app.py

import streamlit as st
from hazm import Normalizer, SentenceTokenizer
import os
import docx
from langchain.chat_models import ChatOpenAI
from langchain.schema import SystemMessage, HumanMessage
from rapidfuzz import fuzz
import concurrent.futures
import time
import numpy as np
from hazm import *
import re
import nltk
nltk.download('punkt')

st.markdown("""
    <style>
        .stAppHeader.st-emotion-cache-12fmjuu.e4hpqof0 {
            background-color: rgba(46,59,46, 0.8) !important;  /* سبز متمایل به خاکی */
            color: #2e3b2e !important;  /* رنگ متن روشن */
            font-family: 'Vazirmatn', Tahoma, sans-serif !important;
            padding: 20px !important;  /* فضای داخلی بیشتر */
            border-radius: 10px !important;  /* گوشه‌های گرد */
            box-shadow: 0 4px 8px rgba(0, 0, 0, 0.3) !important;  /* سایه برای برجسته شدن */
        }
    </style>
""", unsafe_allow_html=True)
st.markdown("""
    <style>
    @font-face {
        font-family: 'Roboto';
        src: url('https://fonts.googleapis.com/css2?family=Roboto:wght@400;500;700&display=swap') format('woff2');
        font-weight: 400;
        font-style: normal;
    }
    html, body, [class*="css"] {
        font-family: 'Roboto', Tahoma, sans-serif !important;
        font-weight: 400 !important;
        direction: rtl;
        text-align: right;
ظ        color: #ffffff;
    }
    .stApp {
        background: linear-gradient(to left, #4b5e40, #2e3b2e);
        color: #ffffff;
    }
    [data-testid="stSidebar"] {
        width: 260px !important;
        background-color: #1a2b1e;
        border: none !important;
        padding-top: 20px;
    }
    .menu-item {
        display: flex;
        align-items: center;
        gap: 12px;
        padding: 12px 20px;
        font-size: 16px;
        font-weight: 600;
        color: #d4d4d4;
        cursor: pointer;
        transition: background-color 0.3s ease;
    }
    .menu-item:hover {
        background-color: #2e3b2e;
        color: #b8860b;
    }
    .menu-item img {
        width: 25px;
        height: 25px;
    }
    .stButton>button {
        background-color: #b8860b !important;
        color: #1a2b1e !important;
        font-family: 'Roboto', Tahoma, sans-serif;
        font-weight: 700 !important;
        border-radius: 10px;
        padding: 12px 24px;
        border: none;
        transition: all 0.3s ease;
        font-size: 16px;
        width: 100%;
        margin: 10px 0;
    }
    .stButton>button:hover {
        background-color: #8b6508 !important;
        transform: translateY(-2px);
        box-shadow: 0 4px 8px rgba(0,0,0,0.3);
    }
.header-text {
    text-align: center;
    margin: 20px 0;
    background-color: rgba(26, 43, 30, 0.9);
    padding: 25px;
    border-radius: 15px;
    box-shadow: 0 6px 12px rgba(0,0,0,0.4);
    font-family: 'Roboto', Tahoma, sans-serif; /* اضافه شد */
}
    .subtitle {
        font-size: 18px;
        color: #d4d4d4;
        font-weight: 600;
        margin-top: 10px;
    }
    .chat-message {
        flex-wrap: wrap;
        background-color: rgba(26, 43, 30, 0.95);
        border: 2px solid #b8860b;
        border-radius: 15px;
        padding: 20px;
        margin: 15px 0;
        box-shadow: 0 6px 12px rgba(0,0,0,0.3);
        animation: fadeIn 0.6s ease;
        font-size: 18px;
        color: #d4d4d4;
        font-weight: 600;
        display: flex;
        flex-wrap: wrap;
        align-items: center;
        gap: 15px;
    }
    @keyframes fadeIn {
        from { opacity: 0; transform: translateY(10px); }
        to { opacity: 1; transform: translateY(0); }
    }
    .stTextInput>div>input, .stTextArea textarea {
        background-color: rgba(26, 43, 30, 0.95) !important;
        border-radius: 10px !important;
        border: 1px solid #b8860b !important;
        padding: 12px !important;
        font-family: 'Roboto', Tahoma;
        font-weight: 500;
        font-size: 16px;
        color: #d4d4d4 !important;
    }
    hr {
        border: 1px solid #b8860b;
        margin: 15px 0;
    }
    [data-testid="stSidebar"] > div {
        border: none !important;
    }
</style>
""", unsafe_allow_html=True)


if "authenticated" not in st.session_state:
    st.session_state.authenticated = False

if not st.session_state.authenticated:
    st.markdown('<style>.stTextInput > div[data-baseweb="input"] + div, .stTextInput div:has(div[role="alert"]) { display: none !important; }</style>', unsafe_allow_html=True)
    st.markdown("""
    <style>
        input {
            background-color: #2e3b2e;
            color: gold;
            border: 1px solid gold;
            border-radius: 10px;
            padding: 10px;
        }
    </style>
""", unsafe_allow_html=True)
    st.markdown("""
    <style>
        html, body, [class*="css"] {
            font-family: 'Vazir', sans-serif;
        }
        label {
            font-size: 20px !important;
            color: #ffffff !important;  
            font-weight: 800 !important;
            margin-bottom: 10px !important;
            display: block;
        }
        input[type="text"], 
        input[type="password"], 
        input[type="text"]:focus, 
        input[type="password"]:focus, 
        input[type="text"]:hover, 
        input[type="password"]:hover {
            background-color: #ffffff !important;
            color: #000000 !important;  
            font-size: 18px !important;
            font-family: 'Vazir', sans-serif !important;
        }
        ::placeholder {
            color: #bbbbbb !important;
            opacity: 0.8 !important;
            font-size: 16px;
        }
    </style>
""", unsafe_allow_html=True)

    username = st.text_input("نام کاربری:", placeholder="شناسه  خود را وارد کنید", 
                            label_visibility="visible")

    password = st.text_input("رمز عبور:", placeholder="رمز عبور ", type="password", 
                         label_visibility="visible")
    st.markdown("""
    <style>
        div.stButton > button {
            background-image: url("https://upload.wikimedia.org/wikipedia/commons/5/59/US_Army_Universal_Camouflage_Pattern.jpg");
            background-size: cover;
            background-repeat: no-repeat;
            background-position: center;
            color: #f5deb3;
            font-family: 'Vazir', sans-serif;
            font-size: 20px;
            font-weight: bold;
            padding: 14px 35px;
            border: 2px solid #d4af37;
            border-radius: 14px;
            box-shadow: 0 0 18px rgba(0,0,0,0.6);
            transition: all 0.3s ease-in-out;
        }
        div.stButton > button:hover {
            filter: brightness(1.2);
            box-shadow: 0 0 22px #b8860b;
            transform: scale(1.03);
        }
        div.stButton > button:active {
            transform: scale(0.97);
            box-shadow: 0 0 12px #000;
        }
    </style>
""", unsafe_allow_html=True)

    if st.button("ورود"):
        if username == "admin" and password == "123":
            st.session_state.authenticated = True
            st.rerun()
        else:
            st.markdown("""
                <div style="background-color: rgba(241, 196, 15, 0.6); color: #2e3b2e; padding: 10px; border-radius: 10px; border: 2px solid #2e3b2e; margin-top: 20px; text-align: center; backdrop-filter: blur(5px);">
                    نام کاربری یا رمز عبور اشتباه است.
                </div>
            """, unsafe_allow_html=True)
    st.stop()

with st.sidebar:
    st.image("log.png", use_container_width=True)

    menu_items = [
        ("گزارش عملیاتی", "https://cdn-icons-png.flaticon.com/512/3596/3596165.png", "https://m17idd-reporting.hf.space"),
        ("تاریخچه ماموریت‌ها", "https://cdn-icons-png.flaticon.com/512/709/709496.png", None),
        ("تحلیل داده‌های نظامی", "https://cdn-icons-png.flaticon.com/512/1828/1828932.png", "https://m17idd-test.hf.space"),
        ("مدیریت منابع", "https://cdn-icons-png.flaticon.com/512/681/681494.png", None),
        ("دستیار فرماندهی", "https://cdn-icons-png.flaticon.com/512/3601/3601646.png", None),
        ("تنظیمات امنیتی", "https://cdn-icons-png.flaticon.com/512/2099/2099058.png", None),
        ("پشتیبانی فنی", "https://cdn-icons-png.flaticon.com/512/597/597177.png", None),
    ]

    st.markdown("""
        <link href="https://cdn.jsdelivr.net/gh/rastikerdar/vazir-font@v30.1.0/dist/font-face.css" rel="stylesheet" type="text/css" />
    """, unsafe_allow_html=True)

    for idx, (text, icon, link) in enumerate(menu_items):
        content = f"""
            <div class="menu-item" style="display: flex; align-items: center; margin-bottom: 10px;">
                <img src="{icon}" width="20" height="20" style="margin-left: 10px;" />
                <span style="color: white; font-family: 'Vazir', sans-serif; font-weight: bold;">{text}</span>
            </div>
        """

        if link:
            content = f'<a href="{link}" target="_blank" style="text-decoration: none;">{content}</a>'

        st.markdown(content, unsafe_allow_html=True)

        if idx in [1, 3, 5]:
            st.markdown("<hr style='border-top: 1px solid #555;'/>", unsafe_allow_html=True)

st.markdown("""
    <style>
        .header-text {
            text-align: center;
            margin: 50px 0;
            background: #2e3b2e; 
            padding: 60px 30px;
            border-radius: 25px;
            box-shadow: 0 12px 24px rgba(0, 0, 0, 0.8); 
            animation: slideIn 2s ease-in-out, fadeIn 3s ease-in-out;
            background-size: cover;
            background-position: center;
            position: relative;
        }
        @keyframes fadeIn {
            0% { opacity: 0; transform: translateY(30px); }
            100% { opacity: 1; transform: translateY(0); }
        }
        @keyframes slideIn {
            0% { transform: translateX(-50%); opacity: 0; }
            100% { transform: translateX(0); opacity: 1; }
        }
        .header-text h1 {
            font-family: 'Vazir', sans-serif;
            font-size: 62px;
            color: #d89b00; 
            margin: 0;
            font-weight: 900;
            letter-spacing: 4px;
            text-shadow: 4px 4px 15px rgba(0, 0, 0, 0.9); 
            transform: scale(1.08); 
            animation: glow 2s ease-in-out infinite alternate;
        }
        .subtitle {
            font-family: 'Vazir', sans-serif;
            font-size: 24px;
            color: #f8f8f8;
            font-weight: 700;
            margin-top: 15px;
            letter-spacing: 2px;
            text-shadow: 3px 3px 10px rgba(0,0,0,0.8); 
            animation: fadeInSubtitle 2s ease-in-out;
        }
        @keyframes fadeInSubtitle {
            0% { opacity: 0; transform: translateY(20px); }
            100% { opacity: 1; transform: translateY(0); }
        }
        .stButton>button {
            background-color: #e67e22 !important; 
            color: #4b5320 !important;
            font-family: 'Vazir', sans-serif;
            font-weight: 700 !important;
            border-radius: 20px;
            padding: 15px 30px;
            border: none;
            transition: all 0.3s ease;
            font-size: 18px;
            width: 100%;
            margin: 20px 0;
            box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
        }
        .stButton>button:hover {
            background-color: #f39c12 !important;
            transform: translateY(-4px);
            box-shadow: 0 8px 20px rgba(0, 0, 0, 0.6);
        }
        .stApp {
            background: #2e3b2e; 
            color: white;
            font-family: 'Vazir', sans-serif;
        }
    </style>
    <div class="header-text">
        <h1>رزم‌‌یار‌ارتش</h1>
        <div class="subtitle">دستیارهوشمندارتش جمهوری اسلامی ایران</div>
    </div>
""", unsafe_allow_html=True)

llm = ChatOpenAI(
    base_url="https://api.together.xyz/v1",
    api_key='0291f33aee03412a47fa5d8e562e515182dcc5d9aac5a7fb5eefdd1759005979',
    model="meta-llama/Llama-3.3-70B-Instruct-Turbo-Free",
    max_tokens=1024  # specify the max tokens as per your requirement

)


st.markdown("""
    <style>
        .st-emotion-cache-128upt6.eht7o1d3 {
            background-color: rgba(46,59,46, 0.8) !important;  /* سبز تیره (44533f) */
            border-radius: 10px !important;  /* گوشه‌های گرد */
            color: #d4d4d4 !important;  /* رنگ متن روشن */
            font-family: 'Vazirmatn', Tahoma, sans-serif !important;
            padding: 15px !important;  /* فضای داخلی بیشتر */
            box-shadow: 0 4px 8px rgba(0, 0, 0, 0.3) !important;  /* سایه برای برجسته شدن */
        }
    </style>
""", unsafe_allow_html=True)


st.markdown("""
<style>
    .st-af.st-ah.st-bb.st-ar.st-as.st-ax.st-ay.st-az.st-b0.st-b1.st-b2.st-bc.st-b7 {
        background-color: #3a5338 !important;
        color: #d4d4d4 !important;
        border: 1px solid #c8a200 !important;
        border-radius: 10px;
        padding: 15px;
    }
</style>
""", unsafe_allow_html=True)

st.markdown("""
    <style>
        .st-emotion-cache-yd4u6l.e1togvvn1 {
            background-color: rgba(106, 127, 83, 0.8) !important;  
            border-radius: 10px !important; 
            color: #d4d4d4 !important;  
            font-family: 'Vazirmatn', Tahoma, sans-serif !important;
            padding: 15px !important;  
            box-shadow: 0 4px 8px rgba(0, 0, 0, 0.3) !important; 
        }
    </style>
""", unsafe_allow_html=True)
st.markdown("""
    <style>
        .stAppHeader.st-emotion-cache-12fmjuu.e4hpqof0 {
            background-color: rgba(42, 55, 39, 0.9) !important;
            color: #d4d4d4 !important;  
            font-family: 'Vazirmatn', Tahoma, sans-serif !important;
            padding: 20px !important; 
            border-radius: 10px !important; 
            box-shadow: 0 4px 8px rgba(0, 0, 0, 0.3) !important;  
        }
    </style>
""", unsafe_allow_html=True)

st.markdown("""
<style>
textarea::placeholder {
    color: #ffffff !important; 
    opacity: 1 !important; 
}
textarea {
    color: #ffffff !important; 
    border-radius: 10px !important;
    padding: 10px !important;
}
</style>
""", unsafe_allow_html=True)
query = st.chat_input("چطور می‌تونم کمک کنم؟")


if query:
    st.markdown(f'<div class="chat-message">{query}</div>', unsafe_allow_html=True)
    
    think = st.markdown("""
    <div class="thinking-message">
        <p>در حال فکر کردن...</p>
        <div class="spinner"></div>
    </div>
    """, unsafe_allow_html=True)
   
else:
    st.markdown("")

st.markdown("""
    <style>
    .thinking-message {
        display: flex;
        align-items: center;
        font-size: 18px;
        color: #ffffff;
    }
    .thinking-message p {
        margin-right: 10px;
    }
    .spinner {
        border: 4px solid #f3f3f3;
        border-top: 4px solid #4b6d3d;
        border-radius: 50%;
        width: 20px;
        height: 20px;
        animation: spin 2s linear infinite;
    }
    @keyframes spin {
        0% { transform: rotate(0deg); }
        100% { transform: rotate(360deg); }
    }
    </style>
""", unsafe_allow_html=True)



import os
import re
import docx
import streamlit as st
import concurrent.futures
from hazm import Normalizer
from rapidfuzz import fuzz
from langchain.schema import SystemMessage, HumanMessage

folder_path = '46'
normalizer = Normalizer()

@st.cache_data(show_spinner="در حال پردازش اسناد... لطفاً صبور باشید.")
def load_and_process_documents(path):
    def process_docx(filename):
        try:
            full_path = os.path.join(path, filename)
            doc = docx.Document(full_path)
            text = "\n".join([para.text for para in doc.paragraphs])
            normalized = normalizer.normalize(text)
            return filename, normalized
        except Exception as e:
            print(f"Error processing {filename}: {e}")
            return filename, ""

    filenames = [f for f in os.listdir(path) if f.endswith(".docx")]
    doc_texts = {}

    with concurrent.futures.ThreadPoolExecutor() as executor:
        for filename, content in executor.map(process_docx, filenames):
            doc_texts[filename] = content

    return doc_texts

doc_texts = load_and_process_documents(folder_path)

with open('stopwords.txt', 'r', encoding='utf-8') as file:
    stop_words = set(file.read().splitlines())

def remove_stop_words(text, stop_words):
    words = text.split()
    return " ".join([word for word in words if word not in stop_words])

def extract_keywords_from_text(text, query_words):
    matched_lines = []
    lines = text.split("\n")
    
    for line in lines:
        if any(query_word in line for query_word in query_words):
            matched_lines.append(line)
    return matched_lines

def clean_text(text):
    return re.sub(r'[^آ-ی۰-۹0-9،.؟!؛+\-* ]+', '', text)


from collections import Counter
import heapq

def summarize_text_by_frequency(text, num_sentences=1):
    sentences = text.split('\n')
    word_freq = Counter()

    for sentence in sentences:
        for word in sentence.split():
            if word not in stop_words:
                word_freq[word] += 1

    sentence_scores = {}
    for sentence in sentences:
        for word in sentence.split():
            if word in word_freq:
                sentence_scores[sentence] = sentence_scores.get(sentence, 0) + word_freq[word]

    summarized_sentences = heapq.nlargest(num_sentences, sentence_scores, key=sentence_scores.get)
    return "\n".join(summarized_sentences)

    

def find_closest_lines(query, doc_texts, stop_words, top_n=5):
    cleaned_query = remove_stop_words(query, stop_words)
    query_words = cleaned_query.split()

    all_matched_lines = []
    
    for filename, text in doc_texts.items():
        matched_lines = extract_keywords_from_text(text, query_words)
        for line in matched_lines:
            similarity = fuzz.partial_ratio(query, line)  
            all_matched_lines.append((line, similarity))
    
    all_matched_lines.sort(key=lambda x: x[1], reverse=True)

    closest_lines = [line for line, _ in all_matched_lines[:top_n]]

    return closest_lines

def remove_stop_words_from_lines(lines, stop_words):
    cleaned_lines = []
    for line in lines:
        words = line.split()
        cleaned_words = [word for word in words if word not in stop_words]
        cleaned_lines.append(" ".join(cleaned_words))
    return cleaned_lines

if query:
    closest_lines = find_closest_lines(query, doc_texts, stop_words, top_n=5)

    cleaned_closest_lines = [
        clean_text(" ".join([word for word in line.split() if word not in stop_words]))
        for line in closest_lines
    ]

    summarized_text = summarize_text_by_frequency("\n".join(cleaned_closest_lines), num_sentences=1)

    if summarized_text:
        prompt = f"""
        تعدادی جمله مرتبط با سوال زیر استخراج شده است. لطفاً ابتدا این جملات را بررسی کن، سپس با در نظر گرفتن محتوای سوال و لحن آن، یک پاسخ نهایی حرفه‌ای، دقیق و روان ارائه کن که هم به سوال پاسخ دهد و هم از نظر نگارشی و ساختاری در سطح بالایی باشد. پاسخ نهایی باید حداکثر 1024 کاراکتر و حداقل 512 کاراکتر باشد، خلاصه و واضح نوشته شود و فقط به زبان فارسی باشد. از تکرار اضافی پرهیز کن و در صورت نیاز، محتوای جملات را ترکیب کن.
        سوال:
        {query}
        جملات مرتبط:
        {summarized_text}
        پاسخ نهایی حرفه‌ای بازنویسی‌شده:
        """
        response = llm([
            SystemMessage(content="You are a helpful assistant."),
            HumanMessage(content=prompt)
        ])
        rewritten = response.content.strip()

        review_prompt = f"""
        لطفاً بررسی کن که آیا پاسخ زیر به سوال داده‌شده مرتبط، صحیح، معتبر و قابل قبول است یا نه. اگر پاسخ مرتبط و صحیح است، فقط بنویس: 'تأیید شد'. اگر پاسخ اشتباه است یا ربطی به سوال ندارد یا معتبر نیست، فقط بنویس: 'نیاز به اصلاح دارد'.
        سوال:
        {query}
        پاسخ:
        {rewritten}
        """
        review_response = llm([
            SystemMessage(content="You are a helpful assistant."),
            HumanMessage(content=review_prompt)
        ])
        review_result = review_response.content.strip()

        if "تأیید شد" in review_result:
            rewritten = clean_text(rewritten)
            st.markdown(f'<div class="chat-message">{rewritten}</div>', unsafe_allow_html=True)
            think.empty()  
    else:
        prompt = f"""
        هیچ جمله مرتبط مستقیمی با سوال یافت نشد. لطفاً با توجه به سوال زیر، یک پاسخ حرفه‌ای، مرتبط، معنادار و معتبر تولید کن. فقط از جملات موجود در اسناد معتبر استفاده کن و از ساخت جملات ساختگی یا استفاده از زبان غیر فارسی خودداری کن.
        سوال:
        {query}
        """
        response = llm([
            SystemMessage(content="You are a helpful assistant."),
            HumanMessage(content=prompt)
        ])
        rewritten = clean_text(response.content.strip())
        st.markdown(f'<div class="chat-message">{rewritten}</div>', unsafe_allow_html=True)
        think.empty()