139 lines
5.2 KiB
Markdown
139 lines
5.2 KiB
Markdown
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# Documentation
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- Class name: IF_SaveText
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- Category: ImpactFrames💥🎞️
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- Output node: True
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- Repo Ref: https://github.com/chrisgoringe/Custom-classifier-nodes/tree/main
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IF_SaveText节点旨在处理并可选择性保存与交互相关的文本数据，如问题、回答和负面反馈，并支持多种文件格式。该节点的功能包括为每次交互生成唯一标识符、格式化交互数据，以及以指定格式和模式将数据保存到文件中，从而增强数据管理和检索能力，便于进一步分析或记录保存。
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# Input types
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## Required
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- question_input
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- 交互中的问题部分，作为生成交互记录的关键输入。
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- Comfy dtype: STRING
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- Python dtype: str
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- response_input
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- 对问题的回答，对记录交互至关重要。
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- Comfy dtype: STRING
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- Python dtype: str
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- negative_input
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- 与交互相关的负面反馈或输入，提供额外的上下文信息。
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- Comfy dtype: STRING
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- Python dtype: str
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## Optional
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- save_file
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- 布尔标志，指示是否将交互数据保存到文件中。
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- Comfy dtype: BOOLEAN
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- Python dtype: bool
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- file_format
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- 指定保存交互数据的文件格式（csv、txt、json）。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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- save_mode
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- 决定文件的保存方式：创建新文件、覆盖现有文件或追加到现有文件。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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# Output types
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- Question
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- Comfy dtype: STRING
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- 返回交互中的问题部分。
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- Python dtype: str
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- Response
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- Comfy dtype: STRING
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- 返回交互中的回答部分。
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- Python dtype: str
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- Negative
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- Comfy dtype: STRING
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- 返回与交互相关的负面反馈或输入。
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- Python dtype: str
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- Turn
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- Comfy dtype: STRING
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- 返回一个格式化的字符串，包含交互的唯一标识符、问题、回答和负面输入。
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- Python dtype: str
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## Usage tips
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- Infra type: `CPU`
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- Common nodes: unknown
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## Source code
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```python
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class IFSaveText:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"question_input": ("STRING", {"forceInput": True}),
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"response_input": ("STRING", {"forceInput": True}),
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"negative_input": ("STRING", {"forceInput": True}),
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#"turn": ("STRING", {"forceInput": True}),
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},
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"optional": {
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"save_file": ("BOOLEAN", {"default": False, "label_on": "Save Text", "label_off": "Don't Save"}),
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"file_format": (["csv", "txt", "json"],),
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"save_mode": (["create", "overwrite", "append"],),
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},
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#"hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
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}
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RETURN_TYPES = ("STRING", "STRING", "STRING", "STRING",)
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RETURN_NAMES = ("Question", "Response", "Negative", "Turn",)
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FUNCTION = "process_text"
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OUTPUT_NODE = True
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CATEGORY = "ImpactFrames💥🎞️"
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def process_text(self, question_input, negative_input, response_input, save_file=False, file_format="txt", save_mode="create"):
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turn_id = str(uuid.uuid4())
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turn_data = {"id": turn_id, "question": question_input, "response": response_input, "negative": negative_input}
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if save_file:
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self.save_text_to_file(turn_data, file_format, save_mode)
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turn = f"ID: {turn_id}\nQuestion: {question_input}\nResponse: {response_input}\nNegative: {negative_input}"
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return (question_input, response_input, negative_input, turn)
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def save_text_to_file(self, turn_data, file_format, save_mode):
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save_text_dir = folder_paths.get_output_directory()
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os.makedirs(save_text_dir, exist_ok=True)
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file_path = os.path.join(save_text_dir, f"output.{file_format}")
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file_mode = "w" if save_mode in ["create", "overwrite"] else "a"
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if file_format == "csv":
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with open(file_path, file_mode, newline='') as csvfile:
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fieldnames = ['question', 'response']
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writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
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if save_mode == "create" or save_mode == "overwrite":
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writer.writeheader()
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writer.writerow(turn_data)
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elif file_format == "txt":
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with open(file_path, file_mode) as txtfile:
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txtfile.write(f"{turn_data}\n")
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elif file_format == "json":
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with open(file_path, file_mode) as jsonfile:
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if save_mode == "append":
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try:
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data = json.load(jsonfile)
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except:
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data = []
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data.append(turn_data)
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jsonfile.seek(0)
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else:
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data = [turn_data]
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json.dump(data, jsonfile, indent=4)
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"""@classmethod
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def IS_CHANGED(cls, turn_id, question_input, negative_input, response_input, turn, save_file, file_format, save_mode, unique_id=None, prompt=None, extra_pnginfo=None):
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turn = f"ID: {turn_id}\nQuestion: {question_input}\nResponse: {response_input}\nNegative: {negative_input}"
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return {"ui": {"string": [turn]}, "result": (turn,)}"""
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```
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