chore: import upstream snapshot with attribution

examples/flows/standard/maths-to-code/code_refine.py

@@ -0,0 +1,58 @@
+from promptflow.core import tool
+import ast
+import json
+
+
+def infinite_loop_check(code_snippet):
+    tree = ast.parse(code_snippet)
+    for node in ast.walk(tree):
+        if isinstance(node, ast.While):
+            if not node.orelse:
+                return True
+    return False
+
+
+def syntax_error_check(code_snippet):
+    try:
+        ast.parse(code_snippet)
+    except SyntaxError:
+        return True
+    return False
+
+
+def error_fix(code_snippet):
+    tree = ast.parse(code_snippet)
+    for node in ast.walk(tree):
+        if isinstance(node, ast.While):
+            if not node.orelse:
+                node.orelse = [ast.Pass()]
+    return ast.unparse(tree)
+
+
+@tool
+def code_refine(original_code: str) -> str:
+
+    try:
+        original_code = json.loads(original_code)["code"]
+        fixed_code = None
+
+        if infinite_loop_check(original_code):
+            fixed_code = error_fix(original_code)
+        else:
+            fixed_code = original_code
+
+        if syntax_error_check(fixed_code):
+            fixed_code = error_fix(fixed_code)
+
+        return fixed_code
+    except json.JSONDecodeError:
+        return "JSONDecodeError"
+    except Exception as e:
+        return "Unknown Error:" + str(e)
+
+
+if __name__ == "__main__":
+    code = "{\n    \"code\": \"distance_A = 10 * 0.5\\ndistance_B = 15 * t\\n\\n\
+        equation: distance_A = distance_B\\n\\n\10 * 0.5 = 15 * t\\n\\nt = (10 * 0.5) / 15\\n\\nprint(t)\"\n}"
+    code_refine = code_refine(code)
+    print(code_refine)