search

microsoft / graphrag

A modular graph-based Retrieval-Augmented Generation (RAG) system
https://microsoft.github.io/graphrag/
MIT License
19.89k stars 1.95k forks source link

Indexer Error #464

Closed kinfey closed 4 months ago

kinfey commented 4 months ago

Describe the bug

When I run Indexer, it always give me this error

image


{"type": "error", "data": "Error executing verb \"cluster_graph\" in create_base_entity_graph: EmptyNetworkError", "stack": "Traceback (most recent call last):\n  File \"/Users/lokinfey/conda/envs/pydev/lib/python3.10/site-packages/datashaper/workflow/workflow.py\", line 410, in _execute_verb\n    result = node.verb.func(**verb_args)\n  File \"/Users/lokinfey/conda/envs/pydev/lib/python3.10/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  File \"/Users/lokinfey/conda/envs/pydev/lib/python3.10/site-packages/pandas/core/series.py\", line 4924, in apply\n    ).apply()\n  File \"/Users/lokinfey/conda/envs/pydev/lib/python3.10/site-packages/pandas/core/apply.py\", line 1427, in apply\n    return self.apply_standard()\n  File \"/Users/lokinfey/conda/envs/pydev/lib/python3.10/site-packages/pandas/core/apply.py\", line 1507, in apply_standard\n    mapped = obj._map_values(\n  File \"/Users/lokinfey/conda/envs/pydev/lib/python3.10/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  File \"/Users/lokinfey/conda/envs/pydev/lib/python3.10/site-packages/pandas/core/algorithms.py\", line 1743, in map_array\n    return lib.map_infer(values, mapper, convert=convert)\n  File \"lib.pyx\", line 2972, in pandas._libs.lib.map_infer\n  File \"/Users/lokinfey/conda/envs/pydev/lib/python3.10/site-packages/graphrag/index/verbs/graph/clustering/cluster_graph.py\", line 61, in <lambda>\n    results = output_df[column].apply(lambda graph: run_layout(strategy, graph))\n  File \"/Users/lokinfey/conda/envs/pydev/lib/python3.10/site-packages/graphrag/index/verbs/graph/clustering/cluster_graph.py\", line 167, in run_layout\n    clusters = run_leiden(graph, strategy)\n  File \"/Users/lokinfey/conda/envs/pydev/lib/python3.10/site-packages/graphrag/index/verbs/graph/clustering/strategies/leiden.py\", line 26, in run\n    node_id_to_community_map = _compute_leiden_communities(\n  File \"/Users/lokinfey/conda/envs/pydev/lib/python3.10/site-packages/graphrag/index/verbs/graph/clustering/strategies/leiden.py\", line 61, in _compute_leiden_communities\n    community_mapping = hierarchical_leiden(\n  File \"<@beartype(graspologic.partition.leiden.hierarchical_leiden) at 0x330776e60>\", line 304, in hierarchical_leiden\n  File \"/Users/lokinfey/conda/envs/pydev/lib/python3.10/site-packages/graspologic/partition/leiden.py\", line 588, in hierarchical_leiden\n    hierarchical_clusters_native = gn.hierarchical_leiden(\nleiden.EmptyNetworkError: EmptyNetworkError\n", "source": "EmptyNetworkError", "details": null}

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: phi-3-mini
  model_supports_json: true # recommended if this is available for your model.
  max_tokens: 13000
  request_timeout: 2800.0
  api_base: http://localhost:5146/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

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: jinaai
    request_timeout: 2800.0
    api_base: http://localhost:5146/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: 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: [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
  model_supports_json: false 

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
  # 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

No response

Additional Information

sriharshaguthikonda commented 4 months ago

got similar error...let me know if you find a solution...Tqs in advance.!!

AlonsoGuevara commented 4 months ago

Hi

My general rule of thumb when facing this issue is:

Can you please check and share any of your llm responses from the cache folder?

kinfey commented 4 months ago

cache.zip @AlonsoGuevara this is my cache folder

cove9988 commented 4 months ago

check your log report at /outputs/latestdate-time/reports. mostly the llm was not working...

kinfey commented 4 months ago

but it can gen something in backend

Nuclear6 commented 4 months ago

Can you post the detailed log file?

natoverse commented 4 months ago

Consolidating alternate model issues here: #657