diff --git a/mem0/reranker/cohere_reranker.py b/mem0/reranker/cohere_reranker.py index 8de2d4ac9..281fabcc6 100644 --- a/mem0/reranker/cohere_reranker.py +++ b/mem0/reranker/cohere_reranker.py @@ -1,3 +1,4 @@ +import logging import os from typing import List, Dict, Any @@ -9,6 +10,8 @@ try: except ImportError: COHERE_AVAILABLE = False +logger = logging.getLogger(__name__) + class CohereReranker(BaseReranker): """Cohere-based reranker implementation.""" @@ -78,8 +81,9 @@ class CohereReranker(BaseReranker): return reranked_docs - except Exception: + except Exception as e: # Fallback to original order if reranking fails + logger.warning("Cohere reranking failed, falling back to original order: %s", e) for doc in documents: doc['rerank_score'] = 0.0 final_top_k = top_k or self.config.top_k diff --git a/mem0/reranker/huggingface_reranker.py b/mem0/reranker/huggingface_reranker.py index 6d641964a..8116c012e 100644 --- a/mem0/reranker/huggingface_reranker.py +++ b/mem0/reranker/huggingface_reranker.py @@ -1,3 +1,4 @@ +import logging from typing import List, Dict, Any, Union import numpy as np @@ -12,6 +13,8 @@ try: except ImportError: TRANSFORMERS_AVAILABLE = False +logger = logging.getLogger(__name__) + class HuggingFaceReranker(BaseReranker): """HuggingFace Transformers based reranker implementation.""" @@ -139,8 +142,9 @@ class HuggingFaceReranker(BaseReranker): return reranked_docs - except Exception: + except Exception as e: # Fallback to original order if reranking fails + logger.warning("HuggingFace reranking failed, falling back to original order: %s", e) for doc in documents: doc['rerank_score'] = 0.0 final_top_k = top_k or self.config.top_k diff --git a/mem0/reranker/llm_reranker.py b/mem0/reranker/llm_reranker.py index b89e25f4a..cef2dee66 100644 --- a/mem0/reranker/llm_reranker.py +++ b/mem0/reranker/llm_reranker.py @@ -1,3 +1,4 @@ +import logging import re from typing import Any, Dict, List, Union @@ -6,6 +7,8 @@ from mem0.configs.rerankers.llm import LLMRerankerConfig from mem0.reranker.base import BaseReranker from mem0.utils.factory import LlmFactory +logger = logging.getLogger(__name__) + class LLMReranker(BaseReranker): """LLM-based reranker implementation.""" @@ -151,8 +154,9 @@ class LLMReranker(BaseReranker): scored_doc['rerank_score'] = score scored_docs.append(scored_doc) - except Exception: + except Exception as e: # Fallback: assign neutral score if scoring fails + logger.warning("LLM reranking failed for a document, assigning neutral score: %s", e) scored_doc = doc.copy() scored_doc['rerank_score'] = 0.5 scored_docs.append(scored_doc) diff --git a/mem0/reranker/sentence_transformer_reranker.py b/mem0/reranker/sentence_transformer_reranker.py index 2df3b05e6..d891294f1 100644 --- a/mem0/reranker/sentence_transformer_reranker.py +++ b/mem0/reranker/sentence_transformer_reranker.py @@ -1,3 +1,4 @@ +import logging from typing import List, Dict, Any, Union import numpy as np @@ -11,6 +12,8 @@ try: except ImportError: SENTENCE_TRANSFORMERS_AVAILABLE = False +logger = logging.getLogger(__name__) + class SentenceTransformerReranker(BaseReranker): """Sentence Transformer based reranker implementation.""" @@ -102,8 +105,9 @@ class SentenceTransformerReranker(BaseReranker): return reranked_docs - except Exception: + except Exception as e: # Fallback to original order if reranking fails + logger.warning("SentenceTransformer reranking failed, falling back to original order: %s", e) for doc in documents: doc['rerank_score'] = 0.0 final_top_k = top_k or self.config.top_k diff --git a/mem0/reranker/zero_entropy_reranker.py b/mem0/reranker/zero_entropy_reranker.py index df5762306..dcf71bfaf 100644 --- a/mem0/reranker/zero_entropy_reranker.py +++ b/mem0/reranker/zero_entropy_reranker.py @@ -1,3 +1,4 @@ +import logging import os from typing import List, Dict, Any @@ -9,6 +10,8 @@ try: except ImportError: ZERO_ENTROPY_AVAILABLE = False +logger = logging.getLogger(__name__) + class ZeroEntropyReranker(BaseReranker): """Zero Entropy-based reranker implementation.""" @@ -89,8 +92,9 @@ class ZeroEntropyReranker(BaseReranker): return reranked_docs - except Exception: + except Exception as e: # Fallback to original order if reranking fails + logger.warning("Zero Entropy reranking failed, falling back to original order: %s", e) for doc in documents: doc['rerank_score'] = 0.0 final_top_k = top_k or self.config.top_k diff --git a/tests/rerankers/test_reranker_failure_logging.py b/tests/rerankers/test_reranker_failure_logging.py new file mode 100644 index 000000000..d94a5a663 --- /dev/null +++ b/tests/rerankers/test_reranker_failure_logging.py @@ -0,0 +1,32 @@ +"""Reranker failures must be logged, not silently swallowed. + +Uses the LLMReranker because it is constructible without heavy ML deps (the +``mock_llm`` fixture stubs the LLM factory). The fix under test is shared by all +reranker providers: the ``except`` fallback now emits a ``logger.warning`` before +degrading to the original order / a neutral score. +""" + +import logging + +from mem0.reranker.llm_reranker import LLMReranker + + +class TestRerankerFailureLogging: + def test_llm_failure_is_logged_and_falls_back(self, mock_llm, caplog): + _factory, llm_instance = mock_llm + llm_instance.generate_response.side_effect = RuntimeError("upstream 500") + + reranker = LLMReranker({"provider": "openai"}) + docs = [{"memory": "alpha"}, {"memory": "beta"}] + + with caplog.at_level(logging.WARNING, logger="mem0.reranker.llm_reranker"): + result = reranker.rerank("q", docs) + + # Graceful degradation preserved: every doc still comes back, scored neutral. + assert len(result) == 2 + assert all(d["rerank_score"] == 0.5 for d in result) + + # The failure is no longer silent. + warnings = [r for r in caplog.records if r.levelno == logging.WARNING] + assert warnings, "expected a warning to be logged on reranking failure" + assert "upstream 500" in caplog.text