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zylon-ai / private-gpt

Interact with your documents using the power of GPT, 100% privately, no data leaks
https://privategpt.dev
Apache License 2.0
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Getting a JSONDecodeError on startup #1513

Open matbee-eth opened 8 months ago

matbee-eth commented 8 months ago 
Traceback (most recent call last):
  File "<frozen runpy>", line 198, in _run_module_as_main
  File "<frozen runpy>", line 88, in _run_code
  File "/home/acidhax/dev/privateGPT/private_gpt/__main__.py", line 5, in <module>
    from private_gpt.main import app
  File "/home/acidhax/dev/privateGPT/private_gpt/main.py", line 11, in <module>
    app = create_app(global_injector)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/dev/privateGPT/private_gpt/launcher.py", line 50, in create_app
    ui = root_injector.get(PrivateGptUi)
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper
    return function(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 974, in get
    provider_instance = scope_instance.get(interface, binding.provider)
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper
    return function(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 800, in get
    instance = self._get_instance(key, provider, self.injector)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 811, in _get_instance
    return provider.get(injector)
           ^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 264, in get
    return injector.create_object(self._cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 998, in create_object
    self.call_with_injection(init, self_=instance, kwargs=additional_kwargs)
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 1031, in call_with_injection
    dependencies = self.args_to_inject(
                   ^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper
    return function(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 1079, in args_to_inject
    instance: Any = self.get(interface)
                    ^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper
    return function(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 974, in get
    provider_instance = scope_instance.get(interface, binding.provider)
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper
    return function(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 800, in get
    instance = self._get_instance(key, provider, self.injector)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 811, in _get_instance
    return provider.get(injector)
           ^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 264, in get
    return injector.create_object(self._cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 998, in create_object
    self.call_with_injection(init, self_=instance, kwargs=additional_kwargs)
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 1031, in call_with_injection
    dependencies = self.args_to_inject(
                   ^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper
    return function(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 1079, in args_to_inject
    instance: Any = self.get(interface)
                    ^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper
    return function(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 974, in get
    provider_instance = scope_instance.get(interface, binding.provider)
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper
    return function(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 800, in get
    instance = self._get_instance(key, provider, self.injector)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 811, in _get_instance
    return provider.get(injector)
           ^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 264, in get
    return injector.create_object(self._cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 998, in create_object
    self.call_with_injection(init, self_=instance, kwargs=additional_kwargs)
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/injector/__init__.py", line 1040, in call_with_injection
    return callable(*full_args, **dependencies)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/dev/privateGPT/private_gpt/components/vector_store/vector_store_component.py", line 83, in __init__
    client = QdrantClient(
             ^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/qdrant_client/qdrant_client.py", line 99, in __init__
    self._client = QdrantLocal(
                   ^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/qdrant_client/local/qdrant_local.py", line 48, in __init__
    self._load()
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/site-packages/qdrant_client/local/qdrant_local.py", line 71, in _load
    meta = json.load(f)
           ^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/json/__init__.py", line 293, in load
    return loads(fp.read(),
           ^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/json/__init__.py", line 346, in loads
    return _default_decoder.decode(s)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/json/decoder.py", line 337, in decode
    obj, end = self.raw_decode(s, idx=_w(s, 0).end())
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/acidhax/anaconda3/envs/privategpt/lib/python3.11/json/decoder.py", line 355, in raw_decode
    raise JSONDecodeError("Expecting value", s, err.value) from None
json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)

Additional logs if necessary

(privategpt) acidhax@MatsBeastyPC:~/dev/privateGPT$ poetry run python -m private_gpt
15:40:45.785 [INFO    ] private_gpt.settings.settings_loader - Starting application with profiles=['default']
15:40:48.489 [INFO    ] private_gpt.components.llm.llm_component - Initializing the LLM in mode=local
ggml_init_cublas: GGML_CUDA_FORCE_MMQ:   no
ggml_init_cublas: CUDA_USE_TENSOR_CORES: yes
ggml_init_cublas: found 1 CUDA devices:
  Device 0: NVIDIA GeForce RTX 4090, compute capability 8.9, VMM: yes
llama_model_loader: loaded meta data with 24 key-value pairs and 291 tensors from /home/acidhax/dev/privateGPT/models/mistral-7b-instruct-v0.2.Q4_K_M.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv   0:                       general.architecture str              = llama
llama_model_loader: - kv   1:                               general.name str              = mistralai_mistral-7b-instruct-v0.2
llama_model_loader: - kv   2:                       llama.context_length u32              = 32768
llama_model_loader: - kv   3:                     llama.embedding_length u32              = 4096
llama_model_loader: - kv   4:                          llama.block_count u32              = 32
llama_model_loader: - kv   5:                  llama.feed_forward_length u32              = 14336
llama_model_loader: - kv   6:                 llama.rope.dimension_count u32              = 128
llama_model_loader: - kv   7:                 llama.attention.head_count u32              = 32
llama_model_loader: - kv   8:              llama.attention.head_count_kv u32              = 8
llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  10:                       llama.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv  11:                          general.file_type u32              = 15
llama_model_loader: - kv  12:                       tokenizer.ggml.model str              = llama
llama_model_loader: - kv  13:                      tokenizer.ggml.tokens arr[str,32000]   = ["<unk>", "<s>", "</s>", "<0x00>", "<...
llama_model_loader: - kv  14:                      tokenizer.ggml.scores arr[f32,32000]   = [0.000000, 0.000000, 0.000000, 0.0000...
llama_model_loader: - kv  15:                  tokenizer.ggml.token_type arr[i32,32000]   = [2, 3, 3, 6, 6, 6, 6, 6, 6, 6, 6, 6, ...
llama_model_loader: - kv  16:                tokenizer.ggml.bos_token_id u32              = 1
llama_model_loader: - kv  17:                tokenizer.ggml.eos_token_id u32              = 2
llama_model_loader: - kv  18:            tokenizer.ggml.unknown_token_id u32              = 0
llama_model_loader: - kv  19:            tokenizer.ggml.padding_token_id u32              = 0
llama_model_loader: - kv  20:               tokenizer.ggml.add_bos_token bool             = true
llama_model_loader: - kv  21:               tokenizer.ggml.add_eos_token bool             = false
llama_model_loader: - kv  22:                    tokenizer.chat_template str              = {{ bos_token }}{% for message in mess...
llama_model_loader: - kv  23:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:   65 tensors
llama_model_loader: - type q4_K:  193 tensors
llama_model_loader: - type q6_K:   33 tensors
llm_load_vocab: special tokens definition check successful ( 259/32000 ).
llm_load_print_meta: format           = GGUF V3 (latest)
llm_load_print_meta: arch             = llama
llm_load_print_meta: vocab type       = SPM
llm_load_print_meta: n_vocab          = 32000
llm_load_print_meta: n_merges         = 0
llm_load_print_meta: n_ctx_train      = 32768
llm_load_print_meta: n_embd           = 4096
llm_load_print_meta: n_head           = 32
llm_load_print_meta: n_head_kv        = 8
llm_load_print_meta: n_layer          = 32
llm_load_print_meta: n_rot            = 128
llm_load_print_meta: n_embd_head_k    = 128
llm_load_print_meta: n_embd_head_v    = 128
llm_load_print_meta: n_gqa            = 4
llm_load_print_meta: n_embd_k_gqa     = 1024
llm_load_print_meta: n_embd_v_gqa     = 1024
llm_load_print_meta: f_norm_eps       = 0.0e+00
llm_load_print_meta: f_norm_rms_eps   = 1.0e-05
llm_load_print_meta: f_clamp_kqv      = 0.0e+00
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
llm_load_print_meta: n_ff             = 14336
llm_load_print_meta: n_expert         = 0
llm_load_print_meta: n_expert_used    = 0
llm_load_print_meta: rope scaling     = linear
llm_load_print_meta: freq_base_train  = 1000000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_yarn_orig_ctx  = 32768
llm_load_print_meta: rope_finetuned   = unknown
llm_load_print_meta: model type       = 7B
llm_load_print_meta: model ftype      = Q4_K - Medium
llm_load_print_meta: model params     = 7.24 B
llm_load_print_meta: model size       = 4.07 GiB (4.83 BPW)
llm_load_print_meta: general.name     = mistralai_mistral-7b-instruct-v0.2
llm_load_print_meta: BOS token        = 1 '<s>'
llm_load_print_meta: EOS token        = 2 '</s>'
llm_load_print_meta: UNK token        = 0 '<unk>'
llm_load_print_meta: PAD token        = 0 '<unk>'
llm_load_print_meta: LF token         = 13 '<0x0A>'
llm_load_tensors: ggml ctx size =    0.22 MiB
llm_load_tensors: offloading 32 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 33/33 layers to GPU
llm_load_tensors:        CPU buffer size =    70.31 MiB
llm_load_tensors:      CUDA0 buffer size =  4095.05 MiB
...............................................................................................
llama_new_context_with_model: n_ctx      = 3900
llama_new_context_with_model: freq_base  = 1000000.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init:  CUDA_Host KV buffer size =   487.50 MiB
llama_new_context_with_model: KV self size  =  487.50 MiB, K (f16):  243.75 MiB, V (f16):  243.75 MiB
llama_new_context_with_model: graph splits (measure): 66
llama_new_context_with_model:      CUDA0 compute buffer size =   282.99 MiB
llama_new_context_with_model:  CUDA_Host compute buffer size =    19.62 MiB
AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 1 | AVX512_VBMI = 1 | AVX512_VNNI = 1 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 |
matbee-eth commented 8 months ago

Error doesnt exist on 0.2 release

github-actions[bot] commented 8 months ago

Stale issue

q8ing commented 5 months ago

I encountered such a problem when I closed the program before it had finished deleting the injested files I wanted to erase. To solve this issue, delete the 'private_gpt' folder inside 'local_data' directory, then restart the program, and you will get rid of the error message.