NeuroPulse a ai/ml chatbot

Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady Submission 🦥

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady

Keeping up with Artificial Intelligence and Machine Learning feels like a full-time job. Between 80-page whitepapers, convoluted mathematical equations, 3-hour video tutorials, and endless forum debates, understanding even basic concepts like backpropagation, contrastive loss, or transformer attention usually takes hours of digging.

In honor of International Sloth Day and this week’s "Slow and Steady" challenge, I built NeuroPulse — a local, privacy-first Retrieval-Augmented Generation (RAG) assistant designed to reward intellectual laziness.

Instead of wading through dozens of open browser tabs, reading bloated medium articles, or paying monthly subscription fees to proprietary AI APIs, NeuroPulse does all the heavy reading for you. You ask a direct question, and it retrieves grounded knowledge from a curated vector database, validates the topic, and synthesizes a punchy, accurate answer with verifiable source citations — running 100% offline on your own machine.

Developers, students, and engineers who dread information overload get to be a whole lot lazier without falling behind.

NeuroPulse features both a clean, modern conversational web interface and a terminal CLI:

The complete source code is open source under the MIT License: https://github.com/Mohammad1sami/AI-ML-chatbot

AI Chatbot/ ├── aiml_knowledge_base.csv # 118 verified AI/ML knowledge entries & categories ├── chroma_langchain_db/ # Persistent local Chroma vector database ├── chroma_langchain_db.csv.sha256# SHA-256 change detector for zero-waste indexing ├── vector.py # Chunking, mxbai embeddings, and Chroma retriever setup ├── server.py # FastAPI server with SSE streaming & REST endpoints ├── main.py # CLI interactive runner └── static/ # Fast, minimalist frontend (HTML5/CSS3/Vanilla JS) ├── index.html ├── style.css └── app.js Enter fullscreen mode Exit fullscreen mode How I Built It NeuroPulse is built exclusively on top of open-source AI and open-weight models — no closed cloud endpoints or commercial APIs:

To keep things fast and prevent hallucinated ramblings, the system implements two LangChain chains:

# Automatic SHA-256 change detection: only re-index when your knowledge base edits! with open ( " aiml_knowledge_base.csv ", " rb " ) as f: csv_hash = hashlib. sha256 ( f. read ()). hexdigest () if csv_hash!= previous_hash: # Split, embed with mxbai-embed-large, and persist into ChromaDB chunks = splitter. split_documents ( source_documents ) vector_store. add_documents ( documents = chunks, ids = ids ) with open ( HASH_PATH, " w ", encoding = " utf-8 " ) as f: f. write ( csv_hash ) Enter fullscreen mode Exit fullscreen mode Why Does Open Innovation Matter? Open innovation is what makes this project practical, trustworthy, and sustainable:

Here is the sloth math on how much effort NeuroPulse saves:

Built with ❤️ for Hacktoberfest 2026. Happy Sloth Day — work less, build open, and let the local models do the heavy lifting!