Image Captioner — Misa
Three AI projects in one: a DeepSeek-powered chatbot, an unbeatable Tic-Tac-Toe AI, and a BLIP-based image caption generator.
Built by Sandeep Prajapati
Three AI projects in one: a DeepSeek-powered chatbot, an unbeatable Tic-Tac-Toe AI, and a BLIP-based image caption generator.
Built by Sandeep Prajapati
Three AI mini-projects bundled into one, built during the MISA program — each exploring a different corner of applied AI: a conversational chatbot, a game-playing agent, and a vision-language captioner.
1. DeepSeek-powered chatbot — a conversational assistant built on the DeepSeek R1 model.
2. Unbeatable Tic-Tac-Toe AI — a game agent using the Minimax algorithm; it never loses.
3. BLIP image caption generator — a vision-language model (BLIP via Hugging Face) that generates natural-language descriptions of uploaded images.
AI / ML: BLIP, Hugging Face Transformers, DeepSeek R1
Algorithms: Minimax (game AI)
Languages: Python, JavaScript
A compact tour of three AI paradigms — LLM chat, classical game-search, and multimodal vision-language — implemented end to end.
Tic-Tac-Toe AI
Web-based Tic-Tac-Toe with an unbeatable AI opponent powered by the Minimax Algorithm with Alpha-Beta Pruning.
Noloop
A glass-box medical claims adjudication and fraud-defense platform — an AI agent pipeline turns unstructured claim documents into explainable, role-specific decisions for patients, hospitals, and insurers.
RAG Document Assistant
A production-style Retrieval-Augmented Generation system — documents are chunked, embedded with SentenceTransformers, indexed in Endee's HNSW vector database, and retrieved via cosine-similarity k-NN search to ground Groq's Llama 3.3 70B in a user-provided knowledge base with full source attribution.