99 lines
2.7 KiB
Python
99 lines
2.7 KiB
Python
from groq import Groq
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import requests
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import os
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import base64
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import io
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from PIL import Image
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import numpy as np
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def getGroqModels(key):
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try:
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url = "https://api.groq.com/openai/v1/models"
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headers = {
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"Authorization": f"Bearer {key}",
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"Content-Type": "application/json"
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}
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response = requests.get(url, headers=headers)
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response.raise_for_status()
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response = response.json()
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return [item['id'] for item in response['data'] if 'id' in item]
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except (requests.exceptions.RequestException, KeyError, ValueError):
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return ['Key Error']
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api_key = os.environ.get("GROQ_API_KEY")
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api_models = getGroqModels(api_key)
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class DataSet_GroqChatImage:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"image": ("IMAGE",),
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"model": (api_models, {"default": api_models[0]}),
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"user_prompt": ("STRING", {"multiline": True, "default": ""}),
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"max_tokens": ("INT", {"default": 1024})
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}
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}
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FUNCTION = "generate"
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RETURN_TYPES = ("STRING",)
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def to_base64(self, image):
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image = image[0]
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i = 255. * image.cpu().numpy()
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img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
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buffered = io.BytesIO()
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img.save(buffered, format="PNG")
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return base64.b64encode(buffered.getvalue()).decode("utf-8")
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def generate(self, image, model, user_prompt, max_tokens):
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try:
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base64img = self.to_base64(image)
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api_client = Groq(
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api_key=api_key,
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)
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chat_completion = api_client.chat.completions.create(
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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": user_prompt},
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{
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"type": "image_url",
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"image_url": {
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"url": f"data:image/png;base64,{base64img}",
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},
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},
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],
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}
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],
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model=model,
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temperature=0.5,
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max_tokens=max_tokens,
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top_p=1,
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stop=None,
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stream=False,
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)
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return (chat_completion.choices[0].message.content,)
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except Exception as e:
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return (f"Error: {str(e)}",)
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N_CLASS_MAPPINGS = {
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"DataSet_GroqChatImage": DataSet_GroqChatImage,
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}
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N_DISPLAY_NAME_MAPPINGS = {
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"DataSet_GroqChatImage": "DataSet_GroqChatImage",
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}
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