AttributeError: 'DualStreamProcessor' object has no attribute 'flush'

[pseudotensor]

GPT4All does some horrible wrapping of all prints for streaming, so have to avoid prints once model loaded in case race with a print from main gradio block

Running on local URL:  http://0.0.0.0:7860
Distance: min: 1.2514867782592773 max: 1.388384461402893 mean: 1.315113604068756 median: 1.310291588306427
Running on public URL: https://24eb03829b71ef3927.gradio.liveThis share link expires in 72 hours. For free permanent hosting and GPU upgrades (NEW!), check out Spaces: https://huggingface.co/spacesStarted GUIKilling tunnel 0.0.0.0:7860 <> https://24eb03829b71ef3927.gradio.live╭───────────────────── Traceback (most recent call last) ──────────────────────╮
│ /home/jon/h2o-llm/generate.py:1504 in <module>                               │
│                                                                              │
│   1501 │                                                                     │
│   1502 │   python generate.py --base_model=h2oai/h2ogpt-oig-oasst1-512-6_9b  │
│   1503 │   """                                                               │
│ ❱ 1504 │   fire.Fire(main)                                                   │
│   1505                                                                       │
│                                                                              │
│ /home/jon/miniconda3/envs/h2ollm/lib/python3.10/site-packages/fire/core.py:1 │
│ 41 in Fire                                                                   │
│                                                                              │
│   138 │   context.update(caller_globals)                                     │
│   139 │   context.update(caller_locals)                                      │
│   140                                                                        │
│ ❱ 141   component_trace = _Fire(component, args, parsed_flag_args, context,  │
│   142                                                                        │
│   143   if component_trace.HasError():                                       │
│   144 │   _DisplayError(component_trace)                                     │
│                                                                              │
│ /home/jon/miniconda3/envs/h2ollm/lib/python3.10/site-packages/fire/core.py:4 │
│ 75 in _Fire                                                                  │
│                                                                              │
│   472 │     is_class = inspect.isclass(component)                            │
│   473 │                                                                      │
│   474 │     try:                                                             │
│ ❱ 475 │   │   component, remaining_args = _CallAndUpdateTrace(               │
│   476 │   │   │   component,                                                 │
│   477 │   │   │   remaining_args,                                            │
│   478 │   │   │   component_trace,                                           │
│                                                                              │
│ /home/jon/miniconda3/envs/h2ollm/lib/python3.10/site-packages/fire/core.py:6 │
│ 91 in _CallAndUpdateTrace                                                    │
│                                                                              │
│   688 │   loop = asyncio.get_event_loop()                                    │
│   689 │   component = loop.run_until_complete(fn(*varargs, **kwargs))        │
│   690   else:                                                                │
│ ❱ 691 │   component = fn(*varargs, **kwargs)                                 │
│   692                                                                        │
│   693   if treatment == 'class':                                             │
│   694 │   action = trace.INSTANTIATED_CLASS                                  │
│                                                                              │
│ /home/jon/h2o-llm/generate.py:430 in main                                    │
│                                                                              │
│    427 │   │   │   caption_loader = False                                    │
│    428 │   │                                                                 │
│    429 │   │   # assume gradio needs everything                              │
│ ❱  430 │   │   go_gradio(**locals())                                         │
│    431                                                                       │
│    432                                                                       │
│    433 def get_non_lora_model(base_model, model_loader, load_half, model_kwa │
│                                                                              │
│ /home/jon/h2o-llm/gradio_runner.py:1429 in go_gradio                         │
│                                                                              │
│   1426 │   demo.launch(share=kwargs['share'], server_name="0.0.0.0", show_er │
│   1427 │   │   │   │   favicon_path=favicon_path, prevent_thread_lock=True,  │
│   1428 │   │   │   │   auth=kwargs['auth'])                                  │
│ ❱ 1429 │   print("Started GUI", flush=True)                                  │
│   1430 │   if kwargs['block_gradio_exit']:                                   │
│   1431 │   │   demo.block_thread()                                           │
│   1432                                                                       │
╰──────────────────────────────────────────────────────────────────────────────╯
AttributeError: 'DualStreamProcessor' object has no attribute 'flush'
Exception ignored in: <gpt4all.pyllmodel.DualStreamProcessor object at 0x7f332460d090>
AttributeError: 'DualStreamProcessor' object has no attribute 'flush'

Process finished with exit code 120