Fix misc errors in tutorials 1 and 3

[gao-hongnan]

Applying Structured Output to RAG applications

While following the tutorial, named Applying Structured Output to RAG applications, I noticed some cells are not rendered correctly.

Some of the fixes involve the following (not exhaustive):

1. One block of code has the response_model to be s, where s is undefined, inferring from earlier content, I tentatively replaced s to be Iterable[Extraction].

    ```python
    extractions = client.chat.completions.create(
        model="gpt-4-1106-preview",
        stream=True,
        response_model=Iterable[Extraction], # original is `response_model=s`
        messages=[
            {
                "role": "system",
                "content": "Your role is to extract chunks from the following and create a set of topics.",
            },
            {"role": "user", "content": text_chunk},
        ],
    )
    ```
   

2. The helpers script/module is not defined, I did a search, which lead me to https://github.com/wandb/edu/blob/main/llm-structured-extraction/helpers.py and added the missing function(s).

   ```python
   from helpers import dicts_to_df
   ```
   
   leading to `ModuleNotFoundError: No module named 'helpers'` and halting the program at the next cell.
   

3. Small linguistic fix:

    ```text
    One of the big limitations is that often times the query we embed and the text A common method ...
    ```
    
    is changed to
    
    ```text
    Example 1) Improving Extractions
    One of the big limitations is that often times the query we embed and the text we are searching for may not have a direct match, leading to suboptimal results. A common method
    ```
   

Working with structured outputs

While going through the first tutorial, I noticed many cells will render error (by design) to show readers how validations work. It might be cleaner to use try-except with traceback here so in future, if we ever use execute=True or something, the notebook will render and not halt. An example below:

for obj in data:
    name = obj.get("first_name")
    age = obj.get("age")
    try:
        age_next_year = age + 1
        print(f"Next year {name} will be {age_next_year} years old")
    except TypeError:
        traceback.print_exc()

[ellipsis-dev]

Skipped PR review on 7b774fe because no changed files had a supported extension. If you think this was in error, please contact us and we'll fix it right away.

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