From 1c32d60a5609c02732da4c84b09d7aaed53e684b Mon Sep 17 00:00:00 2001
From: mcDandy <danda.martinek@gmail.com>
Date: Tue, 24 Feb 2026 20:13:19 +0100
Subject: [PATCH] add string support to []

---
 more_math/Parser/UnifiedMathVisitor.py | 37 ++++++++++++++++++++++++--
 1 file changed, 35 insertions(+), 2 deletions(-)

diff --git a/more_math/Parser/UnifiedMathVisitor.py b/more_math/Parser/UnifiedMathVisitor.py
index 8369871..9dbcad8 100644
--- a/more_math/Parser/UnifiedMathVisitor.py
+++ b/more_math/Parser/UnifiedMathVisitor.py
@@ -248,6 +248,26 @@ class UnifiedMathVisitor(MathExprVisitor):
 
         # Use standard PyTorch/list indexing
         if self._is_tensor(val):
+            if len(indices) > val.ndim:
+                raise ValueError(f"{ctx.start.line}:{ctx.start.column}: Expacted up to {val.ndim} dimensions but got {indices}.")
+
+            for dim, idx in enumerate(indices):
+                if isinstance(idx, int):
+                    size = val.shape[dim]
+                    if idx < 0 or idx >= size:
+                        raise ValueError(
+                            f"{ctx.start.line}:{ctx.start.column}: Index {idx} out of bounds for dimension {dim} with size {size}"
+                        )
+                else:
+                    idx_tensor = idx
+                    if self._is_tensor(idx_tensor):
+                        if idx_tensor.numel() == 0:
+                            raise ValueError(f"{ctx.start.line}:{ctx.start.column}: Empty tensor for dimension {dim}")
+                        if torch.any(idx_tensor < 0) or torch.any(idx_tensor >= val.shape[dim]):
+                            raise ValueError(
+                                f"{ctx.start.line}:{ctx.start.column}: Index out of bounds for dimension {dim} with size {val.shape[dim]}"
+                            )
+
             idx_tuple = tuple(indices)
             result = val[idx_tuple]
             if self._is_tensor(result):
@@ -255,17 +275,30 @@ class UnifiedMathVisitor(MathExprVisitor):
                     return result.item()
                 return result.contiguous()
             return result
+            current = val
+            for idx in indices:
+                if isinstance(idx, torch.Tensor):
+                    if idx.numel() != 1:
+                        raise ValueError(f"{ctx.start.line}:{ctx.start.column}: Too many indecies for string with 1 dimension. Got {idx.numel()}")
+                    idx = int(idx.flatten()[0].item())
+                if idx >= len(current) or idx < 0:
+                    raise ValueError(f"{ctx.start.line}:{ctx.start.column}: Index {idx} out of bounds for string of length {len(current)}")
+                current = current[idx]
+            return current
         elif self._is_list(val):
             # Navigate through nested lists
             current = val
             for idx in indices:
                 if isinstance(idx, torch.Tensor):
+                    if idx.numel() != 1:
+                        raise ValueError(f"{ctx.start.line}:{ctx.start.column}: List index must be a scalar. Got tensor with length of {idx.numel()}")
                     idx = int(idx.item())
+                if idx >= len(current) or idx < 0:
+                    raise ValueError(f"{ctx.start.line}:{ctx.start.column}: Index {idx} out of bounds for list of length {len(current)}")
                 current = current[idx]
             return current
-
         error_prefix = f"{ctx.start.line}:{ctx.start.column}:"
-        raise ValueError(f"{error_prefix} Indexing only supported on tensors and lists (found {type(val).__name__})")
+        raise ValueError(f"{error_prefix} Indexing only supported on tensors, lists, and strings (found {type(val).__name__})")
 
     def visitToAtom(self, ctx):
         return (yield ctx.atom())