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

tests/test_reranking.py

@@ -0,0 +1,62 @@
+from unittest.mock import patch
+
+import pytest
+from openai.types.chat.chat_completion import ChatCompletion
+
+from kotaemon.base import Document
+from kotaemon.llms.chats.openai import AzureChatOpenAI
+from kotaemon.pipelines.reranking import LLMReranking
+
+_openai_chat_completion_responses = [
+    ChatCompletion.parse_obj(
+        {
+            "id": "chatcmpl-7qyuw6Q1CFCpcKsMdFkmUPUa7JP2x",
+            "object": "chat.completion",
+            "created": 1692338378,
+            "model": "gpt-35-turbo",
+            "system_fingerprint": None,
+            "choices": [
+                {
+                    "index": 0,
+                    "finish_reason": "stop",
+                    "message": {
+                        "role": "assistant",
+                        "content": text,
+                        "function_call": None,
+                        "tool_calls": None,
+                    },
+                }
+            ],
+            "usage": {"completion_tokens": 9, "prompt_tokens": 10, "total_tokens": 19},
+        }
+    )
+    for text in [
+        "YES",
+        "NO",
+        "YES",
+    ]
+]
+
+
+@pytest.fixture
+def llm():
+    return AzureChatOpenAI(
+        azure_endpoint="https://dummy.openai.azure.com/",
+        openai_api_key="dummy",
+        openai_api_version="2023-03-15-preview",
+        temperature=0,
+    )
+
+
+@patch(
+    "openai.resources.chat.completions.Completions.create",
+    side_effect=_openai_chat_completion_responses,
+)
+def test_reranking(openai_completion, llm):
+    documents = [Document(text=f"test {idx}") for idx in range(3)]
+    query = "test query"
+
+    reranker = LLMReranking(llm=llm, concurrent=False)
+    rerank_docs = reranker(documents, query=query)
+
+    assert len(rerank_docs) == 2