处理单个批次的LLM请求
(item_batch, llm_processer, ref_kg_path)
| 32 | |
| 33 | |
| 34 | def process_llm_batch(item_batch, llm_processer, ref_kg_path): |
| 35 | """ |
| 36 | 处理单个批次的LLM请求 |
| 37 | """ |
| 38 | doc_name, source_id, text, match_words = ( |
| 39 | item_batch["doc_name"], |
| 40 | item_batch["source_id"], |
| 41 | item_batch["text"], |
| 42 | item_batch["match_words"] |
| 43 | ) |
| 44 | |
| 45 | # 生成大模型推理输入文件 |
| 46 | prompt = llm_processer.extract_triple_prompt(text, match_words, ref_kg_path) |
| 47 | # 大模型推理 |
| 48 | response = llm_processer.infer(prompt) |
| 49 | # 推理结果后处理（三元组过滤） |
| 50 | infer_triples, head_entities, tail_entities = Triple.get_triple(match_words, response) |
| 51 | # 再次调用大模型对实体进行验证 |
| 52 | verify_entities = llm_processer.entity_evaluate(tail_entities) |
| 53 | |
| 54 | return { |
| 55 | "doc_name": doc_name, |
| 56 | "source_id": source_id, |
| 57 | "infer_triples": infer_triples, |
| 58 | "head_entities": head_entities, |
| 59 | "verify_entities": verify_entities |
| 60 | } |
| 61 | |
| 62 | |
| 63 | def extract_desc(triple_path, corpus_path, task_conf, llm_processer): |
nothing calls this directly
no test coverage detected