Navigating Bureaucracy with a Powerful RAG System: My Journey

In an innovative blend of cutting-edge technology and public service, I’ve developed a robust retrieval-augmented generation (RAG) system that leverages official U.S. government data in conjunction with OpenAI’s GPT-4. This unique approach aims to simplify the often complex landscape of governmental processes and resources. You can explore this project at Clerkly.

The Development Journey

Locating the Data

The first step in this project was identifying the plethora of relevant government data available through various federal and local resources. I delved deep into .gov domains, spending considerable time researching and mapping out the necessary sources to ensure comprehensive coverage for our users.

Scraping the Data

Armed with a list of sources, I utilized the Apify platform to scrape data from publicly accessible government websites. This process wasn’t without its hurdles; establishing effective crawlers while filtering out irrelevant pages—such as cluttered address books and archives—required a tailored approach. To enhance the efficiency of this stage, I relied on Llama2 for rapid data processing.

Processing the Data

Transforming the scraped data into manageable chunks suitable for vector store retrieval presented its own set of challenges. While I drew inspiration from the LLamaIndex library, the need to create a custom solution became apparent as the existing tool didn’t fully satisfy my requirements.

Storing and Linking Data

For the organization of data, I opted for GraphDB, where I utilized entities extracted using Llama2 to establish meaningful linkages. This structured storage enables swift and effective retrieval operations crucial for user queries.

Retrieval Strategies

The retrieval phase is vital, as it directly influences the quality of answers generated by GPT-4. This stage involves significant experimentation and optimization, with a sharp focus on user needs to deliver accurate and contextually rich information.

Generating Answers

Finally, once a query has been processed and the relevant context has been secured, I call the GPT-4 API with a carefully formulated RAG prompt to generate the necessary results. This culmination of data retrieval and advanced AI capabilities transforms bureaucratic navigation from a daunting task into a streamlined experience.

The synthesis of official governmental sources and advanced generative AI not only enhances user interaction but also fostered a deeper understanding of available resources. I invite you to try out the project and experience the ease of navigating bureaucracy at [Clerkly