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claim_extraction:
prompt: "prompts/claim_extraction.txt"
description: "Any claims or facts that could be relevant to information discovery."
max_gleanings: 0
Traceback shows:
`INFO: Reading settings from rag_understanding_kernel/settings.yaml
creating llm client with {'api_key': 'REDACTED,len=9', 'type': "openai_chat", 'model': 'qwen2', 'max_tokens': 4000, 'temperature': 0.0, 'top_p': 1.0, 'request_timeout': 180.0, 'api_base': 'http://localhost:11434/v1', 'api_version': None, 'organization': None, 'proxy': None, 'cognitive_services_endpoint': None, 'deployment_name': None, 'model_supports_json': None, 'tokens_per_minute': 0, 'requests_per_minute': 0, 'max_retries': 10, 'max_retry_wait': 10.0, 'sleep_on_rate_limit_recommendation': True, 'concurrent_requests': 25}
Error parsing search response json
Traceback (most recent call last):
File "/mnt/codes/graphrag/graphrag-local-ollama/graphrag/query/structured_search/global_search/search.py", line 194, in _map_response_single_batch
processed_response = self.parse_search_response(search_response)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/mnt/codes/graphrag/graphrag-local-ollama/graphrag/query/structured_search/global_search/search.py", line 232, in parse_search_response
parsed_elements = json.loads(search_response)["points"]
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/mnt/anaconda3_install/envs/graphrag-ollama-local/lib/python3.11/json/init.py", line 346, in loads
return _default_decoder.decode(s)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/mnt/anaconda3_install/envs/graphrag-ollama-local/lib/python3.11/json/decoder.py", line 337, in decode
obj, end = self.raw_decode(s, idx=_w(s, 0).end())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/mnt/anaconda3_install/envs/graphrag-ollama-local/lib/python3.11/json/decoder.py", line 355, in raw_decode
raise JSONDecodeError("Expecting value", s, err.value) from None
json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)
Error parsing search response json
Traceback (most recent call last):
File "/mnt/codes/graphrag/graphrag-local-ollama/graphrag/query/structured_search/global_search/search.py", line 194, in _map_response_single_batch
processed_response = self.parse_search_response(search_response)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/mnt/codes/graphrag/graphrag-local-ollama/graphrag/query/structured_search/global_search/search.py", line 232, in parse_search_response
parsed_elements = json.loads(search_response)["points"]
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/mnt/anaconda3_install/envs/graphrag-ollama-local/lib/python3.11/json/init.py", line 346, in loads
return _default_decoder.decode(s)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/mnt/anaconda3_install/envs/graphrag-ollama-local/lib/python3.11/json/decoder.py", line 337, in decode
obj, end = self.raw_decode(s, idx=_w(s, 0).end())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/mnt/anaconda3_install/envs/graphrag-ollama-local/lib/python3.11/json/decoder.py", line 355, in raw_decode
raise JSONDecodeError("Expecting value", s, err.value) from None
json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)
Error parsing search response json
Traceback (most recent call last):
File "/mnt/codes/graphrag/graphrag-local-ollama/graphrag/query/structured_search/global_search/search.py", line 194, in _map_response_single_batch
processed_response = self.parse_search_response(search_response)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/mnt/codes/graphrag/graphrag-local-ollama/graphrag/query/structured_search/global_search/search.py", line 232, in parse_search_response
parsed_elements = json.loads(search_response)["points"]
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/mnt/anaconda3_install/envs/graphrag-ollama-local/lib/python3.11/json/init.py", line 346, in loads
return _default_decoder.decode(s)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/mnt/anaconda3_install/envs/graphrag-ollama-local/lib/python3.11/json/decoder.py", line 337, in decode
obj, end = self.raw_decode(s, idx=_w(s, 0).end())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/mnt/anaconda3_install/envs/graphrag-ollama-local/lib/python3.11/json/decoder.py", line 355, in raw_decode
raise JSONDecodeError("Expecting value", s, err.value) from None
json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)
SUCCESS: Global Search Response: I am sorry but I am unable to answer this question given the provided data.
`
My setting.yaml shows:
`encoding_model: cl100k_base
skip_workflows: []
llm:
api_key: ${GRAPHRAG_API_KEY}
type: openai_chat # or azure_openai_chat
model: qwen2
api_base: http://localhost:11434/v1
parallelization:
stagger: 0.3
async_mode: threaded # or asyncio
embeddings:
parallelization: override the global parallelization settings for embeddings
async_mode: threaded # or asyncio
llm:
api_key: ${GRAPHRAG_API_KEY}
type: openai_embedding # or azure_openai_embedding
model: nomic-embed-text
api_base: http://localhost:11434/api
chunks:
size: 300
overlap: 100
group_by_columns: [id] # by default, we don't allow chunks to cross documents
input:
type: file # or blob
file_type: text # or csv
base_dir: "input"
file_encoding: utf-8
file_pattern: ".*\.md$"
cache:
type: file # or blob
base_dir: "cache"
storage:
type: file # or blob
base_dir: "output/${timestamp}/artifacts"
reporting:
type: file # or console, blob
base_dir: "output/${timestamp}/reports"
entity_extraction:
prompt: "prompts/entity_extraction.txt"
entity_types: [organization,person,geo,event]
max_gleanings: 0
summarize_descriptions:
prompt: "prompts/summarize_descriptions.txt"
max_length: 500
claim_extraction:
prompt: "prompts/claim_extraction.txt"
description: "Any claims or facts that could be relevant to information discovery."
max_gleanings: 0
community_report:
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
umap:
enabled: false # if true, will generate UMAP embeddings for nodes
snapshots:
graphml: yes
raw_entities: yes
top_level_nodes: yes
local_search:
global_search:
max_tokens: 12000
data_max_tokens: 12000
map_max_tokens: 1000
reduce_max_tokens: 2000
concurrency: 32
`
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