app.py

import gradio as gr
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
from fastapi.responses import JSONResponse

# Import semua fungsi dari sentiment_api
from sentiment_api import analyze_sentiment, load_model, model_loaded

# Create FastAPI app
app = FastAPI(
    title="Indonesian Sentiment Analysis API",
    description="API untuk analisis sentimen bahasa Indonesia dengan dukungan bahasa gaul",
    version="1.0.0"
)

# Add CORS middleware
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

class TextRequest(BaseModel):
    text: str

# FastAPI endpoints
@app.get("/")
async def root():
    return {
        "message": "Indonesian Sentiment Analysis API",
        "version": "1.0.0",
        "docs": "/docs",
        "model_loaded": model_loaded,
        "status": "🎉 Ready!"
    }

@app.get("/health")
async def health_check():
    return {
        "status": "healthy",
        "model_loaded": model_loaded,
        "ready": True
    }

@app.post("/predict")
async def predict_api(req: TextRequest):
    """API endpoint untuk analisis sentimen"""
    try:
        stars = analyze_sentiment(req.text)
        return JSONResponse(content={"stars": stars})
    except Exception as e:
        return JSONResponse(
            status_code=500,
            content={"error": str(e), "stars": 3}
        )

# Gradio interface function
def predict_gradio(text):
    """Function untuk Gradio interface"""
    if not text.strip():
        return "❌ Mohon masukkan teks terlebih dahulu"
    
    try:
        stars = analyze_sentiment(text)
        
        if stars == 5:
            return f"⭐⭐⭐⭐⭐ ({stars}/5) - Sangat Positif!"
        elif stars == 4:
            return f"⭐⭐⭐⭐ ({stars}/5) - Positif"
        elif stars == 3:
            return f"⭐⭐⭐ ({stars}/5) - Netral"
        elif stars == 2:
            return f"⭐⭐ ({stars}/5) - Negatif"
        else:
            return f"⭐ ({stars}/5) - Sangat Negatif"
            
    except Exception as e:
        return f"❌ Error: {str(e)}"

# Create Gradio interface
demo = gr.Interface(
    fn=predict_gradio,
    inputs=gr.Textbox(
        label="📝 Masukkan teks bahasa Indonesia", 
        placeholder="Contoh: gue seneng banget hari ini",
        lines=3
    ),
    outputs=gr.Textbox(label="🎭 Hasil Analisis Sentimen"),
    title="🎭 Indonesian Sentiment Analysis",
    description="""
    **API analisis sentimen bahasa Indonesia dengan dukungan bahasa gaul menggunakan IndoBERT**
    
    🎯 **API Endpoints:**
    - `POST /predict` - Analisis sentimen (JSON: {"text": "your text"})
    - `GET /` - Info API
    - `GET /health` - Health check
    - `GET /docs` - API documentation
    
    📊 **Response:** `{"stars": 1-5}`
    """,
    examples=[
        ["gue seneng banget hari ini"],
        ["capek bgt tapi gak stress"],
        ["anjay mantul banget dah"],
        ["lagi gabut nih, bosen"],
        ["bahagia banget sama hasil ini"]
    ]
)

# Mount Gradio on FastAPI
app = gr.mount_gradio_app(app, demo, path="/")

if __name__ == "__main__":
    demo.launch()