106 lines
4.5 KiB
Python
106 lines
4.5 KiB
Python
"""
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===================================
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@Auther：WenZ
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@Company: BooWay
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@project：booway_dm
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===================================
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"""
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from dialogue_management import QuestionInfo, DialogType, DialogInfo, QuestionType, NLUInfo, ScenInfo, TalkInfo, ChatRecord
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from chains_ceshi import Vertical_classification, small_talk, intention_judge, domain_judge, judge_5W2H, extract_keywords, answer_questions, domain_judge, domain_judge_v2
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from kg_management import retriever_txt_faiss1
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from kg_management import retriever_txt_faiss2
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from kg_management import retriever_txt_faiss3
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from kg_management import retriever_txt_faiss4
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from kg_management import retriever_txt_faiss5
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from kg_management import retriever_txt_faiss6
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from kg_management import retriever_txt_faiss7
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from kg_management import retriever_txt_faiss8
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from kg_management import retriever_txt_faiss9
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from kg_management import input_index_csv_path
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from kg_management import xizang_input_csv_path
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from kg_management import cuceng_input_csv_path
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from kg_management import jigai_input_csv_path
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from kg_management import process_domain_category
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chain_vertical = Vertical_classification() # 垂直/开放分类
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chain_intention = intention_judge() # 意图分类
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chain_domain = domain_judge() # 领域分类
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chain_5w2h = judge_5W2H() # 5W2H分类
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chain_keywords = extract_keywords() # 关键语义提取
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chains_qa = answer_questions() # 检索回答
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chain_domain_v2 = domain_judge_v2()
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domain_mapping = {
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'西藏造价软件Z1': (retriever_txt_faiss1, retriever_txt_faiss2, retriever_txt_faiss3, xizang_input_csv_path),
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'新型储能计价通C1': (retriever_txt_faiss4, retriever_txt_faiss5, retriever_txt_faiss6, cuceng_input_csv_path),
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'技改检修计价通T1': (retriever_txt_faiss7, retriever_txt_faiss8, retriever_txt_faiss9, jigai_input_csv_path)
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}
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while True:
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input_str = input("用户：")
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if input_str.lower() in ["退出", "bye", "再见"]:
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print("booway软件助手：再见")
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break
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vertical_category = chain_vertical.invoke(input_str)
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if vertical_category == '闲聊':
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print("booway软件助手：闲聊服务只提供给内测用户")
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continue
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elif vertical_category == '软件咨询':
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# 1. DST：NLUInfo初始化
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nlu_info = NLUInfo(vertical_category="软件咨询")
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# 2. DST: 更新NLUInfo
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intention_info = chain_intention.invoke(input_str)
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nlu_info.intent_category = intention_info
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domain_info = chain_domain.invoke(input_str)
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nlu_info.domain_category = domain_info
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# 多轮对话逻辑
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while nlu_info.domain_category == '未知':
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print("booway软件助手: 请问是什么软件？")
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software_name = input("用户: ").strip()
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# domain_info = chain_domain_v2.invoke(software_name)
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print(software_name)
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nlu_info.domain_category = software_name
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if nlu_info.domain_category not in domain_mapping:
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print("booway软件助手：请输入一个有效的软件名称")
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# 多轮对话触发条件：领域信息缺失
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# print(f"当前的 domain_info: {domain_info}")
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# print(f"当前的 nlu_info.domain_category: {nlu_info.domain_category}")
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# print(f"当前的 domain_mapping.keys(): {list(domain_mapping.keys())}")
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_5w2h_info = chain_5w2h.invoke(input_str)
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nlu_info.question_type = _5w2h_info
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keywords_info = chain_keywords.invoke({"software_name": domain_info,
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"_5w2h_type": _5w2h_info,
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"query": input_str})
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nlu_info.retrieve_keywords = keywords_info
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# 3. 检索分析
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retrievers, input_csv_path = domain_mapping[nlu_info.domain_category][:3], \
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domain_mapping[nlu_info.domain_category][3]
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kg = process_domain_category(nlu_info, retrievers, input_csv_path, input_index_csv_path)
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# print(kg)
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if kg != []:
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extracted_index = [item[5:] for item in kg if item.startswith("检索知识")]
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print(f"系统：检索到的知识为{extracted_index}，分析如下：\n")
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print(chains_qa.invoke({"query": input_str, "kg": '\n'.join(kg)}))
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else:
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print("无相关检索知识，请重新提出问题")
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else:
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print("booway软件助手：抱歉，我不明白你的问题，请尝试重新表述")
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continue
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