diff --git a/.semversioner/next-release/patch-20250213164253709667.json b/.semversioner/next-release/patch-20250213164253709667.json
new file mode 100644
index 00000000..213f2a9c
--- /dev/null
+++ b/.semversioner/next-release/patch-20250213164253709667.json
@@ -0,0 +1,4 @@
+{
+  "type": "patch",
+  "description": "add dynamic retry logic."
+}
diff --git a/graphrag/api/prompt_tune.py b/graphrag/api/prompt_tune.py
index 19754cbb..b11546f4 100644
--- a/graphrag/api/prompt_tune.py
+++ b/graphrag/api/prompt_tune.py
@@ -13,6 +13,7 @@ Backwards compatibility is not guaranteed at this time.
 
 from pydantic import PositiveInt, validate_call
 
+import graphrag.config.defaults as defs
 from graphrag.callbacks.noop_workflow_callbacks import NoopWorkflowCallbacks
 from graphrag.config.models.graph_rag_config import GraphRagConfig
 from graphrag.index.llm.load_llm import load_llm
@@ -95,8 +96,14 @@ async def generate_indexing_prompts(
     )
 
     # Create LLM from config
-    # TODO: Expose way to specify Prompt Tuning model ID through config
+    # TODO: Expose a way to specify Prompt Tuning model ID through config
     default_llm_settings = config.get_language_model_config(PROMPT_TUNING_MODEL_ID)
+
+    # if max_retries is not set, inject a dynamically assigned value based on the number of expected LLM calls
+    # to be made or fallback to a default value in the worst case
+    if default_llm_settings.max_retries == -1:
+        default_llm_settings.max_retries = min(len(doc_list), defs.LLM_MAX_RETRIES)
+
     llm = load_llm(
         "prompt_tuning",
         default_llm_settings,
diff --git a/graphrag/config/defaults.py b/graphrag/config/defaults.py
index dc03d5e5..deb91cac 100644
--- a/graphrag/config/defaults.py
+++ b/graphrag/config/defaults.py
@@ -24,7 +24,7 @@ DEFAULT_CHAT_MODEL_ID = "default_chat_model"
 DEFAULT_EMBEDDING_MODEL_ID = "default_embedding_model"
 ASYNC_MODE = AsyncType.Threaded
 ENCODING_MODEL = "cl100k_base"
-AZURE_AUDIENCE = "https://cognitiveservices.azure.com/.default"
+COGNITIVE_SERVICES_AUDIENCE = "https://cognitiveservices.azure.com/.default"
 AUTH_TYPE = AuthType.APIKey
 #
 # LLM Parameters
@@ -39,15 +39,12 @@ LLM_N = 1
 LLM_REQUEST_TIMEOUT = 180.0
 LLM_TOKENS_PER_MINUTE = 50_000
 LLM_REQUESTS_PER_MINUTE = 1_000
+RETRY_STRATEGY = "native"
 LLM_MAX_RETRIES = 10
 LLM_MAX_RETRY_WAIT = 10.0
 LLM_PRESENCE_PENALTY = 0.0
-LLM_SLEEP_ON_RATE_LIMIT_RECOMMENDATION = True
 LLM_CONCURRENT_REQUESTS = 25
 
-PARALLELIZATION_STAGGER = 0.3
-PARALLELIZATION_NUM_THREADS = 50
-
 #
 # Text embedding
 #
diff --git a/graphrag/config/init_content.py b/graphrag/config/init_content.py
index 5aff9192..f11eb609 100644
--- a/graphrag/config/init_content.py
+++ b/graphrag/config/init_content.py
@@ -14,32 +14,41 @@ INIT_YAML = f"""\
 
 models:
   {defs.DEFAULT_CHAT_MODEL_ID}:
-    api_key: ${{GRAPHRAG_API_KEY}} # set this in the generated .env file
     type: {defs.LLM_TYPE.value} # or azure_openai_chat
+    # api_base: https://<instance>.openai.azure.com
+    # api_version: 2024-05-01-preview
     auth_type: {defs.AUTH_TYPE.value} # or azure_managed_identity
+    api_key: ${{GRAPHRAG_API_KEY}} # set this in the generated .env file
+    # audience: "https://cognitiveservices.azure.com/.default"
+    # organization: <organization_id>
     model: {defs.LLM_MODEL}
+    # deployment_name: <azure_model_deployment_name>
+    # encoding_model: {defs.ENCODING_MODEL} # automatically set by tiktoken if left undefined
     model_supports_json: true # recommended if this is available for your model.
-    parallelization_num_threads: {defs.PARALLELIZATION_NUM_THREADS}
-    parallelization_stagger: {defs.PARALLELIZATION_STAGGER}
+    concurrent_requests: {defs.LLM_CONCURRENT_REQUESTS} # max number of simultaneous LLM requests allowed
     async_mode: {defs.ASYNC_MODE.value} # or asyncio
-    # audience: "https://cognitiveservices.azure.com/.default"
-    # api_base: https://<instance>.openai.azure.com
-    # api_version: 2024-02-15-preview
-    # organization: <organization_id>
-    # deployment_name: <azure_model_deployment_name>
+    retry_strategy: native
+    max_retries: -1                   # set to -1 for dynamic retry logic (most optimal setting based on server response)
+    tokens_per_minute: 0              # set to 0 to disable rate limiting
+    requests_per_minute: 0            # set to 0 to disable rate limiting
   {defs.DEFAULT_EMBEDDING_MODEL_ID}:
-    api_key: ${{GRAPHRAG_API_KEY}}
     type: {defs.EMBEDDING_TYPE.value} # or azure_openai_embedding
-    auth_type: {defs.AUTH_TYPE.value} # or azure_managed_identity
-    model: {defs.EMBEDDING_MODEL}
-    parallelization_num_threads: {defs.PARALLELIZATION_NUM_THREADS}
-    parallelization_stagger: {defs.PARALLELIZATION_STAGGER}
-    async_mode: {defs.ASYNC_MODE.value} # or asyncio
     # api_base: https://<instance>.openai.azure.com
-    # api_version: 2024-02-15-preview
+    # api_version: 2024-05-01-preview
+    auth_type: {defs.AUTH_TYPE.value} # or azure_managed_identity
+    api_key: ${{GRAPHRAG_API_KEY}}
     # audience: "https://cognitiveservices.azure.com/.default"
     # organization: <organization_id>
+    model: {defs.EMBEDDING_MODEL}
     # deployment_name: <azure_model_deployment_name>
+    # encoding_model: {defs.ENCODING_MODEL} # automatically set by tiktoken if left undefined
+    model_supports_json: true # recommended if this is available for your model.
+    concurrent_requests: {defs.LLM_CONCURRENT_REQUESTS} # max number of simultaneous LLM requests allowed
+    async_mode: {defs.ASYNC_MODE.value} # or asyncio
+    retry_strategy: native
+    max_retries: -1                   # set to -1 for dynamic retry logic (most optimal setting based on server response)
+    tokens_per_minute: 0              # set to 0 to disable rate limiting
+    requests_per_minute: 0            # set to 0 to disable rate limiting
 
 vector_store:
   {defs.VECTOR_STORE_DEFAULT_ID}:
diff --git a/graphrag/config/models/community_reports_config.py b/graphrag/config/models/community_reports_config.py
index e9aaf28a..62384e44 100644
--- a/graphrag/config/models/community_reports_config.py
+++ b/graphrag/config/models/community_reports_config.py
@@ -49,8 +49,7 @@ class CommunityReportsConfig(BaseModel):
         return self.strategy or {
             "type": CreateCommunityReportsStrategyType.graph_intelligence,
             "llm": model_config.model_dump(),
-            "stagger": model_config.parallelization_stagger,
-            "num_threads": model_config.parallelization_num_threads,
+            "num_threads": model_config.concurrent_requests,
             "graph_prompt": (Path(root_dir) / self.graph_prompt).read_text(
                 encoding="utf-8"
             )
diff --git a/graphrag/config/models/extract_claims_config.py b/graphrag/config/models/extract_claims_config.py
index e719c53b..a61f6e78 100644
--- a/graphrag/config/models/extract_claims_config.py
+++ b/graphrag/config/models/extract_claims_config.py
@@ -46,8 +46,7 @@ class ClaimExtractionConfig(BaseModel):
         """Get the resolved claim extraction strategy."""
         return self.strategy or {
             "llm": model_config.model_dump(),
-            "stagger": model_config.parallelization_stagger,
-            "num_threads": model_config.parallelization_num_threads,
+            "num_threads": model_config.concurrent_requests,
             "extraction_prompt": (Path(root_dir) / self.prompt).read_text(
                 encoding="utf-8"
             )
diff --git a/graphrag/config/models/extract_graph_config.py b/graphrag/config/models/extract_graph_config.py
index f5491865..b40a33e2 100644
--- a/graphrag/config/models/extract_graph_config.py
+++ b/graphrag/config/models/extract_graph_config.py
@@ -47,8 +47,7 @@ class ExtractGraphConfig(BaseModel):
         return self.strategy or {
             "type": ExtractEntityStrategyType.graph_intelligence,
             "llm": model_config.model_dump(),
-            "stagger": model_config.parallelization_stagger,
-            "num_threads": model_config.parallelization_num_threads,
+            "num_threads": model_config.concurrent_requests,
             "extraction_prompt": (Path(root_dir) / self.prompt).read_text(
                 encoding="utf-8"
             )
diff --git a/graphrag/config/models/extract_graph_nlp_config.py b/graphrag/config/models/extract_graph_nlp_config.py
index 90f7b5fc..fd56db83 100644
--- a/graphrag/config/models/extract_graph_nlp_config.py
+++ b/graphrag/config/models/extract_graph_nlp_config.py
@@ -64,7 +64,7 @@ class ExtractGraphNLPConfig(BaseModel):
     text_analyzer: TextAnalyzerConfig = Field(
         description="The text analyzer configuration.", default=TextAnalyzerConfig()
     )
-    parallelization_num_threads: int = Field(
+    concurrent_requests: int = Field(
         description="The number of threads to use for the extraction process.",
-        default=defs.PARALLELIZATION_NUM_THREADS,
+        default=defs.LLM_CONCURRENT_REQUESTS,
     )
diff --git a/graphrag/config/models/language_model_config.py b/graphrag/config/models/language_model_config.py
index f403d4fb..8bb6fad2 100644
--- a/graphrag/config/models/language_model_config.py
+++ b/graphrag/config/models/language_model_config.py
@@ -31,7 +31,7 @@ class LanguageModelConfig(BaseModel):
         API Key is required when using OpenAI API
         or when using Azure API with API Key authentication.
         For the time being, this check is extra verbose for clarity.
-        It will also through an exception if an API Key is provided
+        It will also raise an exception if an API Key is provided
         when one is not expected such as the case of using Azure
         Managed Identity.
 
@@ -199,6 +199,10 @@ class LanguageModelConfig(BaseModel):
         description="The number of requests per minute to use for the LLM service.",
         default=defs.LLM_REQUESTS_PER_MINUTE,
     )
+    retry_strategy: str = Field(
+        description="The retry strategy to use for the LLM service.",
+        default=defs.RETRY_STRATEGY,
+    )
     max_retries: int = Field(
         description="The maximum number of retries to use for the LLM service.",
         default=defs.LLM_MAX_RETRIES,
@@ -207,10 +211,6 @@ class LanguageModelConfig(BaseModel):
         description="The maximum retry wait to use for the LLM service.",
         default=defs.LLM_MAX_RETRY_WAIT,
     )
-    sleep_on_rate_limit_recommendation: bool = Field(
-        description="Whether to sleep on rate limit recommendations.",
-        default=defs.LLM_SLEEP_ON_RATE_LIMIT_RECOMMENDATION,
-    )
     concurrent_requests: int = Field(
         description="Whether to use concurrent requests for the LLM service.",
         default=defs.LLM_CONCURRENT_REQUESTS,
@@ -218,14 +218,6 @@ class LanguageModelConfig(BaseModel):
     responses: list[str | BaseModel] | None = Field(
         default=None, description="Static responses to use in mock mode."
     )
-    parallelization_stagger: float = Field(
-        description="The stagger to use for the LLM service.",
-        default=defs.PARALLELIZATION_STAGGER,
-    )
-    parallelization_num_threads: int = Field(
-        description="The number of threads to use for the LLM service.",
-        default=defs.PARALLELIZATION_NUM_THREADS,
-    )
     async_mode: AsyncType = Field(
         description="The async mode to use.", default=defs.ASYNC_MODE
     )
diff --git a/graphrag/config/models/summarize_descriptions_config.py b/graphrag/config/models/summarize_descriptions_config.py
index 67ed7ed8..25138061 100644
--- a/graphrag/config/models/summarize_descriptions_config.py
+++ b/graphrag/config/models/summarize_descriptions_config.py
@@ -40,8 +40,7 @@ class SummarizeDescriptionsConfig(BaseModel):
         return self.strategy or {
             "type": SummarizeStrategyType.graph_intelligence,
             "llm": model_config.model_dump(),
-            "stagger": model_config.parallelization_stagger,
-            "num_threads": model_config.parallelization_num_threads,
+            "num_threads": model_config.concurrent_requests,
             "summarize_prompt": (Path(root_dir) / self.prompt).read_text(
                 encoding="utf-8"
             )
diff --git a/graphrag/config/models/text_embedding_config.py b/graphrag/config/models/text_embedding_config.py
index 9a8763fd..d6508b65 100644
--- a/graphrag/config/models/text_embedding_config.py
+++ b/graphrag/config/models/text_embedding_config.py
@@ -48,8 +48,7 @@ class TextEmbeddingConfig(BaseModel):
         return self.strategy or {
             "type": TextEmbedStrategyType.openai,
             "llm": model_config.model_dump(),
-            "stagger": model_config.parallelization_stagger,
-            "num_threads": model_config.parallelization_num_threads,
+            "num_threads": model_config.concurrent_requests,
             "batch_size": self.batch_size,
             "batch_max_tokens": self.batch_max_tokens,
         }
diff --git a/graphrag/index/flows/extract_graph_nlp.py b/graphrag/index/flows/extract_graph_nlp.py
index ed0161a4..741dfe42 100644
--- a/graphrag/index/flows/extract_graph_nlp.py
+++ b/graphrag/index/flows/extract_graph_nlp.py
@@ -37,7 +37,7 @@ async def extract_graph_nlp(
         text_units,
         text_analyzer=text_analyzer,
         normalize_edge_weights=extraction_config.normalize_edge_weights,
-        num_threads=extraction_config.parallelization_num_threads,
+        num_threads=extraction_config.concurrent_requests,
         cache=cache,
     )
 
diff --git a/graphrag/index/llm/load_llm.py b/graphrag/index/llm/load_llm.py
index 7965e7a0..19fcf305 100644
--- a/graphrag/index/llm/load_llm.py
+++ b/graphrag/index/llm/load_llm.py
@@ -8,8 +8,9 @@ from __future__ import annotations
 import logging
 from typing import TYPE_CHECKING, Any
 
-from fnllm import ChatLLM, EmbeddingsLLM, JsonStrategy, LLMEvents
+from fnllm.base.config import JsonStrategy, RetryStrategy
 from fnllm.caching import Cache as LLMCache
+from fnllm.events import LLMEvents
 from fnllm.openai import (
     AzureOpenAIConfig,
     OpenAIConfig,
@@ -30,6 +31,8 @@ from graphrag.index.llm.manager import ChatLLMSingleton, EmbeddingsLLMSingleton
 from .mock_llm import MockChatLLM
 
 if TYPE_CHECKING:
+    from fnllm.types import ChatLLM, EmbeddingsLLM
+
     from graphrag.cache.pipeline_cache import PipelineCache
     from graphrag.callbacks.workflow_callbacks import WorkflowCallbacks
     from graphrag.index.typing import ErrorHandlerFn
@@ -209,7 +212,7 @@ def _create_openai_config(config: LanguageModelConfig, azure: bool) -> OpenAICon
             msg = "Azure OpenAI Chat LLM requires an API base"
             raise ValueError(msg)
 
-        audience = config.audience or defs.AZURE_AUDIENCE
+        audience = config.audience or defs.COGNITIVE_SERVICES_AUDIENCE
         return AzureOpenAIConfig(
             api_key=config.api_key,
             endpoint=config.api_base,
@@ -220,19 +223,22 @@ def _create_openai_config(config: LanguageModelConfig, azure: bool) -> OpenAICon
             max_retry_wait=config.max_retry_wait,
             requests_per_minute=config.requests_per_minute,
             tokens_per_minute=config.tokens_per_minute,
-            cognitive_services_endpoint=audience,
+            audience=audience,
+            retry_strategy=RetryStrategy(config.retry_strategy),
             timeout=config.request_timeout,
             max_concurrency=config.concurrent_requests,
             model=config.model,
             encoding=encoding_model,
             deployment=config.deployment_name,
             chat_parameters=chat_parameters,
+            sleep_on_rate_limit_recommendation=True,
         )
     return PublicOpenAIConfig(
         api_key=config.api_key,
         base_url=config.api_base,
         json_strategy=json_strategy,
         organization=config.organization,
+        retry_strategy=RetryStrategy(config.retry_strategy),
         max_retries=config.max_retries,
         max_retry_wait=config.max_retry_wait,
         requests_per_minute=config.requests_per_minute,
@@ -242,6 +248,7 @@ def _create_openai_config(config: LanguageModelConfig, azure: bool) -> OpenAICon
         model=config.model,
         encoding=encoding_model,
         chat_parameters=chat_parameters,
+        sleep_on_rate_limit_recommendation=True,
     )
 
 
diff --git a/graphrag/index/llm/manager.py b/graphrag/index/llm/manager.py
index 2e35cd89..51940e2e 100644
--- a/graphrag/index/llm/manager.py
+++ b/graphrag/index/llm/manager.py
@@ -5,7 +5,7 @@
 
 from functools import cache
 
-from fnllm import ChatLLM, EmbeddingsLLM
+from fnllm.types import ChatLLM, EmbeddingsLLM
 
 
 @cache
diff --git a/graphrag/index/llm/mock_llm.py b/graphrag/index/llm/mock_llm.py
index 296c833b..866a358b 100644
--- a/graphrag/index/llm/mock_llm.py
+++ b/graphrag/index/llm/mock_llm.py
@@ -5,8 +5,9 @@
 from dataclasses import dataclass
 from typing import Any, cast
 
-from fnllm import ChatLLM, LLMInput, LLMOutput
+from fnllm.types import ChatLLM
 from fnllm.types.generics import THistoryEntry, TJsonModel, TModelParameters
+from fnllm.types.io import LLMInput, LLMOutput
 from pydantic import BaseModel
 from typing_extensions import Unpack
 
diff --git a/graphrag/index/operations/embed_text/embed_text.py b/graphrag/index/operations/embed_text/embed_text.py
index c735d102..0b294b35 100644
--- a/graphrag/index/operations/embed_text/embed_text.py
+++ b/graphrag/index/operations/embed_text/embed_text.py
@@ -116,10 +116,10 @@ async def _text_embed_in_memory(
 ):
     strategy_type = strategy["type"]
     strategy_exec = load_strategy(strategy_type)
-    strategy_args = {**strategy}
+    strategy_config = {**strategy}
 
     texts: list[str] = input[embed_column].to_numpy().tolist()
-    result = await strategy_exec(texts, callbacks, cache, strategy_args)
+    result = await strategy_exec(texts, callbacks, cache, strategy_config)
 
     return result.embeddings
 
@@ -137,7 +137,11 @@ async def _text_embed_with_vector_store(
 ):
     strategy_type = strategy["type"]
     strategy_exec = load_strategy(strategy_type)
-    strategy_args = {**strategy}
+    strategy_config = {**strategy}
+
+    # if max_retries is not set, inject a dynamically assigned value based on the total number of expected LLM calls to be made
+    if strategy_config.get("llm") and strategy_config["llm"]["max_retries"] == -1:
+        strategy_config["llm"]["max_retries"] = len(input)
 
     # Get vector-storage configuration
     insert_batch_size: int = (
@@ -176,7 +180,7 @@ async def _text_embed_with_vector_store(
         texts: list[str] = batch[embed_column].to_numpy().tolist()
         titles: list[str] = batch[title].to_numpy().tolist()
         ids: list[str] = batch[id_column].to_numpy().tolist()
-        result = await strategy_exec(texts, callbacks, cache, strategy_args)
+        result = await strategy_exec(texts, callbacks, cache, strategy_config)
         if result.embeddings:
             embeddings = [
                 embedding for embedding in result.embeddings if embedding is not None
diff --git a/graphrag/index/operations/embed_text/strategies/openai.py b/graphrag/index/operations/embed_text/strategies/openai.py
index ab10b285..eceed765 100644
--- a/graphrag/index/operations/embed_text/strategies/openai.py
+++ b/graphrag/index/operations/embed_text/strategies/openai.py
@@ -8,7 +8,7 @@ import logging
 from typing import Any
 
 import numpy as np
-from fnllm import EmbeddingsLLM
+from fnllm.types import EmbeddingsLLM
 
 from graphrag.cache.pipeline_cache import PipelineCache
 from graphrag.callbacks.workflow_callbacks import WorkflowCallbacks
diff --git a/graphrag/index/operations/extract_covariates/claim_extractor.py b/graphrag/index/operations/extract_covariates/claim_extractor.py
index 18cb83eb..35bbd428 100644
--- a/graphrag/index/operations/extract_covariates/claim_extractor.py
+++ b/graphrag/index/operations/extract_covariates/claim_extractor.py
@@ -9,7 +9,7 @@ from dataclasses import dataclass
 from typing import Any
 
 import tiktoken
-from fnllm import ChatLLM
+from fnllm.types import ChatLLM
 
 import graphrag.config.defaults as defs
 from graphrag.index.typing import ErrorHandlerFn
diff --git a/graphrag/index/operations/extract_covariates/extract_covariates.py b/graphrag/index/operations/extract_covariates/extract_covariates.py
index 6cbebd2b..10c54c8a 100644
--- a/graphrag/index/operations/extract_covariates/extract_covariates.py
+++ b/graphrag/index/operations/extract_covariates/extract_covariates.py
@@ -50,6 +50,10 @@ async def extract_covariates(
     strategy = strategy or {}
     strategy_config = {**strategy}
 
+    # if max_retries is not set, inject a dynamically assigned value based on the total number of expected LLM calls to be made
+    if strategy_config.get("llm") and strategy_config["llm"]["max_retries"] == -1:
+        strategy_config["llm"]["max_retries"] = len(input)
+
     async def run_strategy(row):
         text = row[column]
         result = await run_extract_claims(
diff --git a/graphrag/index/operations/extract_graph/extract_graph.py b/graphrag/index/operations/extract_graph/extract_graph.py
index cbc11f18..dc4a7842 100644
--- a/graphrag/index/operations/extract_graph/extract_graph.py
+++ b/graphrag/index/operations/extract_graph/extract_graph.py
@@ -94,6 +94,10 @@ async def extract_graph(
     )
     strategy_config = {**strategy}
 
+    # if max_retries is not set, inject a dynamically assigned value based on the total number of expected LLM calls to be made
+    if strategy_config.get("llm") and strategy_config["llm"]["max_retries"] == -1:
+        strategy_config["llm"]["max_retries"] = len(text_units)
+
     num_started = 0
 
     async def run_strategy(row):
diff --git a/graphrag/index/operations/extract_graph/graph_extractor.py b/graphrag/index/operations/extract_graph/graph_extractor.py
index 1597316f..bf5a2776 100644
--- a/graphrag/index/operations/extract_graph/graph_extractor.py
+++ b/graphrag/index/operations/extract_graph/graph_extractor.py
@@ -12,7 +12,7 @@ from typing import Any
 
 import networkx as nx
 import tiktoken
-from fnllm import ChatLLM
+from fnllm.types import ChatLLM
 
 import graphrag.config.defaults as defs
 from graphrag.index.typing import ErrorHandlerFn
diff --git a/graphrag/index/operations/extract_graph/graph_intelligence_strategy.py b/graphrag/index/operations/extract_graph/graph_intelligence_strategy.py
index baf68b44..608cc271 100644
--- a/graphrag/index/operations/extract_graph/graph_intelligence_strategy.py
+++ b/graphrag/index/operations/extract_graph/graph_intelligence_strategy.py
@@ -4,7 +4,7 @@
 """A module containing run_graph_intelligence,  run_extract_graph and _create_text_splitter methods to run graph intelligence."""
 
 import networkx as nx
-from fnllm import ChatLLM
+from fnllm.types import ChatLLM
 
 import graphrag.config.defaults as defs
 from graphrag.cache.pipeline_cache import PipelineCache
diff --git a/graphrag/index/operations/summarize_communities/community_reports_extractor.py b/graphrag/index/operations/summarize_communities/community_reports_extractor.py
index ae550b52..0d70b18e 100644
--- a/graphrag/index/operations/summarize_communities/community_reports_extractor.py
+++ b/graphrag/index/operations/summarize_communities/community_reports_extractor.py
@@ -8,7 +8,7 @@ import traceback
 from dataclasses import dataclass
 from typing import Any
 
-from fnllm import ChatLLM
+from fnllm.types import ChatLLM
 from pydantic import BaseModel, Field
 
 from graphrag.index.typing import ErrorHandlerFn
diff --git a/graphrag/index/operations/summarize_communities/strategies.py b/graphrag/index/operations/summarize_communities/strategies.py
index 48793066..4a4e7ba5 100644
--- a/graphrag/index/operations/summarize_communities/strategies.py
+++ b/graphrag/index/operations/summarize_communities/strategies.py
@@ -6,7 +6,7 @@
 import logging
 import traceback
 
-from fnllm import ChatLLM
+from fnllm.types import ChatLLM
 
 from graphrag.cache.pipeline_cache import PipelineCache
 from graphrag.callbacks.workflow_callbacks import WorkflowCallbacks
diff --git a/graphrag/index/operations/summarize_communities/summarize_communities.py b/graphrag/index/operations/summarize_communities/summarize_communities.py
index 016d2a00..17ffa904 100644
--- a/graphrag/index/operations/summarize_communities/summarize_communities.py
+++ b/graphrag/index/operations/summarize_communities/summarize_communities.py
@@ -42,7 +42,12 @@ async def summarize_communities(
     """Generate community summaries."""
     reports: list[CommunityReport | None] = []
     tick = progress_ticker(callbacks.progress, len(local_contexts))
-    runner = load_strategy(strategy["type"])
+    strategy_exec = load_strategy(strategy["type"])
+    strategy_config = {**strategy}
+
+    # if max_retries is not set, inject a dynamically assigned value based on the total number of expected LLM calls to be made
+    if strategy_config.get("llm") and strategy_config["llm"]["max_retries"] == -1:
+        strategy_config["llm"]["max_retries"] = len(nodes)
 
     community_hierarchy = restore_community_hierarchy(nodes)
     levels = get_levels(nodes)
@@ -62,13 +67,13 @@ async def summarize_communities(
 
         async def run_generate(record):
             result = await _generate_report(
-                runner,
+                strategy_exec,
                 community_id=record[schemas.COMMUNITY_ID],
                 community_level=record[schemas.COMMUNITY_LEVEL],
                 community_context=record[schemas.CONTEXT_STRING],
                 callbacks=callbacks,
                 cache=cache,
-                strategy=strategy,
+                strategy=strategy_config,
             )
             tick()
             return result
diff --git a/graphrag/index/operations/summarize_descriptions/description_summary_extractor.py b/graphrag/index/operations/summarize_descriptions/description_summary_extractor.py
index ee59c649..74071f3e 100644
--- a/graphrag/index/operations/summarize_descriptions/description_summary_extractor.py
+++ b/graphrag/index/operations/summarize_descriptions/description_summary_extractor.py
@@ -6,7 +6,7 @@
 import json
 from dataclasses import dataclass
 
-from fnllm import ChatLLM
+from fnllm.types import ChatLLM
 
 from graphrag.index.typing import ErrorHandlerFn
 from graphrag.index.utils.tokens import num_tokens_from_string
diff --git a/graphrag/index/operations/summarize_descriptions/graph_intelligence_strategy.py b/graphrag/index/operations/summarize_descriptions/graph_intelligence_strategy.py
index aa4efd7d..e7323712 100644
--- a/graphrag/index/operations/summarize_descriptions/graph_intelligence_strategy.py
+++ b/graphrag/index/operations/summarize_descriptions/graph_intelligence_strategy.py
@@ -3,7 +3,7 @@
 
 """A module containing run_graph_intelligence,  run_resolve_entities and _create_text_list_splitter methods to run graph intelligence."""
 
-from fnllm import ChatLLM
+from fnllm.types import ChatLLM
 
 from graphrag.cache.pipeline_cache import PipelineCache
 from graphrag.callbacks.workflow_callbacks import WorkflowCallbacks
diff --git a/graphrag/index/operations/summarize_descriptions/summarize_descriptions.py b/graphrag/index/operations/summarize_descriptions/summarize_descriptions.py
index ca1baa61..31dcf96d 100644
--- a/graphrag/index/operations/summarize_descriptions/summarize_descriptions.py
+++ b/graphrag/index/operations/summarize_descriptions/summarize_descriptions.py
@@ -76,6 +76,10 @@ async def summarize_descriptions(
     )
     strategy_config = {**strategy}
 
+    # if max_retries is not set, inject a dynamically assigned value based on the maximum number of expected LLM calls to be made
+    if strategy_config.get("llm") and strategy_config["llm"]["max_retries"] == -1:
+        strategy_config["llm"]["max_retries"] = len(entities_df) + len(relationships_df)
+
     async def get_summarized(
         nodes: pd.DataFrame, edges: pd.DataFrame, semaphore: asyncio.Semaphore
     ):
diff --git a/graphrag/index/validate_config.py b/graphrag/index/validate_config.py
index a024a586..a833317c 100644
--- a/graphrag/index/validate_config.py
+++ b/graphrag/index/validate_config.py
@@ -6,6 +6,7 @@
 import asyncio
 import sys
 
+import graphrag.config.defaults as defs
 from graphrag.callbacks.noop_workflow_callbacks import NoopWorkflowCallbacks
 from graphrag.config.models.graph_rag_config import GraphRagConfig
 from graphrag.index.llm.load_llm import load_llm, load_llm_embeddings
@@ -17,6 +18,9 @@ def validate_config_names(logger: ProgressLogger, parameters: GraphRagConfig) ->
     # Validate Chat LLM configs
     # TODO: Replace default_chat_model with a way to select the model
     default_llm_settings = parameters.get_language_model_config("default_chat_model")
+    # if max_retries is not set, set it to the default value
+    if default_llm_settings.max_retries == -1:
+        default_llm_settings.max_retries = defs.LLM_MAX_RETRIES
     llm = load_llm(
         name="test-llm",
         config=default_llm_settings,
diff --git a/graphrag/index/workflows/create_community_reports.py b/graphrag/index/workflows/create_community_reports.py
index 3bdd09ea..9f6ff72e 100644
--- a/graphrag/index/workflows/create_community_reports.py
+++ b/graphrag/index/workflows/create_community_reports.py
@@ -39,7 +39,7 @@ async def run_workflow(
         config.community_reports.model_id
     )
     async_mode = community_reports_llm_settings.async_mode
-    num_threads = community_reports_llm_settings.parallelization_num_threads
+    num_threads = community_reports_llm_settings.concurrent_requests
     summarization_strategy = config.community_reports.resolved_strategy(
         config.root_dir, community_reports_llm_settings
     )
diff --git a/graphrag/index/workflows/create_community_reports_text.py b/graphrag/index/workflows/create_community_reports_text.py
index 7e1effbb..79cdbc93 100644
--- a/graphrag/index/workflows/create_community_reports_text.py
+++ b/graphrag/index/workflows/create_community_reports_text.py
@@ -31,7 +31,7 @@ async def run_workflow(
         config.community_reports.model_id
     )
     async_mode = community_reports_llm_settings.async_mode
-    num_threads = community_reports_llm_settings.parallelization_num_threads
+    num_threads = community_reports_llm_settings.concurrent_requests
     summarization_strategy = config.community_reports.resolved_strategy(
         config.root_dir, community_reports_llm_settings
     )
diff --git a/graphrag/index/workflows/extract_covariates.py b/graphrag/index/workflows/extract_covariates.py
index 43f9bda0..7df4ce19 100644
--- a/graphrag/index/workflows/extract_covariates.py
+++ b/graphrag/index/workflows/extract_covariates.py
@@ -32,7 +32,7 @@ async def run_workflow(
     )
 
     async_mode = extract_claims_llm_settings.async_mode
-    num_threads = extract_claims_llm_settings.parallelization_num_threads
+    num_threads = extract_claims_llm_settings.concurrent_requests
 
     output = await extract_covariates(
         text_units,
diff --git a/graphrag/index/workflows/extract_graph.py b/graphrag/index/workflows/extract_graph.py
index eb64e757..cac1f2ce 100644
--- a/graphrag/index/workflows/extract_graph.py
+++ b/graphrag/index/workflows/extract_graph.py
@@ -32,9 +32,6 @@ async def run_workflow(
     extraction_strategy = config.extract_graph.resolved_strategy(
         config.root_dir, extract_graph_llm_settings
     )
-    extraction_num_threads = extract_graph_llm_settings.parallelization_num_threads
-    extraction_async_mode = extract_graph_llm_settings.async_mode
-    entity_types = config.extract_graph.entity_types
 
     summarization_llm_settings = config.get_language_model_config(
         config.summarize_descriptions.model_id
@@ -42,18 +39,17 @@ async def run_workflow(
     summarization_strategy = config.summarize_descriptions.resolved_strategy(
         config.root_dir, summarization_llm_settings
     )
-    summarization_num_threads = summarization_llm_settings.parallelization_num_threads
 
     entities, relationships = await extract_graph(
         text_units=text_units,
         callbacks=callbacks,
         cache=context.cache,
         extraction_strategy=extraction_strategy,
-        extraction_num_threads=extraction_num_threads,
-        extraction_async_mode=extraction_async_mode,
-        entity_types=entity_types,
+        extraction_num_threads=extract_graph_llm_settings.concurrent_requests,
+        extraction_async_mode=extract_graph_llm_settings.async_mode,
+        entity_types=config.extract_graph.entity_types,
         summarization_strategy=summarization_strategy,
-        summarization_num_threads=summarization_num_threads,
+        summarization_num_threads=summarization_llm_settings.concurrent_requests,
         embed_config=config.embed_graph,
         layout_enabled=config.umap.enabled,
     )
diff --git a/graphrag/prompt_tune/generator/community_report_rating.py b/graphrag/prompt_tune/generator/community_report_rating.py
index 4c8c18f9..9954a339 100644
--- a/graphrag/prompt_tune/generator/community_report_rating.py
+++ b/graphrag/prompt_tune/generator/community_report_rating.py
@@ -3,7 +3,7 @@
 # Copyright (c) 2024 Microsoft Corporation.
 # Licensed under the MIT License
 
-from fnllm import ChatLLM
+from fnllm.types import ChatLLM
 
 from graphrag.prompt_tune.prompt.community_report_rating import (
     GENERATE_REPORT_RATING_PROMPT,
diff --git a/graphrag/prompt_tune/generator/community_reporter_role.py b/graphrag/prompt_tune/generator/community_reporter_role.py
index d2e85f81..cd512903 100644
--- a/graphrag/prompt_tune/generator/community_reporter_role.py
+++ b/graphrag/prompt_tune/generator/community_reporter_role.py
@@ -3,7 +3,7 @@
 
 """Generate a community reporter role for community summarization."""
 
-from fnllm import ChatLLM
+from fnllm.types import ChatLLM
 
 from graphrag.prompt_tune.prompt.community_reporter_role import (
     GENERATE_COMMUNITY_REPORTER_ROLE_PROMPT,
diff --git a/graphrag/prompt_tune/generator/domain.py b/graphrag/prompt_tune/generator/domain.py
index 2e129c0c..186a676c 100644
--- a/graphrag/prompt_tune/generator/domain.py
+++ b/graphrag/prompt_tune/generator/domain.py
@@ -3,7 +3,7 @@
 
 """Domain generation for GraphRAG prompts."""
 
-from fnllm import ChatLLM
+from fnllm.types import ChatLLM
 
 from graphrag.prompt_tune.prompt.domain import GENERATE_DOMAIN_PROMPT
 
diff --git a/graphrag/prompt_tune/generator/entity_relationship.py b/graphrag/prompt_tune/generator/entity_relationship.py
index 38873bd5..3194c5c6 100644
--- a/graphrag/prompt_tune/generator/entity_relationship.py
+++ b/graphrag/prompt_tune/generator/entity_relationship.py
@@ -6,7 +6,7 @@
 import asyncio
 import json
 
-from fnllm import ChatLLM
+from fnllm.types import ChatLLM
 
 from graphrag.prompt_tune.prompt.entity_relationship import (
     ENTITY_RELATIONSHIPS_GENERATION_JSON_PROMPT,
diff --git a/graphrag/prompt_tune/generator/entity_types.py b/graphrag/prompt_tune/generator/entity_types.py
index b64f1a68..4bb5b329 100644
--- a/graphrag/prompt_tune/generator/entity_types.py
+++ b/graphrag/prompt_tune/generator/entity_types.py
@@ -3,7 +3,7 @@
 
 """Entity type generation module for fine-tuning."""
 
-from fnllm import ChatLLM
+from fnllm.types import ChatLLM
 from pydantic import BaseModel
 
 from graphrag.prompt_tune.defaults import DEFAULT_TASK
diff --git a/graphrag/prompt_tune/generator/language.py b/graphrag/prompt_tune/generator/language.py
index 7327e125..c876a341 100644
--- a/graphrag/prompt_tune/generator/language.py
+++ b/graphrag/prompt_tune/generator/language.py
@@ -3,7 +3,7 @@
 
 """Language detection for GraphRAG prompts."""
 
-from fnllm import ChatLLM
+from fnllm.types import ChatLLM
 
 from graphrag.prompt_tune.prompt.language import DETECT_LANGUAGE_PROMPT
 
diff --git a/graphrag/prompt_tune/generator/persona.py b/graphrag/prompt_tune/generator/persona.py
index d5fc5e59..be6b752c 100644
--- a/graphrag/prompt_tune/generator/persona.py
+++ b/graphrag/prompt_tune/generator/persona.py
@@ -3,7 +3,7 @@
 
 """Persona generating module for fine-tuning GraphRAG prompts."""
 
-from fnllm import ChatLLM
+from fnllm.types import ChatLLM
 
 from graphrag.prompt_tune.defaults import DEFAULT_TASK
 from graphrag.prompt_tune.prompt.persona import GENERATE_PERSONA_PROMPT
diff --git a/graphrag/prompt_tune/loader/input.py b/graphrag/prompt_tune/loader/input.py
index 7f7831de..671a867a 100644
--- a/graphrag/prompt_tune/loader/input.py
+++ b/graphrag/prompt_tune/loader/input.py
@@ -5,7 +5,7 @@
 
 import numpy as np
 import pandas as pd
-from fnllm import ChatLLM
+from fnllm.types import ChatLLM
 
 import graphrag.config.defaults as defs
 from graphrag.callbacks.noop_workflow_callbacks import NoopWorkflowCallbacks
diff --git a/graphrag/query/llm/get_client.py b/graphrag/query/llm/get_client.py
index a70ca8c5..f36d9e31 100644
--- a/graphrag/query/llm/get_client.py
+++ b/graphrag/query/llm/get_client.py
@@ -5,6 +5,7 @@
 
 from azure.identity import DefaultAzureCredential, get_bearer_token_provider
 
+import graphrag.config.defaults as defs
 from graphrag.config.enums import AuthType, LLMType
 from graphrag.config.models.graph_rag_config import GraphRagConfig
 from graphrag.query.llm.oai.chat_openai import ChatOpenAI
@@ -14,67 +15,68 @@ from graphrag.query.llm.oai.typing import OpenaiApiType
 
 def get_llm(config: GraphRagConfig) -> ChatOpenAI:
     """Get the LLM client."""
-    default_llm_settings = config.get_language_model_config("default_chat_model")
-    is_azure_client = default_llm_settings.type == LLMType.AzureOpenAIChat
-    debug_llm_key = default_llm_settings.api_key or ""
+    llm_config = config.get_language_model_config("default_chat_model")
+    is_azure_client = llm_config.type == LLMType.AzureOpenAIChat
+    debug_llm_key = llm_config.api_key or ""
     llm_debug_info = {
-        **default_llm_settings.model_dump(),
+        **llm_config.model_dump(),
         "api_key": f"REDACTED,len={len(debug_llm_key)}",
     }
     audience = (
-        default_llm_settings.audience
-        if default_llm_settings.audience
+        llm_config.audience
+        if llm_config.audience
         else "https://cognitiveservices.azure.com/.default"
     )
     print(f"creating llm client with {llm_debug_info}")  # noqa T201
     return ChatOpenAI(
-        api_key=default_llm_settings.api_key,
+        api_key=llm_config.api_key,
         azure_ad_token_provider=(
             get_bearer_token_provider(DefaultAzureCredential(), audience)
-            if is_azure_client
-            and default_llm_settings.auth_type == AuthType.AzureManagedIdentity
+            if is_azure_client and llm_config.auth_type == AuthType.AzureManagedIdentity
             else None
         ),
-        api_base=default_llm_settings.api_base,
-        organization=default_llm_settings.organization,
-        model=default_llm_settings.model,
+        api_base=llm_config.api_base,
+        organization=llm_config.organization,
+        model=llm_config.model,
         api_type=OpenaiApiType.AzureOpenAI if is_azure_client else OpenaiApiType.OpenAI,
-        deployment_name=default_llm_settings.deployment_name,
-        api_version=default_llm_settings.api_version,
-        max_retries=default_llm_settings.max_retries,
-        request_timeout=default_llm_settings.request_timeout,
+        deployment_name=llm_config.deployment_name,
+        api_version=llm_config.api_version,
+        max_retries=llm_config.max_retries
+        if llm_config.max_retries != -1
+        else defs.LLM_MAX_RETRIES,
+        request_timeout=llm_config.request_timeout,
     )
 
 
 def get_text_embedder(config: GraphRagConfig) -> OpenAIEmbedding:
     """Get the LLM client for embeddings."""
-    embeddings_llm_settings = config.get_language_model_config(
-        config.embed_text.model_id
-    )
-    is_azure_client = embeddings_llm_settings.type == LLMType.AzureOpenAIEmbedding
-    debug_embedding_api_key = embeddings_llm_settings.api_key or ""
+    embeddings_llm_config = config.get_language_model_config(config.embed_text.model_id)
+    is_azure_client = embeddings_llm_config.type == LLMType.AzureOpenAIEmbedding
+    debug_embedding_api_key = embeddings_llm_config.api_key or ""
     llm_debug_info = {
-        **embeddings_llm_settings.model_dump(),
+        **embeddings_llm_config.model_dump(),
         "api_key": f"REDACTED,len={len(debug_embedding_api_key)}",
     }
-    if embeddings_llm_settings.audience is None:
+    if embeddings_llm_config.audience is None:
         audience = "https://cognitiveservices.azure.com/.default"
     else:
-        audience = embeddings_llm_settings.audience
+        audience = embeddings_llm_config.audience
     print(f"creating embedding llm client with {llm_debug_info}")  # noqa T201
     return OpenAIEmbedding(
-        api_key=embeddings_llm_settings.api_key,
+        api_key=embeddings_llm_config.api_key,
         azure_ad_token_provider=(
             get_bearer_token_provider(DefaultAzureCredential(), audience)
             if is_azure_client
-            and embeddings_llm_settings.auth_type == AuthType.AzureManagedIdentity
+            and embeddings_llm_config.auth_type == AuthType.AzureManagedIdentity
             else None
         ),
-        api_base=embeddings_llm_settings.api_base,
-        organization=embeddings_llm_settings.organization,
+        api_base=embeddings_llm_config.api_base,
+        organization=embeddings_llm_config.organization,
         api_type=OpenaiApiType.AzureOpenAI if is_azure_client else OpenaiApiType.OpenAI,
-        model=embeddings_llm_settings.model,
-        deployment_name=embeddings_llm_settings.deployment_name,
-        api_version=embeddings_llm_settings.api_version,
-        max_retries=embeddings_llm_settings.max_retries,
+        model=embeddings_llm_config.model,
+        deployment_name=embeddings_llm_config.deployment_name,
+        api_version=embeddings_llm_config.api_version,
+        max_retries=embeddings_llm_config.max_retries
+        if embeddings_llm_config.max_retries != -1
+        else defs.LLM_MAX_RETRIES,
     )
diff --git a/poetry.lock b/poetry.lock
index 036099d9..b53340e7 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.5 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
 
 [[package]]
 name = "aiofiles"
@@ -190,13 +190,13 @@ typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.11\""}
 
 [[package]]
 name = "attrs"
-version = "24.3.0"
+version = "25.1.0"
 description = "Classes Without Boilerplate"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "attrs-24.3.0-py3-none-any.whl", hash = "sha256:ac96cd038792094f438ad1f6ff80837353805ac950cd2aa0e0625ef19850c308"},
-    {file = "attrs-24.3.0.tar.gz", hash = "sha256:8f5c07333d543103541ba7be0e2ce16eeee8130cb0b3f9238ab904ce1e85baff"},
+    {file = "attrs-25.1.0-py3-none-any.whl", hash = "sha256:c75a69e28a550a7e93789579c22aa26b0f5b83b75dc4e08fe092980051e1090a"},
+    {file = "attrs-25.1.0.tar.gz", hash = "sha256:1c97078a80c814273a76b2a298a932eb681c87415c11dee0a6921de7f1b02c3e"},
 ]
 
 [package.extras]
@@ -271,13 +271,13 @@ typing-extensions = ">=4.6.0"
 
 [[package]]
 name = "azure-identity"
-version = "1.19.0"
+version = "1.20.0"
 description = "Microsoft Azure Identity Library for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "azure_identity-1.19.0-py3-none-any.whl", hash = "sha256:e3f6558c181692d7509f09de10cca527c7dce426776454fb97df512a46527e81"},
-    {file = "azure_identity-1.19.0.tar.gz", hash = "sha256:500144dc18197d7019b81501165d4fa92225f03778f17d7ca8a2a180129a9c83"},
+    {file = "azure_identity-1.20.0-py3-none-any.whl", hash = "sha256:5f23fc4889a66330e840bd78830287e14f3761820fe3c5f77ac875edcb9ec998"},
+    {file = "azure_identity-1.20.0.tar.gz", hash = "sha256:40597210d56c83e15031b0fe2ea3b26420189e1e7f3e20bdbb292315da1ba014"},
 ]
 
 [package.dependencies]
@@ -306,13 +306,13 @@ typing-extensions = ">=4.6.0"
 
 [[package]]
 name = "azure-storage-blob"
-version = "12.24.0"
+version = "12.24.1"
 description = "Microsoft Azure Blob Storage Client Library for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "azure_storage_blob-12.24.0-py3-none-any.whl", hash = "sha256:4f0bb4592ea79a2d986063696514c781c9e62be240f09f6397986e01755bc071"},
-    {file = "azure_storage_blob-12.24.0.tar.gz", hash = "sha256:eaaaa1507c8c363d6e1d1342bd549938fdf1adec9b1ada8658c8f5bf3aea844e"},
+    {file = "azure_storage_blob-12.24.1-py3-none-any.whl", hash = "sha256:77fb823fdbac7f3c11f7d86a5892e2f85e161e8440a7489babe2195bf248f09e"},
+    {file = "azure_storage_blob-12.24.1.tar.gz", hash = "sha256:052b2a1ea41725ba12e2f4f17be85a54df1129e13ea0321f5a2fcc851cbf47d4"},
 ]
 
 [package.dependencies]
@@ -326,17 +326,17 @@ aio = ["azure-core[aio] (>=1.30.0)"]
 
 [[package]]
 name = "babel"
-version = "2.16.0"
+version = "2.17.0"
 description = "Internationalization utilities"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "babel-2.16.0-py3-none-any.whl", hash = "sha256:368b5b98b37c06b7daf6696391c3240c938b37767d4584413e8438c5c435fa8b"},
-    {file = "babel-2.16.0.tar.gz", hash = "sha256:d1f3554ca26605fe173f3de0c65f750f5a42f924499bf134de6423582298e316"},
+    {file = "babel-2.17.0-py3-none-any.whl", hash = "sha256:4d0b53093fdfb4b21c92b5213dba5a1b23885afa8383709427046b21c366e5f2"},
+    {file = "babel-2.17.0.tar.gz", hash = "sha256:0c54cffb19f690cdcc52a3b50bcbf71e07a808d1c80d549f2459b9d2cf0afb9d"},
 ]
 
 [package.extras]
-dev = ["freezegun (>=1.0,<2.0)", "pytest (>=6.0)", "pytest-cov"]
+dev = ["backports.zoneinfo", "freezegun (>=1.0,<2.0)", "jinja2 (>=3.0)", "pytest (>=6.0)", "pytest-cov", "pytz", "setuptools", "tzdata"]
 
 [[package]]
 name = "beartype"
@@ -358,17 +358,18 @@ test-tox-coverage = ["coverage (>=5.5)"]
 
 [[package]]
 name = "beautifulsoup4"
-version = "4.12.3"
+version = "4.13.3"
 description = "Screen-scraping library"
 optional = false
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 [package.dependencies]
 soupsieve = ">1.2"
+typing-extensions = ">=4.0.0"
 
 [package.extras]
 cchardet = ["cchardet"]
@@ -449,13 +450,13 @@ files = [
 
 [[package]]
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-version = "2024.12.14"
+version = "2025.1.31"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
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 [[package]]
@@ -790,73 +791,74 @@ test-no-images = ["pytest", "pytest-cov", "pytest-rerunfailures", "pytest-xdist"
 
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 [package.extras]
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 test-randomorder = ["pytest-randomly"]
 
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 [[package]]
@@ -1151,13 +1157,13 @@ test = ["pytest (>=6)"]
 
 [[package]]
 name = "executing"
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+version = "2.2.0"
 description = "Get the currently executing AST node of a frame, and other information"
 optional = false
 python-versions = ">=3.8"
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 [package.extras]
@@ -1179,83 +1185,88 @@ devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benc
 
 [[package]]
 name = "fnllm"
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 pydantic = ">=2.8.2"
 tenacity = ">=8.5.0"
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 [package.extras]
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+numpy = ["numpy (>=1.26.4)"]
 openai = ["openai (>=1.35.12)", "tiktoken (>=0.7.0)"]
 
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 [package.extras]
@@ -1388,15 +1399,15 @@ umap-learn = ">=0.5.6,<0.6.0"
 
 [[package]]
 name = "graspologic-native"
-version = "1.2.1"
+version = "1.2.3"
 description = "Python native companion module to the graspologic library"
 optional = false
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+python-versions = "<3.14,>=3.8"
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 ]
 
 [[package]]
@@ -1532,13 +1543,13 @@ test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio
 
 [[package]]
 name = "ipython"
-version = "8.31.0"
+version = "8.32.0"
 description = "IPython: Productive Interactive Computing"
 optional = false
 python-versions = ">=3.10"
 files = [
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 ]
 
 [package.dependencies]
@@ -1912,17 +1923,18 @@ test = ["ipykernel", "pre-commit", "pytest (<8)", "pytest-cov", "pytest-timeout"
 
 [[package]]
 name = "jupyter-events"
-version = "0.11.0"
+version = "0.12.0"
 description = "Jupyter Event System library"
 optional = false
 python-versions = ">=3.9"
 files = [
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 ]
 
 [package.dependencies]
 jsonschema = {version = ">=4.18.0", extras = ["format-nongpl"]}
+packaging = "*"
 python-json-logger = ">=2.0.4"
 pyyaml = ">=5.3"
 referencing = "*"
@@ -2006,13 +2018,13 @@ test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (>
 
 [[package]]
 name = "jupyterlab"
-version = "4.3.4"
+version = "4.3.5"
 description = "JupyterLab computational environment"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -2087,13 +2099,13 @@ files = [
 
 [[package]]
 name = "jupytext"
-version = "1.16.6"
+version = "1.16.7"
 description = "Jupyter notebooks as Markdown documents, Julia, Python or R scripts"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -2272,32 +2284,32 @@ test = ["pytest", "pytest-cov"]
 
 [[package]]
 name = "llvmlite"
-version = "0.43.0"
+version = "0.44.0"
 description = "lightweight wrapper around basic LLVM functionality"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 files = [
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+    {file = "llvmlite-0.44.0.tar.gz", hash = "sha256:07667d66a5d150abed9157ab6c0b9393c9356f229784a4385c02f99e94fc94d4"},
 ]
 
 [[package]]
@@ -2502,13 +2514,13 @@ files = [
 
 [[package]]
 name = "marshmallow"
-version = "3.25.1"
+version = "3.26.1"
 description = "A lightweight library for converting complex datatypes to and from native Python datatypes."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "marshmallow-3.25.1-py3-none-any.whl", hash = "sha256:ec5d00d873ce473b7f2ffcb7104286a376c354cab0c2fa12f5573dab03e87210"},
-    {file = "marshmallow-3.25.1.tar.gz", hash = "sha256:f4debda3bb11153d81ac34b0d582bf23053055ee11e791b54b4b35493468040a"},
+    {file = "marshmallow-3.26.1-py3-none-any.whl", hash = "sha256:3350409f20a70a7e4e11a27661187b77cdcaeb20abca41c1454fe33636bea09c"},
+    {file = "marshmallow-3.26.1.tar.gz", hash = "sha256:e6d8affb6cb61d39d26402096dc0aee12d5a26d490a121f118d2e81dc0719dc6"},
 ]
 
 [package.dependencies]
@@ -2633,13 +2645,13 @@ files = [
 
 [[package]]
 name = "mistune"
-version = "3.1.0"
+version = "3.1.1"
 description = "A sane and fast Markdown parser with useful plugins and renderers"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "mistune-3.1.0-py3-none-any.whl", hash = "sha256:b05198cf6d671b3deba6c87ec6cf0d4eb7b72c524636eddb6dbf13823b52cee1"},
-    {file = "mistune-3.1.0.tar.gz", hash = "sha256:dbcac2f78292b9dc066cd03b7a3a26b62d85f8159f2ea5fd28e55df79908d667"},
+    {file = "mistune-3.1.1-py3-none-any.whl", hash = "sha256:02106ac2aa4f66e769debbfa028509a275069dcffce0dfa578edd7b991ee700a"},
+    {file = "mistune-3.1.1.tar.gz", hash = "sha256:e0740d635f515119f7d1feb6f9b192ee60f0cc649f80a8f944f905706a21654c"},
 ]
 
 [package.dependencies]
@@ -2726,13 +2738,13 @@ pygments = ">2.12.0"
 
 [[package]]
 name = "mkdocs-material"
-version = "9.5.49"
+version = "9.6.4"
 description = "Documentation that simply works"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "mkdocs_material-9.5.49-py3-none-any.whl", hash = "sha256:c3c2d8176b18198435d3a3e119011922f3e11424074645c24019c2dcf08a360e"},
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+    {file = "mkdocs_material-9.6.4-py3-none-any.whl", hash = "sha256:414e8376551def6d644b8e6f77226022868532a792eb2c9accf52199009f568f"},
+    {file = "mkdocs_material-9.6.4.tar.gz", hash = "sha256:4d1d35e1c1d3e15294cb7fa5d02e0abaee70d408f75027dc7be6e30fb32e6867"},
 ]
 
 [package.dependencies]
@@ -2749,7 +2761,7 @@ regex = ">=2022.4"
 requests = ">=2.26,<3.0"
 
 [package.extras]
-git = ["mkdocs-git-committers-plugin-2 (>=1.1,<2.0)", "mkdocs-git-revision-date-localized-plugin (>=1.2.4,<2.0)"]
+git = ["mkdocs-git-committers-plugin-2 (>=1.1,<3)", "mkdocs-git-revision-date-localized-plugin (>=1.2.4,<2.0)"]
 imaging = ["cairosvg (>=2.6,<3.0)", "pillow (>=10.2,<11.0)"]
 recommended = ["mkdocs-minify-plugin (>=0.7,<1.0)", "mkdocs-redirects (>=1.2,<2.0)", "mkdocs-rss-plugin (>=1.6,<2.0)"]
 
@@ -2882,13 +2894,13 @@ test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>=
 
 [[package]]
 name = "nbconvert"
-version = "7.16.5"
+version = "7.16.6"
 description = "Converting Jupyter Notebooks (.ipynb files) to other formats.  Output formats include asciidoc, html, latex, markdown, pdf, py, rst, script.  nbconvert can be used both as a Python library (`import nbconvert`) or as a command line tool (invoked as `jupyter nbconvert ...`)."
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "nbconvert-7.16.6-py3-none-any.whl", hash = "sha256:1375a7b67e0c2883678c48e506dc320febb57685e5ee67faa51b18a90f3a712b"},
+    {file = "nbconvert-7.16.6.tar.gz", hash = "sha256:576a7e37c6480da7b8465eefa66c17844243816ce1ccc372633c6b71c3c0f582"},
 ]
 
 [package.dependencies]
@@ -3045,37 +3057,37 @@ test = ["pytest", "pytest-console-scripts", "pytest-jupyter", "pytest-tornasync"
 
 [[package]]
 name = "numba"
-version = "0.60.0"
+version = "0.61.0"
 description = "compiling Python code using LLVM"
 optional = false
-python-versions = ">=3.9"
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 [package.dependencies]
-llvmlite = "==0.43.*"
-numpy = ">=1.22,<2.1"
+llvmlite = "==0.44.*"
+numpy = ">=1.24,<2.2"
 
 [[package]]
 name = "numpy"
@@ -3124,13 +3136,13 @@ files = [
 
 [[package]]
 name = "openai"
-version = "1.59.7"
+version = "1.62.0"
 description = "The official Python library for the openai API"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -3632,13 +3644,13 @@ twisted = ["twisted"]
 
 [[package]]
 name = "prompt-toolkit"
-version = "3.0.48"
+version = "3.0.50"
 description = "Library for building powerful interactive command lines in Python"
 optional = false
-python-versions = ">=3.7.0"
+python-versions = ">=3.8.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -3760,13 +3772,13 @@ files = [
 
 [[package]]
 name = "pydantic"
-version = "2.10.5"
+version = "2.10.6"
 description = "Data validation using Python type hints"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -3954,13 +3966,13 @@ torch = ["torch"]
 
 [[package]]
 name = "pymdown-extensions"
-version = "10.14"
+version = "10.14.3"
 description = "Extension pack for Python Markdown."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -4004,13 +4016,13 @@ diagrams = ["jinja2", "railroad-diagrams"]
 
 [[package]]
 name = "pyright"
-version = "1.1.391"
+version = "1.1.394"
 description = "Command line wrapper for pyright"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -4135,13 +4147,13 @@ dev = ["backports.zoneinfo", "black", "build", "freezegun", "mdx_truly_sane_list
 
 [[package]]
 name = "pytz"
-version = "2024.2"
+version = "2025.1"
 description = "World timezone definitions, modern and historical"
 optional = false
 python-versions = "*"
 files = [
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 ]
 
 [[package]]
@@ -4173,17 +4185,18 @@ files = [
 
 [[package]]
 name = "pywinpty"
-version = "2.0.14"
+version = "2.0.15"
 description = "Pseudo terminal support for Windows from Python."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
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 ]
 
 [[package]]
@@ -4264,120 +4277,120 @@ pyyaml = "*"
 
 [[package]]
 name = "pyzmq"
-version = "26.2.0"
+version = "26.2.1"
 description = "Python bindings for 0MQ"
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "pyzmq-26.2.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0995fd3530f2e89d6b69a2202e340bbada3191014352af978fa795cb7a446331"},
+    {file = "pyzmq-26.2.1-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:7c6160fe513654e65665332740f63de29ce0d165e053c0c14a161fa60dd0da01"},
+    {file = "pyzmq-26.2.1-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:8ec8e3aea6146b761d6c57fcf8f81fcb19f187afecc19bf1701a48db9617a217"},
+    {file = "pyzmq-26.2.1.tar.gz", hash = "sha256:17d72a74e5e9ff3829deb72897a175333d3ef5b5413948cae3cf7ebf0b02ecca"},
 ]
 
 [package.dependencies]
@@ -4385,18 +4398,19 @@ cffi = {version = "*", markers = "implementation_name == \"pypy\""}
 
 [[package]]
 name = "referencing"
-version = "0.35.1"
+version = "0.36.2"
 description = "JSON Referencing + Python"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "referencing-0.35.1-py3-none-any.whl", hash = "sha256:eda6d3234d62814d1c64e305c1331c9a3a6132da475ab6382eaa997b21ee75de"},
-    {file = "referencing-0.35.1.tar.gz", hash = "sha256:25b42124a6c8b632a425174f24087783efb348a6f1e0008e63cd4466fedf703c"},
+    {file = "referencing-0.36.2-py3-none-any.whl", hash = "sha256:e8699adbbf8b5c7de96d8ffa0eb5c158b3beafce084968e2ea8bb08c6794dcd0"},
+    {file = "referencing-0.36.2.tar.gz", hash = "sha256:df2e89862cd09deabbdba16944cc3f10feb6b3e6f18e902f7cc25609a34775aa"},
 ]
 
 [package.dependencies]
 attrs = ">=22.2.0"
 rpds-py = ">=0.7.0"
+typing-extensions = {version = ">=4.4.0", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "regex"
@@ -5509,13 +5523,13 @@ files = [
 
 [[package]]
 name = "types-setuptools"
-version = "75.8.0.20250110"
+version = "75.8.0.20250210"
 description = "Typing stubs for setuptools"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "types_setuptools-75.8.0.20250110-py3-none-any.whl", hash = "sha256:a9f12980bbf9bcdc23ecd80755789085bad6bfce4060c2275bc2b4ca9f2bc480"},
-    {file = "types_setuptools-75.8.0.20250110.tar.gz", hash = "sha256:96f7ec8bbd6e0a54ea180d66ad68ad7a1d7954e7281a710ea2de75e355545271"},
+    {file = "types_setuptools-75.8.0.20250210-py3-none-any.whl", hash = "sha256:a217d7b4d59be04c29e23d142c959a0f85e71292fd3fc4313f016ca11f0b56dc"},
+    {file = "types_setuptools-75.8.0.20250210.tar.gz", hash = "sha256:c1547361b2441f07c94e25dce8a068e18c611593ad4b6fdd727b1a8f5d1fda33"},
 ]
 
 [[package]]
@@ -5531,13 +5545,13 @@ files = [
 
 [[package]]
 name = "tzdata"
-version = "2024.2"
+version = "2025.1"
 description = "Provider of IANA time zone data"
 optional = false
 python-versions = ">=2"
 files = [
-    {file = "tzdata-2024.2-py2.py3-none-any.whl", hash = "sha256:a48093786cdcde33cad18c2555e8532f34422074448fbc874186f0abd79565cd"},
-    {file = "tzdata-2024.2.tar.gz", hash = "sha256:7d85cc416e9382e69095b7bdf4afd9e3880418a2413feec7069d533d6b4e31cc"},
+    {file = "tzdata-2025.1-py2.py3-none-any.whl", hash = "sha256:7e127113816800496f027041c570f50bcd464a020098a3b6b199517772303639"},
+    {file = "tzdata-2025.1.tar.gz", hash = "sha256:24894909e88cdb28bd1636c6887801df64cb485bd593f2fd83ef29075a81d694"},
 ]
 
 [[package]]
@@ -5838,4 +5852,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<3.13"
-content-hash = "83c64d24a87f5e1d8698d168deed9845bd45f913b363f8854b861277533d360f"
+content-hash = "4234b26af4903ae30799cdaea6221f19acf77be5cd4f9ffaf576949dbfc76e33"
diff --git a/pyproject.toml b/pyproject.toml
index 53c2a165..9917fc23 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -57,11 +57,15 @@ lancedb = "^0.17.0"
 aiofiles = "^24.1.0"
 
 # LLM
+fnllm = {extras = ["azure", "openai"], version = "^0.1.2"}
+httpx = "^0.28.1"
+json-repair = "^0.30.3"
 openai = "^1.57.0"
 nltk = "3.9.1"
+tenacity = "^9.0.0"
 tiktoken = "^0.8.0"
 
-# Data-Sci
+# Data-Science
 numpy = "^1.25.2"
 graspologic = "^3.4.1"
 networkx = "^3.4.2"
@@ -78,22 +82,18 @@ rich = "^13.9.4"
 devtools = "^0.12.2"
 typing-extensions = "^4.12.2"
 
-#Azure
+# Azure
 azure-cosmos = "^4.9.0"
 azure-identity = "^1.19.0"
 azure-storage-blob = "^12.24.0"
 
 future = "^1.0.0" # Needed until graspologic fixes their dependency
 typer = "^0.15.1"
-fnllm = "^0.0.10"
-
-tenacity = "^9.0.0"
-json-repair = "^0.30.3"
 tqdm = "^4.67.1"
-httpx = "^0.28.1"
 
 textblob = "^0.18.0.post0"
 spacy = "^3.8.4"
+
 [tool.poetry.group.dev.dependencies]
 coverage = "^7.6.9"
 ipykernel = "^6.29.5"
diff --git a/tests/fixtures/min-csv/config.json b/tests/fixtures/min-csv/config.json
index 2c32c250..53f075a8 100644
--- a/tests/fixtures/min-csv/config.json
+++ b/tests/fixtures/min-csv/config.json
@@ -15,7 +15,7 @@
                 1,
                 2500
             ],
-            "max_runtime": 300,
+            "max_runtime": 500,
             "expected_artifacts": 2
         },
         "create_communities": {
diff --git a/tests/fixtures/min-csv/settings.yml b/tests/fixtures/min-csv/settings.yml
index 98ab2638..f1877bc2 100644
--- a/tests/fixtures/min-csv/settings.yml
+++ b/tests/fixtures/min-csv/settings.yml
@@ -10,8 +10,7 @@ models:
     tokens_per_minute: ${GRAPHRAG_LLM_TPM}
     requests_per_minute: ${GRAPHRAG_LLM_RPM}
     model_supports_json: true
-    parallelization_num_threads: 50
-    parallelization_stagger: 0.3
+    concurrent_requests: 50
     async_mode: threaded
   default_embedding_model:
     azure_auth_type: api_key
@@ -23,8 +22,7 @@ models:
     model: ${GRAPHRAG_EMBEDDING_MODEL}
     tokens_per_minute: ${GRAPHRAG_EMBEDDING_TPM}
     requests_per_minute: ${GRAPHRAG_EMBEDDING_RPM}
-    parallelization_num_threads: 50
-    parallelization_stagger: 0.3
+    concurrent_requests: 50
     async_mode: threaded
 
 vector_store:
diff --git a/tests/fixtures/text/config.json b/tests/fixtures/text/config.json
index c7af6854..4ed5d85d 100644
--- a/tests/fixtures/text/config.json
+++ b/tests/fixtures/text/config.json
@@ -15,7 +15,7 @@
                 1,
                 2500
             ],
-            "max_runtime": 300,
+            "max_runtime": 500,
             "expected_artifacts": 2
         },
         "extract_covariates": {
diff --git a/tests/fixtures/text/settings.yml b/tests/fixtures/text/settings.yml
index 3d95cd97..c5c4fe74 100644
--- a/tests/fixtures/text/settings.yml
+++ b/tests/fixtures/text/settings.yml
@@ -10,8 +10,7 @@ models:
     tokens_per_minute: ${GRAPHRAG_LLM_TPM}
     requests_per_minute: ${GRAPHRAG_LLM_RPM}
     model_supports_json: true
-    parallelization_num_threads: 50
-    parallelization_stagger: 0.3
+    concurrent_requests: 50
     async_mode: threaded
   default_embedding_model:
     azure_auth_type: api_key
@@ -23,8 +22,7 @@ models:
     model: ${GRAPHRAG_EMBEDDING_MODEL}
     tokens_per_minute: ${GRAPHRAG_EMBEDDING_TPM}
     requests_per_minute: ${GRAPHRAG_EMBEDDING_RPM}
-    parallelization_num_threads: 50
-    parallelization_stagger: 0.3
+    concurrent_requests: 50
     async_mode: threaded
 
 vector_store:
diff --git a/tests/unit/config/utils.py b/tests/unit/config/utils.py
index d7a2d20c..5e5de015 100644
--- a/tests/unit/config/utils.py
+++ b/tests/unit/config/utils.py
@@ -265,13 +265,7 @@ def assert_language_model_configs(
     assert actual.requests_per_minute == expected.requests_per_minute
     assert actual.max_retries == expected.max_retries
     assert actual.max_retry_wait == expected.max_retry_wait
-    assert (
-        actual.sleep_on_rate_limit_recommendation
-        == expected.sleep_on_rate_limit_recommendation
-    )
     assert actual.concurrent_requests == expected.concurrent_requests
-    assert actual.parallelization_stagger == expected.parallelization_stagger
-    assert actual.parallelization_num_threads == expected.parallelization_num_threads
     assert actual.async_mode == expected.async_mode
     if actual.responses is not None:
         assert expected.responses is not None
diff --git a/tests/unit/indexing/verbs/helpers/mock_llm.py b/tests/unit/indexing/verbs/helpers/mock_llm.py
index c9464e41..e869047b 100644
--- a/tests/unit/indexing/verbs/helpers/mock_llm.py
+++ b/tests/unit/indexing/verbs/helpers/mock_llm.py
@@ -1,6 +1,6 @@
 # Copyright (c) 2024 Microsoft Corporation.
 # Licensed under the MIT License
-from fnllm import ChatLLM
+from fnllm.types import ChatLLM
 from pydantic import BaseModel
 
 from graphrag.index.llm.mock_llm import MockChatLLM