bug in gradio 4.40.0: index.js:288 Could not get api details: Failed to execute 'fetch' on 'Window': Failed to parse URL from http://127.0.0.1:7860http://127.0.0.1:7860/info

[fgtm2023]

Peace, gradio keep loading forever after local URL: http://127.0.0.1:7860 is opened, i checked browser console and this is the conole log:

index.js:288 Could not get api details: Failed to execute 'fetch' on 'Window': Failed to parse URL from http://127.0.0.1:7860http://127.0.0.1:7860/info
C @ index.js:288
index.js:1606 Uncaught TypeError: Failed to construct 'URL': Invalid URL
at parseURL (index.js:1606:27)
at isRelativeHrefOnAbsolutePath (index.js:1625:21)
at getRulesSync (index.js:5680:18)
at Object.details (index.js:5799:27)
at index.js:7041:47
at Array.map ()
at index.js:7041:22
at handleStyleOperations (index.js:6222:17)
at handleMinorTreeMutations (index.js:6249:13)
at index.js:479:25

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python launch.py --theme dark --disable-safe-unpickle --disable-xformers
Python 3.10.12 (main, Jul 29 2024, 16:56:48) [GCC 11.4.0]
Version: f2.0.1v1.10.1-previous-456-g0abb6c46
Commit hash: 0abb6c4
Launching Web UI with arguments: --theme dark --disable-safe-unpickle --disable-xformers
Total VRAM 8176 MB, total RAM 19941 MB
pytorch version: 2.5.0.dev20240828+rocm6.2
Set vram state to: NORMAL_VRAM
Device: cuda:0 Radeon RX Vega : native
VAE dtype preferences: [torch.float32] -> torch.float32
CUDA Using Stream: False
2024-08-28 18:12:31.068254: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-08-28 18:12:31.947702: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
Using sub quadratic optimization for cross attention
Using split attention for VAE
ControlNet preprocessor location: /home/abdo/stable-diffusion-webui-forge/models/ControlNetPreprocessor
2024-08-28 18:12:39,676 - ControlNet - INFO - ControlNet UI callback registered.
Using online LoRAs in FP16: False
Running on local URL: http://127.0.0.1:7860

To create a public link, set share=True in launch().
Startup time: 18.2s (prepare environment: 3.1s, import torch: 9.3s, other imports: 0.4s, load scripts: 1.9s, create ui: 2.2s, gradio launch: 1.1s).
Opening in existing browser session.

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my pc specs is:

-OS: Ubuntu 22.04.4 LTS x86_64
-Kernel: 6.8.0-40-generic
-Shell: zsh 5.8.1
-CPU: Intel i7-4790K (8) @ 4.600GHz
-GPU: AMD ATI Radeon RX Vega 56 8GiB
-Memory: 20GiB

-pip list | grep -i rocm
pytorch-triton-rocm 3.0.0+21eae954ef
torch 2.5.0.dev20240828+rocm6.2
torchaudio 2.5.0.dev20240828+rocm6.2
torchvision 0.20.0.dev20240828+rocm6.2

-pip list | grep -i cuda
nvidia-cuda-cupti-cu11 11.7.101
nvidia-cuda-cupti-cu12 12.1.105
nvidia-cuda-nvrtc-cu11 11.7.99
nvidia-cuda-nvrtc-cu12 12.1.105
nvidia-cuda-runtime-cu11 11.7.99
nvidia-cuda-runtime-cu12 12.1.105

-pip list | grep -i amd
amdsmi 24.5.1+c5106a9

-pip list | grep -i torch
lion-pytorch 0.2.2
open-clip-torch 2.20.0
pytorch-ignite 0.5.1
pytorch-lightning 1.9.4
pytorch-triton-rocm 3.0.0+21eae954ef
torch 2.5.0.dev20240828+rocm6.2
torchaudio 2.5.0.dev20240828+rocm6.2
torchdiffeq 0.2.3
torchmetrics 1.4.1
torchsde 0.2.6
torchvision 0.20.0.dev20240828+rocm6.2

-rocminfo
ROCk module is loaded

HSA System Attributes

Runtime Version: 1.13
Runtime Ext Version: 1.4
System Timestamp Freq.: 1000.000000MHz
Sig. Max Wait Duration: 18446744073709551615 (0xFFFFFFFFFFFFFFFF) (timestamp count)
Machine Model: LARGE
System Endianness: LITTLE
Mwaitx: DISABLED
DMAbuf Support: YES

==========
HSA Agents

---

Agent 1

---

Name: Intel(R) Core(TM) i7-4790K CPU @ 4.00GHz
Uuid: CPU-XX
Marketing Name: Intel(R) Core(TM) i7-4790K CPU @ 4.00GHz
Vendor Name: CPU
Feature: None specified
Profile: FULL_PROFILE
Float Round Mode: NEAR
Max Queue Number: 0(0x0)
Queue Min Size: 0(0x0)
Queue Max Size: 0(0x0)
Queue Type: MULTI
Node: 0
Device Type: CPU
Cache Info:
L1: 32768(0x8000) KB
Chip ID: 0(0x0)
ASIC Revision: 0(0x0)
Cacheline Size: 64(0x40)
Max Clock Freq. (MHz): 4600
BDFID: 0
Internal Node ID: 0
Compute Unit: 8
SIMDs per CU: 0
Shader Engines: 0
Shader Arrs. per Eng.: 0
WatchPts on Addr. Ranges:1
Features: None
Pool Info:
Pool 1
Segment: GLOBAL; FLAGS: FINE GRAINED
Size: 20419288(0x13792d8) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Recommended Granule:4KB
Alloc Alignment: 4KB
Accessible by all: TRUE
Pool 2
Segment: GLOBAL; FLAGS: KERNARG, FINE GRAINED
Size: 20419288(0x13792d8) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Recommended Granule:4KB
Alloc Alignment: 4KB
Accessible by all: TRUE
Pool 3
Segment: GLOBAL; FLAGS: COARSE GRAINED
Size: 20419288(0x13792d8) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Recommended Granule:4KB
Alloc Alignment: 4KB
Accessible by all: TRUE
ISA Info:

---

Agent 2

---

Name: gfx900
Uuid: GPU-0214ff7c0fe82844
Marketing Name: Radeon RX Vega
Vendor Name: AMD
Feature: KERNEL_DISPATCH
Profile: BASE_PROFILE
Float Round Mode: NEAR
Max Queue Number: 128(0x80)
Queue Min Size: 64(0x40)
Queue Max Size: 131072(0x20000)
Queue Type: MULTI
Node: 1
Device Type: GPU
Cache Info:
L1: 16(0x10) KB
L2: 4096(0x1000) KB
Chip ID: 26751(0x687f)
ASIC Revision: 1(0x1)
Cacheline Size: 64(0x40)
Max Clock Freq. (MHz): 1590
BDFID: 768
Internal Node ID: 1
Compute Unit: 56
SIMDs per CU: 4
Shader Engines: 4
Shader Arrs. per Eng.: 1
WatchPts on Addr. Ranges:4
Coherent Host Access: FALSE
Features: KERNEL_DISPATCH
Fast F16 Operation: TRUE
Wavefront Size: 64(0x40)
Workgroup Max Size: 1024(0x400)
Workgroup Max Size per Dimension:
x 1024(0x400)
y 1024(0x400)
z 1024(0x400)
Max Waves Per CU: 40(0x28)
Max Work-item Per CU: 2560(0xa00)
Grid Max Size: 4294967295(0xffffffff)
Grid Max Size per Dimension:
x 4294967295(0xffffffff)
y 4294967295(0xffffffff)
z 4294967295(0xffffffff)
Max fbarriers/Workgrp: 32
Packet Processor uCode:: 464
SDMA engine uCode:: 434
IOMMU Support:: None
Pool Info:
Pool 1
Segment: GLOBAL; FLAGS: COARSE GRAINED
Size: 8372224(0x7fc000) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Recommended Granule:2048KB
Alloc Alignment: 4KB
Accessible by all: FALSE
Pool 2
Segment: GLOBAL; FLAGS: EXTENDED FINE GRAINED
Size: 8372224(0x7fc000) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Recommended Granule:2048KB
Alloc Alignment: 4KB
Accessible by all: FALSE
Pool 3
Segment: GROUP
Size: 64(0x40) KB
Allocatable: FALSE
Alloc Granule: 0KB
Alloc Recommended Granule:0KB
Alloc Alignment: 0KB
Accessible by all: FALSE
ISA Info:
ISA 1
Name: amdgcn-amd-amdhsa--gfx900:xnack-
Machine Models: HSA_MACHINE_MODEL_LARGE
Profiles: HSA_PROFILE_BASE
Default Rounding Mode: NEAR
Default Rounding Mode: NEAR
Fast f16: TRUE
Workgroup Max Size: 1024(0x400)
Workgroup Max Size per Dimension:
x 1024(0x400)
y 1024(0x400)
z 1024(0x400)
Grid Max Size: 4294967295(0xffffffff)
Grid Max Size per Dimension:
x 4294967295(0xffffffff)
y 4294967295(0xffffffff)
z 4294967295(0xffffffff)
FBarrier Max Size: 32
*** Done ***

[fgtm2023]

New update, now i solved the problem by this:
1- replaced gradio==4.40.0 to gradio==4.42.0 in requirements_versions.txt
2- pip install -r requirements_versions.txt --upgrade
now the problem solved by these steps, but the same problem is still present with gradio 4.40.0, so i will keep this issue opened.