first init
Browse files- .gitignore +2 -0
- README.md +3 -0
- app.py +217 -0
- avatar.png +0 -0
- demo.png +0 -0
- requirements.txt +0 -0
.gitignore
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/.idea/
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/.img/
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README.md
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@@ -11,3 +11,6 @@ license: apache-2.0
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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import base64
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import io
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import json
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import os
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import os.path
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import re
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import time
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from abc import ABC
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from typing import Any
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from uuid import uuid4
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import gradio as gr
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import requests
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from PIL import Image
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from langchain.agents import initialize_agent
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from langchain.chat_models import AzureChatOpenAI
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from langchain.memory import ConversationBufferWindowMemory
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from langchain.tools import BaseTool
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SAVE_FOLDER = "./img"
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SDXL_API_KEY = "XXX"
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SDXL_API_SECRET = "XXXX"
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AZURE_END_POINT = "https://aimodelgpt.openai.azure.com"
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AZURE_OPEN_KEY = "XXXX"
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class SdxlImage(BaseTool, ABC):
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name = "AI SDXL Image Generator"
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description = 'use this tool when you need to generate images by using SDXL model, To use the tool, you must ' \
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'provide prompt parameters prompt, prompt is the description and number of the image, for example, ' \
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'if you want to generate two images about a cute cat, set prompt = a cute cat[SEP]2'
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NEGATIVE_PROMPT = "worst quality, low quality, normal quality, lowres, watermark, monochrome, grayscale, ugly, " \
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"blurry, Tan skin, dark skin, black skin, skin spots, skin blemishes, age spot, glans, " \
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"disabled, distorted, bad anatomy, morbid, malformation, amputation, bad proportions, twins, " \
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"missing body, fused body, extra head, poorly drawn face, bad eyes, deformed eye, unclear eyes, " \
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"cross-eyed, long neck, malformed limbs, extra limbs, extra arms, missing arms, bad tongue, " \
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"strange fingers, mutated hands, missing hands, poorly drawn hands, extra hands, fused hands, " \
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"connected hand, bad hands, wrong fingers, missing fingers, extra fingers, 4 fingers, " \
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"3 fingers, deformed hands, extra legs, bad legs, many legs, more than two legs, bad feet, " \
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"wrong feet, extra feets,"
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api_key: str
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api_secret: str
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# def __init__(self, api_key, api_secret):
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# self.api_key = api_key
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# self.api_secret = api_secret
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def _run(
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self,
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prompt,
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**kwargs: Any,
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) -> Any:
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print(f"execute SDXL Image Tool {prompt}")
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split_items = prompt.split("[SEP]")
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number = 1
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if len(split_items) > 1:
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prompt, number = split_items
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return self.generate_image(query=prompt, number=int(number))
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def get_access_token(self):
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"""
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使用 API Key,Secret Key 获取access_token,替换下列示例中的应用API Key、应用Secret Key
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"""
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url = f'https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id={self.api_key}&client_secret={self.api_secret}'
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payload = json.dumps("")
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headers = {
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'Content-Type': 'application/json',
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'Accept': 'application/json'
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}
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response = requests.request("POST", url, headers=headers, data=payload)
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return response.json().get("access_token")
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def save_image(self, base64_string):
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file_path = _id = str(uuid4()) + ".png"
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image_data = base64.b64decode(base64_string)
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image = Image.open(io.BytesIO(image_data))
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if not os.path.exists(SAVE_FOLDER):
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os.mkdir(SAVE_FOLDER)
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image.save(os.path.join(SAVE_FOLDER, file_path))
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return file_path
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def generate_image(self, query: str, number: int = 1):
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token = self.get_access_token()
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url = "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/text2image/sd_xl?access_token=" + token
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payload = json.dumps({
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"prompt": query,
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"negative_prompt": self.NEGATIVE_PROMPT,
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"size": "768x1024",
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"steps": 25,
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"n": number,
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"sampler_index": "DPM++ SDE Karras"
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})
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headers = {
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'Content-Type': 'application/json'
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}
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response = requests.request("POST", url, headers=headers, data=payload)
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try:
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if response and response.text:
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data = json.loads(response.text)['data']
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if data:
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filenames = ",".join([self.save_image(sub_data['b64_image']) for sub_data in data])
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return f"generate total {number} of the {query}, output is all the files {filenames}"
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except Exception as err:
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print(err)
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return "failed to call tool, got error message"
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class AgentBot:
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def __init__(self):
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chat_llm = AzureChatOpenAI(
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azure_endpoint=AZURE_END_POINT,
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openai_api_key=AZURE_OPEN_KEY,
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deployment_name="gpt-35-turbo",
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openai_api_version="2023-10-01-preview",
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temperature=0.0
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)
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# initialize conversational memory
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conversational_memory = ConversationBufferWindowMemory(
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memory_key='chat_history',
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k=5,
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return_messages=True
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)
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tools = [SdxlImage(api_key=SDXL_API_KEY, api_secret=SDXL_API_SECRET)]
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# initialize agent with tools
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self.agent = initialize_agent(
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agent='chat-conversational-react-description',
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tools=tools,
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llm=chat_llm,
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verbose=True,
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max_iterations=3,
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early_stopping_method='generate',
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memory=conversational_memory
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)
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def run(self, txt) -> str:
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result = self.agent(txt)
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return result["output"]
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def clear(self):
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self.agent.memory.clear()
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bot = AgentBot()
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block_css = """#col_container {width: 1000px; margin-left: auto; margin-right: auto;}
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#chatbot {height: 520px; overflow: auto;}"""
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with gr.Blocks(css=block_css) as demo:
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gr.Markdown("<h3><center>ChatGPT LangChain</center></h3>")
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gr.Markdown(
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"""
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This LangChain GPT can generate SD-XL Image
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"""
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)
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with gr.Row() as input_raw:
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with gr.Column(elem_id="col_container"):
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chatbot = gr.Chatbot([],
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elem_id="chatbot",
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label="ChatBot LangChain for AIGC",
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bubble_full_width=False,
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avatar_images=(None, (os.path.join(os.path.dirname(__file__), "avatar.png"))),
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)
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msg = gr.Textbox()
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with gr.Row():
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with gr.Column(scale=0.10, min_width=0):
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run = gr.Button("🏃♂️Run")
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with gr.Column(scale=0.10, min_width=0):
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clear = gr.Button("🔄Clear️")
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def respond(message, chat_history):
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# bot_message = random.choice(["How are you?", "I love you", "I'm very hungry"])
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bot_message = bot.run(message)
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regx = r'\b[\w-]+\.png'
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match_image = re.findall(regx, bot_message)
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chat_history.append((message, bot_message))
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if match_image:
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for image in match_image:
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image_path = os.path.join(SAVE_FOLDER, image)
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chat_history.append(
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(None, (image_path,)),
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)
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time.sleep(2)
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return "", chat_history
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def clearMessage():
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# clear agent memory
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bot.clear()
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# execute action
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msg.submit(respond, [msg, chatbot], [msg, chatbot])
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run.click(respond, [msg, chatbot], [msg, chatbot])
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clear.click(clearMessage)
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clear.click(lambda: [], None, chatbot)
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gr.Examples(
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examples=["generate a image about a boy reading books using SDXL",
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"generate two images about a gril in the classroom using SDXL",
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],
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inputs=msg
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)
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demo.queue(concurrency_count=10).launch()
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avatar.png
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![]() |
demo.png
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![]() |
requirements.txt
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Binary file (170 Bytes). View file
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