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cache prompt variables #32

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cache prompt variables #32

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14 changes: 9 additions & 5 deletions promptify/prompts/nlp/prompter.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,14 +19,18 @@ def __init__(
self.allowed_missing_variables = allowed_missing_variables
self.model_args_count = self.model.run.__code__.co_argcount
self.model_variables = self.model.run.__code__.co_varnames[1 : self.model_args_count]
self.prompt_variables_map = {}

def list_templates(self) -> List[str]:
return self.environment.list_templates()

def get_template_variables(self, template_name: str) -> List[str]:
if template_name in self.prompt_variables_map:
return self.prompt_variables_map[template_name]
template_source = self.environment.loader.get_source(self.environment, template_name)
parsed_content = self.environment.parse(template_source)
undeclared_variables = meta.find_undeclared_variables(parsed_content)
self.prompt_variables_map[template_name] = undeclared_variables
return undeclared_variables

def generate_prompt(self, template_name, **kwargs) -> str:
Expand All @@ -44,11 +48,11 @@ def fit(self, template_name, **kwargs):
prompt_variables = self.get_template_variables(template_name)
prompt_kwargs = {}
model_kwargs = {}
for variable in kwargs:
if variable in prompt_variables:
prompt_kwargs[variable] = kwargs[variable]
elif variable in self.model_variables:
model_kwargs[variable] = kwargs[variable]
for var_name, val in kwargs.items():
if var_name in prompt_variables:
prompt_kwargs[var_name] = val
elif var_name in self.model_variables:
model_kwargs[var_name] = val
prompt = self.generate_prompt(template_name, **prompt_kwargs)
output = self.model.run(prompts=[prompt], **model_kwargs)
return output[0]