Getting started with the Platform
A comprehensive guide on configuring, and using the PandasAI dockerized UI platform.
Using the Dockerized Platform
PandasAI provides a dockerized client-server architecture for easy deployment and local usage that adds a simple UI for conversational data analysis. This guide will walk you through the steps to set up and run the PandasAI platform on your local machine.
Prerequisites
Before you begin, ensure you have the following installed on your system:
- Docker
- Docker Compose
Note: By default the platform will interact with the csv files located in the server/data
directory. You can add your own csv files to this directory before running the platform and the platform will automatically detect them and make them available for querying. Make sure you replace the existing files with your own files if you want to use your own data.
Step-by-Step Installation Instructions
-
Clone the PandasAI repository:
-
Copy the
.env.example
file to.env
in the client and server directories: -
Edit the
.env
files and update thePANDASAI_API_KEY
with your API key:Replace
YOUR_PANDASAI_API_KEY
with your PandasAI API key. You can get your free API key by signing up at PandasAI. -
Build the Docker images:
Running the Platform
Once you have built the platform, you can run it with:
Accessing the Client and Server
After deployment, the client can be accessed at http://localhost:3000
, and the server will be available at http://localhost:8000
.
Troubleshooting Tips
- If you encounter any issues during the deployment process, ensure Docker and Docker Compose are correctly installed and up to date.
- Check the Docker container logs for any error messages:
Understanding the docker-compose.yml
File
The docker-compose.yml
file outlines the services required for the dockerized platform, including the client and server. Here’s a brief overview of the service configurations:
postgresql
: Configures the PostgreSQL database used by the server.server
: Builds and runs the PandasAI server.client
: Builds and runs the PandasAI client interface.
For detailed information on each service configuration, refer to the comments within the docker-compose.yml
file.
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