Update app.py

app.py

@@ -8,19 +8,6 @@ import re
 hf_token = os.environ.get("HF_TOKEN")
 from gradio_client import Client
 
-
-def safety_check(user_prompt):
-    
-    client = Client("fffiloni/safety-checker-bot", hf_token=hf_token)
-    response = client.predict(
-    		source_space="consistent-character space",
-    		user_prompt=user_prompt,
-    		api_name="/infer"
-    )
-    print(response)
-    
-    return response
-
 from utils.gradio_helpers import parse_outputs, process_outputs
 
 names = ['prompt', 'negative_prompt', 'subject', 'number_of_outputs', 'number_of_images_per_pose', 'randomise_poses', 'output_format', 'output_quality', 'seed']
@@ -34,57 +21,42 @@ def predict(request: gr.Request, *args, progress=gr.Progress(track_tqdm=True)):
         raise gr.Error(f"You forgot to provide a prompt.")
     
     try:
+        # Safety check is removed here
         
-        is_safe = safety_check(args[0])
-        print(is_safe)
-    
-        match = re.search(r'\bYes\b', is_safe)
-    
-        if match:
-            status = 'Yes'
-        else:
-            status = None
-    
-        if status == "Yes" :
-            raise gr.Error("Do not ask for such things.")
-        else:
-    
-            headers = {'Content-Type': 'application/json'}
-    
-            payload = {"input": {}}
-        
-        
-            base_url = "http://0.0.0.0:7860"
-            for i, key in enumerate(names):
-                value = args[i]
-                if value and (os.path.exists(str(value))):
-                    value = f"{base_url}/file=" + value
-                if value is not None and value != "":
-                    payload["input"][key] = value
-    
-            response = requests.post("http://0.0.0.0:5000/predictions", headers=headers, json=payload)
+        headers = {'Content-Type': 'application/json'}
     
+        payload = {"input": {}}
         
-            if response.status_code == 201:
-                follow_up_url = response.json()["urls"]["get"]
+        base_url = "http://0.0.0.0:7860"
+        for i, key in enumerate(names):
+            value = args[i]
+            if value and (os.path.exists(str(value))):
+                value = f"{base_url}/file=" + value
+            if value is not None and value != "":
+                payload["input"][key] = value
+
+        response = requests.post("http://0.0.0.0:5000/predictions", headers=headers, json=payload)
+
+        if response.status_code == 201:
+            follow_up_url = response.json()["urls"]["get"]
+            response = requests.get(follow_up_url, headers=headers)
+            while response.json()["status"] != "succeeded":
+                if response.json()["status"] == "failed":
+                    raise gr.Error("The submission failed!")
                 response = requests.get(follow_up_url, headers=headers)
-                while response.json()["status"] != "succeeded":
-                    if response.json()["status"] == "failed":
-                        raise gr.Error("The submission failed!")
-                    response = requests.get(follow_up_url, headers=headers)
-                    time.sleep(1)
-            if response.status_code == 200:
-                json_response = response.json()
-                #If the output component is JSON return the entire output response 
-                if(outputs[0].get_config()["name"] == "json"):
-                    return json_response["output"]
-                predict_outputs = parse_outputs(json_response["output"])
-                processed_outputs = process_outputs(predict_outputs)        
-                return tuple(processed_outputs) if len(processed_outputs) > 1 else processed_outputs[0]
-            else:
-                if(response.status_code == 409):
-                    raise gr.Error(f"Sorry, the Cog image is still processing. Try again in a bit.")
-                raise gr.Error(f"The submission failed! Error: {response.status_code}")
+                time.sleep(1)
+        if response.status_code == 200:
+            json_response = response.json()
+            # If the output component is JSON return the entire output response 
+            if(outputs[0].get_config()["name"] == "json"):
+                return json_response["output"]
+            predict_outputs = parse_outputs(json_response["output"])
+            processed_outputs = process_outputs(predict_outputs)        
+            return tuple(processed_outputs) if len(processed_outputs) > 1 else processed_outputs[0]
+        else:
+            if(response.status_code == 409):
+                raise gr.Error(f"Sorry, the Cog image is still processing. Try again in a bit.")
+            raise gr.Error(f"The submission failed! Error: {response.status_code}")
 
     except Exception as e:
         # Handle any other type of error
@@ -173,4 +145,3 @@ with gr.Blocks(css=css) as app:
     )
 
 app.queue(max_size=12, api_open=False).launch(share=False, show_api=False, show_error=True)
-