add rerank params

litellm/llms/cohere/rerank.py

@@ -4,6 +4,8 @@ Re rank api
 LiteLLM supports the re rank API format, no paramter transformation occurs
 """
 
+from typing import Any, Dict, List, Optional, Union
+
 import httpx
 from pydantic import BaseModel
 
@@ -21,14 +23,26 @@ class CohereRerank(BaseLLM):
         model: str,
         api_key: str,
         query: str,
-        documents: list[str],
+        documents: list[Union[str, Dict[str, Any]]],
-        top_n: int = 3,
+        top_n: Optional[int] = None,
+        rank_fields: Optional[List[str]] = None,
+        return_documents: Optional[bool] = True,
+        max_chunks_per_doc: Optional[int] = None,
     ) -> RerankResponse:
         client = _get_httpx_client()
+
         request_data = RerankRequest(
-            model=model, query=query, top_n=top_n, documents=documents
+            model=model,
+            query=query,
+            top_n=top_n,
+            documents=documents,
+            rank_fields=rank_fields,
+            return_documents=return_documents,
+            max_chunks_per_doc=max_chunks_per_doc,
         )
 
+        request_data_dict = request_data.dict(exclude_none=True)
+
         response = client.post(
             "https://api.cohere.com/v1/rerank",
             headers={
@@ -36,7 +50,7 @@ class CohereRerank(BaseLLM):
                 "content-type": "application/json",
                 "Authorization": f"bearer {api_key}",
             },
-            json=request_data.dict(),
+            json=request_data_dict,
         )
 
         return RerankResponse(**response.json())

litellm/llms/togetherai/rerank.py

@@ -4,6 +4,8 @@ Re rank api
 LiteLLM supports the re rank API format, no paramter transformation occurs
 """
 
+from typing import Any, Dict, List, Optional, Union
+
 import httpx
 from pydantic import BaseModel
 
@@ -21,15 +23,28 @@ class TogetherAIRerank(BaseLLM):
         model: str,
         api_key: str,
         query: str,
-        documents: list[str],
+        documents: list[Union[str, Dict[str, Any]]],
-        top_n: int = 3,
+        top_n: Optional[int] = None,
+        rank_fields: Optional[List[str]] = None,
+        return_documents: Optional[bool] = True,
+        max_chunks_per_doc: Optional[int] = None,
     ) -> RerankResponse:
         client = _get_httpx_client()
 
         request_data = RerankRequest(
-            model=model, query=query, top_n=top_n, documents=documents
+            model=model,
+            query=query,
+            top_n=top_n,
+            documents=documents,
+            rank_fields=rank_fields,
+            return_documents=return_documents,
         )
 
+        # exclude None values from request_data
+        request_data_dict = request_data.dict(exclude_none=True)
+        if max_chunks_per_doc is not None:
+            raise ValueError("TogetherAI does not support max_chunks_per_doc")
+
         response = client.post(
             "https://api.together.xyz/v1/rerank",
             headers={
@@ -37,10 +52,14 @@ class TogetherAIRerank(BaseLLM):
                 "content-type": "application/json",
                 "authorization": f"Bearer {api_key}",
             },
-            json=request_data.dict(),
+            json=request_data_dict,
         )
 
+        if response.status_code != 200:
+            raise Exception(response.text)
+
         _json_response = response.json()
+
         response = RerankResponse(
             id=_json_response.get("id"),
             results=_json_response.get("results"),

litellm/rerank_api/main.py

@@ -55,9 +55,12 @@ async def arerank(
 def rerank(
     model: str,
     query: str,
-    documents: List[str],
+    documents: List[Union[str, Dict[str, Any]]],
     custom_llm_provider: Optional[Literal["cohere", "together_ai"]] = None,
-    top_n: int = 3,
+    top_n: Optional[int] = None,
+    rank_fields: Optional[List[str]] = None,
+    return_documents: Optional[bool] = True,
+    max_chunks_per_doc: Optional[int] = None,
     **kwargs,
 ) -> Union[RerankResponse, Coroutine[Any, Any, RerankResponse]]:
     """
@@ -107,6 +110,9 @@ def rerank(
                 query=query,
                 documents=documents,
                 top_n=top_n,
+                rank_fields=rank_fields,
+                return_documents=return_documents,
+                max_chunks_per_doc=max_chunks_per_doc,
                 api_key=cohere_key,
             )
             pass
@@ -130,6 +136,9 @@ def rerank(
                 query=query,
                 documents=documents,
                 top_n=top_n,
+                rank_fields=rank_fields,
+                return_documents=return_documents,
+                max_chunks_per_doc=max_chunks_per_doc,
                 api_key=together_key,
             )
 

litellm/rerank_api/types.py

@@ -4,17 +4,22 @@ https://docs.cohere.com/reference/rerank
 
 """
 
+from typing import List, Optional, Union
+
 from pydantic import BaseModel
 
 
 class RerankRequest(BaseModel):
     model: str
     query: str
-    top_n: int
+    top_n: Optional[int] = None
-    documents: list[str]
+    documents: List[Union[str, dict]]
+    rank_fields: Optional[List[str]] = None
+    return_documents: Optional[bool] = None
+    max_chunks_per_doc: Optional[int] = None
 
 
 class RerankResponse(BaseModel):
     id: str
-    results: list[dict]  # Contains index and relevance_score
+    results: List[dict]  # Contains index and relevance_score
     meta: dict  # Contains api_version and billed_units