EmpathAI — AI Mental Health Chatbot Developed EmpathAI, an AI-powered conversational application ...EmpathAI — AI Mental Health Chatbot Developed EmpathAI, an AI-powered conversational application ...
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Developed EmpathAI, an AI-powered conversational application designed to provide empathetic, context-aware conversations through natural language.
The project focused on combining conversational AI with a simple, accessible interface to create a more human-like chatbot experience.
Key Features
AI-powered conversational chatbot for natural-language interactions
Fine-tuned DialoGPT model for conversational responses
Conversational interface built with Streamlit
Firebase integration for storing and managing application data
Context-aware dialogue handling for more coherent conversations
Clean and user-friendly chatbot interface
Deployed through Hugging Face Spaces for public accessibility
End-to-end implementation covering model development, application interface, backend integration, and deployment
Tech Stack
Python · DialoGPT · Hugging Face Transformers · Streamlit · Firebase · Hugging Face Spaces
My Role
AI/ML Engineer — End-to-End Development
Designed and developed the project from the AI model layer through the user-facing application, including conversational model fine-tuning, application development, database integration, and deployment.
The project gave me practical experience in NLP, conversational AI, transformer-based models, model deployment, and building AI applications around real user interactions.
I've built a new mobile AI assistant that brings chat, text and image generation, voice input and document analysis into one app.
It have Smart Chat, Text Creator, Image Create, Voice Input, plus PDF Scanner, Photo Analyze, Social Content and Prompt Ideas, filtered by category.
Almost everything AI can do, just in one place.
Bundling the skills with the template is a smart move, feels like you're selling the workflow and not just the layout. Does the agent keep the page consistent with the existing CMS styles on its own, or do you still end up nudging spacing by hand?
𝐑𝐀𝐆 𝐀𝐈 𝐊𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦 | 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐭 𝐒𝐞𝐚𝐫𝐜𝐡, 𝐀𝐈 𝐀𝐧𝐬𝐰𝐞𝐫𝐬 & 𝐕𝐞𝐜𝐭𝐨𝐫 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞
I designed and built a RAG-powered AI knowledge platform that lets businesses search documents, websites, databases, and internal knowledge using natural language.
The system processes content, creates embeddings, stores them in a vector database, retrieves the most relevant information, and uses AI to generate accurate, source-grounded answers.
My services include: RAG development, document ingestion, semantic search, vector database setup, OpenAI/LLM integration, internal knowledge assistants, API integrations, and analytics.
The solution helps teams find information faster, reduce repetitive research, improve answer consistency, and build scalable AI-powered knowledge systems.