diff --git a/.semversioner/next-release/patch-20241114012244853718.json b/.semversioner/next-release/patch-20241114012244853718.json
new file mode 100644
index 0000000000..9b16cc63c8
--- /dev/null
+++ b/.semversioner/next-release/patch-20241114012244853718.json
@@ -0,0 +1,4 @@
+{
+  "type": "patch",
+  "description": "Centralized prompts and export all for easier injection."
+}
diff --git a/docs/prompt_tuning/manual_prompt_tuning.md b/docs/prompt_tuning/manual_prompt_tuning.md
index 4618c28745..7f10fc8e79 100644
--- a/docs/prompt_tuning/manual_prompt_tuning.md
+++ b/docs/prompt_tuning/manual_prompt_tuning.md
@@ -8,7 +8,7 @@ Each of these prompts may be overridden by writing a custom prompt file in plain
 
 ## Entity/Relationship Extraction
 
-[Prompt Source](http://github.com/microsoft/graphrag/blob/main/graphrag/index/graph/extractors/graph/prompts.py)
+[Prompt Source](http://github.com/microsoft/graphrag/blob/main/graphrag/prompts/entity_extraction.py)
 
 ### Tokens (values provided by extractor)
 
@@ -20,7 +20,7 @@ Each of these prompts may be overridden by writing a custom prompt file in plain
 
 ## Summarize Entity/Relationship Descriptions
 
-[Prompt Source](http://github.com/microsoft/graphrag/blob/main/graphrag/index/graph/extractors/summarize/prompts.py)
+[Prompt Source](http://github.com/microsoft/graphrag/blob/main/graphrag/prompts/summarize_descriptions.py)
 
 ### Tokens (values provided by extractor)
 
@@ -29,7 +29,7 @@ Each of these prompts may be overridden by writing a custom prompt file in plain
 
 ## Claim Extraction
 
-[Prompt Source](http://github.com/microsoft/graphrag/blob/main/graphrag/index/graph/extractors/claims/prompts.py)
+[Prompt Source](http://github.com/microsoft/graphrag/blob/main/graphrag/prompts/claim_extraction.py)
 
 ### Tokens (values provided by extractor)
 
@@ -47,7 +47,7 @@ See the [configuration documentation](../config/overview.md) for details on how
 
 ## Generate Community Reports
 
-[Prompt Source](http://github.com/microsoft/graphrag/blob/main/graphrag/index/graph/extractors/community_reports/prompts.py)
+[Prompt Source](http://github.com/microsoft/graphrag/blob/main/graphrag/prompts/community_report.py)
 
 ### Tokens (values provided by extractor)
 
diff --git a/docs/query/global_search.md b/docs/query/global_search.md
index b7b6bfc8d2..a9685d70be 100644
--- a/docs/query/global_search.md
+++ b/docs/query/global_search.md
@@ -56,11 +56,11 @@ Below are the key parameters of the [GlobalSearch class](https://github.com/micr
 
 * `llm`: OpenAI model object to be used for response generation
 * `context_builder`: [context builder](https://github.com/microsoft/graphrag/blob/main//graphrag/query/structured_search/global_search/community_context.py) object to be used for preparing context data from community reports
-* `map_system_prompt`: prompt template used in the `map` stage. Default template can be found at [map_system_prompt](https://github.com/microsoft/graphrag/blob/main//graphrag/query/structured_search/global_search/map_system_prompt.py)
-* `reduce_system_prompt`: prompt template used in the `reduce` stage, default template can be found at [reduce_system_prompt](https://github.com/microsoft/graphrag/blob/main//graphrag/query/structured_search/global_search/reduce_system_prompt.py)
+* `map_system_prompt`: prompt template used in the `map` stage. Default template can be found at [map_system_prompt](https://github.com/microsoft/graphrag/blob/main//graphrag/prompts/query/global_search_map_system_prompt.py)
+* `reduce_system_prompt`: prompt template used in the `reduce` stage, default template can be found at [reduce_system_prompt](https://github.com/microsoft/graphrag/blob/main//graphrag/prompts/query/global_search_reduce_system_prompt.py)
 * `response_type`: free-form text describing the desired response type and format (e.g., `Multiple Paragraphs`, `Multi-Page Report`)
 * `allow_general_knowledge`: setting this to True will include additional instructions to the `reduce_system_prompt` to prompt the LLM to incorporate relevant real-world knowledge outside of the dataset. Note that this may increase hallucinations, but can be useful for certain scenarios. Default is False
-*`general_knowledge_inclusion_prompt`: instruction to add to the `reduce_system_prompt` if `allow_general_knowledge` is enabled. Default instruction can be found at [general_knowledge_instruction](https://github.com/microsoft/graphrag/blob/main//graphrag/query/structured_search/global_search/reduce_system_prompt.py)
+*`general_knowledge_inclusion_prompt`: instruction to add to the `reduce_system_prompt` if `allow_general_knowledge` is enabled. Default instruction can be found at [general_knowledge_instruction](https://github.com/microsoft/graphrag/blob/main//graphrag/prompts/query/global_search_knowledge_system_prompt.py)
 * `max_data_tokens`: token budget for the context data
 * `map_llm_params`: a dictionary of additional parameters (e.g., temperature, max_tokens) to be passed to the LLM call at the `map` stage
 * `reduce_llm_params`: a dictionary of additional parameters (e.g., temperature, max_tokens) to passed to the LLM call at the `reduce` stage
diff --git a/docs/query/local_search.md b/docs/query/local_search.md
index 7169392cc2..bf0f43e3ce 100644
--- a/docs/query/local_search.md
+++ b/docs/query/local_search.md
@@ -50,7 +50,7 @@ Below are the key parameters of the [LocalSearch class](https://github.com/micro
 
 * `llm`: OpenAI model object to be used for response generation
 * `context_builder`: [context builder](https://github.com/microsoft/graphrag/blob/main//graphrag/query/structured_search/local_search/mixed_context.py) object to be used for preparing context data from collections of knowledge model objects
-* `system_prompt`: prompt template used to generate the search response. Default template can be found at [system_prompt](https://github.com/microsoft/graphrag/blob/main//graphrag/query/structured_search/local_search/system_prompt.py)
+* `system_prompt`: prompt template used to generate the search response. Default template can be found at [system_prompt](https://github.com/microsoft/graphrag/blob/main//graphrag/prompts/query/local_search_system_prompt.py)
 * `response_type`: free-form text describing the desired response type and format (e.g., `Multiple Paragraphs`, `Multi-Page Report`)
 * `llm_params`: a dictionary of additional parameters (e.g., temperature, max_tokens) to be passed to the LLM call
 * `context_builder_params`: a dictionary of additional parameters to be passed to the [`context_builder`](https://github.com/microsoft/graphrag/blob/main//graphrag/query/structured_search/local_search/mixed_context.py) object when building context for the search prompt
diff --git a/docs/query/question_generation.md b/docs/query/question_generation.md
index 43643e3727..525a465499 100644
--- a/docs/query/question_generation.md
+++ b/docs/query/question_generation.md
@@ -13,7 +13,7 @@ Below are the key parameters of the [Question Generation class](https://github.c
 
 * `llm`: OpenAI model object to be used for response generation
 * `context_builder`: [context builder](https://github.com/microsoft/graphrag/blob/main//graphrag/query/structured_search/local_search/mixed_context.py) object to be used for preparing context data from collections of knowledge model objects, using the same context builder class as in local search
-* `system_prompt`: prompt template used to generate candidate questions. Default template can be found at [system_prompt](https://github.com/microsoft/graphrag/blob/main//graphrag/query/question_gen/system_prompt.py)
+* `system_prompt`: prompt template used to generate candidate questions. Default template can be found at [system_prompt](https://github.com/microsoft/graphrag/blob/main//graphrag/prompts/query/question_gen_system_prompt.py)
 * `llm_params`: a dictionary of additional parameters (e.g., temperature, max_tokens) to be passed to the LLM call
 * `context_builder_params`: a dictionary of additional parameters to be passed to the [`context_builder`](https://github.com/microsoft/graphrag/blob/main//graphrag/query/structured_search/local_search/mixed_context.py) object when building context for the question generation prompt
 * `callbacks`: optional callback functions, can be used to provide custom event handlers for LLM's completion streaming events
diff --git a/graphrag/api/query.py b/graphrag/api/query.py
index 4c7941b5f1..21648a12a8 100644
--- a/graphrag/api/query.py
+++ b/graphrag/api/query.py
@@ -98,6 +98,14 @@ async def global_search(
         dynamic_community_selection=dynamic_community_selection,
     )
     _entities = read_indexer_entities(nodes, entities, community_level=community_level)
+    map_prompt = _load_search_prompt(config.root_dir, config.global_search.map_prompt)
+    reduce_prompt = _load_search_prompt(
+        config.root_dir, config.global_search.reduce_prompt
+    )
+    knowledge_prompt = _load_search_prompt(
+        config.root_dir, config.global_search.knowledge_prompt
+    )
+
     search_engine = get_global_search_engine(
         config,
         reports=reports,
@@ -105,6 +113,9 @@ async def global_search(
         communities=_communities,
         response_type=response_type,
         dynamic_community_selection=dynamic_community_selection,
+        map_system_prompt=map_prompt,
+        reduce_system_prompt=reduce_prompt,
+        general_knowledge_inclusion_prompt=knowledge_prompt,
     )
     result: SearchResult = await search_engine.asearch(query=query)
     response = result.response
@@ -156,6 +167,14 @@ async def global_search_streaming(
         dynamic_community_selection=dynamic_community_selection,
     )
     _entities = read_indexer_entities(nodes, entities, community_level=community_level)
+    map_prompt = _load_search_prompt(config.root_dir, config.global_search.map_prompt)
+    reduce_prompt = _load_search_prompt(
+        config.root_dir, config.global_search.reduce_prompt
+    )
+    knowledge_prompt = _load_search_prompt(
+        config.root_dir, config.global_search.knowledge_prompt
+    )
+
     search_engine = get_global_search_engine(
         config,
         reports=reports,
@@ -163,6 +182,9 @@ async def global_search_streaming(
         communities=_communities,
         response_type=response_type,
         dynamic_community_selection=dynamic_community_selection,
+        map_system_prompt=map_prompt,
+        reduce_system_prompt=reduce_prompt,
+        general_knowledge_inclusion_prompt=knowledge_prompt,
     )
     search_result = search_engine.astream_search(query=query)
 
@@ -238,6 +260,7 @@ async def local_search(
 
     _entities = read_indexer_entities(nodes, entities, community_level)
     _covariates = read_indexer_covariates(covariates) if covariates is not None else []
+    prompt = _load_search_prompt(config.root_dir, config.local_search.prompt)
 
     search_engine = get_local_search_engine(
         config=config,
@@ -248,6 +271,7 @@ async def local_search(
         covariates={"claims": _covariates},
         description_embedding_store=description_embedding_store,  # type: ignore
         response_type=response_type,
+        system_prompt=prompt,
     )
 
     result: SearchResult = await search_engine.asearch(query=query)
@@ -312,6 +336,7 @@ async def local_search_streaming(
 
     _entities = read_indexer_entities(nodes, entities, community_level)
     _covariates = read_indexer_covariates(covariates) if covariates is not None else []
+    prompt = _load_search_prompt(config.root_dir, config.local_search.prompt)
 
     search_engine = get_local_search_engine(
         config=config,
@@ -322,6 +347,7 @@ async def local_search_streaming(
         covariates={"claims": _covariates},
         description_embedding_store=description_embedding_store,  # type: ignore
         response_type=response_type,
+        system_prompt=prompt,
     )
     search_result = search_engine.astream_search(query=query)
 
@@ -401,7 +427,7 @@ async def drift_search(
     _entities = read_indexer_entities(nodes, entities, community_level)
     _reports = read_indexer_reports(community_reports, nodes, community_level)
     read_indexer_report_embeddings(_reports, full_content_embedding_store)
-
+    prompt = _load_search_prompt(config.root_dir, config.drift_search.prompt)
     search_engine = get_drift_search_engine(
         config=config,
         reports=_reports,
@@ -409,6 +435,7 @@ async def drift_search(
         entities=_entities,
         relationships=read_indexer_relationships(relationships),
         description_embedding_store=description_embedding_store,  # type: ignore
+        local_system_prompt=prompt,
     )
 
     result: SearchResult = await search_engine.asearch(query=query)
@@ -551,3 +578,17 @@ def _reformat_context_data(context_data: dict) -> dict:
             continue
         final_format[key] = records
     return final_format
+
+
+def _load_search_prompt(root_dir: str, prompt_config: str | None) -> str | None:
+    """
+    Load the search prompt from disk if configured.
+
+    If not, leave it empty - the search functions will load their defaults.
+
+    """
+    if prompt_config:
+        prompt_file = Path(root_dir) / prompt_config
+        if prompt_file.exists():
+            return prompt_file.read_bytes().decode(encoding="utf-8")
+    return None
diff --git a/graphrag/cli/initialize.py b/graphrag/cli/initialize.py
index b861132597..c807397799 100644
--- a/graphrag/cli/initialize.py
+++ b/graphrag/cli/initialize.py
@@ -5,14 +5,24 @@
 
 from pathlib import Path
 
-from graphrag.index.graph.extractors.claims.prompts import CLAIM_EXTRACTION_PROMPT
-from graphrag.index.graph.extractors.community_reports.prompts import (
-    COMMUNITY_REPORT_PROMPT,
-)
-from graphrag.index.graph.extractors.graph.prompts import GRAPH_EXTRACTION_PROMPT
-from graphrag.index.graph.extractors.summarize.prompts import SUMMARIZE_PROMPT
 from graphrag.index.init_content import INIT_DOTENV, INIT_YAML
 from graphrag.logging import ReporterType, create_progress_reporter
+from graphrag.prompts.index.claim_extraction import CLAIM_EXTRACTION_PROMPT
+from graphrag.prompts.index.community_report import (
+    COMMUNITY_REPORT_PROMPT,
+)
+from graphrag.prompts.index.entity_extraction import GRAPH_EXTRACTION_PROMPT
+from graphrag.prompts.index.summarize_descriptions import SUMMARIZE_PROMPT
+from graphrag.prompts.query.drift_search_system_prompt import DRIFT_LOCAL_SYSTEM_PROMPT
+from graphrag.prompts.query.global_search_knowledge_system_prompt import (
+    GENERAL_KNOWLEDGE_INSTRUCTION,
+)
+from graphrag.prompts.query.global_search_map_system_prompt import MAP_SYSTEM_PROMPT
+from graphrag.prompts.query.global_search_reduce_system_prompt import (
+    REDUCE_SYSTEM_PROMPT,
+)
+from graphrag.prompts.query.local_search_system_prompt import LOCAL_SEARCH_SYSTEM_PROMPT
+from graphrag.prompts.query.question_gen_system_prompt import QUESTION_SYSTEM_PROMPT
 
 
 def initialize_project_at(path: Path) -> None:
@@ -40,28 +50,21 @@ def initialize_project_at(path: Path) -> None:
     if not prompts_dir.exists():
         prompts_dir.mkdir(parents=True, exist_ok=True)
 
-    entity_extraction = prompts_dir / "entity_extraction.txt"
-    if not entity_extraction.exists():
-        with entity_extraction.open("wb") as file:
-            file.write(
-                GRAPH_EXTRACTION_PROMPT.encode(encoding="utf-8", errors="strict")
-            )
-
-    summarize_descriptions = prompts_dir / "summarize_descriptions.txt"
-    if not summarize_descriptions.exists():
-        with summarize_descriptions.open("wb") as file:
-            file.write(SUMMARIZE_PROMPT.encode(encoding="utf-8", errors="strict"))
-
-    claim_extraction = prompts_dir / "claim_extraction.txt"
-    if not claim_extraction.exists():
-        with claim_extraction.open("wb") as file:
-            file.write(
-                CLAIM_EXTRACTION_PROMPT.encode(encoding="utf-8", errors="strict")
-            )
+    prompts = {
+        "entity_extraction": GRAPH_EXTRACTION_PROMPT,
+        "summarize_descriptions": SUMMARIZE_PROMPT,
+        "claim_extraction": CLAIM_EXTRACTION_PROMPT,
+        "community_report": COMMUNITY_REPORT_PROMPT,
+        "drift_search_system_prompt": DRIFT_LOCAL_SYSTEM_PROMPT,
+        "global_search_map_system_prompt": MAP_SYSTEM_PROMPT,
+        "global_search_reduce_system_prompt": REDUCE_SYSTEM_PROMPT,
+        "global_search_knowledge_system_prompt": GENERAL_KNOWLEDGE_INSTRUCTION,
+        "local_search_system_prompt": LOCAL_SEARCH_SYSTEM_PROMPT,
+        "question_gen_system_prompt": QUESTION_SYSTEM_PROMPT,
+    }
 
-    community_report = prompts_dir / "community_report.txt"
-    if not community_report.exists():
-        with community_report.open("wb") as file:
-            file.write(
-                COMMUNITY_REPORT_PROMPT.encode(encoding="utf-8", errors="strict")
-            )
+    for name, content in prompts.items():
+        prompt_file = prompts_dir / f"{name}.txt"
+        if not prompt_file.exists():
+            with prompt_file.open("wb") as file:
+                file.write(content.encode(encoding="utf-8", errors="strict"))
diff --git a/graphrag/config/__init__.py b/graphrag/config/__init__.py
index 62708f5d9e..3354f2ccd8 100644
--- a/graphrag/config/__init__.py
+++ b/graphrag/config/__init__.py
@@ -51,6 +51,7 @@
     ClaimExtractionConfig,
     ClusterGraphConfig,
     CommunityReportsConfig,
+    DRIFTSearchConfig,
     EmbedGraphConfig,
     EntityExtractionConfig,
     GlobalSearchConfig,
@@ -85,6 +86,7 @@
     "ClusterGraphConfigInput",
     "CommunityReportsConfig",
     "CommunityReportsConfigInput",
+    "DRIFTSearchConfig",
     "EmbedGraphConfig",
     "EmbedGraphConfigInput",
     "EntityExtractionConfig",
diff --git a/graphrag/config/create_graphrag_config.py b/graphrag/config/create_graphrag_config.py
index a750ae840e..42b250088e 100644
--- a/graphrag/config/create_graphrag_config.py
+++ b/graphrag/config/create_graphrag_config.py
@@ -39,6 +39,7 @@
     ClaimExtractionConfig,
     ClusterGraphConfig,
     CommunityReportsConfig,
+    DRIFTSearchConfig,
     EmbedGraphConfig,
     EntityExtractionConfig,
     GlobalSearchConfig,
@@ -514,6 +515,7 @@ def hydrate_parallelization_params(
             reader.envvar_prefix(Section.local_search),
         ):
             local_search_model = LocalSearchConfig(
+                prompt=reader.str("prompt") or None,
                 text_unit_prop=reader.float("text_unit_prop")
                 or defs.LOCAL_SEARCH_TEXT_UNIT_PROP,
                 community_prop=reader.float("community_prop")
@@ -541,6 +543,9 @@ def hydrate_parallelization_params(
             reader.envvar_prefix(Section.global_search),
         ):
             global_search_model = GlobalSearchConfig(
+                map_prompt=reader.str("map_prompt") or None,
+                reduce_prompt=reader.str("reduce_prompt") or None,
+                knowledge_prompt=reader.str("knowledge_prompt") or None,
                 temperature=reader.float("llm_temperature")
                 or defs.GLOBAL_SEARCH_LLM_TEMPERATURE,
                 top_p=reader.float("llm_top_p") or defs.GLOBAL_SEARCH_LLM_TOP_P,
@@ -556,6 +561,54 @@ def hydrate_parallelization_params(
                 concurrency=reader.int("concurrency") or defs.GLOBAL_SEARCH_CONCURRENCY,
             )
 
+        with (
+            reader.use(values.get("drift_search")),
+            reader.envvar_prefix(Section.drift_search),
+        ):
+            drift_search_model = DRIFTSearchConfig(
+                prompt=reader.str("prompt") or None,
+                temperature=reader.float("llm_temperature")
+                or defs.DRIFT_SEARCH_LLM_TEMPERATURE,
+                top_p=reader.float("llm_top_p") or defs.DRIFT_SEARCH_LLM_TOP_P,
+                n=reader.int("llm_n") or defs.DRIFT_SEARCH_LLM_N,
+                max_tokens=reader.int(Fragment.max_tokens)
+                or defs.DRIFT_SEARCH_MAX_TOKENS,
+                data_max_tokens=reader.int("data_max_tokens")
+                or defs.DRIFT_SEARCH_DATA_MAX_TOKENS,
+                concurrency=reader.int("concurrency") or defs.DRIFT_SEARCH_CONCURRENCY,
+                drift_k_followups=reader.int("drift_k_followups")
+                or defs.DRIFT_SEARCH_K_FOLLOW_UPS,
+                primer_folds=reader.int("primer_folds")
+                or defs.DRIFT_SEARCH_PRIMER_FOLDS,
+                primer_llm_max_tokens=reader.int("primer_llm_max_tokens")
+                or defs.DRIFT_SEARCH_PRIMER_MAX_TOKENS,
+                n_depth=reader.int("n_depth") or defs.DRIFT_N_DEPTH,
+                local_search_text_unit_prop=reader.float("local_search_text_unit_prop")
+                or defs.DRIFT_LOCAL_SEARCH_TEXT_UNIT_PROP,
+                local_search_community_prop=reader.float("local_search_community_prop")
+                or defs.DRIFT_LOCAL_SEARCH_COMMUNITY_PROP,
+                local_search_top_k_mapped_entities=reader.int(
+                    "local_search_top_k_mapped_entities"
+                )
+                or defs.DRIFT_LOCAL_SEARCH_TOP_K_MAPPED_ENTITIES,
+                local_search_top_k_relationships=reader.int(
+                    "local_search_top_k_relationships"
+                )
+                or defs.DRIFT_LOCAL_SEARCH_TOP_K_RELATIONSHIPS,
+                local_search_max_data_tokens=reader.int("local_search_max_data_tokens")
+                or defs.DRIFT_LOCAL_SEARCH_MAX_TOKENS,
+                local_search_temperature=reader.float("local_search_temperature")
+                or defs.DRIFT_LOCAL_SEARCH_LLM_TEMPERATURE,
+                local_search_top_p=reader.float("local_search_top_p")
+                or defs.DRIFT_LOCAL_SEARCH_LLM_TOP_P,
+                local_search_n=reader.int("local_search_n")
+                or defs.DRIFT_LOCAL_SEARCH_LLM_N,
+                local_search_llm_max_gen_tokens=reader.int(
+                    "local_search_llm_max_gen_tokens"
+                )
+                or defs.DRIFT_LOCAL_SEARCH_LLM_MAX_TOKENS,
+            )
+
         encoding_model = reader.str(Fragment.encoding_model) or defs.ENCODING_MODEL
         skip_workflows = reader.list("skip_workflows") or []
 
@@ -583,6 +636,7 @@ def hydrate_parallelization_params(
         skip_workflows=skip_workflows,
         local_search=local_search_model,
         global_search=global_search_model,
+        drift_search=drift_search_model,
     )
 
 
@@ -649,6 +703,7 @@ class Section(str, Enum):
     update_index_storage = "UPDATE_INDEX_STORAGE"
     local_search = "LOCAL_SEARCH"
     global_search = "GLOBAL_SEARCH"
+    drift_search = "DRIFT_SEARCH"
 
 
 def _is_azure(llm_type: LLMType | None) -> bool:
diff --git a/graphrag/config/models/drift_config.py b/graphrag/config/models/drift_config.py
index 03b80150a2..7860f60ae6 100644
--- a/graphrag/config/models/drift_config.py
+++ b/graphrag/config/models/drift_config.py
@@ -11,6 +11,9 @@
 class DRIFTSearchConfig(BaseModel):
     """The default configuration section for Cache."""
 
+    prompt: str | None = Field(
+        description="The drift search prompt to use.", default=None
+    )
     temperature: float = Field(
         description="The temperature to use for token generation.",
         default=defs.DRIFT_SEARCH_LLM_TEMPERATURE,
diff --git a/graphrag/config/models/global_search_config.py b/graphrag/config/models/global_search_config.py
index b528d9a0e0..7f2573d402 100644
--- a/graphrag/config/models/global_search_config.py
+++ b/graphrag/config/models/global_search_config.py
@@ -11,6 +11,15 @@
 class GlobalSearchConfig(BaseModel):
     """The default configuration section for Cache."""
 
+    map_prompt: str | None = Field(
+        description="The global search mapper prompt to use.", default=None
+    )
+    reduce_prompt: str | None = Field(
+        description="The global search reducer to use.", default=None
+    )
+    knowledge_prompt: str | None = Field(
+        description="The global search general prompt to use.", default=None
+    )
     temperature: float | None = Field(
         description="The temperature to use for token generation.",
         default=defs.GLOBAL_SEARCH_LLM_TEMPERATURE,
diff --git a/graphrag/config/models/graph_rag_config.py b/graphrag/config/models/graph_rag_config.py
index 4eaf8c284a..35912e12f5 100644
--- a/graphrag/config/models/graph_rag_config.py
+++ b/graphrag/config/models/graph_rag_config.py
@@ -13,6 +13,7 @@
 from .claim_extraction_config import ClaimExtractionConfig
 from .cluster_graph_config import ClusterGraphConfig
 from .community_reports_config import CommunityReportsConfig
+from .drift_config import DRIFTSearchConfig
 from .embed_graph_config import EmbedGraphConfig
 from .entity_extraction_config import EntityExtractionConfig
 from .global_search_config import GlobalSearchConfig
@@ -141,6 +142,11 @@ def __str__(self):
     )
     """The global search configuration."""
 
+    drift_search: DRIFTSearchConfig = Field(
+        description="The drift search configuration.", default=DRIFTSearchConfig()
+    )
+    """The drift search configuration."""
+
     encoding_model: str = Field(
         description="The encoding model to use.", default=defs.ENCODING_MODEL
     )
diff --git a/graphrag/config/models/local_search_config.py b/graphrag/config/models/local_search_config.py
index c41344daef..c3d8e822e4 100644
--- a/graphrag/config/models/local_search_config.py
+++ b/graphrag/config/models/local_search_config.py
@@ -11,6 +11,9 @@
 class LocalSearchConfig(BaseModel):
     """The default configuration section for Cache."""
 
+    prompt: str | None = Field(
+        description="The local search prompt to use.", default=None
+    )
     text_unit_prop: float = Field(
         description="The text unit proportion.",
         default=defs.LOCAL_SEARCH_TEXT_UNIT_PROP,
diff --git a/graphrag/index/graph/extractors/__init__.py b/graphrag/index/graph/extractors/__init__.py
index 9168d5e207..511695aea6 100644
--- a/graphrag/index/graph/extractors/__init__.py
+++ b/graphrag/index/graph/extractors/__init__.py
@@ -3,16 +3,13 @@
 
 """The Indexing Engine graph extractors package root."""
 
-from .claims import CLAIM_EXTRACTION_PROMPT, ClaimExtractor
+from .claims import ClaimExtractor
 from .community_reports import (
-    COMMUNITY_REPORT_PROMPT,
     CommunityReportsExtractor,
 )
 from .graph import GraphExtractionResult, GraphExtractor
 
 __all__ = [
-    "CLAIM_EXTRACTION_PROMPT",
-    "COMMUNITY_REPORT_PROMPT",
     "ClaimExtractor",
     "CommunityReportsExtractor",
     "GraphExtractionResult",
diff --git a/graphrag/index/graph/extractors/claims/__init__.py b/graphrag/index/graph/extractors/claims/__init__.py
index 3977c8ff83..3a5a22fdb1 100644
--- a/graphrag/index/graph/extractors/claims/__init__.py
+++ b/graphrag/index/graph/extractors/claims/__init__.py
@@ -4,6 +4,5 @@
 """The Indexing Engine graph extractors claims package root."""
 
 from .claim_extractor import ClaimExtractor
-from .prompts import CLAIM_EXTRACTION_PROMPT
 
-__all__ = ["CLAIM_EXTRACTION_PROMPT", "ClaimExtractor"]
+__all__ = ["ClaimExtractor"]
diff --git a/graphrag/index/graph/extractors/claims/claim_extractor.py b/graphrag/index/graph/extractors/claims/claim_extractor.py
index a1881abc86..2842ad7e1a 100644
--- a/graphrag/index/graph/extractors/claims/claim_extractor.py
+++ b/graphrag/index/graph/extractors/claims/claim_extractor.py
@@ -13,8 +13,7 @@
 import graphrag.config.defaults as defs
 from graphrag.index.typing import ErrorHandlerFn
 from graphrag.llm import CompletionLLM
-
-from .prompts import (
+from graphrag.prompts.index.claim_extraction import (
     CLAIM_EXTRACTION_PROMPT,
     CONTINUE_PROMPT,
     LOOP_PROMPT,
diff --git a/graphrag/index/graph/extractors/community_reports/__init__.py b/graphrag/index/graph/extractors/community_reports/__init__.py
index 599f56d60f..da3bf8396a 100644
--- a/graphrag/index/graph/extractors/community_reports/__init__.py
+++ b/graphrag/index/graph/extractors/community_reports/__init__.py
@@ -8,7 +8,6 @@
 from .build_mixed_context import build_mixed_context
 from .community_reports_extractor import CommunityReportsExtractor
 from .prep_community_report_context import prep_community_report_context
-from .prompts import COMMUNITY_REPORT_PROMPT
 from .sort_context import sort_context
 from .utils import (
     filter_claims_to_nodes,
@@ -20,7 +19,6 @@
 )
 
 __all__ = [
-    "COMMUNITY_REPORT_PROMPT",
     "CommunityReportsExtractor",
     "build_mixed_context",
     "filter_claims_to_nodes",
diff --git a/graphrag/index/graph/extractors/community_reports/community_reports_extractor.py b/graphrag/index/graph/extractors/community_reports/community_reports_extractor.py
index b54f613144..291e61af69 100644
--- a/graphrag/index/graph/extractors/community_reports/community_reports_extractor.py
+++ b/graphrag/index/graph/extractors/community_reports/community_reports_extractor.py
@@ -11,8 +11,7 @@
 from graphrag.index.typing import ErrorHandlerFn
 from graphrag.index.utils import dict_has_keys_with_types
 from graphrag.llm import CompletionLLM
-
-from .prompts import COMMUNITY_REPORT_PROMPT
+from graphrag.prompts.index.community_report import COMMUNITY_REPORT_PROMPT
 
 log = logging.getLogger(__name__)
 
diff --git a/graphrag/index/graph/extractors/graph/__init__.py b/graphrag/index/graph/extractors/graph/__init__.py
index 94e03ab9f7..7f8d19c9ca 100644
--- a/graphrag/index/graph/extractors/graph/__init__.py
+++ b/graphrag/index/graph/extractors/graph/__init__.py
@@ -8,11 +8,9 @@
     GraphExtractionResult,
     GraphExtractor,
 )
-from .prompts import GRAPH_EXTRACTION_PROMPT
 
 __all__ = [
     "DEFAULT_ENTITY_TYPES",
-    "GRAPH_EXTRACTION_PROMPT",
     "GraphExtractionResult",
     "GraphExtractor",
 ]
diff --git a/graphrag/index/graph/extractors/graph/graph_extractor.py b/graphrag/index/graph/extractors/graph/graph_extractor.py
index 87bd8a4aa6..b669cfa004 100644
--- a/graphrag/index/graph/extractors/graph/graph_extractor.py
+++ b/graphrag/index/graph/extractors/graph/graph_extractor.py
@@ -17,8 +17,11 @@
 from graphrag.index.typing import ErrorHandlerFn
 from graphrag.index.utils import clean_str
 from graphrag.llm import CompletionLLM
-
-from .prompts import CONTINUE_PROMPT, GRAPH_EXTRACTION_PROMPT, LOOP_PROMPT
+from graphrag.prompts.index.entity_extraction import (
+    CONTINUE_PROMPT,
+    GRAPH_EXTRACTION_PROMPT,
+    LOOP_PROMPT,
+)
 
 DEFAULT_TUPLE_DELIMITER = "<|>"
 DEFAULT_RECORD_DELIMITER = "##"
diff --git a/graphrag/index/graph/extractors/summarize/__init__.py b/graphrag/index/graph/extractors/summarize/__init__.py
index b4bfe5be87..17fe5095aa 100644
--- a/graphrag/index/graph/extractors/summarize/__init__.py
+++ b/graphrag/index/graph/extractors/summarize/__init__.py
@@ -7,6 +7,5 @@
     SummarizationResult,
     SummarizeExtractor,
 )
-from .prompts import SUMMARIZE_PROMPT
 
-__all__ = ["SUMMARIZE_PROMPT", "SummarizationResult", "SummarizeExtractor"]
+__all__ = ["SummarizationResult", "SummarizeExtractor"]
diff --git a/graphrag/index/graph/extractors/summarize/description_summary_extractor.py b/graphrag/index/graph/extractors/summarize/description_summary_extractor.py
index 9319dba401..8d845d658e 100644
--- a/graphrag/index/graph/extractors/summarize/description_summary_extractor.py
+++ b/graphrag/index/graph/extractors/summarize/description_summary_extractor.py
@@ -9,8 +9,7 @@
 from graphrag.index.typing import ErrorHandlerFn
 from graphrag.index.utils.tokens import num_tokens_from_string
 from graphrag.llm import CompletionLLM
-
-from .prompts import SUMMARIZE_PROMPT
+from graphrag.prompts.index.summarize_descriptions import SUMMARIZE_PROMPT
 
 # Max token size for input prompts
 DEFAULT_MAX_INPUT_TOKENS = 4_000
diff --git a/graphrag/index/init_content.py b/graphrag/index/init_content.py
index 6db1843dc4..93807672f2 100644
--- a/graphrag/index/init_content.py
+++ b/graphrag/index/init_content.py
@@ -158,6 +158,7 @@
   transient: false
 
 local_search:
+  prompt: "prompts/local_search_system_prompt.txt"
   # text_unit_prop: {defs.LOCAL_SEARCH_TEXT_UNIT_PROP}
   # community_prop: {defs.LOCAL_SEARCH_COMMUNITY_PROP}
   # conversation_history_max_turns: {defs.LOCAL_SEARCH_CONVERSATION_HISTORY_MAX_TURNS}
@@ -169,6 +170,9 @@
   # max_tokens: {defs.LOCAL_SEARCH_MAX_TOKENS}
 
 global_search:
+  map_prompt: "prompts/global_search_map_system_prompt.txt"
+  reduce_prompt: "prompts/global_search_reduce_system_prompt.txt"
+  knowledge_prompt: "prompts/global_search_knowledge_system_prompt.txt"
   # llm_temperature: {defs.GLOBAL_SEARCH_LLM_TEMPERATURE} # temperature for sampling
   # llm_top_p: {defs.GLOBAL_SEARCH_LLM_TOP_P} # top-p sampling
   # llm_n: {defs.GLOBAL_SEARCH_LLM_N} # Number of completions to generate
@@ -177,6 +181,28 @@
   # map_max_tokens: {defs.GLOBAL_SEARCH_MAP_MAX_TOKENS}
   # reduce_max_tokens: {defs.GLOBAL_SEARCH_REDUCE_MAX_TOKENS}
   # concurrency: {defs.GLOBAL_SEARCH_CONCURRENCY}
+
+drift_search:
+  prompt: "prompts/drift_search_system_prompt.txt"
+  # temperature: {defs.DRIFT_SEARCH_LLM_TEMPERATURE}
+  # top_p: {defs.DRIFT_SEARCH_LLM_TOP_P}
+  # n: {defs.DRIFT_SEARCH_LLM_N}
+  # max_tokens: {defs.DRIFT_SEARCH_MAX_TOKENS}
+  # data_max_tokens: {defs.DRIFT_SEARCH_DATA_MAX_TOKENS}
+  # concurrency: {defs.DRIFT_SEARCH_CONCURRENCY}
+  # drift_k_followups: {defs.DRIFT_SEARCH_K_FOLLOW_UPS}
+  # primer_folds: {defs.DRIFT_SEARCH_PRIMER_FOLDS}
+  # primer_llm_max_tokens: {defs.DRIFT_SEARCH_PRIMER_MAX_TOKENS}
+  # n_depth: {defs.DRIFT_N_DEPTH}
+  # local_search_text_unit_prop: {defs.DRIFT_LOCAL_SEARCH_TEXT_UNIT_PROP}
+  # local_search_community_prop: {defs.DRIFT_LOCAL_SEARCH_COMMUNITY_PROP}
+  # local_search_top_k_mapped_entities: {defs.DRIFT_LOCAL_SEARCH_TOP_K_MAPPED_ENTITIES}
+  # local_search_top_k_relationships: {defs.DRIFT_LOCAL_SEARCH_TOP_K_RELATIONSHIPS}
+  # local_search_max_data_tokens: {defs.DRIFT_LOCAL_SEARCH_MAX_TOKENS}
+  # local_search_temperature: {defs.DRIFT_LOCAL_SEARCH_LLM_TEMPERATURE}
+  # local_search_top_p: {defs.DRIFT_LOCAL_SEARCH_LLM_TOP_P}
+  # local_search_n: {defs.DRIFT_LOCAL_SEARCH_LLM_N}
+  # local_search_llm_max_gen_tokens: {defs.DRIFT_LOCAL_SEARCH_LLM_MAX_TOKENS}
 """
 
 INIT_DOTENV = """\
diff --git a/graphrag/prompts/__init__.py b/graphrag/prompts/__init__.py
new file mode 100644
index 0000000000..6a6123b805
--- /dev/null
+++ b/graphrag/prompts/__init__.py
@@ -0,0 +1,4 @@
+# Copyright (c) 2024 Microsoft Corporation.
+# Licensed under the MIT License
+
+"""All prompts for the system."""
diff --git a/graphrag/prompts/index/__init__.py b/graphrag/prompts/index/__init__.py
new file mode 100644
index 0000000000..6377063bb6
--- /dev/null
+++ b/graphrag/prompts/index/__init__.py
@@ -0,0 +1,4 @@
+# Copyright (c) 2024 Microsoft Corporation.
+# Licensed under the MIT License
+
+"""All prompts for indexing."""
diff --git a/graphrag/index/graph/extractors/claims/prompts.py b/graphrag/prompts/index/claim_extraction.py
similarity index 100%
rename from graphrag/index/graph/extractors/claims/prompts.py
rename to graphrag/prompts/index/claim_extraction.py
diff --git a/graphrag/index/graph/extractors/community_reports/prompts.py b/graphrag/prompts/index/community_report.py
similarity index 100%
rename from graphrag/index/graph/extractors/community_reports/prompts.py
rename to graphrag/prompts/index/community_report.py
diff --git a/graphrag/index/graph/extractors/graph/prompts.py b/graphrag/prompts/index/entity_extraction.py
similarity index 100%
rename from graphrag/index/graph/extractors/graph/prompts.py
rename to graphrag/prompts/index/entity_extraction.py
diff --git a/graphrag/index/graph/extractors/summarize/prompts.py b/graphrag/prompts/index/summarize_descriptions.py
similarity index 100%
rename from graphrag/index/graph/extractors/summarize/prompts.py
rename to graphrag/prompts/index/summarize_descriptions.py
diff --git a/graphrag/prompts/query/__init__.py b/graphrag/prompts/query/__init__.py
new file mode 100644
index 0000000000..79ebce00d8
--- /dev/null
+++ b/graphrag/prompts/query/__init__.py
@@ -0,0 +1,4 @@
+# Copyright (c) 2024 Microsoft Corporation.
+# Licensed under the MIT License
+
+"""All prompts for query."""
diff --git a/graphrag/query/structured_search/drift_search/system_prompt.py b/graphrag/prompts/query/drift_search_system_prompt.py
similarity index 100%
rename from graphrag/query/structured_search/drift_search/system_prompt.py
rename to graphrag/prompts/query/drift_search_system_prompt.py
diff --git a/graphrag/prompts/query/global_search_knowledge_system_prompt.py b/graphrag/prompts/query/global_search_knowledge_system_prompt.py
new file mode 100644
index 0000000000..9125ef31f2
--- /dev/null
+++ b/graphrag/prompts/query/global_search_knowledge_system_prompt.py
@@ -0,0 +1,9 @@
+# Copyright (c) 2024 Microsoft Corporation.
+# Licensed under the MIT License
+
+"""Global Search system prompts."""
+
+GENERAL_KNOWLEDGE_INSTRUCTION = """
+The response may also include relevant real-world knowledge outside the dataset, but it must be explicitly annotated with a verification tag [LLM: verify]. For example:
+"This is an example sentence supported by real-world knowledge [LLM: verify]."
+"""
diff --git a/graphrag/query/structured_search/global_search/map_system_prompt.py b/graphrag/prompts/query/global_search_map_system_prompt.py
similarity index 100%
rename from graphrag/query/structured_search/global_search/map_system_prompt.py
rename to graphrag/prompts/query/global_search_map_system_prompt.py
diff --git a/graphrag/query/structured_search/global_search/reduce_system_prompt.py b/graphrag/prompts/query/global_search_reduce_system_prompt.py
similarity index 93%
rename from graphrag/query/structured_search/global_search/reduce_system_prompt.py
rename to graphrag/prompts/query/global_search_reduce_system_prompt.py
index 701717817c..c9dbb9188d 100644
--- a/graphrag/query/structured_search/global_search/reduce_system_prompt.py
+++ b/graphrag/prompts/query/global_search_reduce_system_prompt.py
@@ -81,8 +81,3 @@
 NO_DATA_ANSWER = (
     "I am sorry but I am unable to answer this question given the provided data."
 )
-
-GENERAL_KNOWLEDGE_INSTRUCTION = """
-The response may also include relevant real-world knowledge outside the dataset, but it must be explicitly annotated with a verification tag [LLM: verify]. For example:
-"This is an example sentence supported by real-world knowledge [LLM: verify]."
-"""
diff --git a/graphrag/query/structured_search/local_search/system_prompt.py b/graphrag/prompts/query/local_search_system_prompt.py
similarity index 100%
rename from graphrag/query/structured_search/local_search/system_prompt.py
rename to graphrag/prompts/query/local_search_system_prompt.py
diff --git a/graphrag/query/question_gen/system_prompt.py b/graphrag/prompts/query/question_gen_system_prompt.py
similarity index 100%
rename from graphrag/query/question_gen/system_prompt.py
rename to graphrag/prompts/query/question_gen_system_prompt.py
diff --git a/graphrag/query/factories.py b/graphrag/query/factories.py
index 3ba411f1ee..2e8a3afd4d 100644
--- a/graphrag/query/factories.py
+++ b/graphrag/query/factories.py
@@ -42,6 +42,7 @@ def get_local_search_engine(
     covariates: dict[str, list[Covariate]],
     response_type: str,
     description_embedding_store: BaseVectorStore,
+    system_prompt: str | None = None,
 ) -> LocalSearch:
     """Create a local search engine based on data + configuration."""
     llm = get_llm(config)
@@ -52,6 +53,7 @@ def get_local_search_engine(
 
     return LocalSearch(
         llm=llm,
+        system_prompt=system_prompt,
         context_builder=LocalSearchMixedContext(
             community_reports=reports,
             text_units=text_units,
@@ -95,6 +97,9 @@ def get_global_search_engine(
     communities: list[Community],
     response_type: str,
     dynamic_community_selection: bool = False,
+    map_system_prompt: str | None = None,
+    reduce_system_prompt: str | None = None,
+    general_knowledge_inclusion_prompt: str | None = None,
 ) -> GlobalSearch:
     """Create a global search engine based on data + configuration."""
     token_encoder = tiktoken.get_encoding(config.encoding_model)
@@ -118,6 +123,9 @@ def get_global_search_engine(
 
     return GlobalSearch(
         llm=get_llm(config),
+        map_system_prompt=map_system_prompt,
+        reduce_system_prompt=reduce_system_prompt,
+        general_knowledge_inclusion_prompt=general_knowledge_inclusion_prompt,
         context_builder=GlobalCommunityContext(
             community_reports=reports,
             communities=communities,
@@ -166,6 +174,7 @@ def get_drift_search_engine(
     entities: list[Entity],
     relationships: list[Relationship],
     description_embedding_store: BaseVectorStore,
+    local_system_prompt: str | None = None,
 ) -> DRIFTSearch:
     """Create a local search engine based on data + configuration."""
     llm = get_llm(config)
@@ -182,6 +191,8 @@ def get_drift_search_engine(
             reports=reports,
             entity_text_embeddings=description_embedding_store,
             text_units=text_units,
+            local_system_prompt=local_system_prompt,
+            config=config.drift_search,
         ),
         token_encoder=token_encoder,
     )
diff --git a/graphrag/query/question_gen/local_gen.py b/graphrag/query/question_gen/local_gen.py
index ca703a66e3..5372d4cf43 100644
--- a/graphrag/query/question_gen/local_gen.py
+++ b/graphrag/query/question_gen/local_gen.py
@@ -9,6 +9,7 @@
 
 import tiktoken
 
+from graphrag.prompts.query.question_gen_system_prompt import QUESTION_SYSTEM_PROMPT
 from graphrag.query.context_builder.builders import LocalContextBuilder
 from graphrag.query.context_builder.conversation_history import (
     ConversationHistory,
@@ -16,7 +17,6 @@
 from graphrag.query.llm.base import BaseLLM, BaseLLMCallback
 from graphrag.query.llm.text_utils import num_tokens
 from graphrag.query.question_gen.base import BaseQuestionGen, QuestionResult
-from graphrag.query.question_gen.system_prompt import QUESTION_SYSTEM_PROMPT
 
 log = logging.getLogger(__name__)
 
diff --git a/graphrag/query/structured_search/drift_search/drift_context.py b/graphrag/query/structured_search/drift_search/drift_context.py
index 64422e3760..d2a271bdac 100644
--- a/graphrag/query/structured_search/drift_search/drift_context.py
+++ b/graphrag/query/structured_search/drift_search/drift_context.py
@@ -19,14 +19,14 @@
     Relationship,
     TextUnit,
 )
+from graphrag.prompts.query.drift_search_system_prompt import (
+    DRIFT_LOCAL_SYSTEM_PROMPT,
+)
 from graphrag.query.context_builder.entity_extraction import EntityVectorStoreKey
 from graphrag.query.llm.base import BaseTextEmbedding
 from graphrag.query.llm.oai.chat_openai import ChatOpenAI
 from graphrag.query.structured_search.base import DRIFTContextBuilder
 from graphrag.query.structured_search.drift_search.primer import PrimerQueryProcessor
-from graphrag.query.structured_search.drift_search.system_prompt import (
-    DRIFT_LOCAL_SYSTEM_PROMPT,
-)
 from graphrag.query.structured_search.local_search.mixed_context import (
     LocalSearchMixedContext,
 )
@@ -51,7 +51,7 @@ def __init__(
         token_encoder: tiktoken.Encoding | None = None,
         embedding_vectorstore_key: str = EntityVectorStoreKey.ID,
         config: DRIFTSearchConfig | None = None,
-        local_system_prompt: str = DRIFT_LOCAL_SYSTEM_PROMPT,
+        local_system_prompt: str | None = None,
         local_mixed_context: LocalSearchMixedContext | None = None,
     ):
         """Initialize the DRIFT search context builder with necessary components."""
@@ -59,7 +59,7 @@ def __init__(
         self.chat_llm = chat_llm
         self.text_embedder = text_embedder
         self.token_encoder = token_encoder
-        self.local_system_prompt = local_system_prompt
+        self.local_system_prompt = local_system_prompt or DRIFT_LOCAL_SYSTEM_PROMPT
 
         self.entities = entities
         self.entity_text_embeddings = entity_text_embeddings
diff --git a/graphrag/query/structured_search/drift_search/primer.py b/graphrag/query/structured_search/drift_search/primer.py
index 47c8b1e2fe..b3d2b26891 100644
--- a/graphrag/query/structured_search/drift_search/primer.py
+++ b/graphrag/query/structured_search/drift_search/primer.py
@@ -15,13 +15,13 @@
 
 from graphrag.config.models.drift_config import DRIFTSearchConfig
 from graphrag.model import CommunityReport
+from graphrag.prompts.query.drift_search_system_prompt import (
+    DRIFT_PRIMER_PROMPT,
+)
 from graphrag.query.llm.base import BaseTextEmbedding
 from graphrag.query.llm.oai.chat_openai import ChatOpenAI
 from graphrag.query.llm.text_utils import num_tokens
 from graphrag.query.structured_search.base import SearchResult
-from graphrag.query.structured_search.drift_search.system_prompt import (
-    DRIFT_PRIMER_PROMPT,
-)
 
 log = logging.getLogger(__name__)
 
diff --git a/graphrag/query/structured_search/global_search/search.py b/graphrag/query/structured_search/global_search/search.py
index 530ea39d6b..6202603dfd 100644
--- a/graphrag/query/structured_search/global_search/search.py
+++ b/graphrag/query/structured_search/global_search/search.py
@@ -16,6 +16,16 @@
 
 from graphrag.callbacks.global_search_callbacks import GlobalSearchLLMCallback
 from graphrag.llm.openai.utils import try_parse_json_object
+from graphrag.prompts.query.global_search_knowledge_system_prompt import (
+    GENERAL_KNOWLEDGE_INSTRUCTION,
+)
+from graphrag.prompts.query.global_search_map_system_prompt import (
+    MAP_SYSTEM_PROMPT,
+)
+from graphrag.prompts.query.global_search_reduce_system_prompt import (
+    NO_DATA_ANSWER,
+    REDUCE_SYSTEM_PROMPT,
+)
 from graphrag.query.context_builder.builders import GlobalContextBuilder
 from graphrag.query.context_builder.conversation_history import (
     ConversationHistory,
@@ -23,14 +33,6 @@
 from graphrag.query.llm.base import BaseLLM
 from graphrag.query.llm.text_utils import num_tokens
 from graphrag.query.structured_search.base import BaseSearch, SearchResult
-from graphrag.query.structured_search.global_search.map_system_prompt import (
-    MAP_SYSTEM_PROMPT,
-)
-from graphrag.query.structured_search.global_search.reduce_system_prompt import (
-    GENERAL_KNOWLEDGE_INSTRUCTION,
-    NO_DATA_ANSWER,
-    REDUCE_SYSTEM_PROMPT,
-)
 
 DEFAULT_MAP_LLM_PARAMS = {
     "max_tokens": 1000,
@@ -62,11 +64,11 @@ def __init__(
         llm: BaseLLM,
         context_builder: GlobalContextBuilder,
         token_encoder: tiktoken.Encoding | None = None,
-        map_system_prompt: str = MAP_SYSTEM_PROMPT,
-        reduce_system_prompt: str = REDUCE_SYSTEM_PROMPT,
+        map_system_prompt: str | None = None,
+        reduce_system_prompt: str | None = None,
         response_type: str = "multiple paragraphs",
         allow_general_knowledge: bool = False,
-        general_knowledge_inclusion_prompt: str = GENERAL_KNOWLEDGE_INSTRUCTION,
+        general_knowledge_inclusion_prompt: str | None = None,
         json_mode: bool = True,
         callbacks: list[GlobalSearchLLMCallback] | None = None,
         max_data_tokens: int = 8000,
@@ -81,11 +83,13 @@ def __init__(
             token_encoder=token_encoder,
             context_builder_params=context_builder_params,
         )
-        self.map_system_prompt = map_system_prompt
-        self.reduce_system_prompt = reduce_system_prompt
+        self.map_system_prompt = map_system_prompt or MAP_SYSTEM_PROMPT
+        self.reduce_system_prompt = reduce_system_prompt or REDUCE_SYSTEM_PROMPT
         self.response_type = response_type
         self.allow_general_knowledge = allow_general_knowledge
-        self.general_knowledge_inclusion_prompt = general_knowledge_inclusion_prompt
+        self.general_knowledge_inclusion_prompt = (
+            general_knowledge_inclusion_prompt or GENERAL_KNOWLEDGE_INSTRUCTION
+        )
         self.callbacks = callbacks
         self.max_data_tokens = max_data_tokens
 
diff --git a/graphrag/query/structured_search/local_search/search.py b/graphrag/query/structured_search/local_search/search.py
index 1ce736027e..1e29bde759 100644
--- a/graphrag/query/structured_search/local_search/search.py
+++ b/graphrag/query/structured_search/local_search/search.py
@@ -10,6 +10,9 @@
 
 import tiktoken
 
+from graphrag.prompts.query.local_search_system_prompt import (
+    LOCAL_SEARCH_SYSTEM_PROMPT,
+)
 from graphrag.query.context_builder.builders import LocalContextBuilder
 from graphrag.query.context_builder.conversation_history import (
     ConversationHistory,
@@ -17,9 +20,6 @@
 from graphrag.query.llm.base import BaseLLM, BaseLLMCallback
 from graphrag.query.llm.text_utils import num_tokens
 from graphrag.query.structured_search.base import BaseSearch, SearchResult
-from graphrag.query.structured_search.local_search.system_prompt import (
-    LOCAL_SEARCH_SYSTEM_PROMPT,
-)
 
 DEFAULT_LLM_PARAMS = {
     "max_tokens": 1500,
@@ -37,7 +37,7 @@ def __init__(
         llm: BaseLLM,
         context_builder: LocalContextBuilder,
         token_encoder: tiktoken.Encoding | None = None,
-        system_prompt: str = LOCAL_SEARCH_SYSTEM_PROMPT,
+        system_prompt: str | None = None,
         response_type: str = "multiple paragraphs",
         callbacks: list[BaseLLMCallback] | None = None,
         llm_params: dict[str, Any] = DEFAULT_LLM_PARAMS,
@@ -50,7 +50,7 @@ def __init__(
             llm_params=llm_params,
             context_builder_params=context_builder_params or {},
         )
-        self.system_prompt = system_prompt
+        self.system_prompt = system_prompt or LOCAL_SEARCH_SYSTEM_PROMPT
         self.callbacks = callbacks
         self.response_type = response_type
 
diff --git a/tests/unit/config/test_default_config.py b/tests/unit/config/test_default_config.py
index 7b5ca7db22..6e57ce3bb8 100644
--- a/tests/unit/config/test_default_config.py
+++ b/tests/unit/config/test_default_config.py
@@ -28,6 +28,7 @@
     ClusterGraphConfigInput,
     CommunityReportsConfig,
     CommunityReportsConfigInput,
+    DRIFTSearchConfig,
     EmbedGraphConfig,
     EmbedGraphConfigInput,
     EntityExtractionConfig,
@@ -202,6 +203,7 @@ def test_clear_warnings(self):
         assert ClaimExtractionConfig is not None
         assert ClusterGraphConfig is not None
         assert CommunityReportsConfig is not None
+        assert DRIFTSearchConfig is not None
         assert EmbedGraphConfig is not None
         assert EntityExtractionConfig is not None
         assert GlobalSearchConfig is not None