import gradio as gr from requests.exceptions import ConnectTimeout import time import requests import base64 global headers global cancel_url global path global output_image global property_name_array property_name_array =[] output_image = '' path = '' cancel_url ='' headers = { 'Content-Type': 'application/json', 'Authorization': 'Token r8_ZGZlzThfRkPZVDMygVclY1XZ9AuxmIQ2qwwPP', "Access-Control-Allow-Headers": "Content-Type", "Access-Control-Allow-Origin": '**', "Access-Control-Allow-Methods": "OPTIONS,POST,GET,PATCH"} with gr.Blocks() as demo: owner = "nightmareai" name = "disco-diffusion" max_retries = 3 retry_delay = 2 for retry in range(max_retries): try: url = f'https://api.replicate.com/v1/models/{owner}/{name}' response = requests.get(url, headers=headers, timeout=10) # Process the response break # Break out of the loop if the request is successful except ConnectTimeout: if retry < max_retries - 1: print(f"Connection timed out. Retrying in {retry_delay} seconds...") time.sleep(retry_delay) else: print("Max retries exceeded. Unable to establish connection.") data = response.json() description =data.get("description", '') title = data.get("default_example",'').get("model",'') version = data.get("default_example",'').get("version",'') gr.Markdown( f""" # {title} {description} """) with gr.Row(): with gr.Column(): inputs =[] schema = data.get("latest_version", {}).get("openapi_schema", {}).get("components", {}).get("schemas", {}) ordered_properties = sorted(schema.get("Input", {}).get("properties", {}).items(), key=lambda x: x[1].get("x-order", 0)) required = schema.get("Input", '').get('required', []) print(required,"required") for property_name, property_info in ordered_properties : property_name_array.append(property_name) if required: for item in required: if item == property_name: label = "*"+ property_info.get('title', '') description = property_info.get('description','') break else: label = property_info.get('title', '') description = property_info.get('description','') else: label = property_info.get('title', '') description = property_info.get('description','') if "x-order" in property_info: order = int(property_info.get('x-order','')) if property_info.get("type", {}) == "integer": value= data.get('default_example', '').get('input','').get(property_name,0) if "minimum" and "maximum" in property_info: if value == 0: 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)) else: inputs.insert(order, gr.Slider(label=label, info= description, value=value, minimum=property_info.get('minimum', ''), maximum=property_info.get('maximum', ''), step=1)) else: if value == 0: inputs.insert(order, gr.Number(label=label, info= description, value=property_info.get('default', value))) else: inputs.insert(order, gr.Number(label=label, info= description, value=value)) elif property_info.get("type", {}) == "string": value= data.get('default_example', '').get('input','').get(property_name,'') if property_info.get('format','') == 'uri': if value : inputs.insert(order, gr.Image(label=label, value=value)) else : inputs.insert(order, gr.Image(label=label)) else: if value == '': inputs.insert(order, gr.Textbox(label=label,info= description, value=property_info.get('default', value))) else: inputs.insert(order, gr.Textbox(label=label,info= description, value=value)) elif property_info.get("type", {}) == "number": value= data.get('default_example', '').get('input','').get(property_name, 0) if "minimum" and "maximum" in property_info: if value == 0: 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', ''))) else: inputs.insert(order, gr.Slider(label=label,info= description, value=value, minimum=property_info.get('minimum', ''), maximum=property_info.get('maximum', ''))) else: if value == 0: inputs.insert(order, gr.Number(label=label,info= description, value=property_info.get('default', value))) else: inputs.insert(order, gr.Number(label=label,info= description, value=value)) elif property_info.get("type", {}) == "boolean": value= data.get('default_example', '').get('input','').get(property_name,'') if value == '': inputs.insert(order, gr.Checkbox(label=label,info= description, value=property_info.get('default', value))) else: inputs.insert(order, gr.Checkbox(label=label,info= description, value=value)) else: value= data.get('default_example', '').get('input','').get(property_name,'') options=schema.get(property_name,'').get('enum',[]) if value == '': inputs.insert(order, gr.Dropdown(label=property_name,info= description,choices=options, value=property_info.get("default", value))) else: inputs.insert(order, gr.Dropdown(label=property_name,info= description,choices=options, value=value)) with gr.Row(): cancel_btn = gr.Button("Cancel") run_btn = gr.Button("Run") with gr.Column(): outputs = [] output_result = data.get("default_example", '').get("output") output_type= schema.get("Output", '').get("type", '') if output_type == 'array': output_image = output_result[-1] else: output_image = output_result print(output_image,'112121') outputs.append(gr.Image(value=output_image)) def run_process(input1, input2, input3, input4, input5, input6, input7, input8, input9, input10, input11, input12, input13, input14,input15, input16, input17, input18, input19, input20, input21, input22, input23, input24, input25, input26, input27, input28, input29, input30, input31, input32, input33, input34, input35, input36, input37, input38, input39, input40, input41, input42, input43): global cancel_url global property_name_array print(len(property_name_array)) cancel_url='' url = 'https://replicate.com/api/predictions' body = { "version": version, "input": { property_name_array[0]: input1, property_name_array[1]: input2, property_name_array[2]: input2, property_name_array[3]: input4, property_name_array[4]: input5, property_name_array[5]: input6, property_name_array[6]: input7, property_name_array[7]: input8, property_name_array[8]: input9, property_name_array[9]: input10, property_name_array[10]: input11, property_name_array[11]: input12, property_name_array[12]: input13, property_name_array[13]: input14, } } response = requests.post(url, json=body) print(response.status_code) if response.status_code == 201: response_data = response.json() get_url = response_data.get('urls','').get('get','') identifier = 'https://replicate.com/api/predictions/'+get_url.split("/")[-1] print(identifier,'') time.sleep(3) output =verify_image(identifier) print(output,'333') if output: return gr.Image(value=output[-1]) return gr.Image() def cancel_process(input1, input2, input3, input4, input5, input6, input7, input8, input9, input10, input11, input12, input13, input14,input15, input16, input17, input18, input19, input20, input21, input22, input23, input24, input25, input26, input27, input28, input29, input30, input31, input32, input33, input34, input35, input36, input37, input38, input39, input40, input41, input42, input43): global cancel_url cancel_url = '123' global output_image return gr.Image(value=output_image) def verify_image(get_url): res = requests.get(get_url) if res.status_code == 200: res_data = res.json() if res_data.get('error',''): return else: if cancel_url: return else: output = res_data.get('output', []) print(output,'111') if output: print(output,'222') return output else: time.sleep(1) val = verify_image(get_url) return val else: return [] run_btn.click(run_process, inputs=inputs, outputs=outputs, api_name="run") cancel_btn.click(cancel_process, inputs=inputs, outputs=outputs, api_name="cancel") demo.launch()