community: creation score_threshold in flashrank_rerank.py (#24016)

Description: 
add a optional score relevance threshold for select only coherent
document, it's in complement of top_n

Discussion:
add relevance score threshold in flashrank_rerank document compressors
#24013

Dependencies:
 no dependencies

---------

Co-authored-by: Benjamin BERNARD <[email protected]>
Co-authored-by: Bagatur <[email protected]>
Co-authored-by: Chester Curme <[email protected]>

libs/community/langchain_community/document_compressors/flashrank_rerank.py

@@ -26,8 +26,12 @@ class FlashrankRerank(BaseDocumentCompressor):
     """Flashrank client to use for compressing documents"""
     top_n: int = 3
     """Number of documents to return."""
+    score_threshold: float = 0.0
+    """Minimum relevance threshold to return."""
     model: Optional[str] = None
     """Model to use for reranking."""
+    prefix_metadata: str = ""
+    """Prefix for flashrank_rerank metadata keys"""
 
     class Config:
         """Configuration for this pydantic object."""
@@ -69,11 +73,14 @@ def compress_documents(
         final_results = []
 
         for r in rerank_response:
-            metadata = r["meta"]
-            metadata["relevance_score"] = r["score"]
-            doc = Document(
-                page_content=r["text"],
-                metadata=metadata,
-            )
-            final_results.append(doc)
+            if r["score"] >= self.score_threshold:
+                doc = Document(
+                    page_content=r["text"],
+                    metadata={
+                        self.prefix_metadata + "id": r["id"],
+                        self.prefix_metadata + "relevance_score": r["score"],
+                        **r["meta"],
+                    },
+                )
+                final_results.append(doc)
         return final_results