Prompting Configuration
The PromptingConfig class controls how Pipelex handles prompting styles for different LLM targets.
Configuration Options
class PromptingConfig(ConfigModel):
default_prompting_style: PromptingStyle
prompting_styles: Dict[str, PromptingStyle]
Fields
default_prompting_style: The default prompting style to use when none is specifiedprompting_styles: Dictionary mapping LLM targets to their specific prompting styles
Prompting Styles
Each prompting style defines how prompts are formatted and presented to the LLM. The style can be customized per LLM target to optimize performance and ensure compatibility.
Example Configuration
[pipelex.prompting_config]
default_prompting_style = "chat"
[pipelex.prompting_config.prompting_styles]
gpt4 = "chat"
claude = "instruction"
llama = "completion"
Usage
The configuration provides a method to get the appropriate prompting style:
def get_prompting_style(self, prompting_target: Optional[LLMPromptingTarget] = None) -> Optional[PromptingStyle]:
if prompting_target:
return self.prompting_styles.get(prompting_target, self.default_prompting_style)
else:
return None
This allows for:
- Target-specific prompting styles
- Fallback to default style when no specific style is defined
- Optional prompting when no target is specified
Best Practices
- Define a sensible default prompting style
- Configure specific styles for LLMs with unique requirements
- Test prompting styles with each LLM target
- Document any special formatting requirements