bump version to 0.30.0pre5 and enhance docstring for resolve_extracted_edge function

- Update version in pyproject.toml to 0.30.0pre5.
- Add detailed docstring to resolve_extracted_edge function in edge_operations.py, clarifying parameters and return values.

This update improves documentation clarity for the edge resolution process.

graphiti_core/utils/maintenance/edge_operations.py

@@ -417,6 +417,34 @@ async def resolve_extracted_edge(
     custom_edge_type_names: set[str] | None = None,
     ensure_ascii: bool = True,
 ) -> tuple[EntityEdge, list[EntityEdge], list[EntityEdge]]:
+    """Resolve an extracted edge against existing graph context.
+
+    Parameters
+    ----------
+    llm_client : LLMClient
+        Client used to invoke the LLM for deduplication and attribute extraction.
+    extracted_edge : EntityEdge
+        Newly extracted edge whose canonical representation is being resolved.
+    related_edges : list[EntityEdge]
+        Candidate edges with identical endpoints used for duplicate detection.
+    existing_edges : list[EntityEdge]
+        Broader set of edges evaluated for contradiction / invalidation.
+    episode : EpisodicNode
+        Episode providing content context when extracting edge attributes.
+    edge_type_candidates : dict[str, type[BaseModel]] | None
+        Custom edge types permitted for the current source/target signature.
+    custom_edge_type_names : set[str] | None
+        Full catalog of registered custom edge names. Used to distinguish
+        between disallowed custom types (which fall back to the default label)
+        and ad-hoc labels emitted by the LLM.
+    ensure_ascii : bool
+        Whether prompt payloads should coerce ASCII output.
+
+    Returns
+    -------
+    tuple[EntityEdge, list[EntityEdge], list[EntityEdge]]
+        The resolved edge, any duplicates, and edges to invalidate.
+    """
     if len(related_edges) == 0 and len(existing_edges) == 0:
         return extracted_edge, [], []
 
@@ -493,7 +521,11 @@ async def resolve_extracted_edge(
     candidate_type_names = set(edge_type_candidates or {})
     custom_type_names = custom_edge_type_names or set()
 
-    if candidate_type_names and fact_type in candidate_type_names:
+    is_default_type = fact_type.upper() == 'DEFAULT'
+    is_custom_type = fact_type in custom_type_names
+    is_allowed_custom_type = fact_type in candidate_type_names
+
+    if is_allowed_custom_type:
         # The LLM selected a custom type that is allowed for the node pair.
         # Adopt the custom type and, if needed, extract its structured attributes.
         resolved_edge.name = fact_type
@@ -514,12 +546,12 @@ async def resolve_extracted_edge(
             )
 
             resolved_edge.attributes = edge_attributes_response
-    elif fact_type.upper() != 'DEFAULT' and fact_type in custom_type_names:
+    elif not is_default_type and is_custom_type:
         # The LLM picked a custom type that is not allowed for this signature.
         # Reset to the default label and drop any structured attributes.
         resolved_edge.name = DEFAULT_EDGE_NAME
         resolved_edge.attributes = {}
-    elif fact_type.upper() != 'DEFAULT':
+    elif not is_default_type:
         # Non-custom labels are allowed to pass through so long as the LLM does
         # not return the sentinel DEFAULT value.
         resolved_edge.name = fact_type

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "graphiti-core"
 description = "A temporal graph building library"
-version = "0.30.0pre4"
+version = "0.30.0pre5"
 authors = [
     { name = "Paul Paliychuk", email = "paul@getzep.com" },
     { name = "Preston Rasmussen", email = "preston@getzep.com" },