Sure! To generate test cases for the given problem statement, we need to carefully construct the test cases such that they follow the constraints and edge cases specified in the problem. Here's a Python function to generate test cases for this problem:

```python
import random

def tcgen():
    # Constraints
    N = random.randint(1, 70)
    K = random.randint(1, 70)
    
    s = ''.join(random.choice(['r', 'b']) for _ in range(K))
    
    return N, K, s

def format_test_case(N, K, s):
    return f"{N} {K}\n{s}"

# Example usage
if __name__ == "__main__":
    for _ in range(5):  # Generate 5 test cases
        N, K, s = tcgen()
        test_case = format_test_case(N, K, s)
        print(test_case)
        print()
```

### Explanation:
1. **Constraints:**
    - Generate \(N\) between 1 and 70.
    - Generate \(K\) between 1 and 70.
    - Create a string \(s\) of length \(K\), consisting of 'r' and 'b' characters.

2. **Random Generation:**
    - Use `random.randint` to generate random values for \(N\) and \(K\) within their respective ranges.
    - Use `random.choice` to randomly select characters 'r' or 'b' to form the string \(s\).

3. **Formatting:**
    - The `format_test_case` function formats the test case in the required input format.

4. **Example Usage:**
    - Generate and print 5 test cases as examples.

This test case generator will create random test cases within the problem's constraints, ensuring a variety of inputs for robust testing.