Refactor config defaults (microsoft#1723)

* Refactor config defaults

- Implement type-safe, hierarchical dataclass for config
defaults instead of namespaced constants.
- Allow for instantiating config directly from defaults data structure.

* fix vector_store db_uri default

---------

Co-authored-by: Alonso Guevara <[email protected]>

Author: dworthen

.semversioner/next-release/patch-20250219182755748457.json

@@ -0,0 +1,4 @@
+{
+  "type": "patch",
+  "description": "Refactor config defaults from constants to type-safe, hierarchical dataclass."
+}

graphrag/api/prompt_tune.py

@@ -13,8 +13,8 @@
 
 from pydantic import PositiveInt, validate_call
 
-import graphrag.config.defaults as defs
 from graphrag.callbacks.noop_workflow_callbacks import NoopWorkflowCallbacks
+from graphrag.config.defaults import language_model_defaults
 from graphrag.config.models.graph_rag_config import GraphRagConfig
 from graphrag.language_model.manager import ModelManager
 from graphrag.logger.print_progress import PrintProgressLogger
@@ -102,7 +102,9 @@ async def generate_indexing_prompts(
     # 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)
+        default_llm_settings.max_retries = min(
+            len(doc_list), language_model_defaults.max_retries
+        )
 
     llm = ModelManager().register_chat(
         name="prompt_tuning",