mirror of
https://git.datalinker.icu/comfyanonymous/ComfyUI
synced 2026-09-04 16:27:07 +08:00
71 lines
2.0 KiB
Python
71 lines
2.0 KiB
Python
from inspect import cleandoc
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from google import genai
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from google.genai.types import HttpOptions
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from comfy.comfy_types.node_typing import IO, ComfyNodeABC, InputTypeDict
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from comfy_api_nodes.apinode_utils import validate_string
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from server import PromptServer
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class VertexGeminiAPI(ComfyNodeABC):
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"""
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Generates images synchronously via OpenAI's GPT Image 1 endpoint.
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"""
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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) -> InputTypeDict:
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return {
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"required": {
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"prompt": (
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IO.STRING,
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{
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"multiline": True,
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"default": "",
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"tooltip": "Text prompt for GPT Image 1",
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},
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),
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"model": (
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IO.STRING,
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{
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"default": "gemini-2.0-flash-001",
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"tooltip": "The gemini model to use"
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}
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)
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},
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}
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RETURN_TYPES = (IO.STRING,)
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FUNCTION = "api_call"
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CATEGORY = "api node/text/gemini/vertex"
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DESCRIPTION = cleandoc(__doc__ or "")
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API_NODE = True
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def api_call(
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self,
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prompt,
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model="gemini-2.0-flash-001",
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**kwargs
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):
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validate_string(prompt, strip_whitespace=False)
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client = genai.Client(http_options=HttpOptions(api_version="v1"))
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response = client.models.generate_content(
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model=model,
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contents=prompt,
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)
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print(response.text)
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PromptServer.instance.send_progress_text(response.text)
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return response.text
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# A dictionary that contains all nodes you want to export with their names
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# NOTE: names should be globally unique
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NODE_CLASS_MAPPINGS = {
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"VertexGeminiAPI": VertexGeminiAPI,
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}
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# A dictionary that contains the friendly/humanly readable titles for the nodes
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NODE_DISPLAY_NAME_MAPPINGS = {
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"VertexGeminiAPI": "VertexGeminiAPI",
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} |