[Bug]: No such file or directory: '/Users/ankushsingal/Desktop/Graphrag/output/20240714-151538/artifacts/create_final_nodes.parquet'<title>

[andysingal]

Describe the bug

i added and ran

export GRAPHRAG_API_KEY=groq-key

python3 -m graphrag.index --init --root .  

whereas

python -m graphrag.query --root . --method local "Who is Scrooge, and what are his main relationships?"

gives

python -m graphrag.query --root . --method local "Who is Scrooge, and what are his main relationships?"
2024-07-14 15:54:41.980181: 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.


INFO: Reading settings from settings.yaml
Traceback (most recent call last):
  File "<frozen runpy>", line 198, in _run_module_as_main
  File "<frozen runpy>", line 88, in _run_code
  File "/Users/ankushsingal/Desktop/GraphRAG/graphragvenv/lib/python3.12/site-packages/graphrag/query/__main__.py", line 75, in <module>
    run_local_search(
  File "/Users/ankushsingal/Desktop/GraphRAG/graphragvenv/lib/python3.12/site-packages/graphrag/query/cli.py", line 105, in run_local_search
    final_nodes = pd.read_parquet(data_path / "create_final_nodes.parquet")
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/ankushsingal/Desktop/GraphRAG/graphragvenv/lib/python3.12/site-packages/pandas/io/parquet.py", line 667, in read_parquet
    return impl.read(
           ^^^^^^^^^^
  File "/Users/ankushsingal/Desktop/GraphRAG/graphragvenv/lib/python3.12/site-packages/pandas/io/parquet.py", line 267, in read
    path_or_handle, handles, filesystem = _get_path_or_handle(
                                          ^^^^^^^^^^^^^^^^^^^^
  File "/Users/ankushsingal/Desktop/GraphRAG/graphragvenv/lib/python3.12/site-packages/pandas/io/parquet.py", line 140, in _get_path_or_handle
    handles = get_handle(
              ^^^^^^^^^^^
  File "/Users/ankushsingal/Desktop/GraphRAG/graphragvenv/lib/python3.12/site-packages/pandas/io/common.py", line 882, in get_handle
    handle = open(handle, ioargs.mode)
             ^^^^^^^^^^^^^^^^^^^^^^^^^
FileNotFoundError: [Errno 2] No such file or directory: '/Users/ankushsingal/Desktop/GraphRAG/output/20240714-155424/artifacts/create_final_nodes.parquet'

Steps to reproduce

settings.yaml
encoding_model: cl100k_base
skip_workflows: []
llm:
  api_key: ${GRAPHRAG_API_KEY}
  type: openai_chat # or azure_openai_chat
  model: mixtral-8x7b-32768
  model_supports_json: true # recommended if this is available for your model.
  # max_tokens: 4000
  # request_timeout: 180.0
  api_base: https://api.groq.com/openai/v1
  # api_version: 2024-02-15-preview
  # organization: <organization_id>
  # deployment_name: <azure_model_deployment_name>
  tokens_per_minute: 3000 # set a leaky bucket throttle
  requests_per_minute: 30 # set a leaky bucket throttle
  max_retries: 3
  max_retry_wait: 10.0
  # sleep_on_rate_limit_recommendation: true # whether to sleep when azure suggests wait-times
  # concurrent_requests: 25 # the number of parallel inflight requests that may be made

parallelization:
  stagger: 0.3
  # num_threads: 50 # the number of threads to use for parallel processing

async_mode: threaded # or asyncio

embeddings:
  ## parallelization: override the global parallelization settings for embeddings
  async_mode: threaded # or asyncio
  llm:
    api_key: ${OPENAI_API_KEY}
    type: openai_embedding # or azure_openai_embedding
    model: text-embedding-3-small
    # api_base: https://<instance>.openai.azure.com
    # api_version: 2024-02-15-preview
    # organization: <organization_id>
    # deployment_name: <azure_model_deployment_name>
    # tokens_per_minute: 150_000 # set a leaky bucket throttle
    # requests_per_minute: 10_000 # set a leaky bucket throttle
    # max_retries: 10
    # max_retry_wait: 10.0
    # sleep_on_rate_limit_recommendation: true # whether to sleep when azure suggests wait-times
    # concurrent_requests: 25 # the number of parallel inflight requests that may be made
    # batch_size: 16 # the number of documents to send in a single request
    # batch_max_tokens: 8191 # the maximum number of tokens to send in a single request
    # target: required # or optional
  


chunks:
  size: 300
  overlap: 100
  group_by_columns: [id] # by default, we don't allow chunks to cross documents
    
input:
  type: file # or blob
  file_type: text # or csv
  base_dir: "input"
  file_encoding: utf-8
  file_pattern: ".*\\.txt$"

cache:
  type: file # or blob
  base_dir: "cache"
  # connection_string: <azure_blob_storage_connection_string>
  # container_name: <azure_blob_storage_container_name>

storage:
  type: file # or blob
  base_dir: "output/${timestamp}/artifacts"
  # connection_string: <azure_blob_storage_connection_string>
  # container_name: <azure_blob_storage_container_name>

reporting:
  type: file # or console, blob
  base_dir: "output/${timestamp}/reports"
  # connection_string: <azure_blob_storage_connection_string>
  # container_name: <azure_blob_storage_container_name>

entity_extraction:
  ## llm: override the global llm settings for this task
  ## parallelization: override the global parallelization settings for this task
  ## async_mode: override the global async_mode settings for this task
  prompt: "prompts/entity_extraction.txt"
  entity_types: [organization,person,geo,event]
  max_gleanings: 0

summarize_descriptions:
  ## llm: override the global llm settings for this task
  ## parallelization: override the global parallelization settings for this task
  ## async_mode: override the global async_mode settings for this task
  prompt: "prompts/summarize_descriptions.txt"
  max_length: 500

claim_extraction:
  ## llm: override the global llm settings for this task
  ## parallelization: override the global parallelization settings for this task
  ## async_mode: override the global async_mode settings for this task
  # enabled: true
  prompt: "prompts/claim_extraction.txt"
  description: "Any claims or facts that could be relevant to information discovery."
  max_gleanings: 0

community_report:
  ## llm: override the global llm settings for this task
  ## parallelization: override the global parallelization settings for this task
  ## async_mode: override the global async_mode settings for this task
  prompt: "prompts/community_report.txt"
  max_length: 2000
  max_input_length: 8000

cluster_graph:
  max_cluster_size: 10

embed_graph:
  enabled: false # if true, will generate node2vec embeddings for nodes
  # num_walks: 10
  # walk_length: 40
  # window_size: 2
  # iterations: 3
  # random_seed: 597832

umap:
  enabled: false # if true, will generate UMAP embeddings for nodes

snapshots:
  graphml: false
  raw_entities: false
  top_level_nodes: false

local_search:
  # text_unit_prop: 0.5
  # community_prop: 0.1
  # conversation_history_max_turns: 5
  # top_k_mapped_entities: 10
  # top_k_relationships: 10
  # max_tokens: 12000

global_search:
  # max_tokens: 12000
  # data_max_tokens: 12000
  # map_max_tokens: 1000
  # reduce_max_tokens: 2000
  # concurrency: 32

Expected Behavior

No response

GraphRAG Config Used

No response

Logs and screenshots

No response

Additional Information

• GraphRAG Version:
• Operating System:
• Python Version:
• Related Issues:

[linghan16]

I also encountered the same problem.

[andysingal]

I also encountered the same problem.

were you able to resolve it ?

[linghan16]

no,There was a problem running the Indexing pipeline, and the parquet files was not generated normally.

[linghan16]

You can try running the command line window as an administrator and re-run the index pipeline. I succeeded.

[andysingal]

and re-ru

i am using mac, let me try.. will keep you posted

[KylinMountain]

check if there's file in that directory. and then you can try the command with --data to specify the output director.

python -m graphrag.query --root . --method local "Who is Scrooge, and what are his main relationships?" --data output/20240714-151538/artifacts

[github-actions[bot]]

This issue has been marked stale due to inactivity after repo maintainer or community member responses that request more information or suggest a solution. It will be closed after five additional days.

[github-actions[bot]]

This issue has been closed after being marked as stale for five days. Please reopen if needed.