# ∞ Markdown Repair ## Documentation - Class name: `LLMMarkdownRepair` - Category: `SALT/Language Toolkit/Tools/Markdown` - Output node: `False` The node is designed to repair malformed Markdown text, ensuring it is transformed into valid, well-structured Markdown without omitting any data. It leverages a language model to analyze and correct the input text based on given instructions. ## Input types ### Required - **`llm_model`** - Specifies the language model to use for repairing the Markdown. It plays a crucial role in understanding and fixing the malformed Markdown based on the provided prompt. - Comfy dtype: `LLM_MODEL` - Python dtype: `dict` - **`text_input`** - The malformed Markdown text that needs to be repaired. This input is critical as it provides the content that the node will work on to produce valid Markdown. - Comfy dtype: `STRING` - Python dtype: `str` ### Optional - **`extra_directions`** - Optional additional instructions for the language model to follow when repairing the Markdown. This can guide the repair process more precisely according to specific requirements. - Comfy dtype: `STRING` - Python dtype: `str` ## Output types - **`markdown_output`** - Comfy dtype: `STRING` - The repaired Markdown text, which is the result of the language model's processing of the input text and any extra directions provided. - Python dtype: `str` ## Usage tips - Infra type: `GPU` - Common nodes: unknown ## Source code ```python class LLMMarkdownRepair: @classmethod def INPUT_TYPES(cls): return { "required": { "llm_model": ("LLM_MODEL",), "text_input": ("STRING", {"multiline": True, "dynamicPrompts": False, "placeholder": "Malformed Markdown..."}), }, "optional": { "extra_directions": ("STRING", {"multiline": True, "dynamicPrompts": False, "placeholder": "Extra directions for the LLM to follow..."}), } } RETURN_TYPES = ("STRING",) RETURN_NAMES = ("markdown_output",) FUNCTION = "repair_markdown" CATEGORY = f"{MENU_NAME}/{SUB_MENU_NAME}/Tools/Markdown" def repair_markdown(self, llm_model, text_input, extra_directions=""): prompt = ( f"{text_input}\n\n###\n\n" "Given the above malformed Markdown, please inspect it and repair it so that it's valid Markdown, without changing or losing any data if possible." f"{extra_directions}\n\n" "Please ensure the Markdown output is well-structured, and does not omit any data." ) response = llm_model['llm'].complete(prompt) return (response.text,) ```