init

app.py

@@ -98,28 +98,27 @@ def bot(messages):
 with gr.Blocks() as demo:
     gr.Markdown("<h1><center>HuggingGPT</center></h1>")
     gr.Markdown("<p align='center'><img src='https://i.ibb.co/qNH3Jym/logo.png' height='25' width='95'></p>")
-
     gr.Markdown("<p align='center' style='font-size: 20px;'>A system to connect LLMs with ML community. See our <a href='https://github.com/microsoft/JARVIS'>Project</a> and <a href='http://arxiv.org/abs/2303.17580'>Paper</a>.</p>")
-    with gr.Row().style(equal_height=True):
+    with gr.Row().style():
         with gr.Column(scale=0.85):
             openai_api_key = gr.Textbox(
                 show_label=False,
                 placeholder="Set your OpenAI API key here and press Enter",
                 lines=1,
                 type="password",
-            )
+            ).style(container=False)
         with gr.Column(scale=0.15, min_width=0):
             btn1 = gr.Button("Submit").style(full_height=True)
 
     chatbot = gr.Chatbot([], elem_id="chatbot").style(height=500)
 
-    with gr.Row().style(equal_height=True):
+    with gr.Row().style():
         with gr.Column(scale=0.85):
             txt = gr.Textbox(
                 show_label=False,
                 placeholder="Enter text and press enter. The url of the multimedia resource must contain the extension name.",
                 lines=1,
-            )
+            ).style(container=False)
         with gr.Column(scale=0.15, min_width=0):
             btn2 = gr.Button("Send").style(full_height=True)
 

models_server.py

@@ -67,8 +67,10 @@ if config["proxy"]:
 
 start = time.time()
 
+# local_models = "models/"
 local_models = ""
 
+
 def load_pipes(local_deployment):
     other_pipes = {}
     standard_pipes = {}
@@ -266,29 +268,24 @@ def load_pipes(local_deployment):
             f"{local_models}runwayml/stable-diffusion-v1-5", controlnet=controlnet, torch_dtype=torch.float16
         )
 
-        def mlsd_control_network():
-            model = MobileV2_MLSD_Large()
-            model.load_state_dict(torch.load(f"{local_models}lllyasviel/ControlNet/annotator/ckpts/mlsd_large_512_fp32.pth"), strict=True)
-            return MLSDdetector(model)
-
 
-        hed_network = Network(f"{local_models}lllyasviel/ControlNet/annotator/ckpts/network-bsds500.pth")
+        hed_network = HEDdetector.from_pretrained('lllyasviel/ControlNet')
 
         controlnet_sd_pipes = {
             "openpose-control": {
-                "model": OpenposeDetector(Body(f"{local_models}lllyasviel/ControlNet/annotator/ckpts/body_pose_model.pth"))
+                "model": OpenposeDetector.from_pretrained('lllyasviel/ControlNet')
             },
             "mlsd-control": {
-                "model": mlsd_control_network()
+                "model": MLSDdetector.from_pretrained('lllyasviel/ControlNet')
             },
             "hed-control": {
-                "model": HEDdetector(hed_network)
+                "model": hed_network
             },
             "scribble-control": {
-                "model": HEDdetector(hed_network)
+                "model": hed_network
             },
             "midas-control": {
-                "model": MidasDetector(model_path=f"{local_models}lllyasviel/ControlNet/annotator/ckpts/dpt_hybrid-midas-501f0c75.pt")
+                "model": MidasDetector.from_pretrained('lllyasviel/ControlNet')
             },
             "canny-control": {
                 "model": CannyDetector()