Ready for Hugging Face Spaces deployment

README.md

@@ -0,0 +1,97 @@
+# 💖 Pickup Line Generator
+
+A modern web application that generates fun, clever, or cringey pickup lines using the SmolLM-135M model. Built with Next.js and Hugging Face's Inference API.
+
+## 🌟 Features
+
+- Generate pickup lines with different vibes:
+  - 💝 Romantic
+  - 😏 Cheesy
+  - 🔬 Nerdy
+  - 😂 Cringe
+  - 💋 Flirty
+- Modern, responsive UI with beautiful animations
+- One-click copy to clipboard
+- Powered by SmolLM-135M model
+
+## 🛠️ Tech Stack
+
+- **Frontend**: Next.js 13+ with App Router
+- **Styling**: TailwindCSS
+- **Model**: SmolLM-135M (via Hugging Face Inference API)
+
+## 🚀 Getting Started
+
+### Prerequisites
+
+- Node.js 18+
+- Python 3.8+
+
+### Installation
+
+1. Clone the repository:
+```bash
+git clone <your-repo-url>
+cd pickup-line-generator
+```
+
+2. Install dependencies:
+```bash
+npm install
+```
+
+3. Run the development server:
+```bash
+npm run dev
+```
+
+Visit `http://localhost:3000` to see the application.
+
+## 🌐 Deployment to Hugging Face Spaces
+
+1. Push your code to GitHub
+2. Create a new Space on Hugging Face:
+   - Choose "Next.js" as the SDK
+   - Connect your GitHub repository
+   - The environment variables are already configured in the repository
+
+The application will automatically build and deploy.
+
+## 📁 Project Structure
+
+```
+pickup-line-generator/
+├── app/
+│   ├── page.tsx           # Main page component
+│   ├── layout.tsx         # Root layout
+│   ├── globals.css        # Global styles
+│   └── api/
+│       └── generate/      # API route for generation
+│           └── route.ts
+├── lib/
+│   └── model.ts          # Model integration
+└── public/               # Static assets
+```
+
+## 🎯 Example Pickup Lines
+
+Here are some examples of what the generator can create:
+
+- 💝 **Romantic**: "Are you a magician? Because whenever I look at you, everyone else disappears."
+- 🔬 **Nerdy**: "Are you made of copper and tellurium? Because you're Cu-Te!"
+- 😏 **Cheesy**: "Are you a parking ticket? Because you've got FINE written all over you!"
+- 😂 **Cringe**: "Are you a dictionary? Because you're adding meaning to my life!"
+- 💋 **Flirty**: "Is your name Google? Because you've got everything I've been searching for!"
+
+## 🤝 Contributing
+
+Contributions are welcome! Please feel free to submit a Pull Request.
+
+## 📝 License
+
+This project is licensed under the MIT License - see the LICENSE file for details.
+
+## 🙏 Acknowledgments
+
+- Built using SmolLM by Hugging Face
+- Deployed on Hugging Face Spaces 

model_server.py

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+from fastapi import FastAPI, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+app = FastAPI()
+
+# Add CORS middleware
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # In production, replace with your Vercel domain
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Load model and tokenizer
+print("Loading SmolLM-135M model...")
+MODEL_NAME = "HuggingFaceTB/SmolLM-135M"
+
+# Check for CUDA availability
+device = "cuda" if torch.cuda.is_available() else "cpu"
+print(f"Using device: {device}")
+
+# Load the model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+tokenizer.pad_token = tokenizer.eos_token
+model = AutoModelForCausalLM.from_pretrained(MODEL_NAME).to(device)
+
+print(f"Model loaded successfully! Memory footprint: {model.get_memory_footprint() / 1e6:.2f} MB")
+
+class VibeRequest(BaseModel):
+    vibe: str
+
+def get_vibe_guidance(vibe: str) -> str:
+    """Get specific guidance for each vibe with examples"""
+    vibe_patterns = {
+        "romantic": """Generate a romantic and sweet pickup line that's genuine and heartfelt.
+Example: 
+Input: Generate a romantic pickup line
+Output: Are you a magician? Because whenever I look at you, everyone else disappears. ❤️
+
+Now generate a romantic pickup line: """,
+
+        "cheesy": """Generate a super cheesy and over-the-top pickup line.
+Example:
+Input: Generate a cheesy pickup line
+Output: Are you a parking ticket? Because you've got FINE written all over you! 😏
+
+Now generate a cheesy pickup line: """,
+
+        "nerdy": """Generate a nerdy, science-themed pickup line.
+Example:
+Input: Generate a nerdy pickup line
+Output: Are you made of copper and tellurium? Because you're Cu-Te! 🔬
+
+Now generate a nerdy pickup line: """,
+
+        "cringe": """Generate the most cringey and over-the-top pickup line imaginable.
+Example:
+Input: Generate a cringe pickup line
+Output: Are you a dictionary? Because you're adding meaning to my life! 📚
+
+Now generate a cringe pickup line: """,
+
+        "flirty": """Generate a bold and flirty pickup line.
+Example:
+Input: Generate a flirty pickup line
+Output: Is your name Google? Because you've got everything I've been searching for! 😏
+
+Now generate a flirty pickup line: """
+    }
+    return vibe_patterns.get(vibe, "Generate a pickup line with a ")
+
+@app.post("/generate")
+async def generate_pickup_line(request: VibeRequest):
+    try:
+        vibe = request.vibe
+        vibe_guide = get_vibe_guidance(vibe)
+        
+        # Create the prompt
+        prompt = f"""Instructions: Generate a pickup line with a {vibe} vibe.
+{vibe_guide}"""
+        
+        # Prepare inputs
+        encoded_input = tokenizer.encode_plus(
+            prompt,
+            return_tensors="pt",
+            padding=True,
+            return_attention_mask=True
+        )
+        input_ids = encoded_input["input_ids"].to(device)
+        attention_mask = encoded_input["attention_mask"].to(device)
+        
+        # Generate response
+        with torch.no_grad():
+            outputs = model.generate(
+                input_ids,
+                attention_mask=attention_mask,
+                max_new_tokens=100,
+                do_sample=True,
+                temperature=0.8,
+                top_p=0.92,
+                top_k=50,
+                pad_token_id=tokenizer.eos_token_id,
+                eos_token_id=tokenizer.eos_token_id,
+            )
+        
+        # Get the full generated text
+        full_response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+        
+        # Extract just the pickup line
+        if full_response.startswith(prompt):
+            response = full_response[len(prompt):].strip()
+        else:
+            response = full_response.replace(prompt, "").strip()
+        
+        # Clean up the response
+        for marker in ["Instructions:", "Generate a pickup line:", "\n"]:
+            if marker in response:
+                response = response.split(marker, 1)[0].strip()
+        
+        # Add appropriate emoji based on vibe
+        if vibe == "romantic":
+            response += " ❤️"
+        elif vibe == "cheesy":
+            response += " 😏"
+        elif vibe == "nerdy":
+            response += " 🔬"
+        elif vibe == "cringe":
+            response += " 😂"
+        elif vibe == "flirty":
+            response += " 💋"
+        
+        return {"pickupLine": response}
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8000) 

pickup-line-generator/.gitignore

@@ -22,12 +22,10 @@ npm-debug.log*
 yarn-debug.log*
 yarn-error.log*
 
-# local env files
-.env*.local
+# environment variables
 .env
-
-# vercel
-.vercel
+.env.*
+!.env.example
 
 # typescript
 *.tsbuildinfo
@@ -48,7 +46,7 @@ next-env.d.ts
 ehthumbs.db
 Thumbs.db
 
-# Python virtual environment (if you're using Python for the model)
+# Python virtual environment
 venv/
 env/
 ENV/
@@ -80,9 +78,4 @@ logs
 *.tgz
 
 # Yarn Integrity file
-.yarn-integrity
-
-# dotenv environment variable files
-.env.development.local
-.env.test.local
-.env.production.local 
+.yarn-integrity 

pickup-line-generator/app/api/generate/route.ts

@@ -1,26 +1,21 @@
 import { NextResponse } from 'next/server';
+import { generatePickupLine } from '@/lib/model';
 
 export async function POST(request: Request) {
   try {
-    const body = await request.json();
+    const { vibe } = await request.json();
     
-    // Forward the request to our model server
-    const response = await fetch(`${process.env.NEXT_PUBLIC_API_URL}/generate`, {
-      method: 'POST',
-      headers: {
-        'Content-Type': 'application/json',
-      },
-      body: JSON.stringify(body),
-    });
-
-    if (!response.ok) {
-      throw new Error('Failed to generate pickup line');
+    if (!vibe) {
+      return NextResponse.json(
+        { error: 'Vibe is required' },
+        { status: 400 }
+      );
     }
 
-    const data = await response.json();
-    return NextResponse.json(data);
+    const pickupLine = await generatePickupLine(vibe);
+    return NextResponse.json({ pickupLine });
   } catch (error) {
-    console.error('Error generating pickup line:', error);
+    console.error('Error:', error);
     return NextResponse.json(
       { error: 'Failed to generate pickup line' },
       { status: 500 }

pickup-line-generator/next.config.js

@@ -1,11 +1,6 @@
 /** @type {import('next').NextConfig} */
 const nextConfig = {
-  output: 'standalone',
-  reactStrictMode: true,
-  swcMinify: true,
-  experimental: {
-    serverActions: true,
-  },
+  output: 'standalone'
 }
 
 module.exports = nextConfig