commune-ai commited on
Commit
ea10883
1 Parent(s): 3b1280f

Create app.py

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  1. app.py +247 -0
app.py ADDED
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+ import gradio as gr
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+ from requests.exceptions import ConnectTimeout
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+ import time
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+ import requests
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+ import base64
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+
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+ global headers
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+ global cancel_url
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+ global path
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+ global output_image
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+ global property_name_array
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+ property_name_array =[]
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+ output_image = ''
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+ path = ''
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+ cancel_url =''
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+ headers = {
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+ 'Content-Type': 'application/json',
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+ 'Authorization': 'Token r8_ZGZlzThfRkPZVDMygVclY1XZ9AuxmIQ2qwwPP',
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+ "Access-Control-Allow-Headers": "Content-Type",
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+ "Access-Control-Allow-Origin": '**',
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+ "Access-Control-Allow-Methods": "OPTIONS,POST,GET,PATCH"}
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+
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+ with gr.Blocks() as demo:
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+ owner = "nateraw"
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+ name = "bge-large-en-v1.5"
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+ max_retries = 3
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+ retry_delay = 2
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+ for retry in range(max_retries):
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+ try:
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+ url = f'https://api.replicate.com/v1/models/{owner}/{name}'
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+ response = requests.get(url, headers=headers, timeout=10)
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+ # Process the response
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+ break # Break out of the loop if the request is successful
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+ except ConnectTimeout:
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+ if retry < max_retries - 1:
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+ print(f"Connection timed out. Retrying in {retry_delay} seconds...")
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+ time.sleep(retry_delay)
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+ else:
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+ print("Max retries exceeded. Unable to establish connection.")
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+
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+ data = response.json()
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+ description =data.get("description", '')
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+ title = data.get("default_example",'').get("model",'')
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+ version = data.get("default_example",'').get("version",'')
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+
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+ gr.Markdown(
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+ f"""
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+ # {title}
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+ {description}
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+ """)
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+
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+ with gr.Row():
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+ with gr.Column():
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+ inputs =[]
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+ schema = data.get("latest_version", {}).get("openapi_schema", {}).get("components", {}).get("schemas", {})
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+ ordered_properties = sorted(schema.get("Input", {}).get("properties", {}).items(), key=lambda x: x[1].get("x-order", 0))
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+ required = schema.get("Input", '').get('required', [])
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+ print(required,"required")
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+ for property_name, property_info in ordered_properties :
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+ property_name_array.append(property_name)
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+ if required:
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+ for item in required:
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+ if item == property_name:
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+ label = "*"+ property_info.get('title', '')
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+ description = property_info.get('description','')
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+ break
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+ else:
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+ label = property_info.get('title', '')
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+ description = property_info.get('description','')
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+ else:
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+ label = property_info.get('title', '')
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+ description = property_info.get('description','')
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+
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+ if "x-order" in property_info:
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+ order = int(property_info.get('x-order',''))
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+ if property_info.get("type", {}) == "integer":
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+ value= data.get('default_example', '').get('input','').get(property_name,0)
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+ if "minimum" and "maximum" in property_info:
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+ if value == 0:
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+ inputs.insert(order, gr.Slider(label=label, info= description, value=property_info.get('default', value), minimum=property_info.get('minimum', ''), maximum=property_info.get('maximum', ''), step=1))
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+ else:
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+ inputs.insert(order, gr.Slider(label=label, info= description, value=value, minimum=property_info.get('minimum', ''), maximum=property_info.get('maximum', ''), step=1))
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+ else:
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+ if value == 0:
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+ inputs.insert(order, gr.Number(label=label, info= description, value=property_info.get('default', value)))
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+ else:
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+ inputs.insert(order, gr.Number(label=label, info= description, value=value))
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+
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+ elif property_info.get("type", {}) == "string":
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+ value= data.get('default_example', '').get('input','').get(property_name,'')
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+ if property_info.get('format','') == 'uri':
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+
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+ if value :
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+ inputs.insert(order, gr.File(label=label, value=value, type="filepath"))
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+ else :
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+ inputs.insert(order, gr.File(label=label, type="filepath"))
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+
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+ else:
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+ if value == '':
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+ inputs.insert(order, gr.Textbox(label=label,info= description, value=property_info.get('default', value)))
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+ else:
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+ inputs.insert(order, gr.Textbox(label=label,info= description, value=value))
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+
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+ elif property_info.get("type", {}) == "number":
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+ value= data.get('default_example', '').get('input','').get(property_name, 0)
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+ if "minimum" and "maximum" in property_info:
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+ if value == 0:
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+ inputs.insert(order, gr.Slider(label=label,info= description, value=property_info.get('default', value), minimum=property_info.get('minimum', ''), maximum=property_info.get('maximum', '')))
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+ else:
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+ inputs.insert(order, gr.Slider(label=label,info= description, value=value, minimum=property_info.get('minimum', ''), maximum=property_info.get('maximum', '')))
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+ else:
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+ if value == 0:
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+ inputs.insert(order, gr.Number(label=label,info= description, value=property_info.get('default', value)))
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+ else:
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+ inputs.insert(order, gr.Number(label=label,info= description, value=value))
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+ elif property_info.get("type", {}) == "boolean":
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+ value= data.get('default_example', '').get('input','').get(property_name,'')
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+ if value == '':
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+ inputs.insert(order, gr.Checkbox(label=label,info= description, value=property_info.get('default', value)))
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+ else:
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+ inputs.insert(order, gr.Checkbox(label=label,info= description, value=value))
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+ else:
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+ value= data.get('default_example', '').get('input','').get(property_name,'')
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+ options=schema.get(property_name,'').get('enum',[])
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+ if value:
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+ inputs.insert(order, gr.Dropdown(label=property_name,info= description,choices=options, value=property_info.get("default", value)))
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+ else:
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+ inputs.insert(order, gr.Dropdown(label=property_name,info= description,choices=options, value=value))
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+
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+ with gr.Row():
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+ cancel_btn = gr.Button("Cancel")
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+ run_btn = gr.Button("Run")
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+
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+ with gr.Column():
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+
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+ outputs = []
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+
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+ output_result = data.get("default_example", '').get("output")
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+ output_type= schema.get("Output", '').get("type", '')
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+ if output_type == 'array':
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+ output_image = output_result
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+ else:
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+ output_image = output_result
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+ print (output_image)
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+ outputs.append(gr.TextArea(value=output_image))
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+ outputs.append(gr.Image(visible=False))
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+ outputs.append(gr.Image(visible=False))
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+ outputs.append(gr.Image(visible=False))
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+
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+
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+
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+ def run_process(input1, input2, input3, input4, input5):
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+ global cancel_url
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+ global property_name_array
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+ print(len(property_name_array))
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+ cancel_url=''
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+ url = 'https://replicate.com/api/predictions'
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+
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+ if input1:
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+ with open(input1, "rb") as file:
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+ data = file.read()
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+
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+ base64_data = base64.b64encode(data).decode("utf-8")
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+ mimetype = "image/jpg"
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+ data_uri_image = f"data:{mimetype};base64,{base64_data}"
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+ else:
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+ data_uri_image=None
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+
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+ print(version, 'version')
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+ if input1:
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+ body = {
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+ "version": version,
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+ "input": {
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+ property_name_array[0]: data_uri_image,
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+ property_name_array[1]: input2,
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+ property_name_array[2]: input3,
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+ property_name_array[3]: input4,
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+ property_name_array[4]: input5,
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+ }
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+ }
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+ else:
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+ body = {
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+ "version": version,
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+ "input": {
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+ property_name_array[1]: input2,
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+ property_name_array[2]: input3,
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+ property_name_array[3]: input4,
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+ property_name_array[4]: input5,
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+ }
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+ }
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+
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+
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+
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+ response = requests.post(url, json=body)
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+ print(response.status_code)
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+ if response.status_code == 201:
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+ response_data = response.json()
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+ get_url = response_data.get('urls','').get('get','')
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+ identifier = 'https://replicate.com/api/predictions/'+get_url.split("/")[-1]
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+
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+ print(identifier,'')
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+ time.sleep(3)
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+ output =verify_image(identifier)
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+ print(output,'333')
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+ if output:
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+ return gr.TextArea(value=output), gr.Image(),gr.Image(),gr.Image()
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+
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+ return gr.Image(),gr.Image(visible=False),gr.Image(visible=False),gr.Image(visible=False)
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+
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+ def cancel_process(input1, input2, input3, input4, input5):
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+ global cancel_url
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+ cancel_url = '123'
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+ global output_image
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+ return gr.TextArea(value=output_image), gr.Image(visible=False),gr.Image(visible=False),gr.Image(visible=False)
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+
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+ def verify_image(get_url):
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+ res = requests.get(get_url)
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+ if res.status_code == 200:
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+ res_data = res.json()
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+ if res_data.get('error',''):
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+ return
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+ else:
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+ if cancel_url:
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+ return
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+ else:
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+ output = res_data.get('output', [])
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+ print(output,'111')
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+ if output:
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+ print(output,'222')
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+ return output
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+
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+ else:
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+ time.sleep(1)
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+ val = verify_image(get_url)
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+ return val
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+ else:
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+ return []
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+
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+ run_btn.click(run_process, inputs=inputs, outputs=outputs, api_name="run")
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+ cancel_btn.click(cancel_process, inputs=inputs, outputs=outputs, api_name="cancel")
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+
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+ demo.launch()
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+
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+
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+
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+
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+