[Agents] text_reader does not work
Author: osanseviero
Pull request: no

### System Info

Google Colab, Python 3.10.11, transformers 4.29.2

### Who can help?

@sgugger @LysandreJik 

### Information

- [ ] The official example scripts
- [ ] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

```
from transformers import load_tool

tool = load_tool("text-to-speech")
audio = tool("This is a text to speech tool")
``` 

or more end-to-end

```
from transformers import OpenAiAgent

agent = OpenAiAgent(model="text-davinci-003", api_key="TOKEN")
agent.chat("can you make an audio recording of someone saying 'hi'?")
```

Full error stacktrace
```
==Explanation from the agent==
I will use the tool `text_reader` to read the text "Hi" out loud.


==Code generated by the agent==
audio_recording = text_reader(text="Hi")


==Result==
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ in <cell line: 1>:1                                                                              │
│                                                                                                  │
│ /usr/local/lib/python3.10/dist-packages/transformers/tools/agents.py:278 in chat                 │
│                                                                                                  │
│   275 │   │   │   │   print("\n\n==Result==")                                                    │
│   276 │   │   │   │   self.cached_tools = resolve_tools(code, self.toolbox, remote=remote, cac   │
│   277 │   │   │   │   self.chat_state.update(kwargs)                                             │
│ ❱ 278 │   │   │   │   return evaluate(code, self.cached_tools, self.chat_state, chat_mode=True   │
│   279 │   │   │   else:                                                                          │
│   280 │   │   │   │   tool_code = get_tool_creation_code(code, self.toolbox, remote=remote)      │
│   281 │   │   │   │   return f"{tool_code}\n{code}"                                              │
│                                                                                                  │
│ /usr/local/lib/python3.10/dist-packages/transformers/tools/python_interpreter.py:61 in evaluate  │
│                                                                                                  │
│    58 │   result = None                                                                          │
│    59 │   for idx, node in enumerate(expression.body):                                           │
│    60 │   │   try:                                                                               │
│ ❱  61 │   │   │   line_result = evaluate_ast(node, state, tools)                                 │
│    62 │   │   except InterpretorError as e:                                                      │
│    63 │   │   │   msg = f"Evaluation of the code stopped at line {idx} before the end because    │
│    64 │   │   │   if chat_mode:                                                                  │
│                                                                                                  │
│ /usr/local/lib/python3.10/dist-packages/transformers/tools/python_interpreter.py:98 in           │
│ evaluate_ast                                                                                     │
│                                                                                                  │
│    95 │   if isinstance(expression, ast.Assign):                                                 │
│    96 │   │   # Assignement -> we evaluate the assignement which should update the state         │
│    97 │   │   # We return the variable assigned as it may be used to determine the final resul   │
│ ❱  98 │   │   return evaluate_assign(expression, state, tools)                                   │
│    99 │   elif isinstance(expression, ast.Call):                                                 │
│   100 │   │   # Function call -> we return the value of the function call                        │
│   101 │   │   return evaluate_call(expression, state, tools)                                     │
│                                                                                                  │
│ /usr/local/lib/python3.10/dist-packages/transformers/tools/python_interpreter.py:139 in          │
│ evaluate_assign                                                                                  │
│                                                                                                  │
│   136                                                                                            │
│   137 def evaluate_assign(assign, state, tools):                                                 │
│   138 │   var_names = assign.targets                                                             │
│ ❱ 139 │   result = evaluate_ast(assign.value, state, tools)                                      │
│   140 │                                                                                          │
│   141 │   if len(var_names) == 1:                                                                │
│   142 │   │   state[var_names[0].id] = result                                                    │
│                                                                                                  │
│ /usr/local/lib/python3.10/dist-packages/transformers/tools/python_interpreter.py:101 in          │
│ evaluate_ast                                                                                     │
│                                                                                                  │
│    98 │   │   return evaluate_assign(expression, state, tools)                                   │
│    99 │   elif isinstance(expression, ast.Call):                                                 │
│   100 │   │   # Function call -> we return the value of the function call                        │
│ ❱ 101 │   │   return evaluate_call(expression, state, tools)                                     │
│   102 │   elif isinstance(expression, ast.Constant):                                             │
│   103 │   │   # Constant -> just return the value                                                │
│   104 │   │   return expression.value                                                            │
│                                                                                                  │
│ /usr/local/lib/python3.10/dist-packages/transformers/tools/python_interpreter.py:167 in          │
│ evaluate_call                                                                                    │
│                                                                                                  │
│   164 │   # Todo deal with args                                                                  │
│   165 │   args = [evaluate_ast(arg, state, tools) for arg in call.args]                          │
│   166 │   kwargs = {keyword.arg: evaluate_ast(keyword.value, state, tools) for keyword in call   │
│ ❱ 167 │   return func(*args, **kwargs)                                                           │
│   168                                                                                            │
│   169                                                                                            │
│   170 def evaluate_subscript(subscript, state, tools):                                           │
│                                                                                                  │
│ /usr/local/lib/python3.10/dist-packages/transformers/tools/base.py:532 in __call__               │
│                                                                                                  │
│   529 │                                                                                          │
│   530 │   def __call__(self, *args, **kwargs):                                                   │
│   531 │   │   if not self.is_initialized:                                                        │
│ ❱ 532 │   │   │   self.setup()                                                                   │
│   533 │   │                                                                                      │
│   534 │   │   encoded_inputs = self.encode(*args, **kwargs)                                      │
│   535 │   │   encoded_inputs = send_to_device(encoded_inputs, self.device)                       │
│                                                                                                  │
│ /usr/local/lib/python3.10/dist-packages/transformers/tools/text_to_speech.py:45 in setup         │
│                                                                                                  │
│   42 │   def setup(self):                                                                        │
│   43 │   │   if self.post_processor is None:                                                     │
│   44 │   │   │   self.post_processor = "microsoft/speecht5_hifigan"                              │
│ ❱ 45 │   │   super().setup()                                                                     │
│   46 │                                                                                           │
│   47 │   def encode(self, text, speaker_embeddings=None):                                        │
│   48 │   │   inputs = self.pre_processor(text=text, return_tensors="pt", truncation=True)        │
│                                                                                                  │
│ /usr/local/lib/python3.10/dist-packages/transformers/tools/base.py:492 in setup                  │
│                                                                                                  │
│   489 │   │   Instantiates the `pre_processor`, `model` and `post_processor` if necessary.       │
│   490 │   │   """                                                                                │
│   491 │   │   if isinstance(self.pre_processor, str):                                            │
│ ❱ 492 │   │   │   self.pre_processor = self.pre_processor_class.from_pretrained(self.pre_proce   │
│   493 │   │                                                                                      │
│   494 │   │   if isinstance(self.model, str):                                                    │
│   495 │   │   │   self.model = self.model_class.from_pretrained(self.model, **self.model_kwarg   │
│                                                                                                  │
│ /usr/local/lib/python3.10/dist-packages/transformers/processing_utils.py:184 in from_pretrained  │
│                                                                                                  │
│   181 │   │   │   │   [`~feature_extraction_utils.FeatureExtractionMixin.from_pretrained`] and   │
│   182 │   │   │   │   [`~tokenization_utils_base.PreTrainedTokenizer.from_pretrained`].          │
│   183 │   │   """                                                                                │
│ ❱ 184 │   │   args = cls._get_arguments_from_pretrained(pretrained_model_name_or_path, **kwarg   │
│   185 │   │   return cls(*args)                                                                  │
│   186 │                                                                                          │
│   187 │   @classmethod                                                                           │
│                                                                                                  │
│ /usr/local/lib/python3.10/dist-packages/transformers/processing_utils.py:228 in                  │
│ _get_arguments_from_pretrained                                                                   │
│                                                                                                  │
│   225 │   │   │   else:                                                                          │
│   226 │   │   │   │   attribute_class = getattr(transformers_module, class_name)                 │
│   227 │   │   │                                                                                  │
│ ❱ 228 │   │   │   args.append(attribute_class.from_pretrained(pretrained_model_name_or_path, *   │
│   229 │   │   return args                                                                        │
│   230 │                                                                                          │
│   231 │   @property                                                                              │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
TypeError: 'NoneType' object is not callable
```

### Expected behavior

It should generate an audio file

Comments:
I'm not able to reproduce locally or on Colab. Are you using the official [demo Colab](https://colab.research.google.com/drive/1c7MHD-T1forUPGcC_jlwsIptOzpG3hSj)? It's probably some missing dependency so would be interesting to know more about the env where this is failing.

I was using Colab, but it seems the issue was not full-restarting after installing `sentencepiece` (which was importable but I should have restarted). Clean colab, installing first, works well

Closing this as it's a user error not a agents error