Allow reranking nodes retrieved from vector DB

ols/customize/__init__.py

@@ -6,3 +6,4 @@
 project = os.getenv("PROJECT", "ols")
 prompts = importlib.import_module(f"ols.customize.{project}.prompts")
 keywords = importlib.import_module(f"ols.customize.{project}.keywords")
+reranker = importlib.import_module(f"ols.customize.{project}.reranker")

ols/customize/ols/reranker.py

@@ -0,0 +1,14 @@
+"""Reranker for post-processing the Vector DB search results."""
+
+import logging
+
+from llama_index.core.schema import NodeWithScore
+
+logger = logging.getLogger(__name__)
+
+
+def rerank(retrieved_nodes: list[NodeWithScore]):
+    """Rerank Vector DB search results."""
+    message = "reranker.rerank() is called with %d result(s)." % len(retrieved_nodes)
+    logger.debug(message)
+    return retrieved_nodes

ols/src/query_helpers/docs_summarizer.py

@@ -11,6 +11,7 @@
 from ols.app.models.models import SummarizerResponse
 from ols.constants import RAG_CONTENT_LIMIT, GenericLLMParameters
 from ols.customize import prompts
+from ols.customize.ols.reranker import rerank
 from ols.src.prompts.prompt_generator import GeneratePrompt
 from ols.src.query_helpers.query_helper import QueryHelper
 from ols.utils.token_handler import TokenHandler
@@ -89,8 +90,10 @@ def summarize(
 
         if vector_index is not None:
             retriever = vector_index.as_retriever(similarity_top_k=RAG_CONTENT_LIMIT)
+            retrieved_nodes = retriever.retrieve(query)
+            retrieved_nodes = rerank(retrieved_nodes)
             rag_chunks, available_tokens = token_handler.truncate_rag_context(
-                retriever.retrieve(query), self.model, available_tokens
+                retrieved_nodes, self.model, available_tokens
             )
         else:
             logger.warning("Proceeding without RAG content. Check start up messages.")

tests/unit/query_helpers/test_docs_summarizer.py

@@ -1,12 +1,15 @@
 """Unit tests for DocsSummarizer class."""
 
+import logging
 from unittest.mock import ANY, patch
 
 import pytest
 
 from ols import config
+from ols.app.models.config import LoggingConfig
 from ols.src.query_helpers.docs_summarizer import DocsSummarizer, QueryHelper
 from ols.utils import suid
+from ols.utils.logging_configurator import configure_logging
 from tests import constants
 from tests.mock_classes.mock_langchain_interface import mock_langchain_interface
 from tests.mock_classes.mock_llama_index import MockLlamaIndex
@@ -129,3 +132,25 @@ def test_summarize_no_reference_content():
     assert question in summary.response
     assert summary.rag_chunks == []
     assert not summary.history_truncated
+
+
+@patch("ols.utils.token_handler.RAG_SIMILARITY_CUTOFF", 0.4)
+@patch("ols.utils.token_handler.MINIMUM_CONTEXT_TOKEN_LIMIT", 3)
+@patch("ols.src.query_helpers.docs_summarizer.LLMChain", new=mock_llm_chain(None))
+def test_summarize_reranker(caplog):
+    """Basic test to make sure the reranker is called as expected."""
+    logging_config = LoggingConfig(app_log_level="debug")
+
+    configure_logging(logging_config)
+    logger = logging.getLogger("ols")
+    logger.handlers = [caplog.handler]  # add caplog handler to logger
+
+    summarizer = DocsSummarizer(llm_loader=mock_llm_loader(None))
+    question = "What's the ultimate question with answer 42?"
+    rag_index = MockLlamaIndex()
+    # no history is passed into summarize() method
+    summary = summarizer.summarize(conversation_id, question, rag_index)
+    check_summary_result(summary, question)
+
+    # Check captured log text to see if reranker was called.
+    assert "reranker.rerank() is called with 1 result(s)." in caplog.text