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I worked as a Full Stack Developer, using React.js and Node.js to develop the entire frontend and backend of this app.
About App: Achieve exceptional email marketing results with Success.ai. Our platform offers advanced features to streamline campaign management and boost deliverability, making every email an opportunity for success.
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The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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Instead of a dead-end error page, we built a full rhythm game - hit the notes in sync with the beat!
Pick your track - Synthwave 15K, Oldskool, Space Ranger - and you've got 3 lives to survive "the void."
Miss too many, and the void wins.
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This project demonstrates a Retrieval-Augmented Generation (RAG) architecture using open-source tools. It solves the "knowledge cutoff" problem of LLMs by giving them access to live tools.
How it works:
Intent Classification: The user's input is first processed by a local Llama 3 instance, which acts as a semantic router. It analyzes the prompt to determine if external data is required.
Tool Execution: If a search intent is detected, the Python backend executes a query against the SerpApi (Google Shopping) endpoint. Data Structuring: The raw JSON response from the API is parsed, cleaned, and structured into standardized product objects.
UI Rendering: The structured data is dynamically rendered into interactive product cards using Streamlit's component system, allowing users to view images and click direct purchase links without leaving the chat interface.
Retrieval- Augmented Generation (RAG) web app that synthesizes real time data from PUBMed.com and ClinicalTrials.gov, a custom React frontend and Node.js backend with MongoDB backend multi turn memory to maintain conversational context and prevent AI hallucinations
