aayushxrj/pluto.ai

Pluto.ai

Pluto.ai is a conversational Retrieval Augmented Generation (RAG) chatbot built with LangChain, Chainlit that uses Claude's capabilities for question-answering from documents.

!https://github.com/aayushxrj/Pluto.ai/assets/***/2cec03e1-1016-440f-875b-1901b34f166c

Quick Start

Clone the Repository

git clone https://github.com/aayushxrj/Pluto.ai

Navigate to the Project Directory

cd ./Pluto.ai/

Now you can get the app up and running using either a https://docs.python.org/3/library/venv.html or https://www.docker.com/.

Set up a Virtual Environment

It's recommended to use a virtual environment to keep your project dependencies isolated. Follow these steps to set up a virtual environment:

1. Create a new virtual environment:

python -m venv venv

2. Activate the virtual environment:

On Windows

./venv/Scripts/activate

On Unix or Linux

source venv/bin/activate

Install Dependencies

3. With your virtual environment activated, install the required dependencies using the following command:

pip install -r requirements.txt

Deactivate the Virtual Environment

4. After installing the dependencies, you can deactivate the virtual environment:

deactivate

Set up Anthropic API Key

Ensure you have an Anthropic API key to access the Claude LLM. You can obtain an API key from the https://console.anthropic.com/dashboard.

5. Create a .env file in the project root directory and add the following line, replacing your_api_key with your actual API key:

ANTHROPIC_API_KEY=your_api_key

Run the Application

6. Run the following script to start the Chainlit server:

chainlit run app.py -w

Interact with the application through the Chainlit interface. You can upload a file and ask questions related to the file's content.

Docker Usage

If you have Docker installed and running, you can also run the application using Docker. Follow these steps:

1. Build the Docker image locally:

docker build -t aayushxrj/pluto.ai:latest .

or directly pull from Docker Hub (recommended):

docker pull aayushxrj/pluto.ai:latest

2. Run the Docker container:

docker run --name pluto.ai -p 8000:8000 -e ANTHROPIC_API_KEY='your_api_key' aayushxrj/pluto.ai:latest

Replace your_api_key with your real Anthropic API key to gain access to the Claude LLM. You can obtain an API key from the https://console.anthropic.com/dashboard.

You can access the app at http://localhost:8000/

Usage

Once the Chainlit server is running, you'll be presented with an interface to upload a file.

!https://github.com/aayushxrj/Pluto.ai/assets/***/b5ca305a-de88-475b-9db8-02119db42439

After uploading a file, you can type your question in the text box and hit Enter.

!https://github.com/aayushxrj/Pluto.ai/assets/***/0494108b-d8d3-4f4f-a779-48bad4b75dfd

The application utilizes the Anthropic's API to access Claude to extract pertinent information from the uploaded file and furnish a response to your inquiry. It displays the source page, complete with page number and content, which serves as the basis for answering the question.

!https://github.com/aayushxrj/Pluto.ai/assets/***/f3e8c33d-1a9b-4d14-988c-02700e51d466

Thanks to Chainlit, it unveils the entire chain of thought that the RAG pipeline utilizes to arrive at the conclusive output at the end.

!https://github.com/aayushxrj/Pluto.ai/assets/***/f13ad146-0222-4d74-a5ec-004cb8ee9ad7

You can continue asking follow-up questions or upload a new file as desired.

Contributing

If you wish to contribute to Project Pluto.ai, please adhere to the following steps:

• Fork the repository: Create a new branch (git checkout -b feature/your-feature-name)
• Commit your changes: Make your modifications (git commit -m 'Add some feature')
• Push to the branch: Upload your changes (git push origin feature/your-feature-name)
• Create a new Pull Request: Submit your alterations for review

License

Project Pluto.ai is licensed under the MIT License.