microsoft
Error executing verb \"cluster_graph\" in create_base_entity_graph: EmptyNetworkError"[Bug]: <title>
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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
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: <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
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: <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: 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:
- Operating System:
- Python Version:
- Related Issues:
