Create app.py

app.py

@@ -0,0 +1,223 @@
+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 = "andreasjansson"
+    name = "clip-features"
+    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, 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 = []
+
+            output_result = data.get("default_example", '').get("output")
+            output_type= schema.get("Output", '').get("type", '')
+            if output_type == 'array':
+                    output_image =  output_result
+            else:
+                output_image = output_result
+            print (output_image)
+            outputs.append(gr.TextArea(value=output_image))
+            outputs.append(gr.Image(visible=False))
+            outputs.append(gr.Image(visible=False))
+            outputs.append(gr.Image(visible=False))
+            
+           
+    
+    def run_process(input1 ):
+       global cancel_url
+       global property_name_array
+       print(len(property_name_array))
+       cancel_url=''
+       url = 'https://replicate.com/api/predictions'
+      
+
+       print(version, 'version')
+       body = {
+            "version": "75b33f253f7714a281ad3e9b28f63e3232d583716ef6718f2e46641077ea040a",
+            "input": {
+                    property_name_array[0]: input1,
+                 
+            }
+            }
+               
+    
+       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.TextArea(value=output), gr.Image(),gr.Image(),gr.Image()
+                
+       return gr.Image(),gr.Image(visible=False),gr.Image(visible=False),gr.Image(visible=False)
+    
+    def cancel_process(input1):
+        global cancel_url
+        cancel_url = '123'
+        global output_image
+        return gr.TextArea(value=output_image), 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()
+
+
+         
+
+