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### Description
Implements synthetic data generation with the fields and preferences
given by the user. Adds showcase notebook.
Corresponding prompt was proposed for langchain-hub.
### Example
```
output = chain({"fields": {"colors": ["blue", "yellow"]}, "preferences": {"style": "Make it in a style of a weather forecast."}})
print(output)
# {'fields': {'colors': ['blue', 'yellow']},
'preferences': {'style': 'Make it in a style of a weather forecast.'},
'text': "Good morning! Today's weather forecast brings a beautiful combination of colors to the sky, with hues of blue and yellow gently blending together like a mesmerizing painting."}
```
### Twitter handle
@deepsense_ai @matt_wosinski
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
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| .. | ||
| autonomous_agents | ||
| comprehend_moderation | ||
| cpal | ||
| data_anonymizer | ||
| fallacy_removal | ||
| generative_agents | ||
| graph_transformers | ||
| llms | ||
| pal_chain | ||
| plan_and_execute | ||
| prompt_injection_identifier | ||
| prompts | ||
| pydantic_v1 | ||
| retrievers | ||
| smart_llm | ||
| sql | ||
| synthetic_data | ||
| tot | ||
| __init__.py | ||
| py.typed | ||