The invention discloses a semantic fuzzy search method based on a sentence-level deep learning language model. In the present invention, the present invention has a high degree of ambiguity, and the present invention introduces a deep learning language model, which fully considers semantic issues, and can retrieve sentences with high semantic similarity with the target sentence, and use the method of hierarchically calculating semantic similarity Efficiently judge the semantic similarity between sentences; the operation speed is fast, and the vectorized processing is used instead of the conventional loop traversal to process text, ensuring that each semantic matching task unit can be processed in parallel, which greatly improves the search speed; The search recall rate is high, and the use of implication index makes the system more robust to grammatical interference, effectively improving the search recall rate; the system is flexible, and the present invention integrates mechanisms such as semantic understanding, fuzzy query, and precise information positioning , and then encapsulate the entire algorithm module with an interface, which is convenient for users to call.