TrendiAI: Cross-Platform AI Research Trend Tracker

A powerful research trend discovery tool that fetches and clusters AI topics from arXiv, GitHub, Reddit, and Exa. Built using Python, NLP, and Streamlit.

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Features

• Unified search across 4 AI research platforms
• KMeans clustering to group topics
• Keyword extraction using KeyBERT
• Ranking based on source priority, relevance, and recency
• Google-style UI built with Streamlit
• Secure API key management using .env

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Technologies Used

• Python 3.10+
• Streamlit
• scikit-learn (TF-IDF, KMeans)
• KeyBERT for keyword extraction
• PRAW (Reddit API), requests, dotenv

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How It Works

1. User enters a research query.
2. API calls made to arXiv, GitHub, Reddit, Exa.
3. Fetched text is cleaned and vectorized using TF-IDF.
4. KMeans clustering groups similar content.
5. KeyBERT extracts keywords to name clusters.
6. Results ranked by source, relevance, and recency.
7. Top 5 clusters with 10 trends each are displayed in Streamlit UI.

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Local Setup

Clone the repo

git clone https://github.com/amith-exe/Trendi-Ai.git
cd Trendi-Ai