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I will develop custom ai chatbot, rag app, and streamlit web app
Muhammad Umer
Acerca de este Servicio
Looking for a premium, production-ready AI interface instead of default, boring templates? You are at the right place!
I specialize in building stunning, modern, and highly responsive Full-Stack AI Chatbots and Web Applications using Streamlit and Python. Whether you need a medical assistant, financial dashboard, or custom LLM deployment, I deliver enterprise-grade UI/UX.
WHAT THIS GIG OFFERS:
Premium SaaS-Style Custom Theme (Dark/Light Mode)
Advanced Session State Management (Flawless conversational flow)
High-Contrast & Modern Typography (WCAG AA Compliant)
Clean Navigation Bars, Custom Sidebars & Real-time Analytics
Integration Ready: LLaMA 3.3, OpenAI, Gemini, LangChain, or custom REST APIs
️ TECH STACK:
Python, Streamlit, FastAPI, LangChain, Custom CSS/HTML Overrides.
Why Choose Me?
- Clean, modular, and error-free code
- Zero hardcoded dependencies for smooth server deployments
- 100% Client Satisfaction with premium visual presentation
Please message me before placing an order so we can map out your structural requirements perfectly!
Conoce a Muhammad Umer
Muhammad Umer
AI ML Engineer LLMs RAG Systems
- DePakistán
- Miembro desdeabr 2026
Idiomas
Inglés, Urdu
AI/ML Engineer specializing in LLM-powered applications,
RAG systems, and end-to-end ML pipelines.
What I deliver:
🤖 LLM Chatbots — Groq, OpenAI, LLaMA integration
📚 RAG Systems — PDF chatbots, semantic search, Chroma
🏥 Health & Domain-Specific AI assistants
📊 ML Pipelines — classification, regression, prediction
🔍 NLP — intent classification, BERT fine-tuning
⚡ FastAPI + Streamlit deployment
Stack: Python, LangChain, Groq API, HuggingFace,
scikit-learn, FastAPI, Streamlit, pandas, SQL
Production-ready code with clean documentation.
Let's build your AI solution.
Otros servicios de Desarrollo de IA que ofrezco
FAQ
Question: What web frameworks and languages do you use to build the apps?
Answer: I build the entire frontend interface using Streamlit (Python web framework) and custom CSS injectors. For premium production architecture, I decouple the app by connecting it with a FastAPI core backend engine.
Question: Can you connect the interface with OpenAI, Gemini, or local LLMs?
Answer: Yes, absolutely! The codebase is completely integration-ready. I can securely link your custom Streamlit interface with external APIs (OpenAI, Gemini, Claude) or local engines like Ollama using Python requests and environment variables.
Question: Will I receive the complete source code of the Python application?
Answer: Yes, 100%! I will deliver the fully functional, clean, and modular Python files (.py) along with the necessary requirements file so you can easily deploy it on any server or Streamlit Cloud.
