---
title: SimpleChatbot
emoji: 🤖
colorFrom: purple
colorTo: pink
sdk: streamlit
sdk_version: 1.31.1
app_file: app.py
pinned: false
license: mit
models:
  - openai/gpt-oss-120b
  - mistralai/Mistral-7B-Instruct-v0.2
  - google/gemma-3-27b-it
  - google/gemma-2-27b-it
  - google/gemma-2-9b-it
  - google/gemma-2-2b-it
  - HuggingFaceH4/zephyr-7b-gemma-v0.1
  - HuggingFaceH4/zephyr-7b-beta
  - meta-llama/Meta-Llama-3-8B-Instruct
  - meta-llama/Meta-Llama-3.1-8B-Instruct
  - deepseek-ai/DeepSeek-R1-Distill-Llama-70B
  - Qwen/Qwen2.5-Coder-32B-Instruct
  - moonshotai/Kimi-K2-Instruct

---

# 🤖 SimpleChatbot

[![Streamlit](https://img.shields.io/badge/Built%20with-Streamlit-FF4B4B?logo=streamlit&logoColor=white)](https://streamlit.io/)
[![Hugging Face Space](https://img.shields.io/badge/Hugging%20Face-Space-yellow?logo=huggingface)](https://huggingface.co/spaces)
[![Python](https://img.shields.io/badge/Python-3.9%2B-blue?logo=python&logoColor=white)](https://www.python.org/)
[![Open Source](https://img.shields.io/badge/Open%20Source-Yes-green)]()

**SimpleChatbot** is a lightweight Streamlit app that lets you chat with multiple large language models (LLMs) from a single interface. It’s built as a simple, interactive way to explore and compare different models without switching tools or setups.

---

## ✨ Features

- Chat with **multiple LLMs** from one UI  
- Switch models on the fly (conversation resets automatically)
- Adjustable **temperature** for response creativity
- Built-in **rate limiting & cooldowns** for fair usage
- Optional **Hugging Face access token** support
- Session-based logging and usage tracking
- Clean, minimal Streamlit interface

---

## 🧠 Supported Models

This app supports a mix of general-purpose, reasoning, and coding-focused models, including:

- OpenAI GPT-OSS-120B  
- Meta Llama 3 / 3.1  
- Google Gemma (2 & 3 series)  
- DeepSeek R1 (distilled)  
- Qwen 2.5 Coder  
- Kimi-K2 Instruct  
- Zephyr & Mistral variants  

> Available models may change depending on backend availability.

---

## 🎯 Why This Exists

This project was built to:

- **Quickly compare LLM behavior** across different model families  
- Provide a **simple reference implementation** for multi-model chat apps  
- Demonstrate how to build a Streamlit chatbot using modern inference APIs  
- Serve as a lightweight demo for experimentation, education, and prototyping  

It intentionally avoids complex agent logic or tooling to keep the focus on **model responses and UX**.

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## 🚀 How to Use

1. Select a **model client** in the sidebar  
2. Choose a **model**  
3. Adjust the **temperature** if desired  
4. Start chatting!

Responses are intentionally kept brief to keep interactions fast and readable.

---

## ⚠️ Notes

- Generated content may be **inaccurate or incorrect**
- API calls are limited per session to prevent abuse
- If a model fails, it may be temporarily unavailable or updating

---

## 👤 Author

Created by **Nigel Gebodh**  
🌐 https://ngebodh.github.io/

Learn how to build this chatbot yourself:  
👉 https://ngebodh.github.io/projects/2024-03-05/