app.py

import streamlit as st
import pandas as pd
import json
import requests
import os

glm2b = pd.read_csv('glm2b-nk.csv')
glm10b = pd.read_csv('glm10b-nk.csv')
gptj = pd.read_csv('gptj-nk.csv')
gptjt = pd.read_csv('gptjt-nk.csv')

glm2b_orig = glm2b[['persona', 'knowledge', 'context', 'prompted text', 'ground truth', 'origin']].rename(columns={'origin': 'inference'})
glm2b_para = glm2b[['persona', 'knowledge', 'context', 'prompted text', 'ground truth', 'parallel']].rename(columns={'parallel': 'inference'})
glm10b_orig = glm10b[['persona', 'knowledge', 'context', 'prompted text', 'ground truth', 'origin']].rename(columns={'origin': 'inference'})
glm10b_para = glm10b[['persona', 'knowledge', 'context', 'prompted text', 'ground truth', 'parallel']].rename(columns={'parallel': 'inference'})
gptj_orig = gptj[['persona', 'knowledge', 'context', 'prompted text', 'ground truth', 'origin']].rename(columns={'origin': 'inference'})
gptj_para = gptj[['persona', 'knowledge', 'context', 'prompted text', 'ground truth', 'parallel']].rename(columns={'parallel': 'inference'})
gptjt_orig = gptjt[['persona', 'knowledge', 'context', 'prompted text', 'ground truth', 'origin']].rename(columns={'origin': 'inference'})
gptjt_para = gptjt[['persona', 'knowledge', 'context', 'prompted text', 'ground truth', 'parallel']].rename(columns={'parallel': 'inference'})

csv_map = [glm2b_orig, glm2b_para, glm10b_orig, glm10b_para, gptj_orig, gptj_para, gptjt_orig, gptjt_para]

truth = glm2b['ground truth'].to_list()
users = json.load(open('data/users.json'))


def new_data(user_data):
    process_bar.progress((user_data['all_process']-user_data['start_process'])/(user_data['stop_process']-user_data['start_process']), text='进度')
    if user_data['all_process'] == user_data['stop_process']:
        return 'finish'
    csv_idx = user_data['model_list'][user_data['all_process']]
    sample = csv_map[csv_idx].iloc[user_data['data_idx'][csv_idx][user_data['process'][csv_idx]]]
    persona = sample.persona.split('\n')
    new_p = []
    for pi in persona:
        new_p += [pi[i:i+60] for i in range(0, len(pi), 60)]
    new_p = '\n'.join(new_p)
    knowledge = sample.knowledge.split('\n')
    new_k = []
    for ki in knowledge:
        new_k += [ki[i:i+60] for i in range(0, len(ki), 60)]
    new_k = '\n'.join(new_k)
    context = sample.context.split('\n')
    context.remove(context[-1])
    new_c = []
    for ci in context:
        new_c += [ci[i:i+120] for i in range(0, len(ci), 120)]
    new_c = '\n'.join(new_c)
    gtruth = sample['ground truth'].split('\n')
    new_g = []
    for gi in gtruth:
        new_g += [gi[i:i+60] for i in range(0, len(gi), 60)]
    new_g = '\n'.join(new_g)
    inf = sample.inference.split('\n')
    new_i = []
    for ii in inf:
        new_i += [ii[i:i+60] for i in range(0, len(ii), 60)]
    new_i = '\n'.join(new_i)
    p.text(new_p)
    k.text(new_k)
    c.text(new_c)
    g.text(new_g)
    infer.text(new_i)
    return 'not finish'


st.set_page_config(layout="wide")
st.title('FoCus Annotation')

t1, t2 = st.columns(2)
with t1:
    username = st.text_input("请输入用户名")
with t2:
    password = st.text_input("请输入密码", type="password")

login_btn = st.button('登录')

col1, col2 = st.columns(2)
with col1:
    with st.expander("人设"):
            p = st.empty()
    
with col2:
    with st.expander("知识"):
        k = st.empty()

with st.expander('对话上下文'):
    c = st.empty()

a1, a2 = st.columns(2)
with a1:
    st.markdown("**真实值**")
    g = st.empty()
with a2:
    st.markdown("**待标注样本**")
    infer = st.empty()

cc, kc, pc, hc, fc = st.columns(5)
with st.container():
    with cc:
        cs = st.selectbox("对话一致性", [0,1,2], key='cs')
    with kc:
        ks = st.selectbox("知识一致性", [0,1,2], key='ks')
    with pc:
        ps = st.selectbox("人设一致性", [0,1,2], key='ps')
    with hc:
        hs = st.selectbox("精炼度", [0,1,2], key='hs')
    with fc:
        fs = st.selectbox("流畅度", [0,1,2], key='fs')

process_bar = st.progress(0.0, text='进度')

col3, col4 = st.columns(2)
with st.container():
    with col3:
        prev = st.button('上一个')
    with col4:
        succ = st.button('下一个')


if username in users and users[username] == password:
    data = {'FocusUser': username}
    user_data=requests.post(os.environ.get("URL"), data=json.dumps(data, ensure_ascii=False).encode('utf-8')).content
    user_data = json.loads(str(user_data, encoding="utf-8"))
    # user_data = json.load(open(f'data/{username}.json'))
    result = new_data(user_data)
else:
    p.text("登录后开始标注")
    c.text("登录后开始标注")
    g.text("登录后开始标注")
    k.text("登录后开始标注")
    infer.text("登录后开始标注")


if login_btn:
    if username in users and users[username] == password:
        st.success('登录成功')
        data = {'FocusUser': username}
        user_data=requests.post(os.environ.get("URL"), data=json.dumps(data, ensure_ascii=False).encode('utf-8')).content
        user_data = json.loads(str(user_data, encoding="utf-8"))
        # user_data = json.load(open(f'data/{username}.json'))
        result = new_data(user_data)
        if result == 'finish':
            st.success('您已完成标注')
    else:
        username = ''
        password = ''
        st.error('用户名或密码错误，请先注册。若已有账号，但忘记密码，请联系管理员修改密码')


if succ:
    if username in users and users[username] == password:
        data = {'FocusUser': username}
        user_data=requests.post(os.environ.get("URL"), data=json.dumps(data, ensure_ascii=False).encode('utf-8')).content
        user_data = json.loads(str(user_data, encoding="utf-8"))
        # user_data = json.load(open(f'data/{username}.json'))
        data_idx, process, all_process, model_list = user_data['data_idx'], user_data['process'], user_data['all_process'], user_data['model_list']
        if all_process == user_data['stop_process']:
            st.success('您已完成标注')
        else:
            csv_idx = model_list[all_process]
            sample = csv_map[csv_idx].iloc[data_idx[csv_idx][process[csv_idx]]]
            user_data['context_relevance'][csv_idx][process[csv_idx]%100] = cs
            user_data['knowledge_relevance'][csv_idx][process[csv_idx]%100] = ks
            user_data['persona_consistency'][csv_idx][process[csv_idx]%100] = ps
            user_data['hallucination'][csv_idx][process[csv_idx]%100] = hs
            user_data['fluency'][csv_idx][process[csv_idx]%100] = fs
            user_data['process'][csv_idx] += 1
            user_data['all_process'] += 1
            data = {'Focus': user_data, 'username': username}
            requests.post(os.environ.get("URL"), data=json.dumps(data, ensure_ascii=False).encode('utf-8'))
            # json.dump(user_data, open(f'data/{username}.json', 'w'), ensure_ascii=False, indent=2)
            result = new_data(user_data)
            if result == 'finish':
                st.success('您已完成标注')
    else:
        st.error('请先登录')


if prev:
    if username in users and users[username] == password:
        data = {'FocusUser': username}
        user_data=requests.post(os.environ.get("URL"), data=json.dumps(data, ensure_ascii=False).encode('utf-8')).content
        user_data = json.loads(str(user_data, encoding="utf-8"))
        # user_data = json.load(open(f'data/{username}.json'))
        model_list = user_data['model_list']
        if user_data['all_process'] == user_data['start_process']:
            result = new_data(user_data)
            st.error('已是首个数据')
        else:
            user_data['all_process'] -= 1
            csv_idx = model_list[user_data['all_process']]
            user_data['process'][csv_idx] -= 1
            result = new_data(user_data)
            data = {'Focus': user_data, 'username': username}
            requests.post(os.environ.get("URL"), data=json.dumps(data, ensure_ascii=False).encode('utf-8'))
            # json.dump(user_data, open(f'data/{username}.json', 'w'), ensure_ascii=False, indent=2)
    else:
        st.error('请先登录')