llm runtime_error ai_generated true

警告：使用来自版本1.0.0的缓存嵌入，但当前模型为版本2.0.0。嵌入可能已过时。

Warning: Using cached embedding from version 1.0.0, but current model is version 2.0.0. Embedding may be stale.

ID: llm/llm-caching-stale-embedding

其他格式: JSON · Markdown 中文 · English
85%修复率
84%置信度
1证据数
2024-05-01首次发现

版本兼容性

版本状态引入弃用备注
langchain 0.1.10 active — — —
langchain 0.1.11 active — — —
chromadb 0.4.22 active — — —

根因分析

模型更新后，来自旧版本的嵌入缓存被重用，导致维度或语义漂移。

English

Embedding cache from a previous model version is reused after model update, causing dimension or semantic drift.

generic

官方文档

https://python.langchain.com/docs/modules/data_connection/retrievers/

解决方案

  1. Clear embedding cache and re-index: chroma_collection.delete(where={}); then re-embed all documents with new model version
  2. Pin embedding model version in config: EMBEDDING_MODEL = 'text-embedding-3-small@v1' (if version pinning is supported)

无效尝试

常见但无效的做法:

  1. Ignoring warning and continuing to use cache 95% 失败

    Stale embeddings cause retrieval failures or inaccurate results, leading to silent data issues.

  2. Disabling caching entirely 70% 失败

    Increases latency and API costs without solving root cause of version mismatch.