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🏈 BigRedChat: A RAG-Based AI Chatbot for Nebraska Huskers Fans
We're excited to share BigRedChat.com — a fan-focused chatbot that uses Retrieval-Augmented Generation (RAG) to bring real-time, AI-powered Husker football knowledge to life.
What is BigRedChat?
BigRedChat is an intelligent assistant designed specifically for fans of Nebraska athletics, especially football. Powered by the OpenAI API and built with a custom backend, the chatbot blends traditional chatbot capabilities with up-to-date sports information.
How it works:
📥 RSS Feed Ingestion
We ingest news articles from a curated set of Nebraska Huskers RSS feeds. These articles are stored in a MySQL database and automatically categorized by sport and date.
📚 Embedding Generation
Using OpenAI’s text-embedding-3-small, we generate semantic embeddings for chunked summaries of each article. These embeddings are stored in a database table alongside metadata for fast vector search.
🧠 Contextual Retrieval with RAG
When a user asks a question, the chatbot retrieves the most relevant chunks based on vector similarity and injects them into the prompt as contextual information. This ensures the assistant can respond with the most current and accurate insights — not just general knowledge.
🎯 HuskerBot Personality
The assistant runs with a custom system prompt that gives it a loyal, slightly obsessive Husker-fan personality — the kind that still talks about the ‘95 team like it was yesterday.
Try it out:
https://BigRedChat.com/
We're excited to share BigRedChat.com — a fan-focused chatbot that uses Retrieval-Augmented Generation (RAG) to bring real-time, AI-powered Husker football knowledge to life.
What is BigRedChat?
BigRedChat is an intelligent assistant designed specifically for fans of Nebraska athletics, especially football. Powered by the OpenAI API and built with a custom backend, the chatbot blends traditional chatbot capabilities with up-to-date sports information.
How it works:
📥 RSS Feed Ingestion
We ingest news articles from a curated set of Nebraska Huskers RSS feeds. These articles are stored in a MySQL database and automatically categorized by sport and date.
📚 Embedding Generation
Using OpenAI’s text-embedding-3-small, we generate semantic embeddings for chunked summaries of each article. These embeddings are stored in a database table alongside metadata for fast vector search.
🧠 Contextual Retrieval with RAG
When a user asks a question, the chatbot retrieves the most relevant chunks based on vector similarity and injects them into the prompt as contextual information. This ensures the assistant can respond with the most current and accurate insights — not just general knowledge.
🎯 HuskerBot Personality
The assistant runs with a custom system prompt that gives it a loyal, slightly obsessive Husker-fan personality — the kind that still talks about the ‘95 team like it was yesterday.
Try it out:
https://BigRedChat.com/
