I've been wanting to build a real public project for a while. So as a student I found that sending pdfs or docx into AI ends up with poor context and hallucinations. Not to mention the file upload limits and token costs. So decided to build an API to fix that problem.

What it does

My project is called ParseFlow, it takes documents (PDFs, DOCX, TXT) and converts them into readable JSON chunks that can be used for search indexing, chatbot context and LLM pipelines.

By converting documents into these organized chunks, you are able to:

Improve context and reduce hallucinations

Reduce token usage compared to uploading PDF/DOCX

Pick and choose what context to add

Keep documents private - nothing is stored

How I built it

I wanted to use this project to learn how to build APIs and use the FastAPI framework. So I started reading the documentation, watching videos and using a lot of Stackoverflow.…