Advanced Telugu sentiment analysis for YouTube comments using Meta Llama 3.2 with 4-bit quantization. Features interactive dashboard, code-mixed text support, real-time processing, and comprehensive evaluation metrics. Perfect for analyzing Telugu social media content and movie reviews.

rfetcher is a powerful Python CLI tool for scraping and categorizing Reddit content with intelligent filtering. Designed for researchers and data analysts, it extracts structured discussions while filtering noise like subreddit references and meta-comments. Outputs organized JSON data with nested comments, post metadata, and category tagging.

CommentSense is an intelligent tool that leverages OpenAI’s Large Language Models (LLMs) to analyze YouTube comments and generate high-level feedback for content creators. Just paste a YouTube link, and CommentSense will summarize what your audience thinks — the good, the bad, and what they want next.

Extract comments from Instagram posts (Reels, Feed) and merge them into a single text file. Perfect for research, sentiment analysis, and social media data processing.

An assesment project for - multi-agent comment analysis system featuring semantic search, LLM-based categorization, and automated insight extraction with comprehensive analytics pipeline.

Analyze comments on YouTube videos using AI.

Sentimental Analysis of comments on YouTube videos. Classify comments as positive, negative, or neutral. Provide visualizations to display the distribution of the sentiments.

🛡️ Detect and catalog developer comments and potential secrets in HTTP responses with Comment Crusader for Burp Suite, enhancing your security assessments.