Global Search

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# Copyright (c) 2024 Microsoft Corporation.
# Licensed under the MIT License.
# Copyright (c) 2024 Microsoft Corporation.
# Licensed under the MIT License.

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import os

import pandas as pd
from graphrag.query.indexer_adapters import (
    read_indexer_communities,
    read_indexer_entities,
    read_indexer_reports,
)
from graphrag.query.structured_search.global_search.community_context import (
    GlobalCommunityContext,
)
from graphrag.query.structured_search.global_search.search import GlobalSearch
from graphrag.tokenizer.get_tokenizer import get_tokenizer
from graphrag_llm.completion import create_completion
from graphrag_llm.config import ModelConfig
import os

import pandas as pd
from graphrag.query.indexer_adapters import (
    read_indexer_communities,
    read_indexer_entities,
    read_indexer_reports,
)
from graphrag.query.structured_search.global_search.community_context import (
    GlobalCommunityContext,
)
from graphrag.query.structured_search.global_search.search import GlobalSearch
from graphrag.tokenizer.get_tokenizer import get_tokenizer
from graphrag_llm.completion import create_completion
from graphrag_llm.config import ModelConfig

Global Search example¶

Global search method generates answers by searching over all AI-generated community reports in a map-reduce fashion. This is a resource-intensive method, but often gives good responses for questions that require an understanding of the dataset as a whole (e.g. What are the most significant values of the herbs mentioned in this notebook?).

LLM setup¶

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api_key = os.environ["GRAPHRAG_API_KEY"]

config = ModelConfig(
    type="litellm",
    model_provider="openai",
    model="gpt-4.1",
    api_key=api_key,
)
model = create_completion(config)

tokenizer = get_tokenizer(config)
api_key = os.environ["GRAPHRAG_API_KEY"]

config = ModelConfig(
    type="litellm",
    model_provider="openai",
    model="gpt-4.1",
    api_key=api_key,
)
model = create_completion(config)

tokenizer = get_tokenizer(config)

Load community reports as context for global search¶

Load all community reports in the community_reports table from GraphRAG, to be used as context data for global search.
Load entities from the entities tables from GraphRAG, to be used for calculating community weights for context ranking. Note that this is optional (if no entities are provided, we will not calculate community weights and only use the rank attribute in the community reports table for context ranking)
Load all communities in the communities table from the GraphRAG, to be used to reconstruct the community graph hierarchy for dynamic community selection.

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# parquet files generated from indexing pipeline
INPUT_DIR = "./inputs/operation dulce"
COMMUNITY_TABLE = "communities"
COMMUNITY_REPORT_TABLE = "community_reports"
ENTITY_TABLE = "entities"

# community level in the Leiden community hierarchy from which we will load the community reports
# higher value means we use reports from more fine-grained communities (at the cost of higher computation cost)
COMMUNITY_LEVEL = 2
# parquet files generated from indexing pipeline
INPUT_DIR = "./inputs/operation dulce"
COMMUNITY_TABLE = "communities"
COMMUNITY_REPORT_TABLE = "community_reports"
ENTITY_TABLE = "entities"

# community level in the Leiden community hierarchy from which we will load the community reports
# higher value means we use reports from more fine-grained communities (at the cost of higher computation cost)
COMMUNITY_LEVEL = 2

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community_df = pd.read_parquet(f"{INPUT_DIR}/{COMMUNITY_TABLE}.parquet")
entity_df = pd.read_parquet(f"{INPUT_DIR}/{ENTITY_TABLE}.parquet")
report_df = pd.read_parquet(f"{INPUT_DIR}/{COMMUNITY_REPORT_TABLE}.parquet")

communities = read_indexer_communities(community_df, report_df)
reports = read_indexer_reports(report_df, community_df, COMMUNITY_LEVEL)
entities = read_indexer_entities(entity_df, community_df, COMMUNITY_LEVEL)

print(f"Total report count: {len(report_df)}")
print(
    f"Report count after filtering by community level {COMMUNITY_LEVEL}: {len(reports)}"
)

report_df.head()
community_df = pd.read_parquet(f"{INPUT_DIR}/{COMMUNITY_TABLE}.parquet")
entity_df = pd.read_parquet(f"{INPUT_DIR}/{ENTITY_TABLE}.parquet")
report_df = pd.read_parquet(f"{INPUT_DIR}/{COMMUNITY_REPORT_TABLE}.parquet")

communities = read_indexer_communities(community_df, report_df)
reports = read_indexer_reports(report_df, community_df, COMMUNITY_LEVEL)
entities = read_indexer_entities(entity_df, community_df, COMMUNITY_LEVEL)

print(f"Total report count: {len(report_df)}")
print(
    f"Report count after filtering by community level {COMMUNITY_LEVEL}: {len(reports)}"
)

report_df.head()

Total report count: 10
Report count after filtering by community level 2: 10

Out[5]:

	id	human_readable_id	community	level	parent	children	title	summary	full_content	rank	rating_explanation	findings	full_content_json	period	size
0	9785e64b429dacd70cce8238051f3438b387ebcd6920ef...	7	7	1	0	[]	Paranormal Military Squad and Operation Dulce	This community centers on the Paranormal Milit...	# Paranormal Military Squad and Operation Dulc...	8.5	The impact severity rating is high due to the ...	[{'explanation': 'The Paranormal Military Squa...	{\n "title": "Paranormal Military Squad and...	2026-01-13	4
1	212c8ff1796bff731abe3d54f3216511ab15d5fb0d97eb...	8	8	1	0	[]	Paranormal Military Squad: Leadership and Scie...	This community centers on the Paranormal Milit...	# Paranormal Military Squad: Leadership and Sc...	8.0	The community poses a high impact due to its i...	[{'explanation': 'Taylor Cruz, often referred ...	{\n "title": "Paranormal Military Squad: Le...	2026-01-13	3
2	dbff99eaacade8ac4337a9bde0f533313445f0643ab3d0...	9	9	1	0	[]	Paranormal Military Squad and Operation: Dulce...	This community centers around the Paranormal M...	# Paranormal Military Squad and Operation: Dul...	8.5	The community poses a high impact severity due...	[{'explanation': 'The military complex is the ...	{\n "title": "Paranormal Military Squad and...	2026-01-13	3
3	b6e8ab1ac8ecc605bbec09ad78819b95ac08d62c5a9991...	0	0	0	-1	[7, 8, 9]	Paranormal Military Squad and Operation: Dulce	This community centers on the Paranormal Milit...	# Paranormal Military Squad and Operation: Dul...	8.5	The community poses a high impact due to its e...	[{'explanation': 'Taylor Cruz is the central a...	{\n "title": "Paranormal Military Squad and...	2026-01-13	10
4	97038bee58306d13b709b615fb2b816cae0c11273a9e73...	1	1	0	-1	[]	Team of Agents Investigating Dulce Base	This community centers on a specialized team o...	# Team of Agents Investigating Dulce Base\n\nT...	7.5	The impact severity rating is high due to the ...	[{'explanation': 'The core of this community i...	{\n "title": "Team of Agents Investigating ...	2026-01-13	5

Build global context based on community reports¶

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context_builder = GlobalCommunityContext(
    community_reports=reports,
    communities=communities,
    entities=entities,  # default to None if you don't want to use community weights for ranking
    tokenizer=tokenizer,
)
context_builder = GlobalCommunityContext(
    community_reports=reports,
    communities=communities,
    entities=entities,  # default to None if you don't want to use community weights for ranking
    tokenizer=tokenizer,
)

Perform global search¶

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context_builder_params = {
    "use_community_summary": False,  # False means using full community reports. True means using community short summaries.
    "shuffle_data": True,
    "include_community_rank": True,
    "min_community_rank": 0,
    "community_rank_name": "rank",
    "include_community_weight": True,
    "community_weight_name": "occurrence weight",
    "normalize_community_weight": True,
    "max_tokens": 12_000,  # change this based on the token limit you have on your model (if you are using a model with 8k limit, a good setting could be 5000)
    "context_name": "Reports",
}

map_llm_params = {
    "max_tokens": 1000,
    "temperature": 0.0,
}

reduce_llm_params = {
    "max_tokens": 2000,  # change this based on the token limit you have on your model (if you are using a model with 8k limit, a good setting could be 1000-1500)
    "temperature": 0.0,
}
context_builder_params = {
    "use_community_summary": False,  # False means using full community reports. True means using community short summaries.
    "shuffle_data": True,
    "include_community_rank": True,
    "min_community_rank": 0,
    "community_rank_name": "rank",
    "include_community_weight": True,
    "community_weight_name": "occurrence weight",
    "normalize_community_weight": True,
    "max_tokens": 12_000,  # change this based on the token limit you have on your model (if you are using a model with 8k limit, a good setting could be 5000)
    "context_name": "Reports",
}

map_llm_params = {
    "max_tokens": 1000,
    "temperature": 0.0,
}

reduce_llm_params = {
    "max_tokens": 2000,  # change this based on the token limit you have on your model (if you are using a model with 8k limit, a good setting could be 1000-1500)
    "temperature": 0.0,
}

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search_engine = GlobalSearch(
    model=model,
    context_builder=context_builder,
    tokenizer=tokenizer,
    max_data_tokens=12_000,  # change this based on the token limit you have on your model (if you are using a model with 8k limit, a good setting could be 5000)
    map_llm_params=dict(map_llm_params),
    reduce_llm_params=dict(reduce_llm_params),
    allow_general_knowledge=False,  # set this to True will add instruction to encourage the LLM to incorporate general knowledge in the response, which may increase hallucinations, but could be useful in some use cases.
    json_mode=False,
    context_builder_params=context_builder_params,
    concurrent_coroutines=32,
    response_type="multiple paragraphs",  # free form text describing the response type and format, can be anything, e.g. prioritized list, single paragraph, multiple paragraphs, multiple-page report
)
search_engine = GlobalSearch(
    model=model,
    context_builder=context_builder,
    tokenizer=tokenizer,
    max_data_tokens=12_000,  # change this based on the token limit you have on your model (if you are using a model with 8k limit, a good setting could be 5000)
    map_llm_params=dict(map_llm_params),
    reduce_llm_params=dict(reduce_llm_params),
    allow_general_knowledge=False,  # set this to True will add instruction to encourage the LLM to incorporate general knowledge in the response, which may increase hallucinations, but could be useful in some use cases.
    json_mode=False,
    context_builder_params=context_builder_params,
    concurrent_coroutines=32,
    response_type="multiple paragraphs",  # free form text describing the response type and format, can be anything, e.g. prioritized list, single paragraph, multiple paragraphs, multiple-page report
)

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result = await search_engine.search("What is operation dulce?")

print(result.response)
result = await search_engine.search("What is operation dulce?")

print(result.response)

Async request failed with exception=litellm.AuthenticationError: AuthenticationError: OpenAIException - Incorrect API key provided: ArzIHXTm************************************************************************dHdW. You can find your API key at https://platform.openai.com/account/api-keys.
Traceback (most recent call last):
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/llms/openai/openai.py", line 888, in acompletion
    headers, response = await self.make_openai_chat_completion_request(
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    ...<4 lines>...
    )
    ^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/litellm_core_utils/logging_utils.py", line 300, in async_wrapper
    result: Final = await func(*args, **kwargs)
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/llms/openai/openai.py", line 447, in make_openai_chat_completion_request
    raise e
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/llms/openai/openai.py", line 423, in make_openai_chat_completion_request
    raw_response = await openai_aclient.chat.completions.with_raw_response.create(**data, timeout=timeout)
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/openai/_legacy_response.py", line 386, in wrapped
    return cast(LegacyAPIResponse[R], await func(*args, **kwargs))
                                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/openai/resources/chat/completions/completions.py", line 2907, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
    ...<55 lines>...
    )
    ^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/openai/_base_client.py", line 1992, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/openai/_base_client.py", line 1777, in request
    raise self._make_status_error_from_response(err.response) from None
openai.AuthenticationError: Error code: 401 - {'error': {'message': 'Incorrect API key provided: ArzIHXTm************************************************************************dHdW. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}}

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/main.py", line 647, in acompletion
    response = await _resolve_dispatched_chat_response(init_response)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/main.py", line 712, in _resolve_dispatched_chat_response
    return await pending
           ^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/llms/openai/openai.py", line 948, in acompletion
    raise OpenAIError(
    ...<4 lines>...
    )
litellm.llms.openai.common_utils.OpenAIError: Error code: 401 - {'error': {'message': 'Incorrect API key provided: ArzIHXTm************************************************************************dHdW. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}}

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/runner/work/graphrag/graphrag/packages/graphrag-llm/graphrag_llm/middleware/with_logging.py", line 64, in _request_count_middleware_async
    return await async_middleware(**kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/packages/graphrag-llm/graphrag_llm/middleware/with_request_count.py", line 72, in _request_count_middleware_async
    result = await async_middleware(**kwargs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/packages/graphrag-llm/graphrag_llm/middleware/with_metrics.py", line 80, in _metrics_middleware_async
    response = await async_middleware(**kwargs)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/packages/graphrag-llm/graphrag_llm/completion/lite_llm_completion.py", line 291, in _base_completion_async
    response = await litellm.acompletion(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^
        **new_args,
        ^^^^^^^^^^^
    )
    ^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/utils.py", line 2065, in wrapper_async
    raise e
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/utils.py", line 1861, in wrapper_async
    result = await original_function(*args, **kwargs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/main.py", line 700, in acompletion
    raise exception_type(
          ~~~~~~~~~~~~~~^
        model=model,
        ^^^^^^^^^^^^
    ...<3 lines>...
        extra_kwargs=kwargs,
        ^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/litellm_core_utils/exception_mapping_utils.py", line 2675, in exception_type
    raise e  # it's already mapped
    ^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/litellm_core_utils/exception_mapping_utils.py", line 2436, in exception_type
    _map_openai_exception(
    ~~~~~~~~~~~~~~~~~~~~~^
        model=model,
        ^^^^^^^^^^^^
    ...<5 lines>...
        extra_information=extra_information,
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/litellm_core_utils/exception_mapping_utils.py", line 409, in _map_openai_exception
    raise AuthenticationError(
    ...<5 lines>...
    )
litellm.exceptions.AuthenticationError: litellm.AuthenticationError: AuthenticationError: OpenAIException - Incorrect API key provided: ArzIHXTm************************************************************************dHdW. You can find your API key at https://platform.openai.com/account/api-keys.

Exception in _map_response_single_batch
Traceback (most recent call last):
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/llms/openai/openai.py", line 888, in acompletion
    headers, response = await self.make_openai_chat_completion_request(
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    ...<4 lines>...
    )
    ^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/litellm_core_utils/logging_utils.py", line 300, in async_wrapper
    result: Final = await func(*args, **kwargs)
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/llms/openai/openai.py", line 447, in make_openai_chat_completion_request
    raise e
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/llms/openai/openai.py", line 423, in make_openai_chat_completion_request
    raw_response = await openai_aclient.chat.completions.with_raw_response.create(**data, timeout=timeout)
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/openai/_legacy_response.py", line 386, in wrapped
    return cast(LegacyAPIResponse[R], await func(*args, **kwargs))
                                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/openai/resources/chat/completions/completions.py", line 2907, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
    ...<55 lines>...
    )
    ^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/openai/_base_client.py", line 1992, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/openai/_base_client.py", line 1777, in request
    raise self._make_status_error_from_response(err.response) from None
openai.AuthenticationError: Error code: 401 - {'error': {'message': 'Incorrect API key provided: ArzIHXTm************************************************************************dHdW. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}}

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/main.py", line 647, in acompletion
    response = await _resolve_dispatched_chat_response(init_response)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/main.py", line 712, in _resolve_dispatched_chat_response
    return await pending
           ^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/llms/openai/openai.py", line 948, in acompletion
    raise OpenAIError(
    ...<4 lines>...
    )
litellm.llms.openai.common_utils.OpenAIError: Error code: 401 - {'error': {'message': 'Incorrect API key provided: ArzIHXTm************************************************************************dHdW. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}}

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/runner/work/graphrag/graphrag/packages/graphrag/graphrag/query/structured_search/global_search/search.py", line 238, in _map_response_single_batch
    model_response = await self.model.completion_async(
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    ...<3 lines>...
    )
    ^
  File "/home/runner/work/graphrag/graphrag/packages/graphrag-llm/graphrag_llm/completion/lite_llm_completion.py", line 194, in completion_async
    response = await self._completion_async(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    ...<4 lines>...
    )
    ^
  File "/home/runner/work/graphrag/graphrag/packages/graphrag-llm/graphrag_llm/middleware/with_logging.py", line 64, in _request_count_middleware_async
    return await async_middleware(**kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/packages/graphrag-llm/graphrag_llm/middleware/with_request_count.py", line 72, in _request_count_middleware_async
    result = await async_middleware(**kwargs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/packages/graphrag-llm/graphrag_llm/middleware/with_metrics.py", line 80, in _metrics_middleware_async
    response = await async_middleware(**kwargs)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/packages/graphrag-llm/graphrag_llm/completion/lite_llm_completion.py", line 291, in _base_completion_async
    response = await litellm.acompletion(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^
        **new_args,
        ^^^^^^^^^^^
    )
    ^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/utils.py", line 2065, in wrapper_async
    raise e
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/utils.py", line 1861, in wrapper_async
    result = await original_function(*args, **kwargs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/main.py", line 700, in acompletion
    raise exception_type(
          ~~~~~~~~~~~~~~^
        model=model,
        ^^^^^^^^^^^^
    ...<3 lines>...
        extra_kwargs=kwargs,
        ^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/litellm_core_utils/exception_mapping_utils.py", line 2675, in exception_type
    raise e  # it's already mapped
    ^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/litellm_core_utils/exception_mapping_utils.py", line 2436, in exception_type
    _map_openai_exception(
    ~~~~~~~~~~~~~~~~~~~~~^
        model=model,
        ^^^^^^^^^^^^
    ...<5 lines>...
        extra_information=extra_information,
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/litellm_core_utils/exception_mapping_utils.py", line 409, in _map_openai_exception
    raise AuthenticationError(
    ...<5 lines>...
    )
litellm.exceptions.AuthenticationError: litellm.AuthenticationError: AuthenticationError: OpenAIException - Incorrect API key provided: ArzIHXTm************************************************************************dHdW. You can find your API key at https://platform.openai.com/account/api-keys.

Async request failed with exception=litellm.AuthenticationError: AuthenticationError: OpenAIException - Incorrect API key provided: ArzIHXTm************************************************************************dHdW. You can find your API key at https://platform.openai.com/account/api-keys.
Traceback (most recent call last):
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/llms/openai/openai.py", line 888, in acompletion
    headers, response = await self.make_openai_chat_completion_request(
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    ...<4 lines>...
    )
    ^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/litellm_core_utils/logging_utils.py", line 300, in async_wrapper
    result: Final = await func(*args, **kwargs)
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/llms/openai/openai.py", line 447, in make_openai_chat_completion_request
    raise e
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/llms/openai/openai.py", line 423, in make_openai_chat_completion_request
    raw_response = await openai_aclient.chat.completions.with_raw_response.create(**data, timeout=timeout)
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/openai/_legacy_response.py", line 386, in wrapped
    return cast(LegacyAPIResponse[R], await func(*args, **kwargs))
                                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/openai/resources/chat/completions/completions.py", line 2907, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
    ...<55 lines>...
    )
    ^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/openai/_base_client.py", line 1992, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/openai/_base_client.py", line 1777, in request
    raise self._make_status_error_from_response(err.response) from None
openai.AuthenticationError: Error code: 401 - {'error': {'message': 'Incorrect API key provided: ArzIHXTm************************************************************************dHdW. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}}

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/main.py", line 647, in acompletion
    response = await _resolve_dispatched_chat_response(init_response)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/main.py", line 712, in _resolve_dispatched_chat_response
    return await pending
           ^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/llms/openai/openai.py", line 948, in acompletion
    raise OpenAIError(
    ...<4 lines>...
    )
litellm.llms.openai.common_utils.OpenAIError: Error code: 401 - {'error': {'message': 'Incorrect API key provided: ArzIHXTm************************************************************************dHdW. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}}

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/runner/work/graphrag/graphrag/packages/graphrag-llm/graphrag_llm/middleware/with_logging.py", line 64, in _request_count_middleware_async
    return await async_middleware(**kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/packages/graphrag-llm/graphrag_llm/middleware/with_request_count.py", line 72, in _request_count_middleware_async
    result = await async_middleware(**kwargs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/packages/graphrag-llm/graphrag_llm/middleware/with_metrics.py", line 80, in _metrics_middleware_async
    response = await async_middleware(**kwargs)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/packages/graphrag-llm/graphrag_llm/completion/lite_llm_completion.py", line 291, in _base_completion_async
    response = await litellm.acompletion(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^
        **new_args,
        ^^^^^^^^^^^
    )
    ^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/utils.py", line 2065, in wrapper_async
    raise e
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/utils.py", line 1861, in wrapper_async
    result = await original_function(*args, **kwargs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/main.py", line 700, in acompletion
    raise exception_type(
          ~~~~~~~~~~~~~~^
        model=model,
        ^^^^^^^^^^^^
    ...<3 lines>...
        extra_kwargs=kwargs,
        ^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/litellm_core_utils/exception_mapping_utils.py", line 2675, in exception_type
    raise e  # it's already mapped
    ^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/litellm_core_utils/exception_mapping_utils.py", line 2436, in exception_type
    _map_openai_exception(
    ~~~~~~~~~~~~~~~~~~~~~^
        model=model,
        ^^^^^^^^^^^^
    ...<5 lines>...
        extra_information=extra_information,
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/litellm_core_utils/exception_mapping_utils.py", line 409, in _map_openai_exception
    raise AuthenticationError(
    ...<5 lines>...
    )
litellm.exceptions.AuthenticationError: litellm.AuthenticationError: AuthenticationError: OpenAIException - Incorrect API key provided: ArzIHXTm************************************************************************dHdW. You can find your API key at https://platform.openai.com/account/api-keys.

Exception in _map_response_single_batch
Traceback (most recent call last):
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/llms/openai/openai.py", line 888, in acompletion
    headers, response = await self.make_openai_chat_completion_request(
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    ...<4 lines>...
    )
    ^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/litellm_core_utils/logging_utils.py", line 300, in async_wrapper
    result: Final = await func(*args, **kwargs)
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/llms/openai/openai.py", line 447, in make_openai_chat_completion_request
    raise e
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/llms/openai/openai.py", line 423, in make_openai_chat_completion_request
    raw_response = await openai_aclient.chat.completions.with_raw_response.create(**data, timeout=timeout)
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/openai/_legacy_response.py", line 386, in wrapped
    return cast(LegacyAPIResponse[R], await func(*args, **kwargs))
                                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/openai/resources/chat/completions/completions.py", line 2907, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
    ...<55 lines>...
    )
    ^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/openai/_base_client.py", line 1992, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/openai/_base_client.py", line 1777, in request
    raise self._make_status_error_from_response(err.response) from None
openai.AuthenticationError: Error code: 401 - {'error': {'message': 'Incorrect API key provided: ArzIHXTm************************************************************************dHdW. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}}

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/main.py", line 647, in acompletion
    response = await _resolve_dispatched_chat_response(init_response)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/main.py", line 712, in _resolve_dispatched_chat_response
    return await pending
           ^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/llms/openai/openai.py", line 948, in acompletion
    raise OpenAIError(
    ...<4 lines>...
    )
litellm.llms.openai.common_utils.OpenAIError: Error code: 401 - {'error': {'message': 'Incorrect API key provided: ArzIHXTm************************************************************************dHdW. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}}

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/runner/work/graphrag/graphrag/packages/graphrag/graphrag/query/structured_search/global_search/search.py", line 238, in _map_response_single_batch
    model_response = await self.model.completion_async(
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    ...<3 lines>...
    )
    ^
  File "/home/runner/work/graphrag/graphrag/packages/graphrag-llm/graphrag_llm/completion/lite_llm_completion.py", line 194, in completion_async
    response = await self._completion_async(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    ...<4 lines>...
    )
    ^
  File "/home/runner/work/graphrag/graphrag/packages/graphrag-llm/graphrag_llm/middleware/with_logging.py", line 64, in _request_count_middleware_async
    return await async_middleware(**kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/packages/graphrag-llm/graphrag_llm/middleware/with_request_count.py", line 72, in _request_count_middleware_async
    result = await async_middleware(**kwargs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/packages/graphrag-llm/graphrag_llm/middleware/with_metrics.py", line 80, in _metrics_middleware_async
    response = await async_middleware(**kwargs)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/packages/graphrag-llm/graphrag_llm/completion/lite_llm_completion.py", line 291, in _base_completion_async
    response = await litellm.acompletion(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^
        **new_args,
        ^^^^^^^^^^^
    )
    ^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/utils.py", line 2065, in wrapper_async
    raise e
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/utils.py", line 1861, in wrapper_async
    result = await original_function(*args, **kwargs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/main.py", line 700, in acompletion
    raise exception_type(
          ~~~~~~~~~~~~~~^
        model=model,
        ^^^^^^^^^^^^
    ...<3 lines>...
        extra_kwargs=kwargs,
        ^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/litellm_core_utils/exception_mapping_utils.py", line 2675, in exception_type
    raise e  # it's already mapped
    ^^^^^^^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/litellm_core_utils/exception_mapping_utils.py", line 2436, in exception_type
    _map_openai_exception(
    ~~~~~~~~~~~~~~~~~~~~~^
        model=model,
        ^^^^^^^^^^^^
    ...<5 lines>...
        extra_information=extra_information,
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.13/site-packages/litellm/litellm_core_utils/exception_mapping_utils.py", line 409, in _map_openai_exception
    raise AuthenticationError(
    ...<5 lines>...
    )
litellm.exceptions.AuthenticationError: litellm.AuthenticationError: AuthenticationError: OpenAIException - Incorrect API key provided: ArzIHXTm************************************************************************dHdW. You can find your API key at https://platform.openai.com/account/api-keys.

Warning: All map responses have score 0 (i.e., no relevant information found from the dataset), returning a canned 'I do not know' answer. You can try enabling `allow_general_knowledge` to encourage the LLM to incorporate relevant general knowledge, at the risk of increasing hallucinations.

I am sorry but I am unable to answer this question given the provided data.

In [10]:

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# inspect the data used to build the context for the LLM responses
result.context_data["reports"]
# inspect the data used to build the context for the LLM responses
result.context_data["reports"]

Out[10]:

	id	title	occurrence weight	content	rank
0	4	Dulce Base and Operation: Dulce Community	1.0	# Dulce Base and Operation: Dulce Community\n\...	9.0
1	0	Paranormal Military Squad and Operation: Dulce	1.0	# Paranormal Military Squad and Operation: Dul...	8.5
2	3	Paranormal Military Squad and Operation: Dulce	1.0	# Paranormal Military Squad and Operation: Dul...	8.5
3	8	Paranormal Military Squad: Leadership and Scie...	1.0	# Paranormal Military Squad: Leadership and Sc...	8.0
4	9	Paranormal Military Squad and Operation: Dulce...	0.2	# Paranormal Military Squad and Operation: Dul...	8.5
5	1	Team of Agents Investigating Dulce Base	0.2	# Team of Agents Investigating Dulce Base\n\nT...	7.5
6	6	Dulce Base Mainframe Room Technology Network	0.2	# Dulce Base Mainframe Room Technology Network...	7.5
7	7	Paranormal Military Squad and Operation Dulce	0.4	# Paranormal Military Squad and Operation Dulc...	8.5
8	5	Dulce Base Operational Command: Briefing Room ...	0.4	# Dulce Base Operational Command: Briefing Roo...	7.5
9	2	Alien Technology Retrieval and Analysis at Dul...	0.2	# Alien Technology Retrieval and Analysis at D...	9.0

In [11]:

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# inspect number of LLM calls and tokens
print(
    f"LLM calls: {result.llm_calls}. Prompt tokens: {result.prompt_tokens}. Output tokens: {result.output_tokens}."
)
# inspect number of LLM calls and tokens
print(
    f"LLM calls: {result.llm_calls}. Prompt tokens: {result.prompt_tokens}. Output tokens: {result.output_tokens}."
)

LLM calls: 2. Prompt tokens: 11395. Output tokens: 0.