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| import gradio as gr | |
| from requests.exceptions import ConnectTimeout | |
| import time | |
| import requests | |
| import base64 | |
| global headers | |
| global cancel_url | |
| global path | |
| 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 = "lucataco" | |
| name = "sdxl-deepcache" | |
| 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 : | |
| 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, type="filepath")) | |
| else : | |
| inputs.insert(order, gr.Image(label=label, type="filepath")) | |
| 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 = [] | |
| outputs.append(gr.Image(value='https://replicate.delivery/pbxt/cj5eFwQqZPwROSKox75sbAVEJvfs58GX2Tswlu5tYzWwdLKSA/out-0.png')) | |
| outputs.append(gr.Image(visible=False)) | |
| outputs.append(gr.Image(visible=False)) | |
| outputs.append(gr.Image(visible=False)) | |
| def run_process(input1,input2,input3,input4,input5,input6,input7, input8, input9,input10,input11,input12, input13,input14, input15): | |
| global cancel_url | |
| cancel_url='' | |
| url = 'https://replicate.com/api/predictions' | |
| if input3: | |
| with open(input3, "rb") as file: | |
| data = file.read() | |
| base64_data = base64.b64encode(data).decode("utf-8") | |
| mimetype = "image/jpg" | |
| data_uri_image = f"data:{mimetype};base64,{base64_data}" | |
| else: | |
| data_uri_image=None | |
| if input4: | |
| with open(input4, "rb") as file: | |
| data = file.read() | |
| base64_data = base64.b64encode(data).decode("utf-8") | |
| mimetype = "image/jpg" | |
| data_uri_mask = f"data:{mimetype};base64,{base64_data}" | |
| else: | |
| data_uri_mask=None | |
| if input3: | |
| if input4: | |
| body = { | |
| "version": version, | |
| "input": { | |
| "prompt": input1, | |
| "negative_prompt": input2, | |
| "image": data_uri_image, | |
| "mask": data_uri_mask, | |
| "width": input5, | |
| "height": input6, | |
| "num_outputs": input7, | |
| "scheduler": input8, | |
| "num_inference_steps": input9, | |
| "guidance_scale": input10, | |
| "prompt_strength":input11, | |
| "seed": input12, | |
| "apply_watermark": input13, | |
| "enable_deepcache": input14 | |
| } | |
| } | |
| else: | |
| body = { | |
| "version": version, | |
| "input": { | |
| "prompt": input1, | |
| "negative_prompt": input2, | |
| "image": data_uri_image, | |
| "width": input5, | |
| "height": input6, | |
| "num_outputs": input7, | |
| "scheduler": input8, | |
| "num_inference_steps": input9, | |
| "guidance_scale": input10, | |
| "prompt_strength":input11, | |
| "seed": input12, | |
| "apply_watermark": input13, | |
| "enable_deepcache": input14 | |
| } | |
| } | |
| else: | |
| if input4: | |
| body = { | |
| "version": version, | |
| "input": { | |
| "prompt": input1, | |
| "negative_prompt": input2, | |
| "mask": data_uri_mask, | |
| "width": input5, | |
| "height": input6, | |
| "num_outputs": input7, | |
| "scheduler": input8, | |
| "num_inference_steps": input9, | |
| "guidance_scale": input10, | |
| "prompt_strength":input11, | |
| "seed": input12, | |
| "apply_watermark": input13, | |
| "enable_deepcache": input14 | |
| } | |
| } | |
| else: | |
| body = { | |
| "version": version, | |
| "input": { | |
| "prompt": input1, | |
| "negative_prompt": input2, | |
| "width": input5, | |
| "height": input6, | |
| "num_outputs": input7, | |
| "scheduler": input8, | |
| "num_inference_steps": input9, | |
| "guidance_scale": input10, | |
| "prompt_strength":input11, | |
| "seed": input12, | |
| "apply_watermark": input13, | |
| "enable_deepcache": 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: | |
| if len(output) == 1: | |
| return gr.Image(value=output[0]), gr.Image(),gr.Image(),gr.Image() | |
| elif len(output) == 2: | |
| return gr.Image(value=output[0]), gr.Image(value=output[1],visible= True),gr.Image(),gr.Image() | |
| elif len(output) == 3: | |
| return gr.Image(value=output[0]), gr.Image(value=output[1],visible= True),gr.Image(value=output[2],visible= True),gr.Image() | |
| elif len(output) == 3: | |
| return gr.Image(value=output[0]), gr.Image(value=output[1],visible= True),gr.Image(value=output[2],visible= True),gr.Image(value=output[2],visible= True) | |
| return gr.Image(),gr.Image(visible=False),gr.Image(visible=False),gr.Image(visible=False) | |
| def cancel_process(input1,input2,input3,input4,input5,input6,input7, input8, input9,input10,input11,input12, input13,input14, input15): | |
| global cancel_url | |
| cancel_url = '123' | |
| return gr.Image(value='https://replicate.delivery/pbxt/cj5eFwQqZPwROSKox75sbAVEJvfs58GX2Tswlu5tYzWwdLKSA/out-0.png'), gr.Image(visible=False),gr.Image(visible=False),gr.Image(visible=False) | |
| 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() | |