mistralai

/

Mistral-7B-Instruct-v0.2

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When I deployed privateGpt locally in windows 10, an error occurred. I tried updating the transforms version above but failed to solve the problem. I did not use a graphics card locally, was it related to nvida?

PS F:\private-gpt-0.5.0\private-gpt-main> $env:PGPT_PROFILES="ollama"
PS F:\private-gpt-0.5.0\private-gpt-main> make run
poetry run python -m private_gpt
10:24:25.303 [INFO ] private_gpt.settings.settings_loader - Starting application with profiles=['default', 'ollama']
None of PyTorch, TensorFlow >= 2.0, or Flax have been found. Models won't be available and only tokenizers, configuration and file/data utilities can be used.
--- Logging error ---
Traceback (most recent call last):
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init_.py", line 798, in get
return self._context[key]
~~~~~~~~~~~~~^^^^^
KeyError: <class 'private_gpt.ui.ui.PrivateGptUi'>

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init_.py", line 798, in get
return self._context[key]
~~~~~~~~~~~~~^^^^^
KeyError: <class 'private_gpt.server.ingest.ingest_service.IngestService'>

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init_.py", line 798, in get
return self._context[key]
~~~~~~~~~~~~~^^^^^
KeyError: <class 'private_gpt.components.llm.llm_component.LLMComponent'>

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "F:\private-gpt-0.5.0\private-gpt-main\private_gpt\components\llm\llm_component.py", line 30, in init
AutoTokenizer.from_pretrained(
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\transformers\models\auto\tokenization_auto.py", line 825, in from_pretrained
return tokenizer_class.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\transformers\tokenization_utils_base.py", line 2048, in from_pretrained
return cls._from_pretrained(
^^^^^^^^^^^^^^^^^^^^^
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\transformers\tokenization_utils_base.py", line 2287, in _from_pretrained
tokenizer = cls(*init_inputs, **init_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\transformers\models\llama\tokenization_llama_fast.py", line 133, in init
super().init(
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\transformers\tokenization_utils_fast.py", line 111, in init
fast_tokenizer = TokenizerFast.from_file(fast_tokenizer_file)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Exception: data did not match any variant of untagged enum PyPreTokenizerTypeWrapper at line 40 column 3

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "D:\Python311\Lib\logging_init.py", line 1110, in emit
msg = self.format(record)
^^^^^^^^^^^^^^^^^^^
File "D:\Python311\Lib\logging_init.py", line 953, in format
return fmt.format(record)
^^^^^^^^^^^^^^^^^^
File "D:\Python311\Lib\logging_init.py", line 687, in format
record.message = record.getMessage()
^^^^^^^^^^^^^^^^^^^
File "D:\Python311\Lib\logging_init.py", line 377, in getMessage
msg = msg % self.args
~~~~^~~~~~~~~~~
TypeError: not all arguments converted during string formatting
Call stack:
File "", line 198, in run_module_as_main
File "", line 88, in run_code
File "F:\private-gpt-0.5.0\private-gpt-main\private_gpt_main.py", line 5, in
from private_gpt.main import app
File "", line 1176, in find_and_load
File "", line 1147, in find_and_load_unlocked
File "", line 690, in load_unlocked
File "", line 940, in exec_module
File "", line 241, in call_with_frames_removed
File "F:\private-gpt-0.5.0\private-gpt-main\private_gpt\main.py", line 6, in
app = create_app(global_injector)
File "F:\private-gpt-0.5.0\private-gpt-main\private_gpt\launcher.py", line 63, in create_app
ui = root_injector.get(PrivateGptUi)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 91, in wrapper
return function(*args, **kwargs)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 974, in get
provider_instance = scope_instance.get(interface, binding.provider)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 91, in wrapper
return function(*args, **kwargs)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 800, in get
instance = self.get_instance(key, provider, self.injector)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 811, in get_instance
return provider.get(injector)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 264, in get
return injector.create_object(self.cls)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 998, in create_object
self.call_with_injection(init, self=instance, kwargs=additional_kwargs)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 1031, in call_with_injection
dependencies = self.args_to_inject(
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 91, in wrapper
return function(*args, **kwargs)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 1079, in args_to_inject
instance: Any = self.get(interface)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 91, in wrapper
return function(*args, **kwargs)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 974, in get
provider_instance = scope_instance.get(interface, binding.provider)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 91, in wrapper
return function(*args, **kwargs)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 800, in get
instance = self.get_instance(key, provider, self.injector)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 811, in get_instance
return provider.get(injector)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 264, in get
return injector.create_object(self.cls)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 998, in create_object
self.call_with_injection(init, self=instance, kwargs=additional_kwargs)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 1031, in call_with_injection
dependencies = self.args_to_inject(
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 91, in wrapper
return function(*args, **kwargs)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 1079, in args_to_inject
instance: Any = self.get(interface)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 91, in wrapper
return function(*args, **kwargs)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 974, in get
provider_instance = scope_instance.get(interface, binding.provider)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 91, in wrapper
return function(*args, **kwargs)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 800, in get
instance = self.get_instance(key, provider, self.injector)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 811, in get_instance
return provider.get(injector)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 264, in get
return injector.create_object(self.cls)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init.py", line 998, in create_object
self.call_with_injection(init, self=instance, kwargs=additional_kwargs)
File "F:\private-gpt-0.5.0\private-gpt-main.venv\Lib\site-packages\injector_init_.py", line 1040, in call_with_injection
return callable(*full_args, **dependencies)
File "F:\private-gpt-0.5.0\private-gpt-main\private_gpt\components\llm\llm_component.py", line 37, in init
logger.warning(
Message: 'Failed to download tokenizer %s. Falling back to default tokenizer.'
Arguments: ('mistralai/Mistral-7B-Instruct-v0.2', Exception('data did not match any variant of untagged enum PyPreTokenizerTypeWrapper at line 40 column 3'))
10:24:28.748 [INFO ] private_gpt.components.llm.llm_component - Initializing the LLM in mode=ollama
10:24:29.225 [INFO ] private_gpt.components.embedding.embedding_component - Initializing the embedding model in mode=ollama
10:24:29.227 [INFO ] llama_index.core.indices.loading - Loading all indices.
10:24:29.513 [INFO ] private_gpt.ui.ui - Mounting the gradio UI, at path=/
10:24:29.631 [INFO ] uvicorn.error - Started server process [20140]
10:24:29.631 [INFO ] uvicorn.error - Waiting for application startup.
10:24:29.632 [INFO ] uvicorn.error - Application startup complete.
10:24:29.634 [INFO ] uvicorn.error - Uvicorn running on http://0.0.0.0:8001 (Press CTRL+C to quit)