ADD 增加多模态LLM节点
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@ -1,4 +1,4 @@
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from .nodes.llm_api import LLMChat
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from .nodes.llm_api import LLMChat, LLMChatMultiModal
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from .nodes.compute_video_point import VideoStartPointDurationCompute
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from .nodes.cos import COSUpload, COSDownload
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from .nodes.face_detect import FaceDetect
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@ -65,7 +65,8 @@ NODE_CLASS_MAPPINGS = {
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"RandomLineSelector": RandomLineSelector,
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"PlugAndPlayWebhook": PlugAndPlayWebhook,
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"SaveImageWithOutput": SaveImageWithOutput,
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"LLMChat": LLMChat
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"LLMChat": LLMChat,
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"LLMChatMultiModal": LLMChatMultiModal
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}
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# A dictionary that contains the friendly/humanly readable titles for the nodes
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@ -104,5 +105,6 @@ NODE_DISPLAY_NAME_MAPPINGS = {
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"RandomLineSelector": "随机选择一行内容",
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"PlugAndPlayWebhook": "Webhook转发器",
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"SaveImageWithOutput": "保存图片(带输出)",
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"LLMChat": "LLM调用"
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"LLMChat": "LLM调用",
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"LLMChatMultiModal": "多模态LLM调用"
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}
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@ -1,10 +1,19 @@
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# LLM API 通过cloudflare gateway调用llm
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import base64
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import io
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import os
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import re
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from mimetypes import guess_type
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from typing import Any, Union
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import httpx
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import numpy as np
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import torch
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from PIL import Image, ImageSequence, ImageOps
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from retry import retry
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import folder_paths
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def find_value_recursive(key:str, data:Union[dict, list]) -> str | None | Any:
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if isinstance(data, dict):
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@ -22,7 +31,7 @@ def find_value_recursive(key:str, data:Union[dict, list]) -> str | None | Any:
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return result
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class LLMChat:
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"""AWS S3下载"""
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"""llm chat"""
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@classmethod
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def INPUT_TYPES(s):
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@ -79,3 +88,70 @@ class LLMChat:
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raise Exception("llm调用失败 {}".format(e))
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return (content,)
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return _chat()
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class LLMChatMultiModal:
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"""llm chat"""
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@classmethod
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def INPUT_TYPES(s):
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input_dir = folder_paths.get_input_directory()
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files = [f for f in os.listdir(input_dir) if os.path.isfile(os.path.join(input_dir, f))]
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files = folder_paths.filter_files_content_types(files, ["image"])
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return {
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"required": {
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"llm_provider": (["gpt-4o-1120",
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"gpt-4.1"],),
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"prompt": ("STRING", {"multiline": True}),
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"image": (sorted(files), {"image_upload": True}),
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"temperature": ("FLOAT",{"default": 0.7, "min": 0.0, "max": 1.0}),
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"max_tokens": ("INT",{"default": 4096, "min":1, "max":65535}),
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"timeout": ("INT", {"default": 120, "min": 30, "max": 900}),
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}
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}
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RETURN_TYPES = ("STRING",)
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RETURN_NAMES = ("llm输出",)
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FUNCTION = "chat"
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CATEGORY = "不忘科技-自定义节点🚩/llm"
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def chat(self, llm_provider:str, prompt:str, image, temperature:float, max_tokens:int, timeout:int):
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@retry(Exception, tries=3, delay=1)
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def _chat():
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try:
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image_path = folder_paths.get_annotated_filepath(image)
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mime_type, _ = guess_type(image_path)
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with open(image_path, "rb") as image_file:
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base64_encoded_data = base64.b64encode(image_file.read()).decode('utf-8')
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with httpx.Client(timeout=httpx.Timeout(timeout, connect=15)) as session:
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resp = session.post("https://gateway.bowong.cc/chat/completions",
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headers={
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"Content-Type": "application/json",
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"Accept": "application/json",
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"Authorization": "Bearer auth-bowong7777"
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},
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json={
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"model": llm_provider,
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"messages": [
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{
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"role": "user",
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"content": [
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{"type": "text", "text": prompt},
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{
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"type": "image_url",
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"image_url": {"url":f"data:{mime_type};base64,{base64_encoded_data}"},
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},
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]
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}
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],
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"temperature": temperature,
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"max_tokens": max_tokens
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})
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resp.raise_for_status()
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resp = resp.json()
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content = find_value_recursive("content", resp)
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content = re.sub(r'\n{2,}', '\n', content)
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except Exception as e:
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# logger.exception("llm调用失败 {}".format(e))
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raise Exception("llm调用失败 {}".format(e))
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return (content,)
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return _chat()
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