{
  "id": "llm/llm-caching-stale-embedding",
  "signature": "Warning: Using cached embedding from version 1.0.0, but current model is version 2.0.0. Embedding may be stale.",
  "signature_zh": "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。",
  "regex": "cached embedding.*version.*stale",
  "domain": "llm",
  "category": "runtime_error",
  "subcategory": null,
  "root_cause": "Embedding cache from a previous model version is reused after model update, causing dimension or semantic drift.",
  "root_cause_type": "generic",
  "root_cause_zh": "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。",
  "versions": [
    {
      "version": "langchain 0.1.10",
      "introduced": null,
      "deprecated": null,
      "removed": null,
      "behavior_change": null,
      "status": "active"
    },
    {
      "version": "langchain 0.1.11",
      "introduced": null,
      "deprecated": null,
      "removed": null,
      "behavior_change": null,
      "status": "active"
    },
    {
      "version": "chromadb 0.4.22",
      "introduced": null,
      "deprecated": null,
      "removed": null,
      "behavior_change": null,
      "status": "active"
    }
  ],
  "os_specific": {},
  "dead_ends": [
    {
      "action": "Ignoring warning and continuing to use cache",
      "why_fails": "Stale embeddings cause retrieval failures or inaccurate results, leading to silent data issues.",
      "fail_rate": 0.95,
      "condition": "",
      "sources": []
    },
    {
      "action": "Disabling caching entirely",
      "why_fails": "Increases latency and API costs without solving root cause of version mismatch.",
      "fail_rate": 0.7,
      "condition": "",
      "sources": []
    }
  ],
  "workarounds": [
    {
      "action": "Clear embedding cache and re-index: chroma_collection.delete(where={}); then re-embed all documents with new model version",
      "success_rate": 0.95,
      "how": "Clear embedding cache and re-index: chroma_collection.delete(where={}); then re-embed all documents with new model version",
      "condition": "",
      "sources": []
    },
    {
      "action": "Pin embedding model version in config: EMBEDDING_MODEL = 'text-embedding-3-small@v1' (if version pinning is supported)",
      "success_rate": 0.8,
      "how": "Pin embedding model version in config: EMBEDDING_MODEL = 'text-embedding-3-small@v1' (if version pinning is supported)",
      "condition": "",
      "sources": []
    }
  ],
  "workarounds_zh": [
    "Clear embedding cache and re-index: chroma_collection.delete(where={}); then re-embed all documents with new model version",
    "Pin embedding model version in config: EMBEDDING_MODEL = 'text-embedding-3-small@v1' (if version pinning is supported)"
  ],
  "transition_graph": {
    "leads_to": [],
    "preceded_by": [],
    "frequently_confused_with": []
  },
  "official_doc_url": "https://python.langchain.com/docs/modules/data_connection/retrievers/",
  "official_doc_section": null,
  "error_code": null,
  "verification_tier": "ai_generated",
  "confidence": 0.84,
  "fix_success_rate": 0.85,
  "resolvable": "true",
  "first_seen": "2024-05-01",
  "last_confirmed": "2024-06-01",
  "last_updated": "2024-06-01",
  "evidence_count": 1,
  "tags": [],
  "locale": "en",
  "aliases": []
}