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39 lines
1.8 KiB
Python
39 lines
1.8 KiB
Python
import re
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from langchain.prompts import SystemMessagePromptTemplate, HumanMessagePromptTemplate, AIMessagePromptTemplate
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from langchain.schema import BaseMessage
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from core.prompt.prompt_template import JinjaPromptTemplate
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class PromptBuilder:
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@classmethod
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def to_system_message(cls, prompt_content: str, inputs: dict) -> BaseMessage:
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prompt_template = JinjaPromptTemplate.from_template(prompt_content)
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system_prompt_template = SystemMessagePromptTemplate(prompt=prompt_template)
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prompt_inputs = {k: inputs[k] for k in system_prompt_template.input_variables if k in inputs}
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system_message = system_prompt_template.format(**prompt_inputs)
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return system_message
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@classmethod
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def to_ai_message(cls, prompt_content: str, inputs: dict) -> BaseMessage:
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prompt_template = JinjaPromptTemplate.from_template(prompt_content)
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ai_prompt_template = AIMessagePromptTemplate(prompt=prompt_template)
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prompt_inputs = {k: inputs[k] for k in ai_prompt_template.input_variables if k in inputs}
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ai_message = ai_prompt_template.format(**prompt_inputs)
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return ai_message
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@classmethod
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def to_human_message(cls, prompt_content: str, inputs: dict) -> BaseMessage:
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prompt_template = JinjaPromptTemplate.from_template(prompt_content)
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human_prompt_template = HumanMessagePromptTemplate(prompt=prompt_template)
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human_message = human_prompt_template.format(**inputs)
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return human_message
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@classmethod
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def process_template(cls, template: str):
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processed_template = re.sub(r'\{{2}(.+)\}{2}', r'{\1}', template)
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# processed_template = re.sub(r'\{([a-zA-Z_]\w+?)\}', r'\1', template)
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# processed_template = re.sub(r'\{\{([a-zA-Z_]\w+?)\}\}', r'{\1}', processed_template)
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return processed_template
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