""" title: Artificium Thought Filter author: projectmoon author_url: https://git.agnos.is/projectmoon/open-webui-filters version: 0.1.0 license: AGPL-3.0+, MIT required_open_webui_version: 0.3.32 """ ######################################################### # OpenWebUI Filter that collapses model reasoning/thinking into a # separate section in the reply. This is specificially for the # Artificium model, based on Llama 3.1. It outputs its thought # processes broken by markdown horizontal rules. Usually, it outputs a # basic thought process followed by a breakdown. GENERALLY, text below # the last horizontal line is the final answer. # # Based on the Add or Delete Text Filter by anfi. # https://openwebui.com/f/anfi/add_or_delete_text # # Therefore, portions of this code are licensed under the MIT license. # The modifications made for "thought enclosure" etc are licensed # under the AGPL using the MIT's sublicensing clause. # # For those portions under the MIT license, the following applies: # # MIT License # # Copyright (c) 2024 anfi # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. ######################################################### from typing import Optional, Dict, List import re from pydantic import BaseModel, Field THOUGHT_ENCLOSURE = """
{{THOUGHT_TITLE}} {{THOUGHTS}} ---
""" DEFAULT_THOUGHT_PLAN = """ Your task execution plan should be: - Break down the problem into the smallest possible steps - Come up with a plan to solve each step, then execute each step. - Analyze each step for mistakes, correct any mistakes found in each step. - Finally, output the solution based on your reasoning. In your reply, break your reasoning down into "Plan", "Execution", "Mistake Analysis", and "Final Output". These should be ## Markdown Headers. """ DETAIL_DELETION_REGEX = r"[\s\S]*?" class Filter: class Valves(BaseModel): priority: int = Field( default=0, description="Priority level for the filter operations." ) task_title: str = Field( default="Task Discovery", description="Title for the collapsible task reasoning section." ) breakdown_title: str = Field( default="Thought Process", description="Title for the collapsible reasoning breakdown section." ) use_thoughts_as_context: bool = Field( default=False, description=("Include previous thought processes as context for the AI. " "Disabled by default.") ) pass def __init__(self): self.valves = self.Valves() def _create_thought_regex(self) -> str: tag = self.valves.thought_tag return f"<{tag}>(.*?)" def _create_thought_tag_deletion_regex(self) -> str: tag = self.valves.thought_tag return "[\s\S]*?".replace("{{THINK}}", tag) def _create_output_tag_deletion_regex(self) -> str: tag = self.valves.output_tag return r"[\s\S]*?".replace("{{OUT}}", tag) def _parse_reply(self, messages: List[Dict[str, str]]) -> dict: reply = messages[-1]["content"] pattern = r'((?<=\n---\n)|^)(.*?)(?=---\n|$)' matches = re.findall(pattern, reply, flags=re.DOTALL) sections = [match[1].strip() for match in matches if match[0] == ''] sections = [section for section in sections if section] print(f"[Artificium Filter] Parsed {len(sections)} section(s)") # a few different situations. # 1. 3+ sections = initial thoughts, breakdown, final output. # 2. 2 sections = thoughts, final output # 3. 1 section or 0 sections = do nothing if len(sections) >= 3: return { "initial": sections[0], "breakdown": "\n\n---\n\n".join(sections[1:-1]), "final": sections[-1] } elif len(sections) == 2: return { "initial": sections[0], "breakdown": None, "final": sections[1] } else: return { "initial": None, "breakdown": None, "final": reply } def _enclose_thoughts(self, messages: List[Dict[str, str]]) -> None: if not messages: return parsed_reply = self._parse_reply(messages) final_reply = "" if parsed_reply["initial"] is not None: initial_thoughts = (THOUGHT_ENCLOSURE .replace("{{THOUGHT_TITLE}}", self.valves.task_title) .replace("{{THOUGHTS}}", parsed_reply["initial"])) final_reply = initial_thoughts if parsed_reply["breakdown"] is not None: breakdown_thoughts = (THOUGHT_ENCLOSURE .replace("{{THOUGHT_TITLE}}", self.valves.breakdown_title) .replace("{{THOUGHTS}}", parsed_reply["breakdown"])) final_reply = f"{final_reply}\n{breakdown_thoughts}" if parsed_reply["final"] is not None: output = parsed_reply["final"] final_reply = f"{final_reply}\n{output}" final_reply = final_reply.strip() if final_reply: messages[-1]["content"] = final_reply def _handle_include_thoughts(self, messages: List[Dict[str, str]]) -> None: """Remove
tags from input, if configured to do so.""" #
tags are created by the outlet filter for display # in OWUI. if self.valves.use_thoughts_as_context: return for message in messages: message["content"] = re.sub( DETAIL_DELETION_REGEX, "", message["content"], count=1 ) def inlet(self, body: Dict[str, any], __user__: Optional[Dict[str, any]] = None) -> Dict[str, any]: try: original_messages: List[Dict[str, str]] = body.get("messages", []) self._handle_include_thoughts(original_messages) body["messages"] = original_messages return body except Exception as e: print(e) return body def outlet(self, body: Dict[str, any], __user__: Optional[Dict[str, any]] = None) -> Dict[str, any]: try: original_messages: List[Dict[str, str]] = body.get("messages", []) self._enclose_thoughts(original_messages) body["messages"] = original_messages return body except Exception as e: print(e) return body