LLMWhisperer Dry Run

Run LLMWhisperer on sample files to check suitability for your projects

Supported operating systems

You should be able to run this on Linux or on a Mac. Windows is not supported.

Keys you'll need

You'll need an API key for LLMWhisperer, which you can get for free. Once you have the key, please add it to the .env file in the root of the project. A sample .env file is provided in the repo for you to copy.

Running the code

Clone this repo and change to the llmwhisperer-dry-run directory. We suggest you run the code after you've created a Python virtual environment. You can create a virtual environment by running the following command:

python3 -m venv .venv

Next, activate the virtual environment:

source .venv/bin/activate

Now, install the dependencies:

pip install -r requirements.txt

Next, copy the sample.env file to .env, edit the .env file to add your and LLMWhisperer key:

cp sample.env .env

Finally, run the code:

python main.py <path to PDF file or directory with PDFs>

Limitations

• Although the LLMWhisperer service supports many different file types like common office document formats, images, PDFs, etc, the code currently only supports PDF files. If you have other file types, you'll need to convert them to PDF before running the code.
• Currently, only Linux and Mac are supported. Windows is not supported.
• In the code, the extraction mode is hardcoded to "text". If you want to extract from scanned documents or images where text is not selectable, you'll need to change the code and set EXTRACTION_MODE to "ocr". Please see the LLMWhisperer API documentation for more information.