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English
$
USD
I will develop custom ai chatbot, rag app, and streamlit web app
Muhammad Umer
About this gig
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!
Get to know Muhammad Umer
Muhammad Umer
AI ML Engineer LLMs RAG Systems
- FromPakistan
- Member sinceApr 2026
- Avg. response time3 hours
Languages
English, 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.
Other AI Development Services I Offer
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.
