Create app.py

app.py

@@ -0,0 +1,193 @@
+import requests
+import os
+import gradio as gr
+from huggingface_hub import HfApi
+from slugify import slugify
+import gradio as gr
+import uuid
+from typing import Optional
+
+def get_json_data(url):
+    api_url = f"https://civitai.com/api/v1/models/{url.split('/')[4]}"
+    try:
+        response = requests.get(api_url)
+        response.raise_for_status()
+        return response.json()
+    except requests.exceptions.RequestException as e:
+        print(f"Error fetching JSON data: {e}")
+        return None
+
+def check_nsfw(json_data):
+    if json_data["nsfw"]:
+        return False
+    for model_version in json_data["modelVersions"]:
+        for image in model_version["images"]:
+            if image["nsfw"] != "None":
+                return False
+    return True
+
+def extract_info(json_data):
+    if json_data["type"] == "LORA":
+        for model_version in json_data["modelVersions"]:
+            if model_version["baseModel"] in ["SDXL 1.0", "SDXL 0.9"]:
+                for file in model_version["files"]:
+                    if file["primary"]:
+                        info = {
+                            "urls_to_download": [
+                                {"url": file["downloadUrl"], "filename": file["name"], "type": "weightName"},
+                                {"url": model_version["images"][0]["url"], "filename": os.path.basename(model_version["images"][0]["url"]), "type": "imageName"}
+                            ],
+                            "id": model_version["id"],
+                            "modelId": model_version["modelId"],
+                            "name": json_data["name"],
+                            "description": json_data["description"],
+                            "trainedWords": model_version["trainedWords"],
+                            "creator": json_data["creator"]["username"]
+                        }
+                        return info
+    return None
+
+def download_files(info, folder="."):
+    downloaded_files = {
+        "imageName": [],
+        "weightName": []
+    }
+    for item in info["urls_to_download"]:
+        download_file(item["url"], item["filename"], folder)
+        downloaded_files[item["type"]].append(item["filename"])
+    return downloaded_files
+
+def download_file(url, filename, folder="."):
+    try:
+        response = requests.get(url)
+        response.raise_for_status()
+        with open(f"{folder}/{filename}", 'wb') as f:
+            f.write(response.content)
+        print(f"{filename} downloaded.")
+    except requests.exceptions.RequestException as e:
+        print(f"Error downloading file: {e}")
+
+def process_url(url, folder="."):
+    json_data = get_json_data(url)
+    if json_data:
+        if check_nsfw(json_data):
+            info = extract_info(json_data)
+            if info:
+                downloaded_files = download_files(info, folder)
+                return info, downloaded_files
+            else:
+                print("No model met the criteria.")
+        else:
+            print("NSFW content found.")
+    else:
+        print("Failed to get JSON data.")
+
+def create_readme(info, downloaded_files, is_author, folder="."):
+    readme_content = ""
+    original_url = f"https://civitai.com/models/{info['id']}"
+    non_author_disclaimer = f'This model was originally uploaded on [CivitAI]({original_url}), by [{info["creator"]}](https://civitai.com/user/{info["creator"]}/models). The information below was provided by the author on CivitAI:'
+    content = f"""---
+license: other
+tags:
+  - text-to-image
+  - stable-diffusion
+  - lora
+  - diffusers
+base_model: stabilityai/stable-diffusion-xl-base-1.0
+instance_prompt: {info["trainedWords"][0]}
+widget:
+  - text: {info["trainedWords"][0]}
+---
+
+# {info["name"]}
+
+{non_author_disclaimer if not is_author else ''}
+
+![Image]({downloaded_files["imageName"][0]})
+
+{info["description"]}
+"""
+    readme_content += content + "\n"
+
+    with open(f"{folder}/README.md", "w") as file:
+        file.write(readme_content)
+
+
+def upload_civit_to_hf(profile: Optional[gr.OAuthProfile], url, is_author, progress=gr.Progress(track_tqdm=True)):
+    if not profile.name:
+        return gr.Error("Are you sure you are logged in?")
+    
+    folder = str(uuid.uuid4())
+    os.makedirs(folder, exist_ok=False)
+    info, downloaded_files = process_url(url, folder)
+    create_readme(info, downloaded_files, False, folder)
+    try:
+        api = HfApi(token=hf_token)
+        username = api.whoami()["name"]
+        slug_name = slugify(info["name"])
+        repo_id = f"{username}/{slug_name}"
+        api.create_repo(repo_id=repo_id, private=True, exist_ok=True)
+        api.upload_folder(
+            folder_path=folder,
+            repo_id=repo_id,
+            repo_type="model"
+        )
+    except:
+        raise gr.Error("something went wrong")
+    return "Model uploaded!"
+
+def swap_fill(profile: Optional[gr.OAuthProfile]):
+    if profile is None:
+        return gr.update(visible=True), gr.update(visible=False)
+    else:
+        return gr.update(visible=False), gr.update(visible=True)
+    
+css = '''
+#login {
+    font-size: 0px;
+    width: 100% !important;
+    margin: 0 auto;
+}
+#login:after {
+    content: 'Authorize this app before uploading your model';
+    visibility: visible;
+    display: block;
+    font-size: var(--button-large-text-size);
+}
+#login:disabled{
+    font-size: var(--button-large-text-size);
+}
+#login:disabled:after{
+    content:''
+}
+#disabled_upload{
+    opacity: 0.5;
+    pointer-events:none;
+}
+'''
+
+with gr.Blocks(css=css) as demo:
+    gr.LoginButton(elem_id="login")
+    with gr.Column(elem_id="disabled_upload") as disabled_area:
+        with gr.Row():
+                        submit_source_civit = gr.Textbox(
+                            label="CivitAI model URL",
+                            info="URL of the CivitAI model, make sure it is a SDXL LoRA",
+                        )
+                        is_author = gr.Checkbox(label="Are you the model author?", info="If you are not the author, a disclaimer with information about the author and the CivitAI source will be added", value=False)
+        submit_button_civit = gr.Button("Upload model to Hugging Face and submit")
+        output = gr.Textbox(label="Output progress")
+    with gr.Column(visible=False) as enabled_area:
+        with gr.Row():
+                        submit_source_civit = gr.Textbox(
+                            label="CivitAI model URL",
+                            info="URL of the CivitAI model, make sure it is a SDXL LoRA",
+                        )
+                        is_author = gr.Checkbox(label="Are you the model author?", info="If you are not the author, a disclaimer with information about the author and the CivitAI source will be added", value=False)
+        submit_button_civit = gr.Button("Upload model to Hugging Face")
+        output = gr.Textbox(label="Output progress")
+    demo.load(fn=swap_fill, outputs=[disabled_area, enabled_area])
+    submit_button_civit.click(fn=upload_civit_to_hf, inputs=[submit_source_civit, is_author], outputs=[output])
+    
+demo.queue()
+demo.launch(share=True)