microsoft
[Bug]: <Error executing verb \"cluster_graph\" in create_base_entity_graph: EmptyNetworkError>
Describe the bug
Error executing verb "cluster_graph" in create_base_entity_graph: EmptyNetworkError With my own dataset, and openai API key. But do have the extracted entities in the entity_extraction folder and summarize_descriptions folders.
Steps to reproduce
No response
Expected Behavior
No response
GraphRAG Config Used
encoding_model: cl100k_base skip_workflows: [] llm: api_key: ${GRAPHRAG_API_KEY} type: openai_chat # or azure_openai_chat
model: gpt-4-turbo-preview
model: gpt-3.5-turbo-1106
model: gpt-4o-2024-05-13
model_supports_json: true # recommended if this is available for your model.
max_tokens: 4000
request_timeout: 180.0
api_base: https://.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
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: ${GRAPHRAG_API_KEY}
type: openai_embedding # or azure_openai_embedding
model: text-embedding-3-small
# api_base: https://
chunks: size: 300 overlap: 100 group_by_columns: [id] # by default, we don't allow chunks to cross documents
input: type: file # or blob file_type: text # or csv base_dir: "input" file_encoding: utf-8 file_pattern: ".*\.txt$"
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
if we wanna graphml files as output -> turn graphml to true
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
Logs and screenshots
{"type": "error", "data": "Error executing verb "cluster_graph" in create_base_entity_graph: EmptyNetworkError", "stack": "Traceback (most recent call last):\n File "/opt/anaconda3/envs/graphrag/lib/python3.11/site-packages/datashaper/workflow/workflow.py", line 410, in _execute_verb\n result = node.verb.func(**verb_args)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File "/opt/anaconda3/envs/graphrag/lib/python3.11/site-packages/graphrag/index/verbs/graph/clustering/cluster_graph.py", line 61, in cluster_graph\n results = output_df[column].apply(lambda graph: run_layout(strategy, graph))\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File "/opt/anaconda3/envs/graphrag/lib/python3.11/site-packages/pandas/core/series.py", line 4924, in apply\n ).apply()\n ^^^^^^^\n File "/opt/anaconda3/envs/graphrag/lib/python3.11/site-packages/pandas/core/apply.py", line 1427, in apply\n return self.apply_standard()\n ^^^^^^^^^^^^^^^^^^^^^\n File "/opt/anaconda3/envs/graphrag/lib/python3.11/site-packages/pandas/core/apply.py", line 1507, in apply_standard\n mapped = obj._map_values(\n ^^^^^^^^^^^^^^^^\n File "/opt/anaconda3/envs/graphrag/lib/python3.11/site-packages/pandas/core/base.py", line 921, in _map_values\n return algorithms.map_array(arr, mapper, na_action=na_action, convert=convert)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File "/opt/anaconda3/envs/graphrag/lib/python3.11/site-packages/pandas/core/algorithms.py", line 1743, in map_array\n return lib.map_infer(values, mapper, convert=convert)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File "lib.pyx", line 2972, in pandas._libs.lib.map_infer\n File "/opt/anaconda3/envs/graphrag/lib/python3.11/site-packages/graphrag/index/verbs/graph/clustering/cluster_graph.py", line 61, in
Additional Information
- GraphRAG Version:
- Operating System:
- Python Version:
- Related Issues:
