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```python
# AI Dev Tool: FastAPI Pydantic v2 Micro-SaaS Boilerplate with Automatic Bird Identification System
# =============================================================================================
# This is a production-ready boilerplate for building micro-SaaS applications with FastAPI and Pydantic v2.
# It includes an automatic bird identification system using computer vision and machine learning.

import os
import cv2
import numpy as np
from fastapi import FastAPI, UploadFile, File
from pydantic import BaseModel
from typing import List
from PIL import Image
from tensorflow.keras.models import load_model

# Load the bird identification model
model = load_model('bird_identification_model.h5')

app = FastAPI()

# Define the request body model for the bird identification endpoint
class BirdIdentificationRequest(BaseModel):
    image: UploadFile = File(...)

# Define the response model for the bird identification endpoint
class BirdIdentificationResponse(BaseModel):
    bird_species: str
    confidence: float

# Define the endpoint for bird identification
@app.post("/identify_bird", response_model=BirdIdentificationResponse)
async def identify_bird(request: BirdIdentificationRequest):
    """
    Identify the bird species in the uploaded image.

Args:
    request (BirdIdentificationRequest): The request body

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