My codes are not running in the python

Course Q&A Agentic AI
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1

My codes are not running from the lesson agentic AI. Does someone know or can help me with this?

2

you are posting your query in incorrect category, kindly move it to right category with detailed description of your issue like post a screenshot of what you are experiencing, if error, post screenshot of the error. But make sure not to post any grade function codes that you wrote, shouldn’t be posted as it is against community guidelines.

if you are not able to move query to right query, atleast provide information about course, assignment name, exercise number in your description.

For better understanding on how to post a topic in community forum, refer FAQ section that has topics explaining how to post your query here.

3

Hi Deepti, I found the code running for my exercise in the jupiter file. Initially I was trying it in the Python software but then realise it is running on the course portal instead. This is for the ungraded lab module 2 of agentic AI. FAQ sounds like a good idea. Thank you!!

4

kind post a screenshot of what you are stating. code are not running? does it encounter error, or you didn’t run the cell.

And lab codes need to run on course platform only, any issue encountered locally in your system cannot be addressed by others as your system settings and variabilities are only know by the person handling it

5 
TypeError                                 Traceback (most recent call last)
Cell In[10], line 8
      5 image_basename="drink_sales"
      7 # Run the complete agentic workflow
----> 8 _ = run_workflow(
      9     dataset_path="coffee_sales.csv",
     10     user_instructions=user_instructions,
     11     generation_model=generation_model,
     12     reflection_model=reflection_model,
     13     image_basename=image_basename
     14 )

Cell In[9], line 41, in run_workflow(dataset_path, user_instructions, generation_model, reflection_model, image_basename)
     39     initial_code = match.group(1).strip()
     40     exec_globals = {"df": df}
---> 41     exec(initial_code, exec_globals)
     42 utils.print_html(out_v1, is_image=True, title="Generated Chart (V1)")
     44 # 3) Reflect on V1 (image + original code) to get feedback and refined code (V2)

File <string>:5

File /usr/local/lib/python3.11/site-packages/pandas/core/ops/common.py:76, in _unpack_zerodim_and_defer.<locals>.new_method(self, other)
     72             return NotImplemented
     74 other = item_from_zerodim(other)
---> 76 return method(self, other)

File /usr/local/lib/python3.11/site-packages/pandas/core/arraylike.py:186, in OpsMixin.__add__(self, other)
     98 @unpack_zerodim_and_defer("__add__")
     99 def __add__(self, other):
    100     """
    101     Get Addition of DataFrame and other, column-wise.
    102 
   (...)
    184     moose     3.0     NaN
    185     """
--> 186     return self._arith_method(other, operator.add)

File /usr/local/lib/python3.11/site-packages/pandas/core/series.py:6154, in Series._arith_method(self, other, op)
   6152 def _arith_method(self, other, op):
   6153     self, other = self._align_for_op(other)
-> 6154     return base.IndexOpsMixin._arith_method(self, other, op)

File /usr/local/lib/python3.11/site-packages/pandas/core/base.py:1391, in IndexOpsMixin._arith_method(self, other, op)
   1388     rvalues = np.arange(rvalues.start, rvalues.stop, rvalues.step)
   1390 with np.errstate(all="ignore"):
-> 1391     result = ops.arithmetic_op(lvalues, rvalues, op)
   1393 return self._construct_result(result, name=res_name)

File /usr/local/lib/python3.11/site-packages/pandas/core/ops/array_ops.py:273, in arithmetic_op(left, right, op)
    260 # NB: We assume that extract_array and ensure_wrapped_if_datetimelike
    261 #  have already been called on `left` and `right`,
    262 #  and `maybe_prepare_scalar_for_op` has already been called on `right`
    263 # We need to special-case datetime64/timedelta64 dtypes (e.g. because numpy
    264 # casts integer dtypes to timedelta64 when operating with timedelta64 - GH#22390)
    266 if (
    267     should_extension_dispatch(left, right)
    268     or isinstance(right, (Timedelta, BaseOffset, Timestamp))
   (...)
    271     # Timedelta/Timestamp and other custom scalars are included in the check
    272     # because numexpr will fail on it, see GH#31457
--> 273     res_values = op(left, right)
    274 else:
    275     # TODO we should handle EAs consistently and move this check before the if/else
    276     # (https://github.com/pandas-dev/pandas/issues/41165)
    277     # error: Argument 2 to "_bool_arith_check" has incompatible type
    278     # "Union[ExtensionArray, ndarray[Any, Any]]"; expected "ndarray[Any, Any]"
    279     _bool_arith_check(op, left, right)  # type: ignore[arg-type]

TypeError: unsupported operand type(s) for +: 'DatetimeArray' and 'str'



​
6

This error shows at the end of the code execution.

7

Add this to your prompt

“Avoid any operand type error”

I also have updated your query to right category and with right tags as per your description

8

Thanks Deepti for the support!!

1 Like
9

I hope your issue is resolved.

Keep learning.

regards
Dr. Deepti