❌ Errors occurred during the pipeline run, see logs for more details (Part 2)

[mscarroll]

This is the error that I'm getting (Windows, PowerShell; Ollama installed)

16 6091f6e9e75fb0c08b45612806cf11e6 OLO (You Only Look Once) and Faster R-CNN leve... ... 300 17 6da66fe5d9df2b209d8e8cb274389bea can be a limiting factor in domains where dat... ... 300 18 31170fdcb9137905634fbe1f6f7312cd s with other neural network types, such as rec... ... 126

[19 rows x 5 columns] 🚀 create_base_extracted_entities entity_graph 0 <graphml xmlns="http://graphml.graphdrawing.or... 🚀 create_summarized_entities entity_graph 0 <graphml xmlns="http://graphml.graphdrawing.or... ❌ create_base_entity_graph None
⠹ GraphRAG Indexer ├── Loading Input (InputFileType.text) - 4 files loaded (0 filtered) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00 0:00:00 ├── create_base_text_units ├── create_base_extracted_entities ├── create_summarized_entities └── create_base_entity_graph ❌ Errors occurred during the pipeline run, see logs for more details

LOG FILE: File \"C:\XXX\gen2Env\Lib\site-packages\pandas\core\indexers\utils.py\", line 390, in check_key_length\n raise ValueError(\"Columns must be same length as key\")\nValueError: Columns must be same length as key\n", "source": "Columns must be same length as key", "details": null}

[yurochang]

same problem

[Computational-social-science]

similar problem

[myyourgit]

same problem met.

[yakeworld]

similar problem

[haiyangheart]

see https://github.com/eust-w/graphrag/commit/ad49d9a3d459858dd729e79ab7c7a8235179c97d

[mscarroll]

Update: I couldn't get @haiyangheart 's patch to work (no doubt my own misunderstanding), but I went back and looked at other issues in this thread and noticed that issue 13 is actually the same as mine (https://github.com/TheAiSingularity/graphrag-local-ollama/issues/13). I tried the fix suggested by @severian42 (manually copying the configuration yaml file).

This allowed me to get past the current error

Sadly after a couple hours of running, I ran into a new one.

❌ create_final_community_reports The last line in the log file is: \Lib\site-packages\pandas\core\indexes\range.py\", line 417, in get_loc\n raise KeyError(key)\nKeyError: 'community'\n", "source": "'community'", "details": null}

Thanks

[alexgoller]

Same error here.

[fivehaitao]

Update: I couldn't get @haiyangheart 's patch to work (no doubt my own misunderstanding), but I went back and looked at other issues in this thread and noticed that issue 13 is actually the same as mine (#13). I tried the fix suggested by @severian42 (manually copying the configuration yaml file).

This allowed me to get past the current error

Sadly after a couple hours of running, I ran into a new one.

❌ create_final_community_reports The last line in the log file is: \Lib\site-packages\pandas\core\indexes\range.py", line 417, in get_loc\n raise KeyError(key)\nKeyError: 'community'\n", "source": "'community'", "details": null}

Thanks

I am so happy to say that it is work. If you are using llama3. I hope copy the yaml file to your config works too.

Here is the links. https://github.com/TheAiSingularity/graphrag-local-ollama/issues/25#issuecomment-2337039447

[fivehaitao]

encoding_model: cl100k_base
skip_workflows: []
llm:
  api_key: ${GRAPHRAG_API_KEY}
  type: openai_chat # or azure_openai_chat
  model: llama3
  model_supports_json: true # recommended if this is available for your model.
  # max_tokens: 4000
  # request_timeout: 180.0
  api_base: http://192.168.0.239:11434/v1
  # 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: 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: ${GRAPHRAG_API_KEY}
    type: openai_embedding # or azure_openai_embedding
    model: nomic-embed-text
    api_base: http://192.168.0.239:11434/api/embeddings
    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: 64
  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: 1000
  max_input_length: 4000

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: yes
  raw_entities: yes
  top_level_nodes: yes

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