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Update app.py
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app.py
CHANGED
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@@ -11,7 +11,6 @@ import math
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import random
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from typing import Literal
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# Below is an example of a tool that does nothing. Amaze us with your creativity !
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import math
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import random
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from typing import Literal
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@@ -22,7 +21,6 @@ def get_approximate_integral(
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expr: str,
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a: float,
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b: float,
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method: Literal["auto", "simpson", "montecarlo"] = "auto",
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samples: int = 1000
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) -> str:
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"""Approximate the definite integral of a function over [a, b].
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@@ -42,24 +40,6 @@ def get_approximate_integral(
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def f(x):
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return eval(code, {"__builtins__": {}}, {"x": x, "math": math})
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# Auto‑choose method by sampling curvature
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if method == "auto":
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mid = (a + b) / 2
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# estimate curvature via second finite difference
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f0, f1, f2 = f(a), f(mid), f(b)
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curvature = abs((f0 - 2*f1 + f2) / ((b - a)/2)**2)
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method = "montecarlo" if curvature > 1e3 else "simpson"
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if method == "simpson":
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n = samples if samples % 2 == 0 else samples + 1
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h = (b - a) / n
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total = f(a) + f(b)
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for i in range(1, n):
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weight = 4 if i % 2 else 2
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total += weight * f(a + i * h)
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result = total * h / 3
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return f'{{"value": {result}, "method": "simpson", "panels": {n}}}'
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-
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# Monte Carlo fallback
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inside = 0.0
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for _ in range(samples):
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import random
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from typing import Literal
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import math
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import random
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from typing import Literal
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expr: str,
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a: float,
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b: float,
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samples: int = 1000
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) -> str:
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"""Approximate the definite integral of a function over [a, b].
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def f(x):
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return eval(code, {"__builtins__": {}}, {"x": x, "math": math})
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# Monte Carlo fallback
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inside = 0.0
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for _ in range(samples):
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