196 lines
6.2 KiB
Python
196 lines
6.2 KiB
Python
import os
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import json
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import requests
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import time
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import jwt
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import re
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import tempfile
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import random
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from PIL import Image
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import base64
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import cv2
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p = os.path.dirname(os.path.realpath(__file__))
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def get_zpai_api_key():
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try:
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config_path = os.path.join(p, 'config.json')
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with open(config_path, 'r') as f:
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config = json.load(f)
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api_key = config["Zpai_API_KEY"]
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except Exception as e:
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raise Exception("Error: API key is required", e)
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return api_key
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def generate_token(apikey_s: str, exp_second: int):
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try:
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id_t, secret = apikey_s.split(".")
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except Exception as e:
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raise Exception("invalid apikey", e)
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payload = {
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"api_key": id_t,
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"exp": int(round(time.time() * 1000)) + exp_second * 1000,
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"timestamp": int(round(time.time() * 1000)),
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}
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return jwt.encode(
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payload,
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secret,
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algorithm="HS256",
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headers={"alg": "HS256", "sign_type": "SIGN"},
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)
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class ZhipuaiApi_Txt:
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def __init__(self):
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self.api_key = get_zpai_api_key()
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if self.api_key is not None:
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client_key = self.api_key
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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, "default": "30 words describe a girl walking on the Moon."}),
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"model_name": (["glm-4", "glm-3-turbo"],),
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"output_language": (["English", "Original_language"],),
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},
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}
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RETURN_TYPES = ("STRING",)
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RETURN_NAMES = ("text",)
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FUNCTION = "zhipuai_txt_api"
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CATEGORY = "ChatGlm_Api"
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def zhipuai_txt_api(self, prompt, model_name, output_language):
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if not self.api_key:
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raise ValueError("API key is required")
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if prompt == None:
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raise ValueError("need prompt")
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else:
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if output_language == "English":
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prompt_txt = 'Reply in English'
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else:
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prompt_txt = '用提问的语言回复我'
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prompt = ''.join([prompt, prompt_txt])
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url = "https://open.bigmodel.cn/api/paas/v4/chat/completions"
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exp_seconds = int(9)
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client_key = str(get_zpai_api_key())
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token = generate_token(apikey_s=client_key, exp_second=exp_seconds)
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header_txt = {
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'Authorization': f'Bearer {token}',
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'Content-Type': 'application/json'
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}
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data_txt = {"model": f"{model_name}", "messages": [{"role": "user", "content": f"{prompt}"}]}
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data_txt = json.dumps(data_txt)
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response = requests.post(url=url, headers=header_txt, data=data_txt)
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txt_content = response.json()
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prompt_txt = txt_content.get("choices", 'Default Value')[0]
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prompt_txt = prompt_txt.get("message", 'Default Value')
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prompt_txt = prompt_txt.get("content", 'Default Value')
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prompt = re.sub(r'\n+', '', prompt_txt)
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return (prompt,)
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class ZhipuaiApi_Img:
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def __init__(self):
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self.api_key = get_zpai_api_key()
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if self.api_key is not None:
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client_key = self.api_key
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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", {"default": "Describe this image", "multiline": True}),
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"image": ("IMAGE",),
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"output_language": (["English", "Original_language"],),
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}
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}
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RETURN_TYPES = ("STRING",)
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RETURN_NAMES = ("text",)
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FUNCTION = "zhipuai_img2txt_api"
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CATEGORY = "ChatGlm_Api"
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def tensor_to_image(self, tensor):
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tensor = tensor.cpu()
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image_np = tensor.squeeze().mul(255).clamp(0, 255).byte().numpy()
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image = Image.fromarray(image_np, mode='RGB')
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return image
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def zhipuai_img2txt_api(self, prompt, image, output_language):
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if not self.api_key:
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raise ValueError("API key is required")
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if prompt == None:
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raise ValueError("need prompt")
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if image == None:
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raise ValueError("Needs img")
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else:
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if output_language == "English":
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prompt_img = 'Reply in English'
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else:
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prompt_img = '用提问的语言回复我'
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prompt = ''.join([prompt, prompt_img])
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url = "https://open.bigmodel.cn/api/paas/v4/chat/completions"
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exp_seconds = int(9)
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client_key = str(get_zpai_api_key())
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token = generate_token(apikey_s=client_key, exp_second=exp_seconds)
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pil_image = self.tensor_to_image(image)
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temp_directory = tempfile.gettempdir()
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unique_suffix = "_temp_" + ''.join(random.choice("abcdefghijklmnopqrstuvwxyz") for _ in range(5))
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filename = f"image{unique_suffix}.png"
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img_path = os.path.join(temp_directory, filename)
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pil_image.save(img_path)
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# img to base64
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img = cv2.imread(img_path)
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img_data = cv2.imencode('test.PNG', img)[1].tobytes()
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base64_data = base64.b64encode(img_data)
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img_base64 = str(base64_data, encoding='utf-8')
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header_img = {
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'Authorization': f'Bearer {token}',
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'Content-Type': 'application/json'
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}
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data_img = {"model": "glm-4v", "messages": [{"role": "user","content": [{"type": "text", "text": f"{prompt}"},{"type": "image_url","image_url": {"url": f"{img_base64}"}}]}]}
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data_img = json.dumps(data_img)
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response = requests.post(url=url, headers=header_img, data=data_img)
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img_content = response.json()
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content_img = img_content.get("choices", 'Default Value')[0]
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content_img = content_img.get("message", 'Default Value')
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content_img = content_img.get("content", 'Default Value')
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prompt = re.sub(r'\n+', '', content_img)
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os.remove(img_path)
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return (prompt,)
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NODE_CLASS_MAPPINGS = {
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"ZhipuaiApi_Txt": ZhipuaiApi_Txt,
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"ZhipuaiApi_img": ZhipuaiApi_Img
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"ZhipuaiApi_Txt": "ZhipuaiApi_Txt",
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"ZhipuaiApi_Img": "ZhipuaiApi_Img"
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}
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