Upload app.py

app.py

@@ -4,7 +4,7 @@ import numpy as np
 
 # DiffuseCraft
 from dc import (infer, _infer, pass_result, get_diffusers_model_list, get_samplers, save_image_history,
-    get_vaes, enable_model_recom_prompt, enable_diffusers_model_detail, extract_exif_data, esrgan_upscale, UPSCALER_KEYS,
+    get_vaes, enable_diffusers_model_detail, extract_exif_data, esrgan_upscale, UPSCALER_KEYS,
     preset_quality, preset_styles, process_style_prompt, get_all_lora_tupled_list, update_loras, apply_lora_prompt,
     download_my_lora, search_civitai_lora, update_civitai_selection, select_civitai_lora, search_civitai_lora_json,
     get_t2i_model_info, get_civitai_tag, CIVITAI_SORT, CIVITAI_PERIOD, CIVITAI_BASEMODEL,
@@ -204,7 +204,7 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css, delete_cache=(60,
         inputs=[prompt, negative_prompt, seed, randomize_seed, width, height,
                 guidance_scale, num_inference_steps, model_name,
                 lora1, lora1_wt, lora2, lora2_wt, lora3, lora3_wt, lora4, lora4_wt, lora5, lora5_wt,
-                sampler, vae_model, auto_trans, schedule_type, schedule_prediction_type],
+                sampler, vae_model, auto_trans, schedule_type, schedule_prediction_type, recom_prompt],
         outputs=[result],
         queue=True,
         show_progress="full",
@@ -217,7 +217,7 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css, delete_cache=(60,
         inputs=[prompt, negative_prompt, seed, randomize_seed, width, height,
                 guidance_scale, num_inference_steps, model_name,
                 lora1, lora1_wt, lora2, lora2_wt, lora3, lora3_wt, lora4, lora4_wt, lora5, lora5_wt,
-                sampler, vae_model, auto_trans, schedule_type, schedule_prediction_type],
+                sampler, vae_model, auto_trans, schedule_type, schedule_prediction_type, recom_prompt],
         outputs=[result],
         queue=False,
         show_api=True,
@@ -240,7 +240,7 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css, delete_cache=(60,
         inputs=[prompt, negative_prompt, seed, randomize_seed, width, height,
                 guidance_scale, num_inference_steps, model_name,
                 lora1, lora1_wt, lora2, lora2_wt, lora3, lora3_wt, lora4, lora4_wt, lora5, lora5_wt,
-                sampler, vae_model, auto_trans, schedule_type, schedule_prediction_type],
+                sampler, vae_model, auto_trans, schedule_type, schedule_prediction_type, recom_prompt],
         outputs=[result],
         queue=True,
         show_progress="full",
@@ -290,7 +290,7 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css, delete_cache=(60,
     )
     lora_search_civitai_gallery.select(update_civitai_selection, None, [lora_search_civitai_result], queue=False, show_api=False)
 
-    recom_prompt.change(enable_model_recom_prompt, [recom_prompt], [recom_prompt], queue=False, show_api=False)
+    #recom_prompt.change(enable_model_recom_prompt, [recom_prompt], [recom_prompt], queue=False, show_api=False)
     gr.on(
         triggers=[quality_selector.change, style_selector.change],
         fn=process_style_prompt,
@@ -301,7 +301,7 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css, delete_cache=(60,
         show_api=False,
     )
 
-    model_detail.change(enable_diffusers_model_detail, [model_detail, model_name], [model_detail, model_name], queue=False, show_api=False)
+    model_detail.change(enable_diffusers_model_detail, [model_detail, model_name, state], [model_detail, model_name, state], queue=False, show_api=False)
     model_name.change(get_t2i_model_info, [model_name], [model_info], queue=False, show_api=False)
 
     chat_model.change(select_dolphin_model, [chat_model, state], [chat_model, chat_format, chat_model_info, state], queue=True, show_progress="full", show_api=False)\