vizro-mcp

# Install Vizro-AI In this guide you'll learn how to set up the prerequisites needed for Vizro-AI, and how to install it. You'll also find out how to verify the Vizro-AI installation succeeded, find the version of Vizro-AI, and learn how to update it. Vizro-AI supports macOS, Linux, and Windows. It works with Python 3.9 and later. You can specify the version of Python to use with Vizro-AI when you set up a virtual environment. ## Set up a virtual environment You should create a virtual environment for each Vizro-AI project you work on to isolate its Python dependencies from those of other projects. See the following references to learn more about [Python virtual environments](https://realpython.com/python-virtual-environments-a-primer/), [Conda virtual environments](https://docs.conda.io/projects/conda/en/latest/user-guide/getting-started.html#starting-conda) or [watch an explainer video about them](https://youtu.be/YKfAwIItO7M). ??? information "How to create a virtual environment for your Vizro-AI project" The simplest way to create a virtual environment in Python is `venv`, which is included in the Python standard library. Create a directory for your project and navigate to it. For example: ```bash mkdir vizroai-project cd vizroai-project ``` Next, create and activate a new virtual environment in this directory with `venv`: ```bash python3 -m venv .venv source .venv/bin/activate ``` Alternatively, you might like to use [`conda` as your virtual environment manager](https://docs.conda.io/projects/conda/en/latest/user-guide/install/). Once installed, you can create and activate a virtual environment from the terminal as follows: ```bash conda create --name vizroai-environment conda activate vizroai-environment ``` ## Install Vizro-AI To install Vizro-AI, use [`pip`](https://pip.pypa.io/en/stable/) in your terminal window: ```bash pip install vizro_ai ``` If you would like to use LLM vendors other than [`OpenAI`](https://platform.openai.com/docs/models) you can choose to install it with the optional dependencies `anthropic` and/or `mistral`, e.g.: ```bash pip install vizro_ai[anthropic,mistral] ``` Vizro-AI works with more vendors than the above, you can install further partner packages beyond the above optional dependencies. See more in [our detailed guide on model setup](customize-vizro-ai.md). ## Confirm a successful installation To confirm the installation was successful, and verify the version of Vizro-AI installed, call the following. You can do this from within a Jupyter Notebook cell, or run the following as a Python script: ```py import vizro_ai print(vizro_ai.__version__) ``` You should see a return output of the form `x.y.z`. ## Set up access to a large language model Vizro-AI supports **any** model that is available via [Langchain's `BaseChatModel` class](https://api.python.langchain.com/en/latest/language_models/langchain_core.language_models.chat_models.BaseChatModel.html#langchain_core.language_models.chat_models.BaseChatModel), and that has the [`with_structured_output` method](https://python.langchain.com/v0.2/docs/how_to/structured_output/#the-with_structured_output-method) implemented. An overview of the [most common vendor models supporting this functionality](https://python.langchain.com/v0.2/docs/integrations/chat/) can be found in Langchain's documentation. ### Set up access to OpenAI (as an example for any vendor) To use OpenAI with Vizro-AI you need an API key, which you can get by [creating an OpenAI account if you don't already have one](https://platform.openai.com/account/api-keys). We recommend that you consult the [third-party API key section of the disclaimer documentation](../explanation/disclaimer.md). There are two common ways to set up the API key in a development environment. __Method 1: Set an environment variable for a single project__ To make the API key available for a single project, you can create a local `.env` file to store it. Then, you can load the API key from that `.env` file in your development environment. The `.env` file should look as follows (containing your key rather than `abc123`): ```text OPENAI_API_KEY=abc123 ``` By default, `vizro-ai` automatically loads the `.env` file, by searching the current directory and, if it does not find `.env`, the search continues upwards through the directory hierarchy. If you would like to customize the `.env` file location and name, you can manually customize the search to override the default and specify the path and name of a custom `.env` file. ??? example "How to override the default location of the .`env` file:" ```python from dotenv import load_dotenv, find_dotenv from pathlib import Path # Specify the exact path to your .env file env_file = Path.cwd() / ".env" # Adjust the path as needed # Alternatively, specify a different .env file name env_file = find_dotenv(".env.dev") # Replace ".env.dev" with your file name # Load the specified .env file load_dotenv(env_file) ``` Refer to [Python-dotenv documentation](https://saurabh-kumar.com/python-dotenv/reference/) for further information. !!! warning "Don't share your secret API key!" You should avoid committing the `.env` file to version control. You can do this for Git by adding `.env` to your `.gitignore` file. __Method 2: Set an environment variable for all projects__ To make the OpenAI API key available for all projects, you can set it as a system environment variable. Refer to the section ["Set up your API key for all projects"](https://platform.openai.com/docs/quickstart/step-2-setup-your-api-key?context=python) in the OpenAI documentation. (It is under the dropdown of "Step 2: Set up your API key"). The documentation gives step-by-step instructions for setting up the API key as an environment variable, on operating systems including Windows and MacOS. !!! note Sometimes setting up the `.env` file can be fiddly. If necessary, you can supply the API key directly to the instantiated model. See [our user guide](./customize-vizro-ai.md#setting-model-via-class-for-additional-configuration) for this option. Remember not to commit this API key to any public space! __Set the base URL (optional)__ You might need to give the base URL if you are using a custom OpenAI resource endpoint. The API base URL used for the OpenAI connector is set to `https://api.openai.com/v1` by default. If you are using a custom API endpoint, for example, if your organization has a designated API gateway, you can change the base URL by setting it as an environment variable. Follow the approach above in Method 2 to add the environment variable `OPENAI_API_BASE` for use by all projects. ## Upgrade the Vizro-AI package Check the [release notes](https://github.com/mckinsey/vizro/blob/main/vizro-ai/CHANGELOG.md) for any notable breaking changes before upgrading the version of Vizro-AI used with an existing project: ```bash pip install -U vizro_ai ```