microsoft
❌ create_final_entities : Unable to run GraphRAG Pipeline
Describe the issue
I was trying to run graphRAG using llama_cpp. Got the following issue:
❌ create_final_entities ⠼ GraphRAG Indexer ├── Loading Input (text) - 1 files loaded (0 filtered) ━━━━━━ 100% 0:00:… 0:00:… ├── create_base_text_units ├── create_base_extracted_entities ├── create_summarized_entities ├── create_base_entity_graph None ⠴ GraphRAG Indexer ├── Loading Input (text) - 1 files loaded (0 filtered) ━━━━━━ 100% 0:00:… 0:00:… ├── create_base_text_units ├── create_base_extracted_entities ├── create_summarized_entities ├── create_base_entity_graph ⠴ GraphRAG Indexer ├── Loading Input (text) - 1 files loaded (0 filtered) ━━━━━━ 100% 0:00:… 0:00:… ├── create_base_text_units ├── create_base_extracted_entities ├── create_summarized_entities ├── create_base_entity_graph └── create_final_entities ❌ Errors occurred during the pipeline run, see logs for more details.
Steps to reproduce
Use the settings.yaml file to replicate the issue
GraphRAG Config Used
The settings.yaml is as follows:
encoding_model: cl100k_base skip_workflows: [] llm: api_key: ${GRAPHRAG_API_KEY} type: openai_chat # or azure_openai_chat model: mistral
model_supports_json: false # recommended if this is available for your model.
max_tokens: 4000
request_timeout: 180.0
api_base: http://localhost:8000/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: 1 # 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: ${GRAPHRAG_API_KEY} type: openai_embedding # or azure_openai_embedding model: mistral api_base: http://localhost:8000/v1 # api_version: 2024-02-15-preview # organization: <organization_id> # deployment_name: <azure_model_deployment_name> # tokens_per_minute: 150_000 # set a leaky bucket throttle # requests_per_minute: 10_000 # set a leaky bucket throttle # max_retries: 10 # max_retry_wait: 10.0 # sleep_on_rate_limit_recommendation: true # whether to sleep when azure suggests wait-times # concurrent_requests: 25 # the number of parallel inflight requests that may be made batch_size: 1 # the number of documents to send in a single request # batch_max_tokens: 8191 # the maximum number of tokens to send in a single request # target: required # or optional
chunks: size: 300 overlap: 100 group_by_columns: [id] # by default, we don't allow chunks to cross documents
input: type: file # or blob file_type: text # or csv base_dir: "input" file_encoding: utf-8 file_pattern: ".*\.txt$"
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: [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
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
Indexing Engine Log file shows this:
04:36:19,87 datashaper.workflow.workflow ERROR Error executing verb "text_embed" in create_final_entities: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (16,) + inhomogeneous part. Traceback (most recent call last): File "/usr/local/lib/python3.10/dist-packages/datashaper/workflow/workflow.py", line 415, in _execute_verb result = await result File "/usr/local/lib/python3.10/dist-packages/graphrag/index/verbs/text/embed/text_embed.py", line 105, in text_embed return await _text_embed_in_memory( File "/usr/local/lib/python3.10/dist-packages/graphrag/index/verbs/text/embed/text_embed.py", line 130, in _text_embed_in_memory result = await strategy_exec(texts, callbacks, cache, strategy_args) File "/usr/local/lib/python3.10/dist-packages/graphrag/index/verbs/text/embed/strategies/openai.py", line 61, in run embeddings = await _execute(llm, text_batches, ticker, semaphore) File "/usr/local/lib/python3.10/dist-packages/graphrag/index/verbs/text/embed/strategies/openai.py", line 105, in _execute results = await asyncio.gather(*futures) File "/usr/local/lib/python3.10/dist-packages/graphrag/index/verbs/text/embed/strategies/openai.py", line 100, in embed result = np.array(chunk_embeddings.output) ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (16,) + inhomogeneous part. 04:36:19,92 graphrag.index.reporting.file_workflow_callbacks INFO Error executing verb "text_embed" in create_final_entities: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (16,) + inhomogeneous part. details=None 04:36:19,96 graphrag.index.run ERROR error running workflow create_final_entities Traceback (most recent call last): File "/usr/local/lib/python3.10/dist-packages/graphrag/index/run.py", line 323, in run_pipeline result = await workflow.run(context, callbacks) File "/usr/local/lib/python3.10/dist-packages/datashaper/workflow/workflow.py", line 369, in run timing = await self._execute_verb(node, context, callbacks) File "/usr/local/lib/python3.10/dist-packages/datashaper/workflow/workflow.py", line 415, in _execute_verb result = await result File "/usr/local/lib/python3.10/dist-packages/graphrag/index/verbs/text/embed/text_embed.py", line 105, in text_embed return await _text_embed_in_memory( File "/usr/local/lib/python3.10/dist-packages/graphrag/index/verbs/text/embed/text_embed.py", line 130, in _text_embed_in_memory result = await strategy_exec(texts, callbacks, cache, strategy_args) File "/usr/local/lib/python3.10/dist-packages/graphrag/index/verbs/text/embed/strategies/openai.py", line 61, in run embeddings = await _execute(llm, text_batches, ticker, semaphore) File "/usr/local/lib/python3.10/dist-packages/graphrag/index/verbs/text/embed/strategies/openai.py", line 105, in _execute results = await asyncio.gather(*futures) File "/usr/local/lib/python3.10/dist-packages/graphrag/index/verbs/text/embed/strategies/openai.py", line 100, in embed result = np.array(chunk_embeddings.output) ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (16,) + inhomogeneous part. 04:36:19,97 graphrag.index.reporting.file_workflow_callbacks INFO Error running pipeline! details=None
Logs.json File shows this:
{"type": "error", "data": "Error executing verb "text_embed" in create_final_entities: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (16,) + inhomogeneous part.", "stack": "Traceback (most recent call last):\n File "/usr/local/lib/python3.10/dist-packages/datashaper/workflow/workflow.py", line 415, in _execute_verb\n result = await result\n File "/usr/local/lib/python3.10/dist-packages/graphrag/index/verbs/text/embed/text_embed.py", line 105, in text_embed\n return await _text_embed_in_memory(\n File "/usr/local/lib/python3.10/dist-packages/graphrag/index/verbs/text/embed/text_embed.py", line 130, in _text_embed_in_memory\n result = await strategy_exec(texts, callbacks, cache, strategy_args)\n File "/usr/local/lib/python3.10/dist-packages/graphrag/index/verbs/text/embed/strategies/openai.py", line 61, in run\n embeddings = await _execute(llm, text_batches, ticker, semaphore)\n File "/usr/local/lib/python3.10/dist-packages/graphrag/index/verbs/text/embed/strategies/openai.py", line 105, in _execute\n results = await asyncio.gather(*futures)\n File "/usr/local/lib/python3.10/dist-packages/graphrag/index/verbs/text/embed/strategies/openai.py", line 100, in embed\n result = np.array(chunk_embeddings.output)\nValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (16,) + inhomogeneous part.\n", "source": "setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (16,) + inhomogeneous part.", "details": null}
{"type": "error", "data": "Error running pipeline!", "stack": "Traceback (most recent call last):\n File "/usr/local/lib/python3.10/dist-packages/graphrag/index/run.py", line 323, in run_pipeline\n result = await workflow.run(context, callbacks)\n File "/usr/local/lib/python3.10/dist-packages/datashaper/workflow/workflow.py", line 369, in run\n timing = await self._execute_verb(node, context, callbacks)\n File "/usr/local/lib/python3.10/dist-packages/datashaper/workflow/workflow.py", line 415, in _execute_verb\n result = await result\n File "/usr/local/lib/python3.10/dist-packages/graphrag/index/verbs/text/embed/text_embed.py", line 105, in text_embed\n return await _text_embed_in_memory(\n File "/usr/local/lib/python3.10/dist-packages/graphrag/index/verbs/text/embed/text_embed.py", line 130, in _text_embed_in_memory\n result = await strategy_exec(texts, callbacks, cache, strategy_args)\n File "/usr/local/lib/python3.10/dist-packages/graphrag/index/verbs/text/embed/strategies/openai.py", line 61, in run\n embeddings = await _execute(llm, text_batches, ticker, semaphore)\n File "/usr/local/lib/python3.10/dist-packages/graphrag/index/verbs/text/embed/strategies/openai.py", line 105, in _execute\n results = await asyncio.gather(*futures)\n File "/usr/local/lib/python3.10/dist-packages/graphrag/index/verbs/text/embed/strategies/openai.py", line 100, in embed\n result = np.array(chunk_embeddings.output)\nValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (16,) + inhomogeneous part.\n", "source": "setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (16,) + inhomogeneous part.", "details": null}
Additional Information
- GraphRAG Version: v0.1.1
- Operating System: Ubuntu 20.04
- Python Version: 3.10.14
- Related Issues: 442
