NIT: Instead of hardcoding k in each definition, define it as a param above. (#2675)

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
Co-authored-by: Davis Chase <130488702+dev2049@users.noreply.github.com>

langchain/vectorstores/chroma.py

@@ -17,7 +17,8 @@ if TYPE_CHECKING:
     import chromadb
     import chromadb.config
 
-logger = logging.getLogger(__name__)
+logger = logging.getLogger()
+DEFAULT_K = 4  # Number of Documents to return.
 
 
 def _results_to_docs(results: Any) -> List[Document]:
@@ -164,7 +165,7 @@ class Chroma(VectorStore):
     def similarity_search(
         self,
         query: str,
-        k: int = 4,
+        k: int = DEFAULT_K,
         filter: Optional[Dict[str, str]] = None,
         **kwargs: Any,
     ) -> List[Document]:
@@ -184,7 +185,7 @@ class Chroma(VectorStore):
     def similarity_search_by_vector(
         self,
         embedding: List[float],
-        k: int = 4,
+        k: int = DEFAULT_K,
         filter: Optional[Dict[str, str]] = None,
         **kwargs: Any,
     ) -> List[Document]:
@@ -204,7 +205,7 @@ class Chroma(VectorStore):
     def similarity_search_with_score(
         self,
         query: str,
-        k: int = 4,
+        k: int = DEFAULT_K,
         filter: Optional[Dict[str, str]] = None,
         **kwargs: Any,
     ) -> List[Tuple[Document, float]]:
@@ -234,7 +235,7 @@ class Chroma(VectorStore):
     def max_marginal_relevance_search_by_vector(
         self,
         embedding: List[float],
-        k: int = 4,
+        k: int = DEFAULT_K,
         fetch_k: int = 20,
         lambda_mult: float = 0.5,
         filter: Optional[Dict[str, str]] = None,
@@ -277,7 +278,7 @@ class Chroma(VectorStore):
     def max_marginal_relevance_search(
         self,
         query: str,
-        k: int = 4,
+        k: int = DEFAULT_K,
         fetch_k: int = 20,
         lambda_mult: float = 0.5,
         filter: Optional[Dict[str, str]] = None,