MCP tool is returning a string representation of a dictionary rather than an actual dictionary object

[bayesways]

Summary:
The code example app.py in Unit 2: Gradio Server does not return json as intended. This causes an error when we run the agent in the following chapter.

Details:
The MCP tool presented in app.py is a sentiment analysis tool. Running the agent from Unit 2: Gradio Client with the prompt "Analyze the sentiment of the following text "This is awesome"" gives the following results

* Running on local URL:  http://127.0.0.1:7861
* To create a public link, set `share=True` in `launch()`.
╭────────────────────────────────── New run ───────────────────────────────────╮
│                                                                              │
│ Analyze the sentiment of the following text "This is awesome"                │
│                                                                              │
╰─ InferenceClientModel - Qwen/Qwen2.5-Coder-32B-Instruct ─────────────────────╯
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Step 1 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 ─ Executing parsed code: ─────────────────────────────────────────────────────
  sentiment_result = sentiment_analysis(text="This is awesome")
  print(sentiment_result)
 ──────────────────────────────────────────────────────────────────────────────
Execution logs:
root={'polarity': 1.0, 'subjectivity': 1.0, 'assessment': 'positive'}

Out: None
[Step 1: Duration 3.17 seconds| Input tokens: 2,046 | Output tokens: 51]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Step 2 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Error in code parsing:
Your code snippet is invalid, because the regex pattern
```(?:py|python)?\s*\n(.*?)\n``` was not found in it.
Here is your code snippet:
Observation:

Make sure to include code with the correct pattern, for instance:
Thoughts: Your thoughts
Code:
```py
# Your python code here
```<end_code>
Make sure to provide correct code blobs.
[Step 2: Duration 0.94 seconds| Input tokens: 4,245 | Output tokens: 54]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Step 3 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 ─ Executing parsed code: ─────────────────────────────────────────────────────
  sentiment_result = sentiment_analysis(text="This is awesome")
  print(sentiment_result)
 ──────────────────────────────────────────────────────────────────────────────
Execution logs:
root={'polarity': 1.0, 'subjectivity': 1.0, 'assessment': 'positive'}

Out: None
[Step 3: Duration 3.07 seconds| Input tokens: 6,574 | Output tokens: 115]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Step 4 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 ─ Executing parsed code: ─────────────────────────────────────────────────────
  final_answer(sentiment_result['assessment'])
 ──────────────────────────────────────────────────────────────────────────────
Code execution failed at line 'final_answer(sentiment_result['assessment'\])'
due to: InterpreterError: Could not index root={'polarity': 1.0, 'subjectivity':
1.0, 'assessment': 'positive'} with 'assessment': TypeError: string indices must
be integers, not 'str'
[Step 4: Duration 4.00 seconds| Input tokens: 9,066 | Output tokens: 192]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Step 5 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 ─ Executing parsed code: ─────────────────────────────────────────────────────
  print(type(sentiment_result))
  print(sentiment_result)
  final_answer(sentiment_result['assessment'])
 ──────────────────────────────────────────────────────────────────────────────
Execution logs:
<class 'str'>
root={'polarity': 1.0, 'subjectivity': 1.0, 'assessment': 'positive'}

Code execution failed at line 'final_answer(sentiment_result['assessment'\])'
due to: InterpreterError: Could not index root={'polarity': 1.0, 'subjectivity':
1.0, 'assessment': 'positive'} with 'assessment': TypeError: string indices must
be integers, not 'str'
[Step 5: Duration 4.26 seconds| Input tokens: 11,789 | Output tokens: 276]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Step 6 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 ─ Executing parsed code: ─────────────────────────────────────────────────────
  import re

  # Parse the string to extract the sentiment assessment
  sentiment_dict = eval(sentiment_result)
  final_answer(sentiment_dict['assessment'])
 ──────────────────────────────────────────────────────────────────────────────
Code execution failed at line 'sentiment_dict = eval(sentiment_result)' due to:
InterpreterError: Forbidden function evaluation: 'eval' is not among the
explicitly allowed tools or defined/imported in the preceding code
[Step 6: Duration 3.83 seconds| Input tokens: 14,799 | Output tokens: 348]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Step 7 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 ─ Executing parsed code: ─────────────────────────────────────────────────────
  import re

  # Use regular expression to extract the sentiment assessment
  match = re.search(r"'assessment':\s*'([^']*)'", sentiment_result)
  if match:
      assessment = match.group(1)
      final_answer(assessment)
  else:
      final_answer("Unable to extract assessment")
 ──────────────────────────────────────────────────────────────────────────────
Out - Final answer: positive
[Step 7: Duration 5.12 seconds| Input tokens: 18,038 | Output tokens: 442]
Error in sse_reader: peer closed connection without sending complete message body (incomplete chunked read)

This is taken from the log of the agent when I tried to run it
The sentiment_analysis tool is returning a string that looks like a dictionary ("root={'polarity': 1.0, 'subjectivity': 1.0, 'assessment': 'positive'}") instead of returning an actual Python dictionary object. See for example the following excerpt from the logs

<class 'str'>
root={'polarity': 1.0, 'subjectivity': 1.0, 'assessment': 'positive'}

The agent tries to use dictionary indexing on a string and fails.

I opened this PR to suggest a fix.