chart visualizations in multiple languages. Let's explore this capability with two examples, starting with Chinese where we inquire about visualizing the GDP per capita over time. +Vizro-AI is versatile, supporting prompts and chart visualizations in multiple languages. Let's explore this capability with two examples, starting with Chinese where we inquire about visualizing the GDP per capita over time. !!! example "Vizro-AI Chinese" === "Code for the cell" @@ -106,7 +106,7 @@ Having unveiled our animated bar chart showcasing population development per cou [AnimatedChart2]: ../../assets/tutorials/chart/animated_bar_chart_2.png -Great, by incorporating the directive `Please improve layout`, we've successfully refined our animation and are now able to better interpret our result. +Great, by incorporating the directive `Please improve layout`, we've successfully refined our animation and are now able to better interpret our result. Now, upon closer inspection, two challenges emerge. Firstly, the legend overlaps the x-axis. Secondly, the y-axis range is insufficient to capture the full spectrum of Asia's population development. Let's run the code below and see how we can improve and finalize our chart. @@ -128,4 +128,4 @@ Now, upon closer inspection, two challenges emerge. Firstly, the legend overlaps [AnimatedChart3]: ../../assets/tutorials/chart/animated_bar_chart_3.png -Congratulations! You've now gained insights into harnessing the power of Vizro-AI for crafting advanced charts and elevating formatting. Don't forget, enabling `explain=True` is a good way of learning more about how a chart can be further improved and formatted. \ No newline at end of file +Congratulations! You've now gained insights into harnessing the power of Vizro-AI for crafting advanced charts and elevating formatting. Don't forget, enabling `explain=True` is a good way of learning more about how a chart can be further improved and formatted. From b2f3c95a8d11621cf00bb1ac3dc3b68042dbdffe Mon Sep 17 00:00:00 2001 From: Chiara Pullem Date: Mon, 13 Nov 2023 16:12:11 +0100 Subject: [PATCH 8/8] change to vizro_ai --- vizro-ai/docs/pages/explanation/disclaimer.md | 2 +- .../docs/pages/explanation/safety_in_vizro_ai.md | 16 ++++++++-------- .../docs/pages/tutorials/explore_vizro_ai.md | 2 +- vizro-ai/docs/pages/tutorials/quickstart.md | 6 +++--- vizro-ai/docs/pages/user_guides/install.md | 2 +- vizro-ai/docs/pages/user_guides/model_config.md | 2 +- 6 files changed, 15 insertions(+), 15 deletions(-) diff --git a/vizro-ai/docs/pages/explanation/disclaimer.md b/vizro-ai/docs/pages/explanation/disclaimer.md index c69ceb00b..71473d98a 100644 --- a/vizro-ai/docs/pages/explanation/disclaimer.md +++ b/vizro-ai/docs/pages/explanation/disclaimer.md @@ -1,6 +1,6 @@ # Disclaimer -Users must select one of the [supported Large Language Models (LLMs)](../user_guides/model_config.md) in order to use the `vizro-ai` package, +Users must select one of the [supported Large Language Models (LLMs)](../user_guides/model_config.md) in order to use the `vizro_ai` package, and are responsible for obtaining their own suitable API key for the relevant model. ## Third Party API diff --git a/vizro-ai/docs/pages/explanation/safety_in_vizro_ai.md b/vizro-ai/docs/pages/explanation/safety_in_vizro_ai.md index 4595d4692..816111b29 100644 --- a/vizro-ai/docs/pages/explanation/safety_in_vizro_ai.md +++ b/vizro-ai/docs/pages/explanation/safety_in_vizro_ai.md @@ -4,7 +4,7 @@ Generative AI models, especially Large Language Models (LLMs) represent signific Vizro-AI also leverages LLMs, however, as with any powerful tool, there are potential risks associated. Users must connect to a generative AI model, specifically LLMs to use Vizro-AI. -We recommend users research and understand the selected model before using `vizro-ai` package. +We recommend users research and understand the selected model before using `vizro_ai` package. Users are encouraged to treat AI-generated content as supplementary, **always apply human judgment**, approach with caution, review the relevant [disclaimer](disclaimer.md) page, and consider the following: @@ -13,7 +13,7 @@ approach with caution, review the relevant [disclaimer](disclaimer.md) page, and Generative models can potentially generate information while appearing factual, being entirely fictitious or misleading. The vendor models might lack real-time knowledge or events beyond its last updates. -`vizro-ai` output may vary and please always verify critical information. +`vizro_ai` output may vary and please always verify critical information. It is the user's responsibility to discern the accuracy, consistent, and reliability of the generated content. ### 2. Unintended and Sensitive output @@ -41,17 +41,17 @@ It's crucial for users to remain informed, cautious, and ethical in their applic ## Dependencies, Code Scanners and Infosec -It may occur that dependencies of `vizro-ai` get flagged by code scanners and other infosec tools. As a consequence it may happen that -`vizro-ai` also get flagged. +It may occur that dependencies of `vizro_ai` get flagged by code scanners and other infosec tools. As a consequence it may happen that +`vizro_ai` also get flagged. While we aim to resolve any flagged issues as soon as possible, there may not always be an immediate available fix, especially in a very dynamic environment such as generative AI. We encourage users to investigate if any flagged infosec issues are actually related -to any functionality used in our code base or if they only concern functionality outside the scope of `vizro-ai`. +to any functionality used in our code base or if they only concern functionality outside the scope of `vizro_ai`. -In case those issues are related to code execution, note that `vizro-ai` has its own process of executing dynamic code (see [Safeguard Execution of Dynamic Code](safeguard.md)), and does not rely on its dependencies to do so. +In case those issues are related to code execution, note that `vizro_ai` has its own process of executing dynamic code (see [Safeguard Execution of Dynamic Code](safeguard.md)), and does not rely on its dependencies to do so. ## Execution of Dynamic Code in Vizro-AI -The `exec()` statement is used in `vizro-ai`. It allows for dynamic execution of Python programs which can be powerful, but can also pose security risk +The `exec()` statement is used in `vizro_ai`. It allows for dynamic execution of Python programs which can be powerful, but can also pose security risk if used without caution. When paired with outputs from generative models, there is potential for unintended or malicious code execution. Users must exercise caution when executing code generated by or influenced by AI models. It's essential to: @@ -60,6 +60,6 @@ Users must exercise caution when executing code generated by or influenced by AI - Always consider using controlled environments, such as virtual machines or containers, to execute uncertain code - Always be aware of potential risks when executing dynamically generated code in environments with access to sensitive data or systems - Always be aware that malicious code execution cannot be mitigated with 100% certainty -- Always review and understand the selected model before connecting with `vizro-ai` +- Always review and understand the selected model before connecting with `vizro_ai` If you would like to learn more about our efforts in safeguarding code execution, please refer to [Safeguard Execution of Dynamic Code](safeguard.md) for more information. diff --git a/vizro-ai/docs/pages/tutorials/explore_vizro_ai.md b/vizro-ai/docs/pages/tutorials/explore_vizro_ai.md index 7a11d0c4e..1a8115c10 100644 --- a/vizro-ai/docs/pages/tutorials/explore_vizro_ai.md +++ b/vizro-ai/docs/pages/tutorials/explore_vizro_ai.md @@ -4,7 +4,7 @@ This tutorial serves as an exploration of the extended applications offered by V By the end of this tutorial, you will have gained an understanding of different language options and leveraging Vizro-AI to enhance the formatting your visualizations. ## Let's get started! -### 1. Install vizro-ai and get ready to run your code +### 1. Install Vizro-AI and get ready to run your code Before proceeding, ensure the installation of the `vizro_ai` package by following the steps outlined in the [installation guide](../user_guides/install.md). Once installed, you can execute your code either by pasting it into a Jupyter notebook cell or running it from a Python script. diff --git a/vizro-ai/docs/pages/tutorials/quickstart.md b/vizro-ai/docs/pages/tutorials/quickstart.md index ba5a43bbe..886e1c604 100644 --- a/vizro-ai/docs/pages/tutorials/quickstart.md +++ b/vizro-ai/docs/pages/tutorials/quickstart.md @@ -3,7 +3,7 @@ This tutorial serves as an introduction to Vizro-AI. It is a step-by-step guide to help you experiment and create your initial Vizro chart using Vizro-AI, our English-to-visualization package. The goal is to provide you with the necessary knowledge to explore further into our documentation. ## Let's get started! -### 1. Install vizro-ai and its dependencies +### 1. Install Vizro-AI and its dependencies If you haven't already installed `vizro_ai` package, follow the [installation guide](../user_guides/install.md) to do so inside a virtual environment. @@ -28,7 +28,7 @@ This opens a browser tab, and you can navigate to your preferred folder for this ??? tip "Beginners/Code novices" If you followed the beginners steps in the [installation guide](../user_guides/install.md), you should already be set, and you can continue below. -Confirm that vizro-ai is installed by typing the following into a jupyter cell in your notebook and running it. +Confirm that `vizro_ai` is installed by typing the following into a jupyter cell in your notebook and running it. ```py import vizro_ai @@ -48,7 +48,7 @@ from dotenv import load_dotenv load_dotenv() ``` -### 4. Ask your first question using vizro-ai +### 4. Ask your first question using Vizro-AI For your first visualization, we will create a chart illustrating the GDP of various continents while including a reference line for the average. diff --git a/vizro-ai/docs/pages/user_guides/install.md b/vizro-ai/docs/pages/user_guides/install.md index 5eb8a24c3..2dfd246f3 100644 --- a/vizro-ai/docs/pages/user_guides/install.md +++ b/vizro-ai/docs/pages/user_guides/install.md @@ -40,7 +40,7 @@ pip install jupyter ??? tip "Beginners/Code novices" If you're new to coding or consider yourself a beginner, you can follow these following steps to avoid using the terminal: - - Search `vizro-ai` and install it using the Anaconda Navigator package manager. You can find instructions [here](https://docs.anaconda.com/free/navigator/tutorials/manage-packages/) + - Search `vizro_ai` and install it using the Anaconda Navigator package manager. You can find instructions [here](https://docs.anaconda.com/free/navigator/tutorials/manage-packages/) - Similarly, search `jupyter` and install it through the same procedure - Once installed, launching a Jupyter notebook becomes straightforward; you can find guidance [here](https://problemsolvingwithpython.com/02-Jupyter-Notebooks/02.04-Opening-a-Jupyter-Notebook/#open-a-jupyter-notebook-with-anaconda-navigator) - With Jupyter, you can easily copy and paste any of the provided examples into a notebook cell, evaluate the cell, and examine the results diff --git a/vizro-ai/docs/pages/user_guides/model_config.md b/vizro-ai/docs/pages/user_guides/model_config.md index d40f125b3..c0de03fd3 100644 --- a/vizro-ai/docs/pages/user_guides/model_config.md +++ b/vizro-ai/docs/pages/user_guides/model_config.md @@ -2,7 +2,7 @@ !!! Warning - Users are recommended to exercise caution and to research and understand the selected Large Language Model (LLM) before using `vizro-ai`. + Users are recommended to exercise caution and to research and understand the selected Large Language Model (LLM) before using `vizro_ai`. Users should be cautious about sharing or inputting any personal or sensitive information. **Data is sent to model vendors if you connect to LLMs via their APIs.**