Idk what to name this title but can you show me how to fix this #27
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Hi there, at least one of the issues is that the microphone or speaker devices has not been configured correctly. Run utils/listAudioDevices.py, and find the correct device numbers and put them in constants.py. Note that if you add or remove a device it will change device numbers, so do it with all the devices that you'll use connected. |
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Thanks but i have another problem with the http ig:
[2025-01-03 13:41:51,580] torch.distributed.elastic.multiprocessing.redirects: [WARNING] NOTE: Redirects are currently not supported in Windows or MacOs. [2025-01-03 13:41:51,899] [WARNING] [config_utils.py:69:_process_deprecated_field] Config parameter replace_method is deprecated. This parameter is no longer needed, please remove from your call to DeepSpeed-inference [2025-01-03 13:41:51,899] [WARNING] [config_utils.py:69:_process_deprecated_field] Config parameter mp_size is deprecated use tensor_parallel.tp_size instead [2025-01-03 13:41:51,899] [INFO] [logging.py:96:log_dist] [Rank -1] quantize_bits = 8 mlp_extra_grouping = False, quantize_groups = 1 [2025-01-03 13:41:52,189] [INFO] [logging.py:96:log_dist] [Rank -1] DeepSpeed-Inference config: {'layer_id': 0, 'hidden_size': 1024, 'intermediate_size': 4096, 'heads': 16, 'num_hidden_layers': -1, 'dtype': torch.float32, 'pre_layer_norm': True, 'norm_type': <NormType.LayerNorm: 1>, 'local_rank': -1, 'stochastic_mode': False, 'epsilon': 1e-05, 'mp_size': 1, 'scale_attention': True, 'triangular_masking': True, 'local_attention': False, 'window_size': 1, 'rotary_dim': -1, 'rotate_half': False, 'rotate_every_two': True, 'return_tuple': True, 'mlp_after_attn': True, 'mlp_act_func_type': <ActivationFuncType.GELU: 1>, 'specialized_mode': False, 'training_mp_size': 1, 'bigscience_bloom': False, 'max_out_tokens': 1024, 'min_out_tokens': 1, 'scale_attn_by_inverse_layer_idx': False, 'enable_qkv_quantization': False, 'use_mup': False, 'return_single_tuple': False, 'set_empty_params': False, 'transposed_mode': False, 'use_triton': False, 'triton_autotune': False, 'num_kv': -1, 'rope_theta': 10000} You are using the default legacy behaviour of the <class 'transformers.models.llama.tokenization_llama_fast.LlamaTokenizerFast'>. This is expected, and simply means that the RealTimeSTT: asyncio - ERROR - Task exception was never retrieved During handling of the above exception, another exception occurred: Traceback (most recent call last): RealTimeSTT: asyncio - ERROR - Task exception was never retrieved During handling of the above exception, another exception occurred: Traceback (most recent call last): During handling of the above exception, another exception occurred: Traceback (most recent call last): PROMPTING AI During handling of the above exception, another exception occurred: Traceback (most recent call last): During handling of the above exception, another exception occurred: Traceback (most recent call last): During handling of the above exception, another exception occurred: Traceback (most recent call last): During handling of the above exception, another exception occurred: Traceback (most recent call last): During handling of the above exception, another exception occurred: Traceback (most recent call last): During handling of the above exception, another exception occurred: Traceback (most recent call last): During handling of the above exception, another exception occurred: Traceback (most recent call last): During handling of the above exception, another exception occurred: Traceback (most recent call last): During handling of the above exception, another exception occurred: Traceback (most recent call last): During handling of the above exception, another exception occurred: Traceback (most recent call last): and this is the log of text-generation-webui: Running on local URL: http://127.0.0.1:7860 This file holds various constants used in the programVariables marked with #UNIQUE# will be unique to your setup and NEED to be changed or the program will not work correctly.CORE SECTION: All constants in this section are necessaryMicrophone/Speaker device indicesUse utils/listAudioDevices.py to find the correct device ID#UNIQUE# How many seconds to wait before prompting AIPATIENCE = 60 URL of LLM API EndpointLLM_ENDPOINT = ""LLM_ENDPOINT = "https://127.0.0.1:5000" Twitch chat messages above this length will be ignoredTWITCH_MAX_MESSAGE_LENGTH = 300 Twitch channel for bot to join#UNIQUE# Voice reference file for TTS#UNIQUE# MULTIMODAL SPECIFIC SECTION: Not needed when not using multimodal capabilitiesMULTIMODAL_ENDPOINT = "" MULTIMODAL_MODEL = "openbmb/MiniCPM-Llama3-V-2_5-int4" MULTIMODAL_CONTEXT_SIZE = 1000 #8192 # Trying out 1000 tokens to limit short term memory This is the multimodal strategy (when to use multimodal/text only llm) that the program will start with.Runtime changes will not be saved here.Valid values are: "always", "never"MULTIMODAL_STRATEGY = "never" This is the monitor index that screenshots will be taken. THIS IS NOT THE MONITOR NUMBER IN DISPLAY SETTINGSMonitor 0 is a "virtual" monitor contains all monitor screens.PRIMARY_MONITOR = 0 LLM SPECIFIC SECTION: Below are constants that are specific to the LLM you are usingThe model you are using, to calculate how many tokens the current message isEnsure this is correct! Used for token count estimationMODEL = "" Context size (maximum number of tokens in the prompt) Will target upto 90% usage of this limitCONTEXT_SIZE = 8192 This is your name#UNIQUE# This is the AI's nameAI_NAME = "Luna" The system prompt. Any character text needs to be here.You MUST ensure it is less than CONTEXT_SIZE tokensSYSTEM_PROMPT = "" List of banned tokens to be passed to the textgen web ui apiFor Mistral 7B v0.2, token 422 is the "#" token. The LLM was spamming #life #vtuber #funfact etc.BANNED_TOKENS = "" List of stopping strings. Necessary for Llama 3STOP_STRINGS = ["\n", "<|eot_id|>"] MEMORY SECTION: Constants relevant to forming new memoriesMEMORY_PROMPT = "\nGiven only the information above, what are 3 most salient high level questions we can answer about the subjects in the conversation? Separate each question and answer pair with "{qa}", and only output the question and answer, no explanations." How many messages in the history to include for querying the database.MEMORY_QUERY_MESSAGE_COUNT = 5 How many memories to recall and insert into contextMEMORY_RECALL_COUNT = 5 VTUBE STUDIO SECTION: Configure & tune model & prop positions here.The defaults are for the Hiyori model on a full 16 by 9 aspect ratio screenVTUBE_MODEL_POSITIONS = { VTUBE_MIC_POSITION = { |
This is the log:
C:\Users\admin\Documents\Neuro>python main.py
Starting Project...
2025-01-02 22:07:24.203231: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable
TF_ENABLE_ONEDNN_OPTS=0.2025-01-02 22:07:26.202536: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable
TF_ENABLE_ONEDNN_OPTS=0.GPT2InferenceModel has generative capabilities, as
prepare_inputs_for_generationis explicitly overwritten. However, it doesn't directly inherit fromGenerationMixin. From 👉v4.50👈 onwards,PreTrainedModelwill NOT inherit fromGenerationMixin, and this model will lose the ability to callgenerateand other related functions.trust_remote_code=True, you can get rid of this warning by loading the model with an auto class. See https://huggingface.co/docs/transformers/en/model_doc/auto#auto-classesGenerationMixin(afterPreTrainedModel, otherwise you'll get an exception).[2025-01-02 22:07:55,993] [INFO] [real_accelerator.py:191:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2025-01-02 22:07:56,720] torch.distributed.elastic.multiprocessing.redirects: [WARNING] NOTE: Redirects are currently not supported in Windows or MacOs.
[2025-01-02 22:07:57,079] [INFO] [logging.py:96:log_dist] [Rank -1] DeepSpeed info: version=0.14.0+ce78a63, git-hash=ce78a63, git-branch=master
[2025-01-02 22:07:57,081] [WARNING] [config_utils.py:69:_process_deprecated_field] Config parameter replace_method is deprecated. This parameter is no longer needed, please remove from your call to DeepSpeed-inference
[2025-01-02 22:07:57,081] [WARNING] [config_utils.py:69:_process_deprecated_field] Config parameter mp_size is deprecated use tensor_parallel.tp_size instead
[2025-01-02 22:07:57,081] [INFO] [logging.py:96:log_dist] [Rank -1] quantize_bits = 8 mlp_extra_grouping = False, quantize_groups = 1
[2025-01-02 22:07:57,416] [INFO] [logging.py:96:log_dist] [Rank -1] DeepSpeed-Inference config: {'layer_id': 0, 'hidden_size': 1024, 'intermediate_size': 4096, 'heads': 16, 'num_hidden_layers': -1, 'dtype': torch.float32, 'pre_layer_norm': True, 'norm_type': <NormType.LayerNorm: 1>, 'local_rank': -1, 'stochastic_mode': False, 'epsilon': 1e-05, 'mp_size': 1, 'scale_attention': True, 'triangular_masking': True, 'local_attention': False, 'window_size': 1, 'rotary_dim': -1, 'rotate_half': False, 'rotate_every_two': True, 'return_tuple': True, 'mlp_after_attn': True, 'mlp_act_func_type': <ActivationFuncType.GELU: 1>, 'specialized_mode': False, 'training_mp_size': 1, 'bigscience_bloom': False, 'max_out_tokens': 1024, 'min_out_tokens': 1, 'scale_attn_by_inverse_layer_idx': False, 'enable_qkv_quantization': False, 'use_mup': False, 'return_single_tuple': False, 'set_empty_params': False, 'transposed_mode': False, 'use_triton': False, 'triton_autotune': False, 'num_kv': -1, 'rope_theta': 10000}
You are using the default legacy behaviour of the <class 'transformers.models.llama.tokenization_llama_fast.LlamaTokenizerFast'>. This is expected, and simply means that the
legacy(previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, setlegacy=False. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in huggingface/transformers#24565 - if you loaded a llama tokenizer from a GGUF file you can ignore this message.2025-01-02 22:08:06.398059: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable
TF_ENABLE_ONEDNN_OPTS=0.2025-01-02 22:08:07.967958: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable
TF_ENABLE_ONEDNN_OPTS=0.MEMORY: Loaded 1 memories from database.
Starting Socket.io server
Prompter loop started
STT Starting
======== Running on http://0.0.0.0:8080 ========
(Press CTRL+C to quit)
Failed to connect to Vtube Studio. Disabling Vtube Studio module.
STT Ready
SYSTEM READY
SIGNALS: Human Talking Start
Could not locate cudnn_ops64_9.dll. Please make sure it is in your library path!
Invalid handle. Cannot load symbol cudnnCreateTensorDescriptor
CoquiEngine: General synthesis error: occured in synthesize worker thread of coqui engine.
Process Process-1:
Traceback (most recent call last):
File "C:\Users\admin\AppData\Local\Programs\Python\Python311\Lib\multiprocessing\connection.py", line 328, in _recv_bytes
nread, err = ov.GetOverlappedResult(True)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
BrokenPipeError: [WinError 109] The pipe has been ended
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Users\admin\AppData\Local\Programs\Python\Python311\Lib\site-packages\RealtimeTTS\engines\coqui_engine.py", line 515, in _synthesize_worker
message = conn.recv()
^^^^^^^^^^^
File "C:\Users\admin\AppData\Local\Programs\Python\Python311\Lib\multiprocessing\connection.py", line 250, in recv
buf = self._recv_bytes()
^^^^^^^^^^^^^^^^^^
File "C:\Users\admin\AppData\Local\Programs\Python\Python311\Lib\multiprocessing\connection.py", line 337, in _recv_bytes
raise EOFError
Exception in thread Thread-2 (poll_connection)EOFError
:
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
Traceback (most recent call last):
File "C:\Users\admin\AppData\Local\Programs\Python\Python311\Lib\threading.py", line 1045, in _bootstrap_inner
File "C:\Users\admin\AppData\Local\Programs\Python\Python311\Lib\multiprocessing\process.py", line 314, in _bootstrap
self.run()
File "C:\Users\admin\AppData\Local\Programs\Python\Python311\Lib\multiprocessing\process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File "C:\Users\admin\AppData\Local\Programs\Python\Python311\Lib\site-packages\RealtimeTTS\engines\coqui_engine.py", line 643, in _synthesize_worker
conn.send(('error', str(e)))
self.run()
File "C:\Users\admin\AppData\Local\Programs\Python\Python311\Lib\multiprocessing\connection.py", line 206, in send
self._send_bytes(_ForkingPickler.dumps(obj))
File "C:\Users\admin\AppData\Local\Programs\Python\Python311\Lib\multiprocessing\connection.py", line 289, in _send_bytes
ov, err = _winapi.WriteFile(self._handle, buf, overlapped=True)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\admin\AppData\Local\Programs\Python\Python311\Lib\threading.py", line 982, in run
BrokenPipeError: [WinError 232] The pipe is being closed
self._target(*self._args, **self._kwargs)
File "C:\Users\admin\AppData\Local\Programs\Python\Python311\Lib\site-packages\RealtimeSTT\audio_recorder.py", line 115, in poll_connection
if self.conn.poll(0.01):
^^^^^^^^^^^^^^^^^^^^
File "C:\Users\admin\AppData\Local\Programs\Python\Python311\Lib\multiprocessing\connection.py", line 257, in poll
return self._poll(timeout)
^^^^^^^^^^^^^^^^^^^
File "C:\Users\admin\AppData\Local\Programs\Python\Python311\Lib\multiprocessing\connection.py", line 344, in _poll
_winapi.PeekNamedPipe(self._handle)[0] != 0):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
BrokenPipeError: [WinError 109] The pipe has been ended
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