Added reranking via model_gateway class

backend/Dockerfile

@@ -33,12 +33,12 @@ RUN if [ "${ADD_VECTORDB}" = "1" ]; then python3 -m pip install --use-pep517 --n
 ARG ADD_PRISMA=0
 RUN if [ "${ADD_PRISMA}" = "1" ]; then prisma version; fi
 
-# TODO (chiragjn): These should be removed from here and directly added as environment variables
-# Temporary addition until templates have been updated using build args as environment variables
-ARG ADD_RERANKER_SVC_URL=""
-ENV RERANKER_SVC_URL=${ADD_RERANKER_SVC_URL}
-ARG ADD_EMBEDDING_SVC_URL=""
-ENV EMBEDDING_SVC_URL=${ADD_EMBEDDING_SVC_URL}
+# TODO: Remove these when templates inject env vars
+ARG MODELS_CONFIG_PATH
+ENV MODELS_CONFIG_PATH=${MODELS_CONFIG_PATH}
+
+ARG INFINITY_API_KEY
+ENV INFINITY_API_KEY=${INFINITY_API_KEY}
 
 # Copy the project files
 COPY . /app

backend/modules/model_gateway/model_gateway.py

@@ -11,6 +11,8 @@
 from backend.settings import settings
 from backend.types import ModelConfig, ModelProviderConfig, ModelType
 
+from .reranker_svc import InfinityRerankerSvc
+
 
 class ModelGateway:
     provider_configs: List[ModelProviderConfig]
@@ -20,8 +22,9 @@ def __init__(self):
         logger.info(f"Loading models config from {settings.MODELS_CONFIG_PATH}")
         with open(settings.MODELS_CONFIG_PATH) as f:
             data = yaml.safe_load(f)
-        print(data)
+        logger.info(f"Loaded models config: {data}")
         _providers = data.get("model_providers") or []
+
         # parse the json data into a list of ModelProviderConfig objects
         self.provider_configs = [
             ModelProviderConfig.parse_obj(item) for item in _providers
@@ -32,6 +35,9 @@ def __init__(self):
         # load embedding models
         self.embedding_models: List[ModelConfig] = []
 
+        # load reranker models
+        self.reranker_models: List[ModelConfig] = []
+
         for provider_config in self.provider_configs:
             if provider_config.api_key_env_var and not os.environ.get(
                 provider_config.api_key_env_var
@@ -65,12 +71,27 @@ def __init__(self):
                     )
                 )
 
+            for model_id in provider_config.reranking_model_ids:
+                model_name = f"{provider_config.provider_name}/{model_id}"
+                self.model_name_to_provider_config[model_name] = provider_config
+
+                # Register the model as a reranker model
+                self.reranker_models.append(
+                    ModelConfig(
+                        name=f"{provider_config.provider_name}/{model_id}",
+                        type=ModelType.reranking,
+                    )
+                )
+
     def get_embedding_models(self) -> List[ModelConfig]:
         return self.embedding_models
 
     def get_llm_models(self) -> List[ModelConfig]:
         return self.llm_models
 
+    def get_reranker_models(self) -> List[ModelConfig]:
+        return self.reranker_models
+
     def get_embedder_from_model_config(self, model_name: str) -> Embeddings:
         if model_name not in self.model_name_to_provider_config:
             raise ValueError(f"Model {model_name} not registered in the model gateway.")
@@ -116,5 +137,25 @@ def get_llm_from_model_config(
             base_url=model_provider_config.base_url,
         )
 
+    def get_reranker_from_model_config(self, model_name: str, top_k: int = 3):
+        if model_name not in self.model_name_to_provider_config:
+            raise ValueError(f"Model {model_name} not registered in the model gateway.")
+
+        model_provider_config: ModelProviderConfig = self.model_name_to_provider_config[
+            model_name
+        ]
+        if not model_provider_config.api_key_env_var:
+            api_key = "EMPTY"
+        else:
+            api_key = os.environ.get(model_provider_config.api_key_env_var, "")
+        model_id = "/".join(model_name.split("/")[1:])
+
+        return InfinityRerankerSvc(
+            model=model_id,
+            api_key=api_key,
+            base_url=model_provider_config.base_url,
+            top_k=top_k,
+        )
+
 
 model_gateway = ModelGateway()

backend/modules/rerankers/reranker_svc.py → backend/modules/model_gateway/reranker_svc.py

@@ -17,8 +17,9 @@ class InfinityRerankerSvc(BaseDocumentCompressor):
     """
 
     model: str
-    top_k: int = 3
-    url = settings.RERANKER_SVC_URL
+    top_k: int
+    base_url: str
+    api_key: str
 
     def compress_documents(
         self,
@@ -36,8 +37,13 @@ def compress_documents(
             "model": self.model,
         }
 
+        headers = {
+            "Authorization": f"Bearer {settings.INFINITY_API_KEY}",
+            "Content-Type": "application/json",
+        }
+
         reranked_docs = requests.post(
-            self.url.rstrip("/") + "/rerank", json=payload
+            self.base_url.rstrip("/") + "/rerank", headers=headers, json=payload
         ).json()
 
         """

backend/modules/query_controllers/__init__.py

@@ -4,5 +4,5 @@
 )
 from backend.modules.query_controllers.query_controller import register_query_controller
 
-register_query_controller("default", BasicRAGQueryController)
+register_query_controller("basic-rag", BasicRAGQueryController)
 register_query_controller("multimodal", MultiModalRAGQueryController)

backend/modules/query_controllers/example/controller.py

@@ -22,28 +22,18 @@
     GENERATION_TIMEOUT_SEC,
     ExampleQueryInput,
 )
-from backend.modules.rerankers.reranker_svc import InfinityRerankerSvc
+
+# from backend.modules.rerankers.reranker_svc import InfinityRerankerSvc
 from backend.modules.vector_db.client import VECTOR_STORE_CLIENT
 from backend.server.decorators import post, query_controller
-from backend.settings import settings
 from backend.types import Collection, ModelConfig
 
 EXAMPLES = {
     "vector-store-similarity": QUERY_WITH_VECTOR_STORE_RETRIEVER_PAYLOAD,
+    "contextual-compression-similarity": QUERY_WITH_CONTEXTUAL_COMPRESSION_RETRIEVER_PAYLOAD,
+    "contextual-compression-multi-query-similarity": QUERY_WITH_CONTEXTUAL_COMPRESSION_MULTI_QUERY_RETRIEVER_SIMILARITY_PAYLOAD,
 }
 
-if settings.RERANKER_SVC_URL:
-    EXAMPLES.update(
-        {
-            "contextual-compression-similarity": QUERY_WITH_CONTEXTUAL_COMPRESSION_RETRIEVER_PAYLOAD,
-        }
-    )
-    EXAMPLES.update(
-        {
-            "contextual-compression-multi-query-similarity": QUERY_WITH_CONTEXTUAL_COMPRESSION_MULTI_QUERY_RETRIEVER_SIMILARITY_PAYLOAD,
-        }
-    )
-
 
 @query_controller("/basic-rag")
 class BasicRAGQueryController:
@@ -111,26 +101,18 @@ def _get_contextual_compression_retriever(self, vector_store, retriever_config):
         Get the contextual compression retriever
         """
         try:
-            if settings.RERANKER_SVC_URL:
-                retriever = self._get_vector_store_retriever(
-                    vector_store, retriever_config
-                )
-                logger.info("Using MxBaiRerankerSmall th' service...")
-                compressor = InfinityRerankerSvc(
-                    top_k=retriever_config.top_k,
-                    model=retriever_config.compressor_model_name,
-                )
+            retriever = self._get_vector_store_retriever(vector_store, retriever_config)
+            logger.info("Using MxBaiRerankerSmall th' service...")
 
-                compression_retriever = ContextualCompressionRetriever(
-                    base_compressor=compressor, base_retriever=retriever
-                )
+            compressor = model_gateway.get_reranker_from_model_config(
+                model_name=retriever_config.compressor_model_name,
+                top_k=retriever_config.top_k,
+            )
+            compression_retriever = ContextualCompressionRetriever(
+                base_compressor=compressor, base_retriever=retriever
+            )
 
-                return compression_retriever
-            else:
-                raise HTTPException(
-                    status_code=500,
-                    detail="Reranker service is not available",
-                )
+            return compression_retriever
         except Exception as e:
             logger.error(f"Error in getting contextual compression retriever: {e}")
             raise HTTPException(

backend/modules/query_controllers/example/payload.py

@@ -84,8 +84,7 @@
     "prompt_template": PROMPT,
     "retriever_name": "contextual-compression",
     "retriever_config": {
-        "compressor_model_provider": "mixedbread-ai",
-        "compressor_model_name": "mixedbread-ai/mxbai-rerank-xsmall-v1",
+        "compressor_model_name": "local-infinity/mixedbread-ai/mxbai-rerank-xsmall-v1",
         "top_k": 5,
         "search_type": "similarity",
         "search_kwargs": {"k": 10},
@@ -113,8 +112,7 @@
     "prompt_template": PROMPT,
     "retriever_name": "contextual-compression",
     "retriever_config": {
-        "compressor_model_provider": "mixedbread-ai",
-        "compressor_model_name": "mixedbread-ai/mxbai-rerank-xsmall-v1",
+        "compressor_model_name": "local-infinity/mixedbread-ai/mxbai-rerank-xsmall-v1",
         "top_k": 5,
         "search_type": "mmr",
         "search_kwargs": {
@@ -130,7 +128,7 @@
     "description": """
         Requires k and fetch_k in search kwargs for mmr.
         search_type can either be similarity or mmr or similarity_score_threshold.
-        Currently only support for mixedbread-ai/mxbai-rerank-xsmall-v1 reranker is added.""",
+        Currently only support for local-infinity/mixedbread-ai/mxbai-rerank-xsmall-v1 reranker is added.""",
     "value": QUERY_WITH_CONTEXTUAL_COMPRESSION_RETRIEVER_SEARCH_TYPE_MMR,
 }
 
@@ -147,8 +145,7 @@
     "prompt_template": PROMPT,
     "retriever_name": "contextual-compression",
     "retriever_config": {
-        "compressor_model_provider": "mixedbread-ai",
-        "compressor_model_name": "mixedbread-ai/mxbai-rerank-xsmall-v1",
+        "compressor_model_name": "local-infinity/mixedbread-ai/mxbai-rerank-xsmall-v1",
         "top_k": 5,
         "search_type": "similarity_score_threshold",
         "search_kwargs": {"score_threshold": 0.7},
@@ -161,7 +158,7 @@
     "description": """
         Requires score_threshold float (0~1) in search kwargs for similarity search.
         search_type can either be similarity or mmr or similarity_score_threshold.
-        Currently only support for mixedbread-ai/mxbai-rerank-xsmall-v1 reranker is added""",
+        Currently only support for local-infinity/mixedbread-ai/mxbai-rerank-xsmall-v1 reranker is added""",
     "value": QUERY_WITH_CONTEXTUAL_COMPRESSION_RETRIEVER_SEARCH_TYPE_SIMILARITY_WITH_SCORE,
 }
 
@@ -273,8 +270,7 @@
     "prompt_template": PROMPT,
     "retriever_name": "contextual-compression-multi-query",
     "retriever_config": {
-        "compressor_model_provider": "mixedbread-ai",
-        "compressor_model_name": "mixedbread-ai/mxbai-rerank-xsmall-v1",
+        "compressor_model_name": "local-infinity/mixedbread-ai/mxbai-rerank-xsmall-v1",
         "top_k": 5,
         "search_type": "mmr",
         "search_kwargs": {
@@ -309,8 +305,7 @@
     "prompt_template": PROMPT,
     "retriever_name": "contextual-compression-multi-query",
     "retriever_config": {
-        "compressor_model_provider": "mixedbread-ai",
-        "compressor_model_name": "mixedbread-ai/mxbai-rerank-xsmall-v1",
+        "compressor_model_name": "local-infinity/mixedbread-ai/mxbai-rerank-xsmall-v1",
         "top_k": 5,
         "search_type": "similarity",
         "search_kwargs": {"k": 10},
@@ -343,8 +338,7 @@
     "prompt_template": PROMPT,
     "retriever_name": "contextual-compression-multi-query",
     "retriever_config": {
-        "compressor_model_provider": "mixedbread-ai",
-        "compressor_model_name": "mixedbread-ai/mxbai-rerank-xsmall-v1",
+        "compressor_model_name": "local-infinity/mixedbread-ai/mxbai-rerank-xsmall-v1",
         "top_k": 5,
         "search_type": "similarity_score_threshold",
         "search_kwargs": {"score_threshold": 0.7},

backend/modules/query_controllers/example/types.py

@@ -73,10 +73,6 @@ class MultiQueryRetrieverConfig(VectorStoreRetrieverConfig):
 
 
 class ContextualCompressionRetrieverConfig(VectorStoreRetrieverConfig):
-    compressor_model_provider: str = Field(
-        title="provider of the compressor model",
-    )
-
     compressor_model_name: str = Field(
         title="model name of the compressor",
     )
@@ -85,14 +81,7 @@ class ContextualCompressionRetrieverConfig(VectorStoreRetrieverConfig):
         title="Top K docs to collect post compression",
     )
 
-    allowed_compressor_model_providers: ClassVar[Collection[str]] = ("mixedbread-ai",)
-
-    @validator("compressor_model_provider")
-    def validate_retriever_type(cls, value) -> Dict:
-        assert (
-            value in cls.allowed_compressor_model_providers
-        ), f"Compressor model of {value} not allowed. Valid values are: {cls.allowed_compressor_model_providers}"
-        return value
+    allowed_compressor_model_providers: ClassVar[Collection[str]]
 
 
 class ContextualCompressionMultiQueryRetrieverConfig(
@@ -101,10 +90,6 @@ class ContextualCompressionMultiQueryRetrieverConfig(
     pass
 
 
-class LordOfRetrievers(ContextualCompressionRetrieverConfig, MultiQueryRetrieverConfig):
-    pass
-
-
 class ExampleQueryInput(BaseModel):
     """
     Model for Query input.
@@ -137,7 +122,6 @@ class ExampleQueryInput(BaseModel):
         "multi-query",
         "contextual-compression",
         "contextual-compression-multi-query",
-        "lord-of-the-retrievers",
     )
 
     stream: Optional[bool] = Field(title="Stream the results", default=False)
@@ -170,9 +154,4 @@ def validate_retriever_type(cls, values: Dict) -> Dict:
                 **values.get("retriever_config")
             )
 
-        elif retriever_name == "lord-of-the-retrievers":
-            values["retriever_config"] = LordOfRetrievers(
-                **values.get("retriever_config")
-            )
-
         return values