celery/postprocess011105.py

import time
from config import simplemodel
from template import xuanxiang
import json
with open('zhaoping_rule', 'r') as f:
    content = f.read()
import json
obj=json.loads(content)
with open('name_label', 'r') as f:
    content = f.read()
import json
name_label=json.loads(content)
tijiaoxian = ['13-95', '13-27', '13-127', '13-128', '13-129', '13-130', '13-131', '13-34', '13-72', '13-76', '13-100']
example1='''
1、用于地下楼梯间、走道地面 做法详见图纸设计及相关图集规范
2、100厚C25细石混凝土随打随抹,内配Φ4@200钢筋网片,抹平压光
'''
example2='''
1、用于消防泵房地面 做法详见图纸设计及相关图集规范
2、50厚C25细石混凝土随打随抹,内配Φ4@200钢筋网片,抹平压光
3、最薄处30厚C20细石混凝土向排水沟、集水坑找1%坡,随打随抹平,立管根部用DS M15砂浆(1:3水泥砂浆)抹小八字角
'''
from fallback import fallback
def aifilter5(A, #options
       B, #data
       aiclient,
             qwclient,
              sfclient,
             dw):
    options=[]
    letters = "ABCDEFGHIJKLMN"
    for i in range(len(tijiaoxian)):
        options.append("给定选项" + letters[i]+"，内容为"+name_label[tijiaoxian[i]] )

    completion = aiclient.chat.completions.create(
        #model="THUDM/GLM-4-9B-0414",
        model="glm-4.5-air",
        #model="Qwen/Qwen3-8B",
        #model="ernie-speed-128k",
        messages=[
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": "问题描述： 给定一段工作内容: " + B['label'] + " " +  B['mc'] + " " + B['tz'] + "。该工作内容的描述中包含踢脚线施工。"+';'.join(options)+'。请选出与工作内容最匹配的一个选项并返回代号。例如，你觉得选项A最匹配，则你应该返回A'},
        ],
        extra_body={"thinking": {"type": "disabled"}},
        #extra_body={"enable_thinking": True},
        #stream=True
    )
    json_string = completion.choices[0].message.content
    print(json_string)
    answer=[]
    if len(json_string) < 4:
        if 'A' in json_string:
            answer.append(name_label[tijiaoxian[0]])
        if 'B' in json_string:
            answer.append(name_label[tijiaoxian[1]])
        if 'C' in json_string:
            answer.append(name_label[tijiaoxian[2]])
        if 'D' in json_string:
            answer.append(name_label[tijiaoxian[3]])
        if 'E' in json_string:
            answer.append(name_label[tijiaoxian[4]])
        if 'F' in json_string:
            answer.append(name_label[tijiaoxian[5]])
        if 'G' in json_string:
            answer.append(name_label[tijiaoxian[6]])
        if 'H' in json_string:
            answer.append(name_label[tijiaoxian[7]])
        if 'I' in json_string:
            answer.append(name_label[tijiaoxian[8]])
        if 'J' in json_string:
            answer.append(name_label[tijiaoxian[9]])
        if 'K' in json_string:
            answer.append(name_label[tijiaoxian[10]])
        return answer
    completion = sfclient.chat.completions.create(
        model=simplemodel(),
        messages=[
            {"role": "system", "content": "You are a helpful assistant.请将最终答案以JSON格式输出"},
            {"role": "user", "content": " 给你一段文字如下， " + json_string + ",其中给出了一个类似于A或者B的英文字母作为答案，请将该字母答案输出"},                       
        ],
        extra_body={"thinking": {"type": "disabled"}},
        #extra_body={"enable_thinking": False},
    )
    json_string = completion.choices[0].message.content
    print(json_string)
    if 'A' in json_string:
        answer.append(name_label[tijiaoxian[0]])
    if 'B' in json_string:
        answer.append(name_label[tijiaoxian[1]])
    if 'C' in json_string:
        answer.append(name_label[tijiaoxian[2]])
    if 'D' in json_string:
        answer.append(name_label[tijiaoxian[3]])
    if 'E' in json_string:
        answer.append(name_label[tijiaoxian[4]])
    if 'F' in json_string:
        answer.append(name_label[tijiaoxian[5]])
    if 'G' in json_string:
        answer.append(name_label[tijiaoxian[6]])
    if 'H' in json_string:
        answer.append(name_label[tijiaoxian[7]])
    if 'I' in json_string:
        answer.append(name_label[tijiaoxian[8]])
    if 'J' in json_string:
        answer.append(name_label[tijiaoxian[9]])
    if 'K' in json_string:
        answer.append(name_label[tijiaoxian[10]])
    return answer
def aifilter3(A, #options
       B, #data
       aiclient,
             qwclient,
              sfclient,
             dw):
    options=[]
    letters = "ABCDEFGHIJKLMN"
    for i in range(len(A)):
        options.append("给定选项" + letters[i]+"，内容为"+A[i] )

    completion = aiclient.chat.completions.create(
        #model="THUDM/GLM-4-9B-0414",
        model="glm-4.5-air",
        #model="Qwen/Qwen3-8B",
        #model="ernie-speed-128k",
        messages=[
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": "问题描述： 细石混凝土内配钢筋网片是一种常见的施工工艺。给定一段工作内容: " + B['label'] + " " +  B['mc'] + " " + B['tz'] + "。请问该工作内容的描述中有同时包含混凝土以及钢筋网片吗？请回答有或者没有"},
        ],
        extra_body={"thinking": {"type": "disabled"}},
        #extra_body={"enable_thinking": True},
        #stream=True
    )
    json_string = completion.choices[0].message.content
    print(json_string)
    if len(json_string) < 4:
        if '没有' in json_string:
            return False
        return True
    completion = sfclient.chat.completions.create(
        model=simplemodel(),
        messages=[
            {"role": "system", "content": "You are a helpful assistant.请将最终答案以JSON格式输出"},
            {"role": "user", "content": " 给你一段文字如下， " + json_string + ",其中给出了一个有或者没有的判断，请将该中文判断输出"},                       
        ],
        extra_body={"thinking": {"type": "disabled"}},
        #extra_body={"enable_thinking": False},
    )
    json_string = completion.choices[0].message.content
    print(json_string)
    if '没有' in json_string:
        return False
    return True

def aifilter4(A, #options
       B, #data
       aiclient,
             qwclient,
              sfclient,
             dw):
    options=[]
    letters = "ABCDEFGHIJKLMN"
    for i in range(len(A)):
        options.append("给定选项" + letters[i]+"，内容为"+A[i] )

    completion = aiclient.chat.completions.create(
        model="glm-4.5-air",
        #model="THUDM/GLM-Z1-9B-0414",
        #model="ernie-speed-128k",
        messages=[
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": " 背景知识：混凝土（砼）整体面层跟混凝土找平层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 背景知识：细石混凝土楼地面不是块料面层，而是混凝土整体面层"},
            {"role": "user", "content": " 背景知识：混凝土（砼）整体面层跟混凝土垫层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 背景知识：混凝土（砼）找平层跟混凝土垫层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 背景知识：水泥砂浆找平层跟水泥砂浆面层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 背景知识：水泥砂浆找平层跟水泥砂浆保护层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 特殊处理要求：如果工作内容描述中明确提到块料面层，比如地砖、石材块料等，则去掉精确包含“细石砼整体面层”字样的选项"},
            {"role": "user", "content": " 重要提示：选项指的是给定的A、B、C之类的选项，不是指的工作内容中的可能的1、2、3这样罗列的特征"},
            {"role": "user", "content": " 重要提示：除特殊处理要求提及的内容外，不需考虑选项内容与工作内容是否符合，只需要根据特殊处理要求做出处理"},
            {"role": "user", "content": "问题描述： 给定一段工作内容: " + B['label'] + " " +  B['mc'] + " " + B['tz'] +  "，".join(options) + "。请根据处理要求做出处理，并返回结果, 删除选项必须对应到明确的特殊处理要求，不要擅自删除选项。例如，如果处理完后剩余A,B,C三个选项，请返回[A,B,C]"},
        ],
        extra_body={"thinking": {"type": "disabled"}},
        #extra_body={"enable_thinking": True},
        #stream=True
    )
    ##done_thinking = False
    ##json_string=""
    ##thinking_json_string=""
    ##for chunk in completion:
    ##    thinking_chunk = chunk.choices[0].delta.reasoning_content
    ##    answer_chunk = chunk.choices[0].delta.content
    ##    if thinking_chunk != '':
    ##        thinking_json_string = thinking_json_string +  thinking_chunk
    ##    elif answer_chunk != '':
    ##        if not done_thinking:
    ##            done_thinking = True
    ##        json_string = json_string + answer_chunk
    json_string = completion.choices[0].message.content
    #print(completion.choices[0].message.reasoning_content)
    print(json_string)
    if len([x for x in json_string if x != ',' and x != '[' and x != ']' and x != ' ' and (x < 'A' or x > 'M')]) < 5:
        answer=[]
        if 'A' in json_string and len(A) > 0:
            answer.append(A[0])
        if 'B' in json_string and len(A) > 1:
            answer.append(A[1])
        if 'C' in json_string and len(A) > 2:
            answer.append(A[2])
        if 'D' in json_string and len(A) > 3:
            answer.append(A[3])
        if 'E' in json_string and len(A) > 4:
            answer.append(A[4])
        if 'F' in json_string and len(A) > 5:
            answer.append(A[5])
        if 'G' in json_string and len(A) > 6:
            answer.append(A[6])
        if 'H' in json_string and len(A) > 7:
            answer.append(A[7])
        if 'I' in json_string and len(A) > 8:
            answer.append(A[8])
        if 'J' in json_string and len(A) > 9:
            answer.append(A[9])
        return answer
    completion = sfclient.chat.completions.create(
        model=simplemodel(),
        #model="glm-4.5-flash",
        messages=xuanxiang(json_string),
        extra_body={"thinking": {"type": "disabled"}},
        #extra_body={"enable_thinking": False},
    )
    json_string = completion.choices[0].message.content
    print(json_string)
    answer=[]
    if 'A' in json_string and len(A) > 0:
        answer.append(A[0])
    if 'B' in json_string and len(A) > 1:
        answer.append(A[1])
    if 'C' in json_string and len(A) > 2:
        answer.append(A[2])
    if 'D' in json_string and len(A) > 3:
        answer.append(A[3])
    if 'E' in json_string and len(A) > 4:
        answer.append(A[4])
    if 'F' in json_string and len(A) > 5:
        answer.append(A[5])
    if 'G' in json_string and len(A) > 6:
        answer.append(A[6])
    if 'H' in json_string and len(A) > 7:
        answer.append(A[7])
    if 'I' in json_string and len(A) > 8:
        answer.append(A[8])
    if 'J' in json_string and len(A) > 9:
        answer.append(A[9])
    return answer
def aifilter1_2(A, #options
       B, #data
       aiclient,
             qwclient,
              sfclient,
             dw):
    options=[]
    letters = "ABCDEFGHIJKLMN"
    for i in range(len(A)):
        options.append("给定选项" + letters[i]+"，内容为"+A[i] )

    completion = aiclient.chat.completions.create(
        model="glm-4.5-air",
        #model="THUDM/GLM-Z1-9B-0414",
        #model="ernie-speed-128k",
        messages=[
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": " 背景知识：混凝土楼地面是面层，跟混凝土垫层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 背景知识：混凝土（砼）整体面层跟混凝土找平层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 背景知识：混凝土（砼）整体面层跟混凝土垫层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 背景知识：混凝土（砼）找平层跟混凝土垫层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 背景知识：水泥砂浆找平层跟水泥砂浆面层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 背景知识：水泥砂浆找平层跟水泥砂浆保护层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 特殊处理要求一：如果工作内容描述中**没有**明确提到素水泥浆，则**去掉**所有含有“素水泥浆”字样的选项"},
            {"role": "user", "content": " 特殊处理要求二：如果工作内容描述中**没有**明确提到“加浆抹光”，则**去掉**所有含有“加浆抹光”字样的选项"},
            {"role": "user", "content": " 特殊处理要求三：如果工作内容描述中**没有**明确提到混凝土垫层，则**去掉**所有混凝土垫层的选项"},
            {"role": "user", "content": " 特殊处理要求四：如果选项中同时存在“冷轧带肋钢筋”选项和“抗裂基层 热镀锌钢丝网”选项，则去掉热镀锌钢丝网的选项"},
            {"role": "user", "content": " 重要提示：选项指的是给定的A、B、C之类的选项，不是指的工作内容中的可能的1、2、3这样罗列的特征"},
            {"role": "user", "content": " 重要提示：除特殊处理要求提及的内容外，不需考虑选项内容与工作内容是否符合，只需要根据特殊处理要求做出处理"},
            {"role": "user", "content": "问题描述： 给定一段工作内容: " + B['label'] + " " +  B['mc'] + " " + B['tz'] +  "，".join(options) + "。请根据处理要求做出处理，并返回结果,删除选项必须对应到明确的特殊处理要求，不要擅自删除选项.例如，如果处理完后剩余A,B,C三个选项，请返回[A,B,C]"},
        ],
        extra_body={"thinking": {"type": "disabled"}},
        #extra_body={"enable_thinking": True},
        #stream=True
    )
    #done_thinking = False
    #json_string=""
    #thinking_json_string=""
    #for chunk in completion:
    #    thinking_chunk = chunk.choices[0].delta.reasoning_content
    #    answer_chunk = chunk.choices[0].delta.content
    #    if thinking_chunk != '':
    #        thinking_json_string = thinking_json_string +  thinking_chunk
    #    elif answer_chunk != '':
    #        if not done_thinking:
    #            done_thinking = True
    #        json_string = json_string + answer_chunk
    json_string = completion.choices[0].message.content
    #print(completion.choices[0].message.reasoning_content)
    print(json_string)
    if len([x for x in json_string if x != ',' and x != '[' and x != ']' and x != ' ' and (x < 'A' or x > 'M')]) < 5:
        answer=[]
        if 'A' in json_string and len(A) > 0:
            answer.append(A[0])
        if 'B' in json_string and len(A) > 1:
            answer.append(A[1])
        if 'C' in json_string and len(A) > 2:
            answer.append(A[2])
        if 'D' in json_string and len(A) > 3:
            answer.append(A[3])
        if 'E' in json_string and len(A) > 4:
            answer.append(A[4])
        if 'F' in json_string and len(A) > 5:
            answer.append(A[5])
        if 'G' in json_string and len(A) > 6:
            answer.append(A[6])
        if 'H' in json_string and len(A) > 7:
            answer.append(A[7])
        if 'I' in json_string and len(A) > 8:
            answer.append(A[8])
        if 'J' in json_string and len(A) > 9:
            answer.append(A[9])
        return answer
    completion = sfclient.chat.completions.create(
        model=simplemodel(),
        messages=xuanxiang(json_string),
        extra_body={"thinking": {"type": "disabled"}},
        #extra_body={"enable_thinking": False},
    )
    json_string = completion.choices[0].message.content
    print(json_string)
    answer=[]
    if 'A' in json_string and len(A) > 0:
        answer.append(A[0])
    if 'B' in json_string and len(A) > 1:
        answer.append(A[1])
    if 'C' in json_string and len(A) > 2:
        answer.append(A[2])
    if 'D' in json_string and len(A) > 3:
        answer.append(A[3])
    if 'E' in json_string and len(A) > 4:
        answer.append(A[4])
    if 'F' in json_string and len(A) > 5:
        answer.append(A[5])
    if 'G' in json_string and len(A) > 6:
        answer.append(A[6])
    if 'H' in json_string and len(A) > 7:
        answer.append(A[7])
    if 'I' in json_string and len(A) > 8:
        answer.append(A[8])
    if 'J' in json_string and len(A) > 9:
        answer.append(A[9])
    return answer
def aifilter1_3(A, #options
       B, #data
       aiclient,
             qwclient,
              sfclient,
             dw):
    options=[]
    letters = "ABCDEFGHIJKLMN"
    for i in range(len(A)):
        options.append("给定选项" + letters[i]+"，内容为"+A[i] )

    completion = aiclient.chat.completions.create(
        model="glm-4.5-air",
        #model="THUDM/GLM-Z1-9B-0414",
        #model="ernie-speed-128k",
        messages=[
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": " 背景知识：混凝土楼地面是面层，跟混凝土垫层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 背景知识：混凝土（砼）整体面层跟混凝土找平层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 背景知识：混凝土（砼）整体面层跟混凝土垫层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 背景知识：混凝土（砼）找平层跟混凝土垫层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 背景知识：水泥砂浆找平层跟水泥砂浆面层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 背景知识：水泥砂浆找平层跟水泥砂浆保护层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 特殊处理要求：如果工作内容描述中没有明确提到石材面刷防护剂，则去掉所有含有“石材面刷防护剂”字样的选项"},
            {"role": "user", "content": " 重要提示：选项指的是给定的A、B、C之类的选项，不是指的工作内容中的可能的1、2、3这样罗列的特征"},
            {"role": "user", "content": " 重要提示：除特殊处理要求提及的内容外，不需考虑选项内容与工作内容是否符合，只需要根据特殊处理要求做出处理"},
            {"role": "user", "content": "问题描述： 给定一段工作内容: " + B['label'] + " " +  B['mc'] + " " + B['tz'] +  "，".join(options) + "。请根据处理要求做出处理，并返回结果,删除选项必须对应到明确的特殊处理要求，不要擅自删除选项.例如，如果处理完后剩余A,B,C三个选项，请返回[A,B,C]"},
        ],
        extra_body={"thinking": {"type": "disabled"}},
        #extra_body={"enable_thinking": True},
        #stream=True
    )
    #done_thinking = False
    #json_string=""
    #thinking_json_string=""
    #for chunk in completion:
    #    thinking_chunk = chunk.choices[0].delta.reasoning_content
    #    answer_chunk = chunk.choices[0].delta.content
    #    if thinking_chunk != '':
    #        thinking_json_string = thinking_json_string +  thinking_chunk
    #    elif answer_chunk != '':
    #        if not done_thinking:
    #            done_thinking = True
    #        json_string = json_string + answer_chunk
    json_string = completion.choices[0].message.content
    #print(completion.choices[0].message.reasoning_content)
    print(json_string)
    if len([x for x in json_string if x != ',' and x != '[' and x != ']' and x != ' ' and (x < 'A' or x > 'M')]) < 5:
        answer=[]
        if 'A' in json_string and len(A) > 0:
            answer.append(A[0])
        if 'B' in json_string and len(A) > 1:
            answer.append(A[1])
        if 'C' in json_string and len(A) > 2:
            answer.append(A[2])
        if 'D' in json_string and len(A) > 3:
            answer.append(A[3])
        if 'E' in json_string and len(A) > 4:
            answer.append(A[4])
        if 'F' in json_string and len(A) > 5:
            answer.append(A[5])
        if 'G' in json_string and len(A) > 6:
            answer.append(A[6])
        if 'H' in json_string and len(A) > 7:
            answer.append(A[7])
        if 'I' in json_string and len(A) > 8:
            answer.append(A[8])
        if 'J' in json_string and len(A) > 9:
            answer.append(A[9])
        return answer
    completion = sfclient.chat.completions.create(
        model=simplemodel(),
        messages=xuanxiang(json_string),
        extra_body={"thinking": {"type": "disabled"}},
        #extra_body={"enable_thinking": False},
    )
    json_string = completion.choices[0].message.content
    print(json_string)
    answer=[]
    if 'A' in json_string and len(A) > 0:
        answer.append(A[0])
    if 'B' in json_string and len(A) > 1:
        answer.append(A[1])
    if 'C' in json_string and len(A) > 2:
        answer.append(A[2])
    if 'D' in json_string and len(A) > 3:
        answer.append(A[3])
    if 'E' in json_string and len(A) > 4:
        answer.append(A[4])
    if 'F' in json_string and len(A) > 5:
        answer.append(A[5])
    if 'G' in json_string and len(A) > 6:
        answer.append(A[6])
    if 'H' in json_string and len(A) > 7:
        answer.append(A[7])
    if 'I' in json_string and len(A) > 8:
        answer.append(A[8])
    if 'J' in json_string and len(A) > 9:
        answer.append(A[9])
    return answer
def aifilter1(A, #options
       B, #data
       aiclient,
             qwclient,
              sfclient,
             dw):
    options=[]
    letters = "ABCDEFGHIJKLMN"
    for i in range(len(A)):
        options.append("给定选项" + letters[i]+"，内容为"+A[i] )

    completion = aiclient.chat.completions.create(
        model="glm-4.5-air",
        #model="THUDM/GLM-Z1-9B-0414",
        #model="ernie-speed-128k",
        messages=[
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": " 背景知识：混凝土楼地面是面层，跟混凝土垫层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 背景知识：混凝土（砼）整体面层跟混凝土找平层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 背景知识：混凝土（砼）整体面层跟混凝土垫层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 背景知识：混凝土（砼）找平层跟混凝土垫层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 背景知识：水泥砂浆找平层跟水泥砂浆面层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 背景知识：水泥砂浆找平层跟水泥砂浆保护层是不同的施工步骤，不得混淆"},
            {"role": "user", "content": " 特殊处理要求：去掉所有模板工程的选项"},
            {"role": "user", "content": " 特殊处理要求：如果工作内容描述中没有明确涉及水泥砂浆面层，且没有提及水泥砂浆保护层，则去掉所有20mm水泥砂浆楼地面面层的选项.注意，是去除面层，不包括找平层"},
            {"role": "user", "content": " 重要提示：选项指的是给定的A、B、C之类的选项，不是指的工作内容中的可能的1、2、3这样罗列的特征"},
            {"role": "user", "content": " 重要提示：除特殊处理要求提及的内容外，不需考虑选项内容与工作内容是否符合，只需要根据特殊处理要求做出处理"},
            {"role": "user", "content": "问题描述： 给定一段工作内容: " + B['label'] + " " +  B['mc'] + " " + B['tz'] +  "，".join(options) + "。请根据处理要求做出处理，并返回结果, 删除选项必须对应到明确的特殊处理要求，不要擅自删除选项。例如，如果处理完后剩余A,B,C三个选项，请返回[A,B,C]"},
        ],
        extra_body={"thinking": {"type": "disabled"}},
        #extra_body={"enable_thinking": True},
        #stream=True
    )
    #done_thinking = False
    #json_string=""
    #thinking_json_string=""
    #for chunk in completion:
    #    thinking_chunk = chunk.choices[0].delta.reasoning_content
    #    answer_chunk = chunk.choices[0].delta.content
    #    if thinking_chunk != '':
    #        thinking_json_string = thinking_json_string +  thinking_chunk
    #    elif answer_chunk != '':
    #        if not done_thinking:
    #            done_thinking = True
    #        json_string = json_string + answer_chunk
    json_string = completion.choices[0].message.content
    #print(completion.choices[0].message.reasoning_content)
    print(json_string)
    if len([x for x in json_string if x != ',' and x != '[' and x != ']' and x != ' ' and (x < 'A' or x > 'M')]) < 5:
        answer=[]
        if 'A' in json_string and len(A) > 0:
            answer.append(A[0])
        if 'B' in json_string and len(A) > 1:
            answer.append(A[1])
        if 'C' in json_string and len(A) > 2:
            answer.append(A[2])
        if 'D' in json_string and len(A) > 3:
            answer.append(A[3])
        if 'E' in json_string and len(A) > 4:
            answer.append(A[4])
        if 'F' in json_string and len(A) > 5:
            answer.append(A[5])
        if 'G' in json_string and len(A) > 6:
            answer.append(A[6])
        if 'H' in json_string and len(A) > 7:
            answer.append(A[7])
        if 'I' in json_string and len(A) > 8:
            answer.append(A[8])
        if 'J' in json_string and len(A) > 9:
            answer.append(A[9])
        return answer
    completion = sfclient.chat.completions.create(
        #model="glm-4.5-flash",
        model=simplemodel(),
        messages=xuanxiang(json_string),
        extra_body={"thinking": {"type": "disabled"}},
        #extra_body={"enable_thinking": False},
    )
    json_string = completion.choices[0].message.content
    print(json_string)
    answer=[]
    if 'A' in json_string and len(A) > 0:
        answer.append(A[0])
    if 'B' in json_string and len(A) > 1:
        answer.append(A[1])
    if 'C' in json_string and len(A) > 2:
        answer.append(A[2])
    if 'D' in json_string and len(A) > 3:
        answer.append(A[3])
    if 'E' in json_string and len(A) > 4:
        answer.append(A[4])
    if 'F' in json_string and len(A) > 5:
        answer.append(A[5])
    if 'G' in json_string and len(A) > 6:
        answer.append(A[6])
    if 'H' in json_string and len(A) > 7:
        answer.append(A[7])
    if 'I' in json_string and len(A) > 8:
        answer.append(A[8])
    if 'J' in json_string and len(A) > 9:
        answer.append(A[9])
    return answer
def aifilter2(A, #options
       B, #data
       aiclient,
             qwclient,
             dw):
    hit_wumian = False
    for entry in A:
        if entry in obj['wumian']:
            hit_wumian=True

    hit_loumian = False
    loumian_entry = ''
    for entry in A:
        if entry in obj['loumian']:
            hit_loumian=True
            loumian_entry = entry
    if hit_wumian and hit_loumian:
        return [x for x in A if x != loumian_entry]
    return A


def postprocess011105(selected, data, aiclient, qwclient, sfclient, label_name, name_dw):
    prime = aifilter1(selected, data, aiclient, qwclient, sfclient, name_dw)
    time.sleep(1)
    prime = aifilter1_2(prime, data, aiclient, qwclient, sfclient, name_dw)
    time.sleep(1)
    prime = aifilter1_3(prime, data, aiclient, qwclient, sfclient, name_dw)
    time.sleep(1)
    prime = [x for x in prime if not '踢脚线' in x]
    xian = aifilter5(selected, data, aiclient, qwclient, sfclient, name_dw)
    prime = prime + xian
    if '界面剂' in data['tz']:##保温
        if len([ x for x in prime if '第十四章  墙柱面工程 14.1  一般抹灰 14.1.3  保温砂浆及抗裂基层 刷界面剂' in x]) == 0:
            prime.append('第十四章  墙柱面工程 14.1  一般抹灰 14.1.3  保温砂浆及抗裂基层 刷界面剂 混凝土面') ##需要换
    return prime