Disha - Chatbot IIIT Nagpur

Welcome to the Disha Chatbot GitHub repository! This project is an innovative solution designed to streamline the user experience for navigating the IIIT Nagpur website. Built with cutting-edge Machine Learning (ML), Natural Language Processing (NLP), and Large Language Models (LLMs), Disha provides instant, user-friendly responses to a variety of queries.

---

Features

Human-like Interaction

• Enables natural and intuitive conversations.
• Provides accurate and contextual answers to queries about IIIT Nagpur.

Voice Input

• OpenAI - Whisper-small-en

Data Processing and Structuring

• Extracts text and images from IIIT Nagpur’s website using OCR.
• Structures data into a comprehensive JSON format for training.

Unified and Accurate Responses

• Combines fine-tuned LLMs and Retrieval-Augmented Generation (RAG) for precise answers.
• Responses are verified for maximum reliability.

Evaluation Metrics

• Measures output quality using BLEU, ROUGE-L, Semantic Similarity, and Human Score metrics.

---

Key Technologies

Machine Learning Models

• LLaMA-3.2-1B: Fine-tuned with rank values R-8, R-16, R-32, and Phi-3.5.
• Phi-3.5-mini
• PEFT Techniques: Efficient fine-tuning with LoRA and QLoRA.

Retrieval-Augmented Generation (RAG)

• Retrieves accurate, contextually relevant data from external databases.
• Utilizes:
  • Pinecone: Vector database for optimized search and retrieval.
  • LangChain: For seamless data pipelines.
  • Google Gemini API: Provides accurate, summarized answers.

---

Evaluation Metrics Table

Model	BLEU	ROUGE-L	Semantic Similarity	Human Evaluation	Trained Parameters
LLAMA-3.2-1b (R=8)	0.925700	0.964550	0.998106	0.934744	12,156,928
LLAMA-3.2-1b (R=16)	0.925950	0.964757	0.998106	0.942012	24,313,856
LLAMA-3.2-1b (R=32)	0.924404	0.963656	0.998096	0.946338	48,627,712
Phi 3.5 Mini	0.785048	0.886750	0.998205	0.852504	29,884,416
RAG	0.964902	0.996087	0.995800	0.967379	0

---

Trained Models

• LLaMA-3.2-1b r=8 Link
• LLaMA-3.2-1b r=16 Link
• LLaMA-3.2-1b r=32 Link
• Phi-3.5-mini Link

---

Web Interface - Hugging Face

---

Architecture Overview

Unified Intelligence

• Integrates RAG and fine-tuned LLMs for robust performance.

Context Preservation

• Ensures all critical details are included in responses.

Natural Flow

• Delivers user-friendly, conversational interactions.

---

Future Plans

• Expand language support beyond Hindi and English.
• Enhance scalability for larger datasets and more complex queries.
• Integrate additional evaluation metrics to improve accuracy.

---

Feel free to fork, contribute, and enhance Disha for broader applications!