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Describe the bug

the former project can run well, but this project i met the problem i dont know how to fix it. I ve checked the encoding is utf-8 and the api key is valid , here is the detailed description in log: 10:25:19,481 datashaper.workflow.workflow ERROR Error executing verb "cluster_graph" in create_base_entity_graph: EmptyNetworkError Traceback (most recent call last): File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\datashaper\workflow\workflow.py", line 410, in _execute_verb result = node.verb.func(verb_args) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\graphrag\index\verbs\graph\clustering\cluster_graph.py", line 61, in cluster_graph results = output_df[column].apply(lambda graph: run_layout(strategy, graph)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\pandas\core\series.py", line 4924, in apply ).apply() ^^^^^^^ File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\pandas\core\apply.py", line 1427, in apply return self.apply_standard() ^^^^^^^^^^^^^^^^^^^^^ File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\pandas\core\apply.py", line 1507, in apply_standard mapped = obj._map_values( ^^^^^^^^^^^^^^^^ File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\pandas\core\base.py", line 921, in _map_values return algorithms.map_array(arr, mapper, na_action=na_action, convert=convert) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\pandas\core\algorithms.py", line 1743, in map_array return lib.map_infer(values, mapper, convert=convert) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "lib.pyx", line 2972, in pandas._libs.lib.map_infer File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\graphrag\index\verbs\graph\clustering\cluster_graph.py", line 61, in results = output_df[column].apply(lambda graph: run_layout(strategy, graph)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\graphrag\index\verbs\graph\clustering\cluster_graph.py", line 167, in run_layout clusters = run_leiden(graph, strategy) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\graphrag\index\verbs\graph\clustering\strategies\leiden.py", line 26, in run node_id_to_community_map = _compute_leiden_communities( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\graphrag\index\verbs\graph\clustering\strategies\leiden.py", line 61, in _compute_leiden_communities community_mapping = hierarchical_leiden( ^^^^^^^^^^^^^^^^^^^^ File "<@beartype(graspologic.partition.leiden.hierarchical_leiden) at 0x20ab1a639c0>", line 304, in hierarchical_leiden File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\graspologic\partition\leiden.py", line 588, in hierarchical_leiden hierarchical_clusters_native = gn.hierarchical_leiden( ^^^^^^^^^^^^^^^^^^^^^^^ leiden.EmptyNetworkError: EmptyNetworkError 10:25:19,487 graphrag.index.reporting.file_workflow_callbacks INFO Error executing verb "cluster_graph" in create_base_entity_graph: EmptyNetworkError details=None 10:25:19,487 graphrag.index.run ERROR error running workflow create_base_entity_graph Traceback (most recent call last): File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\graphrag\index\run.py", line 323, in run_pipeline result = await workflow.run(context, callbacks) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\datashaper\workflow\workflow.py", line 369, in run timing = await self._execute_verb(node, context, callbacks) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\datashaper\workflow\workflow.py", line 410, in _execute_verb result = node.verb.func(verb_args) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\graphrag\index\verbs\graph\clustering\cluster_graph.py", line 61, in cluster_graph results = output_df[column].apply(lambda graph: run_layout(strategy, graph)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\pandas\core\series.py", line 4924, in apply ).apply() ^^^^^^^ File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\pandas\core\apply.py", line 1427, in apply return self.apply_standard() ^^^^^^^^^^^^^^^^^^^^^ File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\pandas\core\apply.py", line 1507, in apply_standard mapped = obj._map_values( ^^^^^^^^^^^^^^^^ File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\pandas\core\base.py", line 921, in _map_values return algorithms.map_array(arr, mapper, na_action=na_action, convert=convert) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\pandas\core\algorithms.py", line 1743, in map_array return lib.map_infer(values, mapper, convert=convert) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "lib.pyx", line 2972, in pandas._libs.lib.map_infer File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\graphrag\index\verbs\graph\clustering\cluster_graph.py", line 61, in results = output_df[column].apply(lambda graph: run_layout(strategy, graph)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\graphrag\index\verbs\graph\clustering\cluster_graph.py", line 167, in run_layout clusters = run_leiden(graph, strategy) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\graphrag\index\verbs\graph\clustering\strategies\leiden.py", line 26, in run node_id_to_community_map = _compute_leiden_communities( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\graphrag\index\verbs\graph\clustering\strategies\leiden.py", line 61, in _compute_leiden_communities community_mapping = hierarchical_leiden( ^^^^^^^^^^^^^^^^^^^^ File "<@beartype(graspologic.partition.leiden.hierarchical_leiden) at 0x20ab1a639c0>", line 304, in hierarchical_leiden File "E:\python\PyCharm Community Edition 2023.2.1\poly_metric_py\venv\Lib\site-packages\graspologic\partition\leiden.py", line 588, in hierarchical_leiden hierarchical_clusters_native = gn.hierarchical_leiden( ^^^^^^^^^^^^^^^^^^^^^^^ leiden.EmptyNetworkError: EmptyNetworkError 10:25:19,488 graphrag.index.reporting.file_workflow_callbacks INFO Error running pipeline! details=None

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-3.5-turbo model_supports_json: true # recommended if this is available for your model.

max_tokens: 4000

request_timeout: 180.0

api_base: "https://api.chatanywhere.tech/v1"

api_version: 2024-02-15-preview

organization:

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

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: openai_embedding # or azure_openai_embedding model: text-embedding-3-small api_base: "https://api.chatanywhere.tech/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: 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] # 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:

container_name:

storage: type: file # or blob base_dir: "output/${timestamp}/artifacts"

connection_string:

container_name:

reporting: type: file # or console, blob base_dir: "output/${timestamp}/reports"

connection_string:

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: 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

microsoft / graphrag

Error executing verb \"cluster_graph\" in create_base_entity_graph: EmptyNetworkError"[Bug]: <title> #864

Do you need to file an issue?

Describe the bug

Steps to reproduce

Expected Behavior

GraphRAG Config Used

max_tokens: 4000

request_timeout: 180.0

api_version: 2024-02-15-preview

organization:

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

temperature: 0 # temperature for sampling

top_p: 1 # top-p sampling

n: 1 # Number of completions to generate

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

parallelization: override the global parallelization settings for embeddings

api_version: 2024-02-15-preview

connection_string:

container_name:

connection_string:

container_name:

connection_string:

container_name:

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

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

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

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

num_walks: 10

walk_length: 40

window_size: 2

iterations: 3

random_seed: 597832

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

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

Additional Information