👐 This is my personal profile. Here I share projects based on my actual needs and hobbies.
About me:
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My name is Francis and I'm a brazilian software developer with 6 years collaborating in projects in PT & EN;
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Before that I worked as a chemical engineer for 10 years.
- I’m currently practicing the latest trendings in AI: Atlas Vector Search and trained models.
In these matters, you can check these repositories that are using generative AI or Vector Search:
This repo is private, but for sure we can talk about it. I made it from scratch, both api and app.
The app is available in ONLY Brazil in Apple Store. Please share your thoughts and let's talk: https://apps.apple.com/br/app/turin-app/id6479428113?l=en-GB
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with Langchain
It is a ecosystem that interact with Internet Movie Database (through bulk catalogue, in user machine), create a curatory of movies, generate blogposts (all of that in Admin project locally), and after that publish the blogposts in a online Blog. The project also has and two APIs, one for each frontend application.
- In admin, user can search in IMDb catalogue, create a list of favorite movies and generate blogposts.
- In blog, users can see the generated blogposts.
Here the 5 public repos that comprehend the application
https://github.com/francisdiasbr/movie-search-frontend (Next project with Redux for state management)
https://github.com/francisdiasbr/movie-search-backend (Python project with Flask) Is the backend for Movie Search. The project comprehends all the endpoints the admin application needs.
https://github.com/francisdiasbr/movie-search-blog (Vite project with Redux for state management)
https://github.com/francisdiasbr/movie-search-blog-backend (Python project with Flask)
https://github.com/francisdiasbr/movie-search-adr (Markdown, in order to write the decisions in this repository)
with Langchain
This POC aims to categorize customer reviews using OpenAI. The analysis will be based on the comment text to assign a specific category that best describes the feedback.
with embeddings & Vector Search
A complete solution for extracting, processing, storing, and searching for information about minerals in a semantic way. It illustrates the application of NLP techniques and semantic search on real datasets, providing a foundation for recommendation systems, enhanced search, and text analysis.
See the projects to learn more about each repository of the application.
Here the 2 public repos
💬 Ask me about my experience as the lead developer of the Turin App, a tourism application where I managed communication with clients, collaborated with UX/UI designers, and published the app on the iOS store.
📫 How to reach me: francisdiasbr@gmail.com