The realest AI debugger in the game.
Project description
debuggpt
The realest AI debugger in the game.
Example code:
/test/test_debug.py
:
from debuggpt import gpt_debug
import pickle
@gpt_debug(show_prompt_only=True)
def func():
with open('test.pkl', 'rb') as f:
df = pickle.load(f)
df['c'] = df.a + df.b
func()
Here's what happens when the above code runs:
test.pkl
stores a pandas DataFrame:
a b
0 1 4
1 2 foo
2 3 6
Since column b
contains a string, 'foo', we get an error when adding it to a
:
TypeError: unsupported operand type(s) for +: 'int' and 'str'
This is tricky to debug because:
- Our code NEVER indicates that
df
is a Pandas DataFrame. In fact, we don't even import pandas! - Our code NEVER mentions the data types, or contents, of
df
. - We can't know which column ('a' or 'b') has mixed types, not even by looking at the error or traceback.
But GPT-4 knew all of this. Including #3.
Here's its response:
The error "TypeError: unsupported operand type(s) for +: 'int' and 'str'" is occurring because you are trying to add an integer and a string together in line 9 of
test/test_debug.py
:df['c'] = df.a + df.bThe DataFrame
df
has mixed types in column 'b' - it contains both integers and the string 'foo'. You cannot add an integer and a string together directly, which is causing the error.To fix this issue, you need to decide how you want to handle the mixed types in column 'b'. One option is to convert the non-numeric values to a default value, like 0, before performing the addition. You can do this using the
pd.to_numeric
function with theerrors='coerce'
argument, which will replace non-numeric values with NaN, and then use thefillna
method to replace NaN with 0.Here's the updated code for
func
:def func(): with open('test.pkl', 'rb') as f: df = pickle.load(f) df['b'] = pd.to_numeric(df['b'], errors='coerce').fillna(0) df['c'] = df.a + df.bThis code will first convert any non-numeric values in column 'b' to NaN, then replace NaN with 0, and finally perform the addition. If you have a different way you'd like to handle the mixed types in column 'b', you can modify the code accordingly.
This is an excellent response.
GPT-4 could see everything.
- It knew the type and exact contents of
df
, the value returned bypickle.load
. - It could see all relevant code, not just the traceback (more on this later)
- It could see everything that was printed during life of our program (including the original error traceback).
Here's what the original traceback looked like:
Traceback (most recent call last):
File "/Users/Ryan.Young3/.pyenv/versions/debuggpt/lib/python3.11/site-packages/pandas/core/ops/array_ops.py", line 171, in _na_arithmetic_op
result = func(left, right)
^^^^^^^^^^^^^^^^^
File "/Users/Ryan.Young3/.pyenv/versions/debuggpt/lib/python3.11/site-packages/pandas/core/computation/expressions.py", line 239, in evaluate
return _evaluate(op, op_str, a, b) # type: ignore[misc]
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/Ryan.Young3/.pyenv/versions/debuggpt/lib/python3.11/site-packages/pandas/core/computation/expressions.py", line 70, in _evaluate_standard
return op(a, b)
^^^^^^^^
TypeError: unsupported operand type(s) for +: 'int' and 'str'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/Users/Ryan.Young3/main/code/debuggpt/test/test_debug.py", line 10, in <module>
func()
File "/Users/Ryan.Young3/main/code/debuggpt/test/test_debug.py", line 8, in func
df['c'] = df.a + df.b
~~~~~^~~~~~
File "/Users/Ryan.Young3/.pyenv/versions/debuggpt/lib/python3.11/site-packages/pandas/core/ops/common.py", line 81, in new_method
return method(self, other)
^^^^^^^^^^^^^^^^^^^
File "/Users/Ryan.Young3/.pyenv/versions/debuggpt/lib/python3.11/site-packages/pandas/core/arraylike.py", line 186, in __add__
return self._arith_method(other, operator.add)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/Ryan.Young3/.pyenv/versions/debuggpt/lib/python3.11/site-packages/pandas/core/series.py", line 6108, in _arith_method
return base.IndexOpsMixin._arith_method(self, other, op)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/Ryan.Young3/.pyenv/versions/debuggpt/lib/python3.11/site-packages/pandas/core/base.py", line 1348, in _arith_method
result = ops.arithmetic_op(lvalues, rvalues, op)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/Ryan.Young3/.pyenv/versions/debuggpt/lib/python3.11/site-packages/pandas/core/ops/array_ops.py", line 232, in arithmetic_op
res_values = _na_arithmetic_op(left, right, op) # type: ignore[arg-type]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/Ryan.Young3/.pyenv/versions/debuggpt/lib/python3.11/site-packages/pandas/core/ops/array_ops.py", line 178, in _na_arithmetic_op
result = _masked_arith_op(left, right, op)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/Ryan.Young3/.pyenv/versions/debuggpt/lib/python3.11/site-packages/pandas/core/ops/array_ops.py", line 116, in _masked_arith_op
result[mask] = op(xrav[mask], yrav[mask])
^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: unsupported operand type(s) for +: 'int' and 'str'
While we do pass this traceback to the model, the magic comes from what we provide next: the code report.
Here is the exact code report we gave the model (in addition, we also provided a prompt, and the printed stdout history)
You are debugging a call to `func`.
CONTEXT SURROUNDING THE LAST CALL TO `func` BEFORE THE ERROR WAS RAISED:
File "/test/test_debug.py", line 10
```python
1| from debuggpt import gpt_debug
2| import pickle
3|
4| @gpt_debug
5| def func():
6| with open('test.pkl', 'rb') as f:
7| df = pickle.load(f)
8| df['c'] = df.a + df.b # <-- LINE 8, THE ORIGINAL LINE THAT CAUSED THE ERROR
9|
10| func() # <-- LINE 10 CALLED
```
LOCAL NAMES, TYPES, AND VALUES, IN THE ABOVE CONTEXT (module, '/test/test_debug.py') WHEN THE ERROR OCCURRED:
gpt_debug: function
pickle: module
func: function
SOURCE CODE FOR `func`, THE FUNCTION YOU'RE DEBUGGING:
File "/test/test_debug.py", line 8
```python
4| @gpt_debug
5| def func():
6| with open('test.pkl', 'rb') as f:
7| df = pickle.load(f)
8| df['c'] = df.a + df.b # <-- LINE 8, THE ORIGINAL LINE THAT CAUSED THE ERROR
```
LOCAL NAMES, TYPES, AND VALUES, IN THE ABOVE CONTEXT (function, `func`) WHEN THE ERROR OCCURRED:
f: BufferedReader =
<_io.BufferedReader name='test.pkl'>
df: DataFrame =
a b
0 1 4
1 2 blah
2 3 6
The report stops here because the remaining calls in the traceback are from pandas code. But normally, if there are more calls from our code, we would provide an extended traceback, showing the context for each call in the stack.
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