allowing multiple lora adapters now

app.py

@@ -173,25 +173,39 @@ def adapters_textual_inversion_change(adapter_textual_inversion, config):
     
     return adapter_textual_inversion_description, in_adapters_textual_inversion_token, config, config, assemble_code(config)
 
-def adapters_lora_change(adapter_lora, config):
+def adapters_lora_change(adapter_loras, config):
     
-    if str(adapter_lora) != 'None' and str(adapter_lora) != 'null' and type(adapter_lora) != list:
-        
-        adapter_lora_description = adapters['lora'][adapter_lora]['description']
-        adapter_lora_token = adapters['lora'][adapter_lora]['token']
-        adapter_lora_weight = adapters['lora'][adapter_lora]['weight']
+    if len(adapter_loras) > 0:
         
+        adapter_lora_description = '; '.join([adapters['lora'][adapter_lora]['description'] for adapter_lora in adapter_loras])
+        adapter_lora_token = [adapters['lora'][adapter_lora]['token'] for adapter_lora in adapter_loras]
+        adapter_lora_weight = [adapters['lora'][adapter_lora]['weight'] for adapter_lora in adapter_loras]
+        adapter_lora_balancing = {}
+        for adapter_lora in adapter_loras:
+            if not adapter_lora in config['adapter_lora_balancing']:
+                adapter_lora_balancing[adapter_lora] = 1
+            else:
+                adapter_lora_balancing[adapter_lora] = config['adapter_lora_balancing'][adapter_lora]
+
     else:
-        adapter_lora_description = ""
-        adapter_lora_token = ""
-        adapter_lora_weight = ""
+        adapter_lora_description = []
+        adapter_lora_token = []
+        adapter_lora_weight = []
+        adapter_lora_balancing = {}
     
-    config = set_config(config, 'adapter_lora', adapter_lora)
+    config = set_config(config, 'adapter_lora', adapter_loras)
     config = set_config(config, 'adapter_lora_token', adapter_lora_token)
     config = set_config(config, 'adapter_lora_weight', adapter_lora_weight)
+    config = set_config(config, 'adapter_lora_balancing', adapter_lora_balancing)
     
-    return adapter_lora_description, adapter_lora_token, adapter_lora_weight, config, config, assemble_code(config)
+    return adapter_lora_description, adapter_lora_token, adapter_lora_weight, adapter_lora_balancing, config, config, assemble_code(config)
+
+def adapters_lora_balancing_change(adapter_lora_balancing, config):
+
+    config = set_config(config, 'adapter_lora_balancing', json.loads(adapter_lora_balancing.replace("'", '"').replace('None', 'null').replace('False', 'False')))
 
+    return config, config, assemble_code(config)
+    
 def textual_inversion_token_change(adapter_textual_inversion_token, config):
     
     config = set_config(config, 'adapter_textual_inversion_token', adapter_textual_inversion_token)
@@ -263,15 +277,21 @@ def run_inference(config, config_history, pipeline, progress=gr.Progress(track_t
             pipeline.load_textual_inversion(config["adapter_textual_inversion"], token=config["adapter_textual_inversion_token"])
         
         # LoRA
-        if str(config["adapter_lora"]).lower() != 'none' and str(config["adapter_lora"]).lower() != 'null':
-            if str(config["adapter_lora_weight"]).lower() != 'none':
-                pipeline.load_lora_weights(config["adapter_lora"], weight_name=config["adapter_lora_weight"], token=config["adapter_lora_token"])
-            else:
-                pipeline.load_lora_weights(config["adapter_lora"], token=config["adapter_lora_token"])
+        if len(config["adapter_lora"]) > 0 and len(config["adapter_lora"]) == len(config["adapter_lora_weight"]):
+            adapter_lora_balancing = []
+            for adapter_lora_index, adapter_lora in enumerate(config["adapter_lora"]):
+                if str(config["adapter_lora_weight"][adapter_lora_index]).lower() != 'none':
+                    pipeline.load_lora_weights(adapter_lora, weight_name=config["adapter_lora_weight"][adapter_lora_index], adapter_name=config["adapter_lora_token"][adapter_lora_index])
+                else:
+                    pipeline.load_lora_weights(adapter_lora, adapter_name=config["adapter_lora_token"][adapter_lora_index])
+                adapter_lora_balancing.append(config["adapter_lora_balancing"][adapter_lora])
+        
+            adapter_weights = {adapter_lora_balancing}
+            pipeline.set_adapters({config["adapter_lora_token"]}, adapter_weights=adapter_weights)
             
         progress((3,3), desc="Creating the result...")
 
-        prompt = config["prompt"] + config["trigger_token"] + config["adapter_textual_inversion_token"] + config["adapter_lora_token"]
+        prompt = config["prompt"] + config["trigger_token"] + config["adapter_textual_inversion_token"] + ' '.join(config["adapter_lora_token"])
         
         image = pipeline(
             prompt = prompt,
@@ -319,9 +339,9 @@ js = '''function js(){
             return [adapter_textual_inversion, null, adapter_textual_inversion, config, null]
         }
         window.set_adapter_lora_cookie = function(adapter_lora, config){
-            document.cookie = 'adapter_lora='+ adapter_lora+'; Path=/; SameSite=Strict';
+            document.cookie = 'adapter_lora='+ JSON.stringify(adapter_lora)+'; Path=/; SameSite=Strict';
             // some things I just don't understand, this is one of them
-            return [adapter_lora, null, null, adapter_lora, config, null]
+            return [adapter_lora, null, null, null, adapter_lora, config, null]
         }
         window.set_cookie_2 = function(key, value, config){
             document.cookie = key+'='+value+'; Path=/; SameSite=Strict';
@@ -400,10 +420,12 @@ with gr.Blocks(analytics_enabled=False) as demo:
     with gr.Row():
         gr.Markdown('(Low-Rank-Adaption is a performant fine tuning technique)')
     with gr.Row():
-        in_adapters_lora = gr.Dropdown(value="None", choices=list(adapters['lora'].keys()), label="LoRA Adapter", info="leave empty to not use an adapter")
-        in_adapters_lora_token = gr.Textbox(value="None", label="Token", info="required to activate the token, will be added to your prompt")
-        in_adapters_lora_weight = gr.Textbox(value="", label="Description")
+        in_adapters_lora = gr.Dropdown(value="None", choices=list(adapters['lora'].keys()), multiselect=True, label="LoRA Adapter", info="leave empty to not use an adapter")
         out_adapters_lora_description = gr.Textbox(value="", label="Description")
+    with gr.Row():
+        in_adapters_lora_token = gr.Textbox(value="None", label="Token(s)", info="required to activate the token, will be added to your prompt")
+        in_adapters_lora_weight = gr.Textbox(value="", label="Weight(s)/Checkpoint(s)")
+        in_adapters_lora_balancing = gr.Textbox(value={}, label="Balancing", info="provide a list of balancing weights in the order of your LoRA adapter (according to `token`s)")
         
     gr.Markdown("### Inference settings")
     with gr.Row():
@@ -432,7 +454,7 @@ with gr.Blocks(analytics_enabled=False) as demo:
     in_schedulers.change(schedulers_change, inputs=[in_schedulers, config], outputs=[out_scheduler_description, config, out_config, out_code], js="(value, config) => set_cookie_2('scheduler', value, config)")
     in_auto_encoders.change(auto_encoders_change, inputs=[in_auto_encoders, config], outputs=[out_auto_encoder_description, config, out_config, out_code], js="(value, config) => set_cookie_2('auto_encoder', value, config)")
     in_adapters_textual_inversion.change(adapters_textual_inversion_change, inputs=[in_adapters_textual_inversion, config], outputs=[out_adapters_textual_inversion_description, in_adapters_textual_inversion_token, config, out_config, out_code], js="(adapter_textual_inversion, config) => set_adapter_textual_inversion_cookie(adapter_textual_inversion, config)")
-    in_adapters_lora.change(adapters_lora_change, inputs=[in_adapters_lora, config], outputs=[out_adapters_lora_description, in_adapters_lora_token, in_adapters_lora_weight, config, out_config, out_code], js="(adapter_lora, config) => set_adapter_lora_cookie(adapter_lora, config)")
+    in_adapters_lora.change(adapters_lora_change, inputs=[in_adapters_lora, config], outputs=[out_adapters_lora_description, in_adapters_lora_token, in_adapters_lora_weight, in_adapters_lora_balancing, config, out_config, out_code], js="(adapter_lora, config) => set_adapter_lora_cookie(adapter_lora, config)")
     
     # `GENERIC` CHANGE LISTENERS, SAME INPUT, SAME OUTPUT STRUCTURE
     in_devices.change(fn=device_change, inputs=[in_devices, config], outputs=[config, out_config, out_code], js="(value, config) => set_cookie('device', value, config)")
@@ -448,7 +470,8 @@ with gr.Blocks(analytics_enabled=False) as demo:
     in_guidance_scale.change(guidance_scale_change, inputs=[in_guidance_scale, config], outputs=[config, out_config, out_code], js="(value, config) => set_cookie('guidance_scale', value, config)")
     in_enable_vae_slicing.change(enable_vae_slicing_change, inputs=[in_enable_vae_slicing, config], outputs=[config, out_config, out_code], js="(value, config) => set_cookie('enable_vae_slicing', value, config)")
     in_enable_vae_tiling.change(enable_vae_tiling_change, inputs=[in_enable_vae_tiling, config], outputs=[config, out_config, out_code], js="(value, config) => set_cookie('enable_vae_tiling', value, config)")
-    in_adapters_textual_inversion_token.change(textual_inversion_token_change, inputs=[in_adapters_textual_inversion_token, config], outputs=[config, out_config, out_code])
+    # in_adapters_textual_inversion_token.change(textual_inversion_token_change, inputs=[in_adapters_textual_inversion_token, config], outputs=[config, out_config, out_code])
+    in_adapters_lora_balancing.change(adapters_lora_balancing_change, inputs=[in_adapters_lora_balancing, config], outputs=[config, out_config, out_code], js="(value, config) => set_cookie('adapter_lora_balancing', value, config)")
     in_prompt.change(prompt_change, inputs=[in_prompt, config], outputs=[config, out_config, out_code], js="(value, config) => set_cookie('prompt', value, config)")
     in_trigger_token.change(trigger_token_change, inputs=[in_trigger_token, config], outputs=[config, out_config, out_code], js="(value, config) => set_cookie('trigger_token', value, config)")
     in_negative_prompt.change(negative_prompt_change, inputs=[in_negative_prompt, config], outputs=[config, out_config, out_code], js="(value, config) => set_cookie('negative_prompt', value, config)")
@@ -484,7 +507,8 @@ with gr.Blocks(analytics_enabled=False) as demo:
             in_adapters_textual_inversion_token,
             in_adapters_lora,
             in_adapters_lora_token,
-            in_adapters_lora_weight
+            in_adapters_lora_weight,
+            in_adapters_lora_balancing,
             ])
 
 demo.launch(show_error=True)

appConfig.json

@@ -79,7 +79,6 @@
             }
         },
         "lora": {
-            "None": {"token": "", "description": "", "weight": ""},
             "nerijs/pixel-art-xl": {
                 "token": "pixel",
                 "weight": "pixel-art-xl.safetensors",

config.py

@@ -54,9 +54,10 @@ def get_initial_config():
         "guidance_scale": 5,
         "adapter_textual_inversion": None,
         "adapter_textual_inversion_token": None,
-        "adapter_lora": None,
-        "adapter_lora_token": None,
-        "adapter_lora_weight": None,
+        "adapter_lora": [],
+        "adapter_lora_token": [],
+        "adapter_lora_weight": [],
+        "adapter_lora_balancing": {},
         "prompt": 'A white rabbit',
         "trigger_token": '',
         "negative_prompt": 'lowres, cropped, worst quality, low quality',
@@ -85,7 +86,10 @@ def get_config_from_url(initial_config, request: Request):
         for key in initial_config.keys():
             if key in request.cookies:
                 value = request.cookies[key]
+                # transform empty values to a "Python-like" None
                 if value == 'null' or value == '': value = None
+                # if value expected to be a list, transform the string to list
+                if type(initial_config[key]) == list: value = json.loads(value)
                 initial_config[key] = value
         
         return_config = initial_config
@@ -113,7 +117,8 @@ def get_config_from_url(initial_config, request: Request):
             return_config['adapter_textual_inversion_token'],
             return_config['adapter_lora'],
             return_config['adapter_lora_token'],
-            return_config['adapter_lora_weight']
+            return_config['adapter_lora_weight'],
+            return_config['adapter_lora_balancing']
             ]
         
 def load_app_config():
@@ -207,13 +212,20 @@ def assemble_code(str_config):
     # ADAPTER
     if str(config["adapter_textual_inversion"]).lower() != 'none':
         code.append(f'pipeline.load_textual_inversion("{config["adapter_textual_inversion"]}", token="{config["adapter_textual_inversion_token"]}")')
-    if str(config["adapter_lora"]).lower() != 'none':
-        if str(config["adapter_lora_weight"]).lower() != 'none':
-            code.append(f'pipeline.load_lora_weights("{config["adapter_lora"]}", weight_name="{config["adapter_lora_weight"]}", adapter_name="{config["adapter_lora_token"]}")')
-        else:
-            code.append(f'pipeline.load_lora_weights("{config["adapter_lora"]}", adapter_name="{config["adapter_lora_token"]}")')
 
-    code.append(f'prompt = "{config["prompt"]} {config["trigger_token"]} {config["adapter_textual_inversion_token"]} {config["adapter_lora_token"]}"')
+    if len(config["adapter_lora"]) > 0 and len(config["adapter_lora"]) == len(config["adapter_lora_weight"]):
+        adapter_lora_balancing = []
+        for adapter_lora_index, adapter_lora in enumerate(config["adapter_lora"]):
+            if str(config["adapter_lora_weight"][adapter_lora_index]).lower() != 'none':
+                code.append(f'pipeline.load_lora_weights("{adapter_lora}", weight_name="{config["adapter_lora_weight"][adapter_lora_index]}", adapter_name="{config["adapter_lora_token"][adapter_lora_index]}")')
+            else:
+                code.append(f'pipeline.load_lora_weights("{adapter_lora}", adapter_name="{config["adapter_lora_token"][adapter_lora_index]}")')
+            adapter_lora_balancing.append(config["adapter_lora_balancing"][adapter_lora])
+    
+        code.append(f'adapter_weights = {adapter_lora_balancing}')
+        code.append(f'pipeline.set_adapters({config["adapter_lora_token"]}, adapter_weights=adapter_weights)')
+
+    code.append(f'prompt = "{config["prompt"]} {config["trigger_token"]} {config["adapter_textual_inversion_token"]} {" ".join(config["adapter_lora_token"])}"')
     code.append(f'negative_prompt = "{config["negative_prompt"]}"')
     code.append(f'inference_steps = {config["inference_steps"]}')
     code.append(f'guidance_scale = {config["guidance_scale"]}')