app.py

from fastapi import FastAPI
from pydantic import BaseModel
import easyocr
import base64
import io
from PIL import Image
import numpy as np

app = FastAPI()

# Load the AI model into memory (runs once on startup)
print("Loading EasyOCR Model...")
reader = easyocr.Reader(['en'])
print("Model Loaded!")

class ImageData(BaseModel):
    image: str

@app.post("/solve")
def solve_captcha(data: ImageData):
    try:
        # 1. Clean the base64 string and decode it
        base64_data = data.image.split(",")[1] if "," in data.image else data.image
        img_bytes = base64.b64decode(base64_data)
        
        # 2. Convert to an image the AI can read
        img = Image.open(io.BytesIO(img_bytes)).convert("RGB")
        img_np = np.array(img)
        
        # 3. Let EasyOCR read it!
        results = reader.readtext(img_np, detail=0)
        text = "".join(results)
        
        # 4. Clean up the text (keep only letters and numbers)
        cleaned = "".join(e for e in text if e.isalnum()).lower()
        
        return {"text": cleaned}
    
    except Exception as e:
        return {"error": str(e)}