Streamlit LangChain Chatbot
Real-Time AI Assistant with Streaming
Modern, responsive chatbot built with Streamlit and LangChain, powered by Google's Gemini AI. Features real-time streaming responses, 40+ model selection (Gemini 1.5, 2.0, 2.5), secure API key management, and a clean professional interface. Includes chat history tracking, dark/light theme toggle, and mobile-friendly responsive design.
Why it mattered
Streaming responses, model selection, chat history, and responsive UI
What shipped
Modern, responsive chatbot built with Streamlit and LangChain, powered by Google's Gemini AI. Features real-time streaming responses, 40+ model selection (Gemini 1.5, 2.0, 2.5), secure API key management, and a clean professional interface. Includes chat history tracking, dark/light theme toggle, and mobile-friendly responsive design.
Proof signal
Streaming responses, model selection, chat history, and responsive UI
System flow
API Configuration -> Model Selection -> Message Input -> Streaming Response -> Chat History -> UI Rendering.
Honest maturity snapshot
A workflow or idea that needed clearer structure, validation, and delivery.
A working product surface with defined features, links, and a reviewable case study.
Features
- Streamlit integrated into the workflow.
- LangChain integrated into the workflow.
- Gemini API integrated into the workflow.
- Python integrated into the workflow.
- API Configuration stage documented in the delivery flow.
- Model Selection stage documented in the delivery flow.
Engineering challenges
- Keeping the implementation clear enough to explain while still solving the core technical problem.
- Choosing a scope that could be shipped, tested, and documented.
- Turning technical work into proof a visitor can evaluate quickly.
Results
- Streaming responses, model selection, chat history, and responsive UI
- Documented the engineering path and important learnings.
- Made source code or technical proof available for review.
What I learned
- Tradeoff learned: Keeping the implementation clear enough to explain while still solving the core technical problem.
- Proof learned: Streaming responses, model selection, chat history, and responsive UI
- Next iteration: Add richer screenshots or a narrated demo.