[Bug]: Global/Local Search with graphrag CLI not working when specifying Azure Storage blob in the settings.json

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Describe the bug

The Global/Local search with graphrag CLI does not work when using Azure Storage Blob to store the content. When running search using CLI, I get an error. It looks for 'create_final_nodes.parquet' in my local file system, instead of Azure Blob, and errors out saying it could not locate that file

Steps to reproduce

1) Settings.json - I have added 'blob' as the storage option, and provided the connection string, container names settings - Copy.txt 2) I initialize the index, and build the index. It completes successfully. I see that the Containers in Azure are populated with the files that we expect from the run 3) Now I perform a local search OR a Global search - it always errors out saying ''C:\create_final_nodes.parquet' could not be found

Expected Behavior

The Global Search and Local Search should have run successfully by referring to the above file(s) in Azure Blob Storage

GraphRAG Config Used

# Paste your config here

encoding_model: cl100k_base
skip_workflows: []
llm:
  api_key: 'my llm key'
  type: 'azure_openai_chat'
  model: 'gpt-4o'
  model_supports_json: true
  # max_tokens: 4000
  # request_timeout: 180.0
  api_base: 'https://my-aoai-endpoint.openai.azure.com/'
  api_version: 2024-02-15-preview
  # organization: <organization_id>
  deployment_name: 'gpt4-0'
  # tokens_per_minute: 150_000
  # requests_per_minute: 10_000
  # 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
  # temperature: 0 # temperature for sampling
  # top_p: 1 # top-p sampling
  # n: 1 # Number of completions to generate

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: "${GRAPHRAG_API_KEY}"
    type: 'azure_openai_embedding'
    model: 'text-embedding-3-small'
    api_base: 'https://my-llm-end-point.openai.azure.com/'
    api_version: 2024-02-15-preview
    # organization: <organization_id>
    deployment_name: 'text-embedding-3-small'
    # 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: 1200
  overlap: 100
  group_by_columns: [id]

input:
  type: file # or blob
  file_type: text # or csv
  base_dir: "input"
  file_encoding: utf-8
  file_pattern: ".*\\.txt$"

cache:
  type: blob
  base_dir: "cache"
  connection_string: 'DefaultEndpointsProtocol=https;AccountName=aistoragesvc;AccountKey=my-account-key;EndpointSuffix=core.windows.net'
  container_name: 'graphrag-ites-sow-cache'

storage:
  type: blob
  base_dir: "output/${timestamp}/artifacts"
  connection_string: 'DefaultEndpointsProtocol=https;AccountName=aistoragesvc;AccountKey=my-account-key;EndpointSuffix=core.windows.net'
  container_name: 'graphrag-ites-sow-output'

reporting:
  type: blob
  base_dir: "output/${timestamp}/reports"
  connection_string: 'DefaultEndpointsProtocol=https;AccountName=aistoragesvc;AccountKey=my-account-key;EndpointSuffix=core.windows.net'
  container_name: 'graphrag-ites-sow-reporting'

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: 1

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: 1

community_reports:
  ## 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
  # llm_temperature: 0 # temperature for sampling
  # llm_top_p: 1 # top-p sampling
  # llm_n: 1 # Number of completions to generate
  # max_tokens: 12000

global_search:
  # llm_temperature: 0 # temperature for sampling
  # llm_top_p: 1 # top-p sampling
  # llm_n: 1 # Number of completions to generate
  # max_tokens: 12000
  # data_max_tokens: 12000
  # map_max_tokens: 1000
  # reduce_max_tokens: 2000
  # concurrency: 32

Logs and screenshots

No response

Additional Information

GraphRAG Version: 0.2.0
Operating System: Windows 11
Python Version: 3.11.9
Related Issues: None

microsoft / graphrag