anal

app.py

@@ -10,8 +10,8 @@ import requests
 st.title('Stable Diffusion (AI that can imagine)')
 model_id = "CompVis/stable-diffusion-v1-4"
 device = "cuda"
-word_list_dataset = load_dataset("stabilityai/word-list", data_files="list.txt", use_auth_token=True)
-word_list = word_list_dataset["train"]['text']
+# word_list_dataset = load_dataset("stabilityai/word-list", data_files="list.txt", use_auth_token=True)
+# word_list = word_list_dataset["train"]['text']
 
 is_gpu_busy = False
 def infer(prompt):
@@ -19,19 +19,19 @@ def infer(prompt):
     samples = 4
     steps = 50
     scale = 7.5
-    #When running locally you can also remove this filter
-    for filter in word_list:
-        if re.search(rf"\b{filter}\b", prompt):
-            raise st.Error("Unsafe content found. Please try again with different prompts.")
-        images = []
-        url = os.getenv('JAX_BACKEND_URL')
-        payload = {'prompt': prompt}
-        images_request = requests.post(url, json = payload)
-        for image in images_request.json()["images"]:
-            image_b64 = (f"data:image/jpeg;base64,{image}")
-            images.append(image_b64)
-        st.image(images)
-        return images 
+    # #When running locally you can also remove this filter
+    # for filter in word_list:
+    #     if re.search(rf"\b{filter}\b", prompt):
+    #         raise st.Error("Unsafe content found. Please try again with different prompts.")
+    images = []
+    url = os.getenv('JAX_BACKEND_URL')
+    payload = {'prompt': prompt}
+    images_request = requests.post(url, json = payload)
+    for image in images_request.json()["images"]:
+        image_b64 = (f"data:image/jpeg;base64,{image}")
+        images.append(image_b64)
+    st.image(images)
+    return images 
     
     prompt=st.text_input('Enter your prompt')
     true=st.button('Generate')