"""
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