{"record":{"id":"7a14bdff1436fcc3","repo":"run-llama/llama_index","slug":"the-embedding-file-file-path-is-empty","errorCode":null,"errorMessage":"The embedding file {file_path} is empty.","messagePattern":"The embedding file (.+?) is empty\\.","errorType":"exception","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"llama-index-core/llama_index/core/embeddings/utils.py","lineNumber":27,"sourceCode":"from llama_index.core.callbacks import CallbackManager\nfrom llama_index.core.embeddings.mock_embed_model import MockEmbedding\nfrom llama_index.core.utils import get_cache_dir\n\nEmbedType = Union[BaseEmbedding, \"LCEmbeddings\", str]\n\n\ndef save_embedding(embedding: List[float], file_path: str) -> None:\n    \"\"\"Save embedding to file.\"\"\"\n    with open(file_path, \"w\", encoding=\"utf-8\") as f:\n        f.write(\",\".join([str(x) for x in embedding]))\n\n\ndef load_embedding(file_path: str) -> List[float]:\n    \"\"\"Load embedding from file. Will only return first embedding in file.\"\"\"\n    with open(file_path, encoding=\"utf-8\") as f:\n        for line in f:\n            return [float(x) for x in line.strip().split(\",\")]\n    raise ValueError(f\"The embedding file {file_path} is empty.\")\n\n\ndef resolve_embed_model(\n    embed_model: Optional[EmbedType] = None,\n    callback_manager: Optional[CallbackManager] = None,\n) -> BaseEmbedding:\n    \"\"\"Resolve embed model.\"\"\"\n    from llama_index.core.settings import Settings\n\n    try:\n        from llama_index.core.bridge.langchain import Embeddings as LCEmbeddings\n    except ImportError:\n        LCEmbeddings = None  # type: ignore\n\n    if embed_model == \"default\":\n        if os.getenv(\"IS_TESTING\"):\n            embed_model = MockEmbedding(embed_dim=8)\n            embed_model.callback_manager = callback_manager or Settings.callback_manager","sourceCodeStart":9,"sourceCodeEnd":45,"githubUrl":"https://github.com/run-llama/llama_index/blob/afd0fef371831f9bda13e5af7167cf4e981278ab/llama-index-core/llama_index/core/embeddings/utils.py#L9-L45","documentation":"load_embedding(file_path) reads a CSV-of-floats file produced by save_embedding() and returns the first line. If the file exists but contains zero lines (empty file), the for-loop body never executes and the function raises ValueError — the file was created but no embedding was ever written to it.","triggerScenarios":"Calling load_embedding on a file that is 0 bytes (created by open(..., 'w') without a write, an interrupted save_embedding, or touch); pointing at a truncated/corrupted cache file.","commonSituations":"A crashed or killed embedding-save job left empty files; filesystem issues truncating cache files; code that pre-creates placeholder files then fails to populate them.","solutions":["Check size before loading: if os.path.getsize(path) == 0: regenerate the embedding and save_embedding(vec, path)","Re-run the code that produces the embedding (save_embedding) so the file contains one comma-separated line","Treat empty cache entries as cache misses and recompute, then overwrite the file"],"exampleFix":"// before\nvec = load_embedding(\"emb.txt\")  # file is empty -> ValueError\n\n// after\nimport os\nif os.path.getsize(\"emb.txt\") == 0:\n    vec = embed_model.get_text_embedding(text)\n    save_embedding(vec, \"emb.txt\")\nelse:\n    vec = load_embedding(\"emb.txt\")","handlingStrategy":"validation","validationCode":"import os\nif not os.path.exists(path) or os.path.getsize(path) == 0:\n    vec = embed_model.get_text_embedding(text)\n    save_embedding(vec, path)\nvec = load_embedding(path)","typeGuard":null,"tryCatchPattern":"try:\n    vec = load_embedding(path)\nexcept ValueError as e:\n    if \"is empty\" in str(e):\n        vec = embed_model.get_text_embedding(text)\n        save_embedding(vec, path)\n    else:\n        raise","preventionTips":["Treat embedding files as a cache: validate size before reading, recompute on miss","Write cache files atomically (write temp then rename) so crashes never leave empty files","Wrap save/load in a small EmbeddingCache class that owns both directions"],"tags":["embeddings","cache","file-io","data-integrity"],"backgroundTag":null,"analyzedSha":"afd0fef371831f9bda13e5af7167cf4e981278ab","analyzedAt":"2026-08-15T05:42:58.429Z","schemaVersion":2},"datasetVersion":"2026-08-15T17:31:12.345Z"}