Repository: confident-ai/deepeval
Issue: generate_goldens_from_goldens doesn't generate expected_output with include_expected_output=True
Root cause: Documentation Deficiency

**Describe the bug**
When running generate_goldens_from_goldens with include_expected_output=True, expected_output is found to be None in all generated Goldens.

The [documentation](https://deepeval.com/docs/synthesizer-generate-from-goldens) states the following:

> [Optional] include_expected_output: a boolean which when set to True, will additionally generate an expected_output for each synthetic Golden. Defaulted to True.

In a separate text box in the same page the following note can be found:

> If your existing Goldens include context, the synthesizer will utilize these contexts to generate synthetic Goldens, ensuring they are grounded in truth. If no context is present, the synthesizer will employ the generate_from_scratch method to create additional inputs based on provided inputs.

Considering `generate_from_scratch` does not have the option to generate expected output, this might be the intended behavior, although poorly described in the `include_expected_output` parameter, where it should state that it requires context to be different from None in order to work.

**To Reproduce**
Run the following code with OPENAI_API_KEY as environment variable (or in a .env file) using deepeval==3.6.0

```python
from deepeval.synthesizer import Synthesizer
from deepeval.synthesizer.config import StylingConfig

from dotenv import load_dotenv
load_dotenv()

styling_config = StylingConfig(
  input_format="Questions in English that asks for data in database.",
  expected_output_format="SQL query based on the given input",
  task="Answering text-to-SQL-related queries by querying a database and returning the results to users",
  scenario="Non-technical users trying to query a database using plain English.",
)

synthesizer = Synthesizer(styling_config=styling_config)

synthesizer.generate_goldens_from_scratch(num_goldens=2)

synthesizer.generate_goldens_from_goldens(
  goldens=synthesizer.synthetic_goldens,
  max_goldens_per_golden=2,
  include_expected_output=True,
)

print(synthesizer.synthetic_goldens)
```
The resulting goldens all have expected_output=None

**Expected behavior**
The resulting goldens should contain expected_output different from None

**Screenshots**
<img width="1303" height="770" alt="Image" src="https://github.com/user-attachments/assets/0e3b1c7c-e611-43cf-b9ff-791250f0806a" /> 


I would like to solve it for hacktoberfest

Hey @aceballos-prode, as you've speculated, this is indeed an intended behavior to not generate any expected outputs with any context in the goldens. This is mainly because we don't want the LLM to generate any expected outputs that were hallucinated (They do it a lot) because they didn't have a ground truth or context to stick to. Thanks for pointing out the issue. We'll add a special note in the docs to make this clear.

Hey @aviralgarg05, thanks for offering to solve the issue, while this may not be available, you can choose any other issue from the issues tab and tag us, we'll be happy to accept a PR as a hacktoberfest contribution.