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title: Simple Chatbot
emoji: π€
colorFrom: indigo
colorTo: purple
sdk: docker
app_port: 7860
pinned: false
---
# π€ Simple Chatbot
A sleek, real-time AI chatbot built with **FastAPI** and vanilla **HTML/CSS/JS**, powered by [OpenRouter](https://openrouter.ai/) for free access to various AI models.



---
## β¨ Features
| Feature | Description |
|---------|-------------|
| π **Streaming Responses** | AI replies appear in real-time, token by token β no waiting for the full response |
| π¬ **Conversation Memory** | Full chat history is maintained within a session so the AI remembers context |
| π¨ **Premium Dark UI** | Glassmorphism design with ambient gradient blobs and smooth animations |
| β‘ **Quick Suggestions** | Clickable prompt starters on the welcome screen to get started fast |
| π **Markdown Rendering** | Supports bold, italic, inline code, and code blocks in responses |
| π± **Responsive Design** | Works beautifully on desktop and mobile screens |
| π **New Chat** | One-click reset to clear history and start fresh |
---
## π Project Structure
```
Simple Chatbot/
βββ main.py # FastAPI backend β API routes & OpenRouter integration
βββ static/
β βββ index.html # Frontend HTML β chat UI layout
β βββ style.css # Styling β dark theme, glassmorphism, animations
β βββ script.js # Frontend logic β streaming, history, markdown
βββ .env # Environment variables (API key)
βββ pyproject.toml # Python project config & dependencies
βββ uv.lock # Dependency lock file
βββ README.md # You are here!
```
---
## π Getting Started
### Prerequisites
- **Python 3.13+** installed
- **[uv](https://docs.astral.sh/uv/)** package manager (recommended) or `pip`
- An **OpenRouter API key** β get one free at [openrouter.ai/keys](https://openrouter.ai/keys)
### 1. Clone the Repository
```bash
git clone <your-repo-url>
cd "Simple Chatbot"
```
### 2. Set Up Environment Variables
Create a `.env` file in the project root:
```env
OPENROUTER_API_KEY=sk-or-v1-your-api-key-here
```
> β οΈ **Never commit your `.env` file to version control.** It's already in `.gitignore`.
### 3. Install Dependencies
**Using uv (recommended):**
```bash
uv sync
```
**Using pip:**
```bash
pip install fastapi uvicorn openai python-dotenv
```
### 4. Run the Server
```bash
uv run python -m uvicorn main:app --reload --port 8000
```
### 5. Open the Chatbot
Navigate to **[http://127.0.0.1:8000](http://127.0.0.1:8000)** in your browser. That's it! π
---
## π§ How It Works
### Architecture Overview
```
ββββββββββββββββ POST /api/chat ββββββββββββββββ Stream ββββββββββββββββ
β β ββββββββββββββββββββββββββββΊ β β ββββββββββββββββΊ β β
β Browser β { messages: [...] } β FastAPI β completions β OpenRouter β
β (Frontend) β ββββββββββββββββββββββββββ β (Backend) β ββββββββββββββ β (AI API) β
β β Streaming text chunks β β SSE chunks β β
ββββββββββββββββ ββββββββββββββββ ββββββββββββββββ
```
### Step-by-Step Flow
1. **User types a message** in the textarea and hits Enter (or clicks send)
2. **Frontend** appends the message to the local `conversationHistory` array
3. **Frontend sends** the full conversation history to `POST /api/chat`
4. **Backend** forwards the messages to OpenRouter's API with `stream=True`
5. **Backend streams** each text chunk back to the frontend as it arrives
6. **Frontend renders** each chunk in real-time with a blinking cursor animation
7. **Assistant response** is saved to `conversationHistory` for context in future messages
### API Endpoint
#### `POST /api/chat`
Streams a chat completion from the AI model.
**Request Body:**
```json
{
"messages": [
{ "role": "user", "content": "Hello, who are you?" },
{ "role": "assistant", "content": "I'm an AI assistant..." },
{ "role": "user", "content": "Tell me a joke" }
]
}
```
**Response:** `text/plain` streamed response (chunked transfer encoding)
---
## π§ Memory & Context
The chatbot maintains **in-session memory**:
- β
**Within a session** β the AI remembers everything you've said
- β **Across page refreshes** β memory is lost (stored in browser JS only)
- β **Across sessions** β no database persistence
The full conversation history is sent with every request, so the AI model has complete context to generate relevant responses.
---
## βοΈ Configuration
### Changing the AI Model
In `main.py`, modify the `model` parameter:
```python
stream = client.chat.completions.create(
model="openrouter/free", # β Change this
messages=[m.model_dump() for m in request.messages],
stream=True,
)
```
**Popular free models on OpenRouter:**
| Model | ID |
|-------|----|
| Auto (free tier) | `openrouter/free` |
| Gemma 3 | `google/gemma-3-27b-it:free` |
| Llama 4 Scout | `meta-llama/llama-4-scout:free` |
| Mistral Small | `mistralai/mistral-small-3.1-24b-instruct:free` |
Browse all models at [openrouter.ai/models](https://openrouter.ai/models).
### Changing the Port
```bash
uv run python -m uvicorn main:app --reload --port 3000
```
---
## π¦ Dependencies
| Package | Purpose |
|---------|---------|
| `fastapi` | Web framework for the API server |
| `uvicorn` | ASGI server to run FastAPI |
| `openai` | OpenAI-compatible client (works with OpenRouter) |
| `python-dotenv` | Loads `.env` variables into the environment |
---
## π οΈ Development
### Hot Reload
The server runs with `--reload`, so any changes to Python files will auto-restart the server. For frontend changes (HTML/CSS/JS), just refresh the browser.
### Project Dependencies
All dependencies are managed via `pyproject.toml` and locked in `uv.lock`. To add a new package:
```bash
uv add <package-name>
```
---
## βοΈ Deploying to Hugging Face Spaces
You can deploy this chatbot for free on [Hugging Face Spaces](https://huggingface.co/spaces) using Docker.
### 1. Create a Hugging Face Account
Sign up at [huggingface.co/join](https://huggingface.co/join) if you don't have an account.
### 2. Create a New Space
1. Go to [huggingface.co/new-space](https://huggingface.co/new-space)
2. Fill in:
- **Space name:** `simple-chatbot`
- **SDK:** Select **Docker**
- **Visibility:** Public or Private
3. Click **Create Space**
### 3. Set Your API Key as a Secret
> β οΈ **Do NOT push your `.env` file.** Use Space Secrets instead.
1. In your Space, go to **Settings** β **Variables and secrets**
2. Click **New secret**
3. Set:
- **Name:** `OPENROUTER_API_KEY`
- **Value:** Your OpenRouter API key
4. Save β HF automatically injects secrets as environment variables
### 4. Push Your Code
**Option A β Add HF as a remote (recommended if you already have a git repo):**
```bash
git remote add hf https://huggingface.co/spaces/YOUR_USERNAME/simple-chatbot
git push hf main
```
**Option B β Clone and copy:**
```bash
git clone https://huggingface.co/spaces/YOUR_USERNAME/simple-chatbot
# Copy your project files into the cloned repo
cd simple-chatbot
git add .
git commit -m "Initial deployment"
git push
```
> π‘ Replace `YOUR_USERNAME` with your Hugging Face username.
### 5. Wait for Build & Go Live
1. Visit `https://huggingface.co/spaces/YOUR_USERNAME/simple-chatbot`
2. Watch the build logs under the **"Building"** status badge
3. Once it shows **"Running"**, your chatbot is live at:
```
https://YOUR_USERNAME-simple-chatbot.hf.space
```
### Troubleshooting
| Issue | Fix |
|-------|-----|
| Build fails on `requirements.txt` | Make sure the file is committed and not in `.dockerignore` |
| "API key not found" crash | Verify the secret name is exactly `OPENROUTER_API_KEY` in Space Settings |
| Port mismatch error | Ensure `app_port: 7860` in README frontmatter matches `EXPOSE 7860` in Dockerfile |
| Space is sleeping | Free Spaces sleep after inactivity β visit the URL to wake it, or upgrade for persistent uptime |
---
## π License
This project is open source and available under the [MIT License](LICENSE).
---
## π Acknowledgments
- [OpenRouter](https://openrouter.ai/) β Free AI model access
- [FastAPI](https://fastapi.tiangolo.com/) β Modern Python web framework
- [Inter Font](https://rsms.me/inter/) β Clean UI typography
|