Add Reranker implementation and integration in Retrieving pipeline (#77)

* Add base Reranker
* Add LLM Reranker
* Add Cohere Reranker
* Add integration of Rerankers in Retrieving pipeline

knowledgehub/pipelines/qa.py

@@ -1,6 +1,6 @@
 import os
 from pathlib import Path
-from typing import List
+from typing import List, Sequence
 
 from theflow import Node
 from theflow.utils.modules import ObjectInitDeclaration as _
@@ -11,6 +11,7 @@ from kotaemon.embeddings import AzureOpenAIEmbeddings
 from kotaemon.llms import PromptTemplate
 from kotaemon.llms.chats.openai import AzureChatOpenAI
 from kotaemon.pipelines.agents import BaseAgent
+from kotaemon.pipelines.reranking import BaseRerankingPipeline
 from kotaemon.pipelines.retrieving import RetrieveDocumentFromVectorStorePipeline
 from kotaemon.pipelines.tools import ComponentTool
 from kotaemon.storages import (
@@ -39,7 +40,7 @@ class QuestionAnsweringPipeline(BaseComponent):
     )
 
     llm: AzureChatOpenAI = AzureChatOpenAI.withx(
-        openai_api_base="https://bleh-dummy-2.openai.azure.com/",
+        azure_endpoint="https://bleh-dummy-2.openai.azure.com/",
         openai_api_key=os.environ.get("OPENAI_API_KEY", ""),
         openai_api_version="2023-03-15-preview",
         deployment_name="dummy-q2-gpt35",
@@ -49,11 +50,12 @@ class QuestionAnsweringPipeline(BaseComponent):
 
     vector_store: _[BaseVectorStore] = _(InMemoryVectorStore)
     doc_store: _[BaseDocumentStore] = _(InMemoryDocumentStore)
+    rerankers: Sequence[BaseRerankingPipeline] = []
 
     embedding: AzureOpenAIEmbeddings = AzureOpenAIEmbeddings.withx(
         model="text-embedding-ada-002",
         deployment="dummy-q2-text-embedding",
-        openai_api_base="https://bleh-dummy-2.openai.azure.com/",
+        azure_endpoint="https://bleh-dummy-2.openai.azure.com/",
         openai_api_key=os.environ.get("OPENAI_API_KEY", ""),
     )
 
@@ -72,6 +74,7 @@ class QuestionAnsweringPipeline(BaseComponent):
             doc_store=self.doc_store,
             embedding=self.embedding,
             top_k=self.retrieval_top_k,
+            rerankers=self.rerankers,
         )
         # load persistent from selected path
         collection_name = file_names_to_collection_name(self.file_name_list)