Redwood | Analytics Intelligence

<Redwood 🌲

Redwood is an open-source Python library built on 🦜️🔗 langchain that aims to simplify the process of data analysis by allowing developers to interact with their data using simple natural language commands. Built on the principles of ease-of-use and flexibility using, Redwood is designed to be a versatile tool in your data analysis toolkit.

Features

📚 Natural Language Processing (NLP): Redwood uses NLP to interpret commands, allowing you to analyze your data using intuitive, human-readable commands.
💾 Data Source Flexibility: Redwood can interact with a variety of data sources, making it easy to load your data no matter where it's stored.
🧠 Intelligent Data Analysis: Based on your natural language commands, Redwood can perform complex analysis on your data using langchain based agents.
📈 Informative Responses: Redwood generates responses that provide insights into your data, based on the performed analysis.
📌 Syntax Mapping: Redwood allows you to define a dictionary of syntax mappings that can be used to translate syntax into sentences.
🔥 JSON Responses: Redwood returns responses in JSON format, making them easy to consume by other programs or libraries.

Get started

To get started with Redwood, follow these steps:

1. Clone the Redwood repository into a public GitHub repository or fork it from https://github.com/your_username/redwood/fork. If you plan to distribute the code, keep the source code public.

git clone https://github.com/your_username/redwood.git

2. Install the required Python libraries:

pip install -r requirements.txt

3. Import the Redwood library in your Python script:

from redwood import Redwood

Usage

Here's a basic example of how to use Redwood with method chaining:


                from redwood.redwood import Redwood 

                # Create an instance of the Redwood class and load data, set a
                model, and set an agent 

                redwood = Redwood().data("data.csv").model("OpenAI",
                api_key="your-api-key").agent("CSV")

                

                # Ask a question about the data 

                response = redwood.ask("how many rows are there?")

                print(response)

In this example, the data, model, and agent methods are chained together to load data from a CSV file, create an OpenAI model instance, and create a CSV agent. The ask method is then called to ask a question about the data and return the response in JSON format.

You can also define a syntax map and use it to ask questions:

Usage with Syntax


                # Define a syntax map 

                syntax_map = { "hvd": "tell me the highest visit day" }

                # Use the syntax map to ask a question 

                redwood.syntax(syntax_map) response = redwood.ask("hvd") 

                print(response)

In this example, the syntax method is called with the syntax_map dictionary to define the syntax for the Redwood instance. The ask method then translates the syntax into a sentence before passing it to the agent and returning the response in JSON format.

Contributing

We welcome contributions! If you're interested in improving Redwood, there are many ways to contribute:

Bug Reports: If you encounter a problem, please create an issue on GitHub with a detailed description of the bug. Feature Requests: If you have an idea for a new feature or an improvement to an existing feature, please create an issue on GitHub to discuss it. Pull Requests: If you're able to contribute code, documentation, or other improvements to Redwood, please create a pull request on GitHub. Before submitting a pull request, please make sure your changes pass all tests and conform to the project's coding style.

License

Redwood is licensed under the MIT License.

Contact support@analyticsintelligence.com If you have any questions or feedback, please feel free to contact us. You can also reach us by creating an issue on the GitHub project page.