Upload 5 files

app.py

@@ -1,116 +1,35 @@
 import gradio as gr
-from convert_url_to_diffusers_sdxl_gr import (
-    convert_url_to_diffusers_repo,
-    SCHEDULER_CONFIG_MAP,
-)
-
-vaes = [
-    "",
-    "https://huggingface.co/madebyollin/sdxl-vae-fp16-fix/blob/main/sdxl.vae.safetensors",
-    "https://huggingface.co/nubby/blessed-sdxl-vae-fp16-fix/blob/main/sdxl_vae-fp16fix-blessed.safetensors",
-    "https://huggingface.co/John6666/safetensors_converting_test/blob/main/xlVAEC_e7.safetensors",
-    "https://huggingface.co/John6666/safetensors_converting_test/blob/main/xlVAEC_f1.safetensors",
-]
-loras = [
-    "",
-    "https://huggingface.co/SPO-Diffusion-Models/SPO-SDXL_4k-p_10ep_LoRA/blob/main/spo_sdxl_10ep_4k-data_lora_diffusers.safetensors",
-    "https://huggingface.co/wangfuyun/PCM_Weights/blob/main/sdxl/pcm_sdxl_smallcfg_2step_converted.safetensors",
-    "https://huggingface.co/wangfuyun/PCM_Weights/blob/main/sdxl/pcm_sdxl_smallcfg_4step_converted.safetensors",
-    "https://huggingface.co/wangfuyun/PCM_Weights/blob/main/sdxl/pcm_sdxl_smallcfg_8step_converted.safetensors",
-    "https://huggingface.co/wangfuyun/PCM_Weights/blob/main/sdxl/pcm_sdxl_normalcfg_8step_converted.safetensors",
-    "https://huggingface.co/wangfuyun/PCM_Weights/blob/main/sdxl/pcm_sdxl_normalcfg_16step_converted.safetensors",
-    "https://huggingface.co/ByteDance/Hyper-SD/blob/main/Hyper-SDXL-1step-lora.safetensors",
-    "https://huggingface.co/ByteDance/Hyper-SD/blob/main/Hyper-SDXL-2steps-lora.safetensors",
-    "https://huggingface.co/ByteDance/Hyper-SD/blob/main/Hyper-SDXL-4steps-lora.safetensors",
-    "https://huggingface.co/ByteDance/Hyper-SD/blob/main/Hyper-SDXL-8steps-CFG-lora.safetensors",
-    "https://huggingface.co/ByteDance/Hyper-SD/blob/main/Hyper-SDXL-12steps-CFG-lora.safetensors",
-    "https://huggingface.co/latent-consistency/lcm-lora-sdxl/blob/main/pytorch_lora_weights.safetensors",
-]
-schedulers = list(SCHEDULER_CONFIG_MAP.keys())
-
-preset_dict = {
-    "Default": [True, "", "Euler a", "", 1.0, "", 1.0, "", 1.0, "", 1.0, "", 1.0],
-    "Bake in standard VAE": [True, "https://huggingface.co/madebyollin/sdxl-vae-fp16-fix/blob/main/sdxl.vae.safetensors",
-                              "Euler a", "", 1.0, "", 1.0, "", 1.0, "", 1.0, "", 1.0],
-    "Hyper-SDXL / SPO": [True, "https://huggingface.co/madebyollin/sdxl-vae-fp16-fix/blob/main/sdxl.vae.safetensors",
-     "TCD", "https://huggingface.co/ByteDance/Hyper-SD/blob/main/Hyper-SDXL-8steps-CFG-lora.safetensors", 1.0,
-     "https://huggingface.co/SPO-Diffusion-Models/SPO-SDXL_4k-p_10ep_LoRA/blob/main/spo_sdxl_10ep_4k-data_lora_diffusers.safetensors",
-       1.0, "", 1.0, "", 1.0, "", 1.0],
-}
-
-
-def set_presets(preset: str="Default"):
-    p = []
-    if preset in preset_dict.keys(): p = preset_dict[preset]
-    else: p = preset_dict["Default"]
-    return p[0], p[1], p[2], p[3], p[4], p[5], p[6], p[7], p[8], p[9], p[10], p[11], p[12]
-
+import os
+from convert_repo_to_safetensors_gr import convert_repo_to_safetensors_multi
+os.environ['HF_OUTPUT_REPO'] = 'John6666/safetensors_converting_test'
 
 css = """"""
 
-with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", css=css) as demo:
-    gr.Markdown("# Download and convert any Stable Diffusion XL safetensors to Diffusers and create your repo")
+with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", fill_width=True, css=css, delete_cache=(60, 3600)) as demo:
     gr.Markdown(
-        f"""
-- [A CLI version of this tool (without uploading-related function) is available here](https://huggingface.co/spaces/John6666/sdxl-to-diffusers-v2/tree/main/local).
-        
-**⚠️IMPORTANT NOTICE⚠️**<br>
-From an information security standpoint, it is dangerous to expose your access token or key to others.
-If you do use it, I recommend that you duplicate this space on your own account before doing so.
-Keys and tokens could be set to SECRET (HF_TOKEN, CIVITAI_API_KEY) if it's placed in your own space.
-It saves you the trouble of typing them in.<br>
-<br>
-**The steps are the following**:
-- Paste a write-access token from [hf.co/settings/tokens](https://huggingface.co/settings/tokens).
-- Input a model download url from the Hub or Civitai or other sites.
-- If you want to download a model from Civitai, paste a Civitai API Key.
-- Input your HF user ID. e.g. 'yourid'.
-- Input your new repo name. If empty, auto-complete. e.g. 'newrepo'.
-- Set the parameters. If not sure, just use the defaults.
-- Click "Submit".
-- Patiently wait until the output changes. It takes approximately 2 to 3 minutes (downloading from HF).
-            """
-    )
-    with gr.Column():
-        dl_url = gr.Textbox(label="URL to download", placeholder="https://huggingface.co/bluepen5805/blue_pencil-XL/blob/main/blue_pencil-XL-v7.0.0.safetensors", value="", max_lines=1)
-        hf_user = gr.Textbox(label="Your HF user ID", placeholder="username", value="", max_lines=1)
-        hf_repo = gr.Textbox(label="New repo name", placeholder="reponame", info="If empty, auto-complete", value="", max_lines=1)
-        hf_token = gr.Textbox(label="Your HF write token", placeholder="hf_...", value="", max_lines=1)
-        civitai_key = gr.Textbox(label="Your Civitai API Key (Optional)", info="If you download model from Civitai...", placeholder="", value="", max_lines=1)
-        is_upload_sf = gr.Checkbox(label="Upload single safetensors file into new repo", value=False)
-        is_private = gr.Checkbox(label="Create private repo", value=True, visible=False)
-        presets = gr.Radio(label="Presets", choices=list(preset_dict.keys()), value="Default")
-        with gr.Accordion("Advanced settings", open=False):
-            is_half = gr.Checkbox(label="Half precision", value=True)
-            vae = gr.Dropdown(label="VAE", choices=vaes, value="", allow_custom_value=True)
-            scheduler = gr.Dropdown(label="Scheduler (Sampler)", choices=schedulers, value="Euler a")
-            lora1 = gr.Dropdown(label="LoRA1", choices=loras, value="", allow_custom_value=True)
-            lora1s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA1 weight scale")
-            lora2 = gr.Dropdown(label="LoRA2", choices=loras, value="", allow_custom_value=True)
-            lora2s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA2 weight scale")
-            lora3 = gr.Dropdown(label="LoRA3", choices=loras, value="", allow_custom_value=True)
-            lora3s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA3 weight scale")
-            lora4 = gr.Dropdown(label="LoRA4", choices=loras, value="", allow_custom_value=True)
-            lora4s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA4 weight scale")
-            lora5 = gr.Dropdown(label="LoRA5", choices=loras, value="", allow_custom_value=True)
-            lora5s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA5 weight scale")
-        run_button = gr.Button(value="Submit")
-        repo_urls = gr.CheckboxGroup(visible=False, choices=[], value=None)
-        output_md = gr.Markdown(label="Output")
-    gr.DuplicateButton(value="Duplicate Space")
+            f"""
+    - [A CLI version of this tool is available here](https://huggingface.co/spaces/John6666/convert_repo_to_safetensors/tree/main/local).
+    """)
+    with gr.Column(): 
+        repo_id = gr.Textbox(label="Repo ID", placeholder="author/model", value="", lines=1)
+        is_upload = gr.Checkbox(label="Upload safetensors to HF Repo", info="Fast download, but files will be public.", value=False)
+        with gr.Accordion("Advanced", open=False):
+            dtype = gr.Radio(label="Output data type", choices=["fp16", "fp32", "bf16", "default"], value="fp16")
+            hf_token = gr.Textbox(label="Your HF write token", placeholder="hf_...", value="", max_lines=1)
+            with gr.Row():
+                newrepo_id = gr.Textbox(label="Upload repo ID", placeholder="author/model", value="", max_lines=1)
+                newrepo_type = gr.Radio(label="Upload repo type", choices=["model", "dataset"], value="model")
+                is_private = gr.Checkbox(label="Create / Use private repo", value=True)
+        uploaded_urls = gr.CheckboxGroup(visible=False, choices=[], value=None) # hidden
+        run_button = gr.Button(value="Convert")
+        st_file = gr.Files(label="Output", interactive=False)
+        st_md = gr.Markdown()
 
     gr.on(
-        triggers=[run_button.click],
-        fn=convert_url_to_diffusers_repo,
-        inputs=[dl_url, hf_user, hf_repo, hf_token, civitai_key, is_private, is_upload_sf, repo_urls, is_half, vae, scheduler,
-                 lora1, lora1s, lora2, lora2s, lora3, lora3s, lora4, lora4s, lora5, lora5s],
-        outputs=[repo_urls, output_md],
-    )
-    presets.change(
-        fn=set_presets,
-        inputs=[presets],
-        outputs=[is_half, vae, scheduler, lora1, lora1s, lora2, lora2s, lora3, lora3s, lora4, lora4s, lora5, lora5s],
-        queue=False,
+        triggers=[repo_id.submit, run_button.click],
+        fn=convert_repo_to_safetensors_multi,
+        inputs=[repo_id, hf_token, st_file, uploaded_urls, dtype, is_upload, newrepo_id, newrepo_type, is_private],
+        outputs=[st_file, uploaded_urls, st_md],
     )
 
 demo.queue()

convert_repo_to_safetensors_gr.py

@@ -374,6 +374,7 @@ def upload_safetensors_to_repo(filename, repo_id, repo_type, is_private, progres
         url = hf_hub_url(repo_id=repo_id, repo_type=repo_type, filename=output_filename, token=get_token())
     except Exception as e:
         print(f"Error: Failed to upload to {repo_id}. {e}")
+        gr.Warning(print(f"Error: Failed to upload to {repo_id}. {e}"))
         return None
     return url
 
@@ -381,8 +382,8 @@ def upload_safetensors_to_repo(filename, repo_id, repo_type, is_private, progres
 def convert_repo_to_safetensors(repo_id, dtype="fp16", progress=gr.Progress(track_tqdm=True)):
     download_dir = f"{repo_id.split('/')[0]}_{repo_id.split('/')[-1]}"
     output_filename = f"{repo_id.split('/')[0]}_{repo_id.split('/')[-1]}.safetensors"
-    download_repo(repo_id, download_dir)
-    convert_diffusers_to_safetensors(download_dir, output_filename, dtype)
+    download_repo(repo_id, download_dir, progress)
+    convert_diffusers_to_safetensors(download_dir, output_filename, dtype, progress)
     return output_filename