feat: 知识库小重构

src/chat/knowledge/ie_process.py

@@ -0,0 +1,98 @@
+import json
+import time
+from typing import List, Union
+
+from .global_logger import logger
+from . import prompt_template
+from .lpmmconfig import global_config, INVALID_ENTITY
+from .llm_client import LLMClient
+from src.chat.knowledge.utils.json_fix import new_fix_broken_generated_json
+
+
+def _entity_extract(llm_client: LLMClient, paragraph: str) -> List[str]:
+    """对段落进行实体提取，返回提取出的实体列表（JSON格式）"""
+    entity_extract_context = prompt_template.build_entity_extract_context(paragraph)
+    _, request_result = llm_client.send_chat_request(
+        global_config["entity_extract"]["llm"]["model"], entity_extract_context
+    )
+
+    # 去除‘{’前的内容（结果中可能有多个‘{’）
+    if "[" in request_result:
+        request_result = request_result[request_result.index("[") :]
+
+    # 去除最后一个‘}’后的内容（结果中可能有多个‘}’）
+    if "]" in request_result:
+        request_result = request_result[: request_result.rindex("]") + 1]
+
+    entity_extract_result = json.loads(new_fix_broken_generated_json(request_result))
+
+    entity_extract_result = [
+        entity
+        for entity in entity_extract_result
+        if (entity is not None) and (entity != "") and (entity not in INVALID_ENTITY)
+    ]
+
+    if len(entity_extract_result) == 0:
+        raise Exception("实体提取结果为空")
+
+    return entity_extract_result
+
+
+def _rdf_triple_extract(llm_client: LLMClient, paragraph: str, entities: list) -> List[List[str]]:
+    """对段落进行实体提取，返回提取出的实体列表（JSON格式）"""
+    entity_extract_context = prompt_template.build_rdf_triple_extract_context(
+        paragraph, entities=json.dumps(entities, ensure_ascii=False)
+    )
+    _, request_result = llm_client.send_chat_request(global_config["rdf_build"]["llm"]["model"], entity_extract_context)
+
+    # 去除‘{’前的内容（结果中可能有多个‘{’）
+    if "[" in request_result:
+        request_result = request_result[request_result.index("[") :]
+
+    # 去除最后一个‘}’后的内容（结果中可能有多个‘}’）
+    if "]" in request_result:
+        request_result = request_result[: request_result.rindex("]") + 1]
+
+    entity_extract_result = json.loads(new_fix_broken_generated_json(request_result))
+
+    for triple in entity_extract_result:
+        if len(triple) != 3 or (triple[0] is None or triple[1] is None or triple[2] is None) or "" in triple:
+            raise Exception("RDF提取结果格式错误")
+
+    return entity_extract_result
+
+
+def info_extract_from_str(
+    llm_client_for_ner: LLMClient, llm_client_for_rdf: LLMClient, paragraph: str
+) -> Union[tuple[None, None], tuple[list[str], list[list[str]]]]:
+    try_count = 0
+    while True:
+        try:
+            entity_extract_result = _entity_extract(llm_client_for_ner, paragraph)
+            break
+        except Exception as e:
+            logger.warning(f"实体提取失败，错误信息：{e}")
+            try_count += 1
+            if try_count < 3:
+                logger.warning("将于5秒后重试")
+                time.sleep(5)
+            else:
+                logger.error("实体提取失败，已达最大重试次数")
+                return None, None
+
+    try_count = 0
+    while True:
+        try:
+            rdf_triple_extract_result = _rdf_triple_extract(llm_client_for_rdf, paragraph, entity_extract_result)
+            break
+        except Exception as e:
+            logger.warning(f"实体提取失败，错误信息：{e}")
+            try_count += 1
+            if try_count < 3:
+                logger.warning("将于5秒后重试")
+                time.sleep(5)
+            else:
+                logger.error("实体提取失败，已达最大重试次数")
+                return None, None
+
+    return entity_extract_result, rdf_triple_extract_result