148 lines
6.3 KiB
Python
148 lines
6.3 KiB
Python
import os
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import io
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import json
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import tempfile
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import numpy as np
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import torch
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from PIL import Image
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from typing import Optional
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from google import genai
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from google.genai import types
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class GeminiChatVertexNode:
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"""ComfyUI Node for Gemini Chat via Vertex AI with optional image input"""
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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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"prompt": ("STRING", {"multiline": True}),
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"project_id": ("STRING", {"multiline": False, "default": ""}),
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"location": ([
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"global", "us-central1", "us-east1", "us-east4", "us-east5", "us-south1",
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"us-west1", "us-west2", "us-west3", "us-west4",
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"northamerica-northeast1", "northamerica-northeast2",
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"southamerica-east1", "southamerica-west1", "africa-south1",
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"europe-west1", "europe-north1", "europe-west2", "europe-west3",
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"europe-west4", "europe-west6", "europe-west8", "europe-west9",
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"europe-west12", "europe-southwest1", "europe-central2",
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"asia-east1", "asia-east2", "asia-northeast1", "asia-northeast2",
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"asia-northeast3", "asia-south1", "asia-south2", "asia-southeast1",
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"asia-southeast2", "australia-southeast1", "australia-southeast2",
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"me-central1", "me-central2", "me-west1"
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], {"default": "us-central1"}),
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"service_account": ("STRING", {"multiline": True, "default": ""}),
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"model": ([
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"gemini-2.5-flash-lite",
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"gemini-2.5-flash",
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"gemini-2.5-pro",
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"gemini-3-pro-preview",
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"gemini-2.0-flash-lite",
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"gemini-2.0-flash"
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], {"default": "gemini-2.5-pro"}),
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"temperature": ("FLOAT", {"default": 0.2, "min": 0.0, "max": 2.0, "step": 0.1}),
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"thinking": ("BOOLEAN", {"default": True}),
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"seed": ("INT", {"default": 69, "min": -1, "max": 2147483646, "step": 1}),
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},
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"optional": {
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"system_instruction": ("STRING", {"multiline": True, "default": ""}),
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"thinking_budget": ("INT", {"default": -1, "min": -1, "max": 24576, "step": 1}),
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"image": ("IMAGE",),
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}
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}
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RETURN_TYPES = ("STRING",)
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RETURN_NAMES = ("response",)
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FUNCTION = "generate"
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CATEGORY = "text/generation"
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def setup_client(self, service_account_json, project_id, location):
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"""Setup Vertex AI client with service account JSON content"""
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if not service_account_json.strip():
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raise ValueError("Service account JSON content is required.")
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if not project_id.strip():
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raise ValueError("Project ID is required.")
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# Validate and write JSON content to temporary file
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try:
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json.loads(service_account_json) # Validate JSON format
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except json.JSONDecodeError as e:
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raise ValueError(f"Invalid JSON content: {str(e)}")
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# Create temporary file with JSON content
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temp_file = tempfile.NamedTemporaryFile(mode='w', suffix='.json', delete=False)
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temp_file.write(service_account_json.strip())
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temp_file.close()
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# Set credentials path
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os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = temp_file.name
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return genai.Client(vertexai=True, project=project_id.strip(), location=location.strip())
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def generate(self, prompt: str, project_id: str, location: str, service_account: str,
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model: str, temperature: float, thinking: bool, seed: int,
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system_instruction: Optional[str] = None, thinking_budget: int = -1,
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image: Optional[torch.Tensor] = None) -> tuple:
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# Initialize Vertex AI client
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client = self.setup_client(service_account, project_id, location)
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parts = [types.Part.from_text(text=prompt)]
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# Handle image input
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if image is not None:
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img_array = image.cpu().numpy() if isinstance(image, torch.Tensor) else image
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if len(img_array.shape) == 4:
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img_array = img_array[0]
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if img_array.dtype in [np.float32, np.float64]:
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img_array = (img_array * 255).astype(np.uint8)
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buffered = io.BytesIO()
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Image.fromarray(img_array).save(buffered, format="PNG")
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parts.append(types.Part.from_bytes(mime_type="image/png", data=buffered.getvalue()))
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model_lower = model.lower()
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# Gemini 2.0 models don't support thinking at all
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if "gemini-2.0" in model_lower:
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print("Gemini-2.0 models do not support thinking - disabling thinking config")
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final_thinking_budget = None
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# Gemini Pro models (2.5-pro, 3-pro) cannot turn thinking off
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elif "pro" in model_lower and ("2.5" in model_lower or "gemini-3" in model_lower):
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print(f"{model} cannot have thinking turned off - thinking is always enabled")
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final_thinking_budget = thinking_budget if thinking_budget != 0 else -1
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# Flash models can toggle thinking on/off
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elif not thinking:
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final_thinking_budget = 0
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else:
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final_thinking_budget = thinking_budget
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config = types.GenerateContentConfig(
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temperature=temperature,
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seed=seed,
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response_mime_type="text/plain"
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)
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if "gemini-2.0" not in model_lower:
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config.thinking_config = types.ThinkingConfig(thinking_budget=final_thinking_budget)
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if system_instruction and system_instruction.strip():
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config.system_instruction = [types.Part.from_text(text=system_instruction.strip())]
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response = client.models.generate_content(
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model=model,
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contents=[types.Content(role="user", parts=parts)],
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config=config
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)
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return (response.text,)
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# Node mappings
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NODE_CLASS_MAPPINGS = {
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"GeminiChatVertexNode": GeminiChatVertexNode
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"GeminiChatVertexNode": "Gemini Chat (Vertex AI)"
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} |