Package: patentgpt-extract
PatentGPTThis repository hosts a prototype for patent analysis with a particular focus on extracting specific technical measurements and their associated valuesQuick StartTo run this package in Google Colab:InstallationStep 1. Installpatentgpt-extract, simply usepip:from patentgpt.main import mainStep 2. Authentication: Before using the package, you need to authenticate with OpenAI. To do this:import os
from getpass import getpass

token = getpass("Enter your OpenAI token: ()")
os.environ["OPENAI_API_KEY"] = str(token)Step 3. Importing and Running:from patentgpt.main import main

main()Then answer these questions::Enter a date in the format 'YYYY-MM-DD': exampe is 2023-01-12Enter the number of patents you want to analyze: example is 5 (this randomly select 5 parsed patents)Do you want to log the results? (yes/no)Select a model for analysis: 1. gpt-3.5-turbo 2. gpt-4Quick Start using repositoryClone this repository.Install the required Python packages by running!pip install -r requirements.txt.Run the Jupyter notebookquick_start.ipynb.Authenticate and add your OpenAI token. Then answer these questions::Enter a date in the format 'YYYY-MM-DD': exampe is 2023-01-12Enter the number of patents you want to analyze: example is 5 (this randomly select 5 parsed patents)Do you want to log the results? (yes/no)Select a model for analysis: 1. gpt-3.5-turbo 2. gpt-4JSON results will be saved in the output folder.System DesignBelow is an image that illustrates the main design and workflow of the patent analysis systemThe project involves the following steps:Downloading a ZIP archive that contains granted patent full-text data (without images) fromhttps://bulkdata.uspto.gov/.Reading the contained patents from XML files and extracting individual XML file, parsing it to text file and saving it in data.Implementing an approach based on a large language model (LLM) to extract measurements from the patents using vector store Chroma. The measurements are returned in a structured format (such as JSON).RequirementsPython 3.10+See requirements.txt for Python packages and versions.LicenseThis project is licensed under the terms of the MIT license. SeeLICENSEfile.CollaborationWe welcome contributions to patentgpt-extract! If you're interested in improving the package, adding features, or even fixing bugs, here's how you can get started:Fork the Repository: Start by forking the repository. This creates your own personal copy of the entire project.Clone Your Fork: Once you've forked the repo, clone your fork to your local machine to start making changes.git clone https://github.com/arminnorouzi/patentGPT.gitCreate a New Branch: Before making changes, create a new branch. This helps in segregating your changes and makes it easier to merge later.git checkout -b new-feature-branchReplace `new-feature-branch`` with a descriptive name for your changes.Make Your Changes: Now, you can start making changes, adding new features, fixing bugs, or improving documentation.Commit and Push: Once you're done, commit your changes and push them to your fork on GitHub.git add .
git commit -m "feat or fix: Description of changes made"
git push origin new-feature-branchOpen a Pull Request: Go to your fork on GitHub and click the "New pull request" button. Ensure you're comparing the correct branches and then submit your pull request with a description of the changes you made.Additional ResourcesFor further questions or if you encounter any problems, please do not hesitate to open an issue.My Website- More details about me and my projects.LinkedIn- See the post related to machine learning and software development on LinkedIn.Medium- See my posts related to ML/AI, algorithms, and system design.