We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Create a way to add your own arm model[FEATURE]
## User Story

<!-- A clear and concise description of what the problem is. 
I want to add my own arm configuration to the list of pre-trained models.

## Potential Solutions

<!-- A clear and concise description of what you want to happen. -->
If there was a comment next to each line of one of the arrays containing the pre-trained model saying what exactly each value was supposed to represent, that would help.
<!-- A clear and concise description of any alternative solutions or features you've considered. -->
I tried looking at the spec sheets of the arms and matching up values but I couldn't figure much out. 



--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `pybotics/predefined_models.py`
Content:
```
1 """Predefined robot models."""
2 import numpy as np  # type: ignore
3 
4 
5 def kuka_lbr_iiwa_7() -> np.ndarray:  # pragma: no cover
6     """Get KUKA LBR iiwa 7 MDH model."""
7     return np.array(
8         [
9             [0, 0, 0, 340],
10             [-np.pi / 2, 0, 0, 0],
11             [np.pi / 2, 0, 0, 400],
12             [np.pi / 2, 0, 0, 0],
13             [-np.pi / 2, 0, 0, 400],
14             [-np.pi / 2, 0, 0, 0],
15             [np.pi / 2, 0, 0, 126],
16         ]
17     )
18 
19 
20 def mecademic_meca500() -> np.ndarray:  # pragma: no cover
21     """Get Meca500 MDH model."""
22     return np.array(
23         [
24             [0, 0, 0, 135],
25             [-np.pi / 2, 0, -np.pi / 2, 0],
26             [0, 135, 0, 0],
27             [-np.pi / 2, 38, 0, 120],
28             [np.pi / 2, 0, 0, 0],
29             [-np.pi / 2, 0, np.pi, 72],
30         ]
31     )
32 
33 
34 def puma560() -> np.ndarray:  # pragma: no cover
35     """Get PUMA560 MDH model."""
36     return np.array(
37         [
38             [0, 0, 0, 0],
39             [-np.pi / 2, 0, 0, 0],
40             [0, 612.7, 0, 0],
41             [0, 571.6, 0, 163.9],
42             [-np.pi / 2, 0, 0, 115.7],
43             [np.pi / 2, 0, np.pi, 92.2],
44         ]
45     )
46 
47 
48 def ur10() -> np.ndarray:  # pragma: no cover
49     """Get UR10 MDH model."""
50     return np.array(
51         [
52             [0, 0, 0, 118],
53             [np.pi / 2, 0, np.pi, 0],
54             [0, 612.7, 0, 0],
55             [0, 571.6, 0, 163.9],
56             [-np.pi / 2, 0, 0, 115.7],
57             [np.pi / 2, 0, np.pi, 92.2],
58         ]
59     )
60 
61 
62 def abb_irb120() -> np.ndarray:  # pragma: no cover
63     """Get ABB irb120 MDH model."""
64     return np.array(
65         [
66             [0, 0, 0, 290],
67             [-np.pi / 2, 0, -np.pi / 2, 0],
68             [0, 270, 0, 0],
69             [-np.pi / 2, 70, 0, 302],
70             [np.pi / 2, 0, 0, 0],
71             [-np.pi / 2, 0, np.pi, 72],
72         ]
73     )
74
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/pybotics/predefined_models.py b/pybotics/predefined_models.py
--- a/pybotics/predefined_models.py
+++ b/pybotics/predefined_models.py
@@ -1,4 +1,8 @@
-"""Predefined robot models."""
+"""Predefined robot models.
+
+These models correspond to the Modified Denavit–Hartenberg parameters:
+https://en.wikipedia.org/wiki/Denavit%E2%80%93Hartenberg_parameters
+"""
 import numpy as np  # type: ignore

{"golden_diff": "diff --git a/pybotics/predefined_models.py b/pybotics/predefined_models.py\n--- a/pybotics/predefined_models.py\n+++ b/pybotics/predefined_models.py\n@@ -1,4 +1,8 @@\n-\"\"\"Predefined robot models.\"\"\"\n+\"\"\"Predefined robot models.\n+\n+These models correspond to the Modified Denavit\u2013Hartenberg parameters:\n+https://en.wikipedia.org/wiki/Denavit%E2%80%93Hartenberg_parameters\n+\"\"\"\n import numpy as np  # type: ignore\n", "issue": "Create a way to add your own arm model[FEATURE]\n## User Story\r\n\r\n<!-- A clear and concise description of what the problem is. \r\nI want to add my own arm configuration to the list of pre-trained models.\r\n\r\n## Potential Solutions\r\n\r\n<!-- A clear and concise description of what you want to happen. -->\r\nIf there was a comment next to each line of one of the arrays containing the pre-trained model saying what exactly each value was supposed to represent, that would help.\r\n<!-- A clear and concise description of any alternative solutions or features you've considered. -->\r\nI tried looking at the spec sheets of the arms and matching up values but I couldn't figure much out. \r\n\r\n\n", "before_files": [{"content": "\"\"\"Predefined robot models.\"\"\"\nimport numpy as np  # type: ignore\n\n\ndef kuka_lbr_iiwa_7() -> np.ndarray:  # pragma: no cover\n    \"\"\"Get KUKA LBR iiwa 7 MDH model.\"\"\"\n    return np.array(\n        [\n            [0, 0, 0, 340],\n            [-np.pi / 2, 0, 0, 0],\n            [np.pi / 2, 0, 0, 400],\n            [np.pi / 2, 0, 0, 0],\n            [-np.pi / 2, 0, 0, 400],\n            [-np.pi / 2, 0, 0, 0],\n            [np.pi / 2, 0, 0, 126],\n        ]\n    )\n\n\ndef mecademic_meca500() -> np.ndarray:  # pragma: no cover\n    \"\"\"Get Meca500 MDH model.\"\"\"\n    return np.array(\n        [\n            [0, 0, 0, 135],\n            [-np.pi / 2, 0, -np.pi / 2, 0],\n            [0, 135, 0, 0],\n            [-np.pi / 2, 38, 0, 120],\n            [np.pi / 2, 0, 0, 0],\n            [-np.pi / 2, 0, np.pi, 72],\n        ]\n    )\n\n\ndef puma560() -> np.ndarray:  # pragma: no cover\n    \"\"\"Get PUMA560 MDH model.\"\"\"\n    return np.array(\n        [\n            [0, 0, 0, 0],\n            [-np.pi / 2, 0, 0, 0],\n            [0, 612.7, 0, 0],\n            [0, 571.6, 0, 163.9],\n            [-np.pi / 2, 0, 0, 115.7],\n            [np.pi / 2, 0, np.pi, 92.2],\n        ]\n    )\n\n\ndef ur10() -> np.ndarray:  # pragma: no cover\n    \"\"\"Get UR10 MDH model.\"\"\"\n    return np.array(\n        [\n            [0, 0, 0, 118],\n            [np.pi / 2, 0, np.pi, 0],\n            [0, 612.7, 0, 0],\n            [0, 571.6, 0, 163.9],\n            [-np.pi / 2, 0, 0, 115.7],\n            [np.pi / 2, 0, np.pi, 92.2],\n        ]\n    )\n\n\ndef abb_irb120() -> np.ndarray:  # pragma: no cover\n    \"\"\"Get ABB irb120 MDH model.\"\"\"\n    return np.array(\n        [\n            [0, 0, 0, 290],\n            [-np.pi / 2, 0, -np.pi / 2, 0],\n            [0, 270, 0, 0],\n            [-np.pi / 2, 70, 0, 302],\n            [np.pi / 2, 0, 0, 0],\n            [-np.pi / 2, 0, np.pi, 72],\n        ]\n    )\n", "path": "pybotics/predefined_models.py"}], "after_files": [{"content": "\"\"\"Predefined robot models.\n\nThese models correspond to the Modified Denavit\u2013Hartenberg parameters:\nhttps://en.wikipedia.org/wiki/Denavit%E2%80%93Hartenberg_parameters\n\"\"\"\nimport numpy as np  # type: ignore\n\n\ndef kuka_lbr_iiwa_7() -> np.ndarray:  # pragma: no cover\n    \"\"\"Get KUKA LBR iiwa 7 MDH model.\"\"\"\n    return np.array(\n        [\n            [0, 0, 0, 340],\n            [-np.pi / 2, 0, 0, 0],\n            [np.pi / 2, 0, 0, 400],\n            [np.pi / 2, 0, 0, 0],\n            [-np.pi / 2, 0, 0, 400],\n            [-np.pi / 2, 0, 0, 0],\n            [np.pi / 2, 0, 0, 126],\n        ]\n    )\n\n\ndef mecademic_meca500() -> np.ndarray:  # pragma: no cover\n    \"\"\"Get Meca500 MDH model.\"\"\"\n    return np.array(\n        [\n            [0, 0, 0, 135],\n            [-np.pi / 2, 0, -np.pi / 2, 0],\n            [0, 135, 0, 0],\n            [-np.pi / 2, 38, 0, 120],\n            [np.pi / 2, 0, 0, 0],\n            [-np.pi / 2, 0, np.pi, 72],\n        ]\n    )\n\n\ndef puma560() -> np.ndarray:  # pragma: no cover\n    \"\"\"Get PUMA560 MDH model.\"\"\"\n    return np.array(\n        [\n            [0, 0, 0, 0],\n            [-np.pi / 2, 0, 0, 0],\n            [0, 612.7, 0, 0],\n            [0, 571.6, 0, 163.9],\n            [-np.pi / 2, 0, 0, 115.7],\n            [np.pi / 2, 0, np.pi, 92.2],\n        ]\n    )\n\n\ndef ur10() -> np.ndarray:  # pragma: no cover\n    \"\"\"Get UR10 MDH model.\"\"\"\n    return np.array(\n        [\n            [0, 0, 0, 118],\n            [np.pi / 2, 0, np.pi, 0],\n            [0, 612.7, 0, 0],\n            [0, 571.6, 0, 163.9],\n            [-np.pi / 2, 0, 0, 115.7],\n            [np.pi / 2, 0, np.pi, 92.2],\n        ]\n    )\n\n\ndef abb_irb120() -> np.ndarray:  # pragma: no cover\n    \"\"\"Get ABB irb120 MDH model.\"\"\"\n    return np.array(\n        [\n            [0, 0, 0, 290],\n            [-np.pi / 2, 0, -np.pi / 2, 0],\n            [0, 270, 0, 0],\n            [-np.pi / 2, 70, 0, 302],\n            [np.pi / 2, 0, 0, 0],\n            [-np.pi / 2, 0, np.pi, 72],\n        ]\n    )\n", "path": "pybotics/predefined_models.py"}]}