""" =================================== @Auther：WenZ @Company: BooWay @project：booway_dm =================================== """ import streamlit as st from utils import judge_define_suffix, match_suffix, retrieve_relevant_software from dialogue_management import QuestionInfo, DialogType, DialogInfo, QuestionType, NLUInfo, ScenInfo, TalkInfo, \ ChatRecord from utils import stop_word_processing import spacy import zh_core_web_sm, zh_core_web_md, zh_core_web_lg, zh_core_web_trf from utils import get_keywords, get_keywords_v2, get_keywords_v3 from vector_load import interface_search # nlp_sm = zh_core_web_sm.load() # nlp_md = zh_core_web_md.load() # nlp_lg = zh_core_web_lg.load() nlp_trf = zh_core_web_trf.load() polite_words = {"你好", "您好", "请", "请问", "谢谢", "不客气", "麻烦", "打扰", "拜托", "辛苦", "劳驾"} from chains_ceshi import suffix_answers from chains_ceshi import Vertical_classification from chains_ceshi import intention_judge from chains_ceshi import domain_judge from chains_ceshi import judge_5W2H from chains_rewrite import software_name_rewrite from chains_rewrite import query_function_rewrite from chains_rewrite import operation_guidance_rewrite from chains_rewrite import troubleshooting_rewrite from chains_rewrite import access_rewrite from kg_management import retriever_txt_faiss1 from kg_management import retriever_txt_faiss2 from kg_management import retriever_txt_faiss3 from kg_management import retriever_txt_faiss4 from kg_management import retriever_txt_faiss5 from kg_management import retriever_txt_faiss6 from kg_management import retriever_txt_faiss7 from kg_management import retriever_txt_faiss8 from kg_management import retriever_txt_faiss9 from kg_management import input_index_csv_path from kg_management import xizang_input_csv_path from kg_management import cuceng_input_csv_path from kg_management import jigai_input_csv_path from kg_management import process_domain_category domain_mapping = { '西藏造价软件Z1': (retriever_txt_faiss1, retriever_txt_faiss2, retriever_txt_faiss3, xizang_input_csv_path), '新型储能计价通C1': (retriever_txt_faiss4, retriever_txt_faiss5, retriever_txt_faiss6, cuceng_input_csv_path), '技改检修计价通T1': (retriever_txt_faiss7, retriever_txt_faiss8, retriever_txt_faiss9, jigai_input_csv_path) } chain_suffix_answers = suffix_answers() # 后缀名问题处理 chain_vertical = Vertical_classification() # 垂直/开放分类 chain_intention = intention_judge() # 意图分类 chain_domain = domain_judge() # 领域分类 chain_5W2H = judge_5W2H() # 5W2H分类 chains_name_rewrite = software_name_rewrite() # 问题改写：软件名改写 chain_function_rewrite = query_function_rewrite() # 问题改写：软件功能查询 chain_guidance_rewrite = operation_guidance_rewrite() # 问题改写：软件操作指导 chain_troubleshooting_rewrite = troubleshooting_rewrite() # 问题改写：软件故障排查类 chain_access_rewrite = access_rewrite() # 问题改写：软件下载与安装 from chains_rewrite import to_normal_rewrite from chains_rewrite import retrieval_rewrite chain_normal_rewrite = to_normal_rewrite() chain_retrieval_rewrite = retrieval_rewrite() # 同义词替换 from utils import normalize_text synonym_dict = { "西藏造价软件Z1": ["西藏造价Z1", "Z1软件", "西藏Z1", "西藏工程造价Z1", "西藏造价通Z1", "Z1", "西藏", "西藏造价z1", "z1软件", "西藏z1", "西藏工程造价z1", "西藏造价通z1", "z1", ], "新型储能计价通C1": ["储能计价通C1", "C1储能计价", "新型储能C1", "储能计价C1", "新型储能计价通", "C1", "储能", "储能计价通c1", "c1储能计价", "新型储能c1", "储能计价c1", "新型储能计价通", "c1"], "技改检修计价通T1": ["技改检修T1", "T1检修计价", "技改计价通T1", "技改检修计价通", "T1技改检修", "T1", "技改", "技改检修t1", "t1检修计价", "技改计价通t1", "技改检修计价通", "t1技改检修", "t1"], "费率": ["费费率"], "下载": ["获取", "安装", "下载下来", "装上"] } import random reponse_prompts = [ "🤔 Booway软件助手：请问您指的是哪个软件？", "🤔 Booway软件助手：请提供软件名称，以便更好地帮助您。", "🤔 Booway软件助手：请问您使用的是什么软件？", "🤔 Booway软件助手：请告诉我您要查询的软件名称。", "🤔 Booway软件助手：请问是哪款软件？" ] import streamlit as st import random st.set_page_config(page_title="Booway 助手", layout="wide") # st.title("🤖 Booway 助手") # 助手简介 st.markdown(""" # 🤖 Booway 软件助手 欢迎使用 **booway 软件助手**，这是一个用于协助用户进行电力造价软件相关问题咨询的智能系统。 **目前可咨询软件为：** - 西藏造价软件Z1 - 新型储能计价通C1 - 技改检修计价通T1 - 后缀名文件咨询 **使用方法：** 直接在下方输入你的问题，例如： - 你好，想问下储能的C1那个软件。初设的基本预备费费率想调整一下,但是没有找到能调整的地方 - 如何把西藏老定额工程升级成西藏Z1的新定额工程 - 储能软件勾选了卸车，总价不变呢 - bjgx用什么软件打开的？ - 设备运杂费率怎么设置 (多轮测试) - 你好，初设的基本预备费费率想调整一下,但是没有找到能调整的地方（多轮测试） **注意：多轮对话** - ~~目前多轮对话中 当机器人询问用户什么软件，则必须是以上软件名字~~ 如果你输入的是闲聊内容，系统将提示仅内测用户可用。 """) input_str = st.text_input("🦉 用户：", "") if input_str: if judge_define_suffix(input_str): nlu_info = NLUInfo(vertical_category="软件咨询") nlu_info.intent_category = "查询功能" nlu_info.domain_category = "后缀名查询" suffix_name = match_suffix(input_str) nlu_info.retrieve_keywords = suffix_name suffix_to_software = retrieve_relevant_software(suffix_name) if isinstance(suffix_to_software, int): st.info("Booway 助手：未查到相关知识") elif isinstance(suffix_to_software, str): query_rewrite = f"{suffix_name}是什么文件？用什么软件打开？" nlu_info.rewrite = query_rewrite query_kg = suffix_to_software result = chain_suffix_answers.invoke({"query": input_str, "kg": query_kg}) st.subheader("识别出的NLU信息") st.json({"垂直分类": nlu_info.vertical_category, "意图分类": nlu_info.intent_category, "领域分类": nlu_info.domain_category, "问题分类": nlu_info.question_type, "检索语义": nlu_info.retrieve_keywords, "改写结果": nlu_info.rewrite, "检索回答": result}) elif isinstance(suffix_to_software, list): suffix_to_software_str = '\n'.join(suffix_to_software) query_rewrite = f"{suffix_name}是什么文件？用什么软件打开？" nlu_info.rewrite = query_rewrite query_kg = suffix_to_software_str result = chain_suffix_answers.invoke({"query": input_str, "kg": query_kg}) st.subheader("识别出的NLU信息") st.json({"垂直分类": nlu_info.vertical_category, "意图分类": nlu_info.intent_category, "领域分类": nlu_info.domain_category, "问题分类": nlu_info.question_type, "检索语义": nlu_info.retrieve_keywords, "改写结果": nlu_info.rewrite, "检索回答": result}) else: # 多轮对话处理 # 第一步：预处理输入 input_str_stoped = stop_word_processing(input_str, nlp_trf, polite_words) input_str_syn = normalize_text(input_str_stoped, synonym_dict) # 第二步：调用分类链判断领域 vertical_category = chain_domain.invoke(input_str_syn) # 第三步：若为未知领域，尝试引导补充软件名 if vertical_category == "未知": # 初始化状态变量 if "mt_input_done" not in st.session_state: st.session_state.mt_input_done = False if "mt_input_value" not in st.session_state: st.session_state.mt_input_value = "" if "mt_prompt" not in st.session_state: st.session_state.mt_prompt = random.choice(reponse_prompts) # 尚未完成补充输入 if not st.session_state.mt_input_done: mt_conversation = st.text_input( f"{st.session_state.mt_prompt}", key="mt_input" ) if mt_conversation: st.session_state.mt_input_value = mt_conversation st.session_state.mt_input_done = True st.rerun() else: st.stop() # 等待输入 # 完成补充输入，重新获取 vertical_category mt_input_str = normalize_text(st.session_state.mt_input_value, synonym_dict) vertical_category = chain_domain.invoke(mt_input_str) # 第四步：NLU构建 nlu_info = NLUInfo(vertical_category="软件咨询") nlu_info.domain_category = vertical_category # 第五步：改写问题并提取关键词 input_str_name_rewrite = chains_name_rewrite.invoke({ "query": input_str, "software_name": nlu_info.domain_category }) input_str_rewrite = chain_normal_rewrite.invoke(input_str_name_rewrite) temp_retriever = get_keywords_v2(input_str_rewrite) nlu_info.question_type = chain_5W2H.invoke(input_str_rewrite) nlu_info.intent_category = chain_intention.invoke(input_str) # 第六步：调用检索器并重写查询 retrievers, input_csv_path = ( domain_mapping[nlu_info.domain_category][:3], domain_mapping[nlu_info.domain_category][3] ) index_keywords = interface_search(temp_retriever, *retrievers) st.info(f"提取关键词：{index_keywords}") nlu_info.rewrite = chain_retrieval_rewrite.invoke({ "query": input_str_rewrite, "question_type": nlu_info.question_type, "intention_type": nlu_info.intent_category, "keywords": index_keywords }) nlu_info.retrieve_keywords = get_keywords_v3(nlu_info.rewrite) # 第七步：展示识别结果 st.subheader("识别出的NLU信息") st.json({"垂直分类":nlu_info.vertical_category, "意图分类":nlu_info.intent_category, "领域分类":nlu_info.domain_category, "问题分类":nlu_info.question_type, "检索语义":nlu_info.retrieve_keywords, "改写结果":nlu_info.rewrite}) for key in ["mt_input_done", "mt_input_value", "mt_prompt", "mt_input"]: if key in st.session_state: del st.session_state[key] # streamlit run streamlit_main.py --server.port 2335