"""
HypothesisGenerator
Generates research hypotheses based on provided background context, domain, and desired format. U...
"""
from typing import Any, Optional, Callable
from ._shared_client import get_shared_client
[docs]
def HypothesisGenerator(
context: str,
domain: str,
number_of_hypotheses: str,
hypothesis_format: Optional[str] = "concise declarative sentences",
*,
stream_callback: Optional[Callable[[str], None]] = None,
use_cache: bool = False,
validate: bool = True,
) -> Any:
"""
Generates research hypotheses based on provided background context, domain, and desired format. U...
Parameters
----------
context : str
Background information, observations, or data description from which to deriv...
domain : str
Field of study or research area (e.g., 'neuroscience', 'ecology', 'materials ...
number_of_hypotheses : str
Number of hypotheses to generate (e.g., '3', '5').
hypothesis_format : str
Optional directive on how to structure each hypothesis. Choose from one of th...
stream_callback : Callable, optional
Callback for streaming output
use_cache : bool, default False
Enable caching
validate : bool, default True
Validate parameters
Returns
-------
Any
"""
# Handle mutable defaults to avoid B006 linting error
return get_shared_client().run_one_function(
{
"name": "HypothesisGenerator",
"arguments": {
"context": context,
"domain": domain,
"number_of_hypotheses": number_of_hypotheses,
"hypothesis_format": hypothesis_format,
},
},
stream_callback=stream_callback,
use_cache=use_cache,
validate=validate,
)
__all__ = ["HypothesisGenerator"]
