2.5 KiB
2.5 KiB
∞ JSON Repair
Documentation
- Class name:
LLMJsonRepair - Category:
SALT/Language Toolkit/Tools/JSON - Output node:
False
The LLMJsonRepair node is designed to correct malformed JSON strings using a language model. It takes a potentially incorrect JSON input and optional directions, and outputs a repaired version of the JSON, ensuring data integrity and proper formatting.
Input types
Required
llm_model- Specifies the language model to use for repairing the JSON. It is crucial for interpreting the input and generating the corrected output.
- Comfy dtype:
LLM_MODEL - Python dtype:
dict
text_input- The malformed JSON string that needs to be repaired. This input is essential for the node to understand what needs fixing.
- Comfy dtype:
STRING - Python dtype:
str
Optional
extra_directions- Optional additional instructions for the language model to follow during the repair process, allowing for more tailored corrections.
- Comfy dtype:
STRING - Python dtype:
str
Output types
json_output- Comfy dtype:
STRING - The repaired JSON string, corrected for syntax and formatting errors to ensure validity.
- Python dtype:
str
- Comfy dtype:
Usage tips
- Infra type:
CPU - Common nodes: unknown
Source code
class LLMJsonRepair:
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"llm_model": ("LLM_MODEL",),
"text_input": ("STRING", {"multiline": True, "dynamicPrompts": False, "placeholder": "Malformed JSON..."}),
},
"optional": {
"extra_directions": ("STRING", {"multiline": True, "dynamicPrompts": False, "placeholder": "Extra directions for the LLM to follow..."}),
}
}
RETURN_TYPES = ("STRING",)
RETURN_NAMES = ("json_output",)
FUNCTION = "compose_json"
CATEGORY = f"{MENU_NAME}/{SUB_MENU_NAME}/Tools/JSON"
def compose_json(self, llm_model, text_input, extra_directions=""):
prompt = (
f"{text_input}\n\n###\n\n"
"Given the above malformed JSON, please inspect it and repair it so that it's valid JSON, without changing or loosing any data if possible."
f"{extra_directions}\n\n"
"Please ensure the JSON output is properly formatted, and does not omit any data."
)
response = llm_model['llm'].complete(prompt)
return (response.text,)