""" title: Thinking Filter author: TrolleK author_url: https://github.com/hosteren & https://huggingface.co/trollek version: 0.1 """ import re from pydantic import BaseModel, Field from typing import Optional class Filter: class Valves(BaseModel): priority: int = Field( default=0, description="Priority level for the filter operations." ) start_thought_token: str = Field( default="<\|thought_start\|>", description="The start of thougt token." ) end_thought_token: str = Field( default="<\|thought_end\|>", description="The end of thought token." ) pass def __init__(self): # Indicates custom file handling logic. This flag helps disengage default routines in favor of custom # implementations, informing the WebUI to defer file-related operations to designated methods within this class. # Alternatively, you can remove the files directly from the body in from the inlet hook # self.file_handler = True # Initialize 'valves' with specific configurations. Using 'Valves' instance helps encapsulate settings, # which ensures settings are managed cohesively and not confused with operational flags like 'file_handler'. self.valves = self.Valves() self.pattern = re.compile(rf'{self.valves.start_thought_token}(.*?){self.valves.end_thought_token}') pass def remove_thought(self, text: str) -> str: # Remove thought markers from text and return the modified text. # This function is used to remove thought markers from a string of text, which are typically used in chat applications to indicate that a message contains a thought or an idea. return self.pattern.sub('', text) def inlet(self, body: dict, __user__: Optional[dict] = None) -> dict: # Modify the request body or validate it before processing by the chat completion API. # This function is the pre-processor for the API where various checks on the input can be performed. # It can also modify the request before sending it to the API. print(f"inlet:{__name__}") print(f"inlet:body:{body}") print(f"inlet:user:{__user__}") return body def outlet(self, body: dict, __user__: Optional[dict] = None) -> dict: # Modify or analyze the response body after processing by the API. # This function is the post-processor for the API, which can be used to modify the response # or perform additional checks and analytics. print(f"outlet:{__name__}") print(f"outlet:body:{body}") print(f"outlet:user:{__user__}") last_message = body["messages"][-1]["content"] if self.pattern.search(last_message): body["messages"][-1]["content"] = self.remove_thought(last_message) return body