Namo Namah: Intelligent Multilingual Festival and Ritual AI Agent
Dataset Creation, Extraction, and Preprocessing
The 'Namo Namah' AI agent's dataset is built from rigorously collected information from books by major Indian publishers, covering all states and widely spoken languages like Hindi, Bengali, and Marathi. A significant challenge was the lack of digital versions for many critical texts, such as 'Vratotsav'. This was overcome using OCR technology and meticulous annotation to create a structured database. Other valuable sources include 'Pooja Parbaner Utsakatha', 'Hindu Fasts and Festivals', and 'Bhartiya Sanskritikosh', ensuring a comprehensive understanding of Indian festivals and rituals.
NamoNamah demostration
Hybrid RAG
Our AI agent, uses an advanced Hybrid-RAG database for accurate, contextually relevant responses on festivals, rituals, and culture. Unlike other systems, it employs manually curated, highly efficient retrieval techniques that outperform conventional methods in precision and recall.Key innovations in Hybrid-RAG architecture lead to superior performance:Optimized Chunking Strategies: Sophisticated algorithms break text into semantically meaningful units, calibrated for cultural/religious texts to preserve critical information.Advanced Triplet Generation: Rich knowledge triplets create structured knowledge graphs, enabling precise connections and hierarchies beyond simple keyword matching, understanding relationships among festivals, deities, and rituals.Intelligent Retrieval Techniques: Proprietary methods integrate semantic understanding, contextual relevance, and query intent, identifying pertinent information even in extensive datasets (e.g., providing historical context, regional variations, and associated deities for a ritual).The synergy of chunking, triplet generation, and intelligent retrieval allows 'Namo Namah' to access, comprehend, and synthesize vast cultural information, delivering accurate, insightful, and contextually appropriate responses for festival and ritual queries.
.gif)
Books used as context for the Namo Namah Festival & Ritual Guide AI
Agentic Festival Companion
The Namo Namah Festival & Ritual Guide AI is an agentic assistant built on LlamaIndex orchestration and powered by Microsoft’s Phi-4 model. It acts autonomously to gather, verify, and present culturally sensitive festival knowledge by invoking specialized tools: search_festival_knowledge, search_historical_poem, search_festival_dates, search_youtube_videos, and a fallback search_web. A custom built Hybrid RAG supplies retrieval-augmented control logic that maps user intent to the appropriate tool, stitches evidence from multiple sources, and enforces policy rules such as language preference and strict provenance. Phi-4 provides fluent, context-aware generation that translates tool outputs into clear, respectful answers. The agent guarantees that festival dates, muhurta, and timings are presented in structured form and that cultural terms are transliterated to the user’s language. Default location is Kanpur when none is provided. Built-in validation routines re-check retrieved passages to avoid unsupported claims, and the system politely declines or redirects queries outside its tool-derived scope.
Future Scope and Improvements
The Namo Namah Festival & Ritual Guide can be expanded by incorporating cross-cultural and multilingual datasets, enabling seamless interaction across diverse Indian languages and global contexts. This ensures inclusivity and wider cultural reach. Future work will focus on building efficient Retrieval-Augmented Generation (RAG) pipelines that optimize query understanding, retrieval accuracy, and response generation, reducing latency while handling large cultural knowledge bases. Integration of adaptive memory and fine-grained personalization can further enhance user experience. By combining scalable RAG-LLM architectures with enriched datasets, the system can evolve into a universal cultural companion bridging traditions, languages, and communities worldwide.