army / app.py
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Update app.py
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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
# from sentence_transformers import SentenceTransformer
import numpy as np
from hazm import *
import re
import nltk
nltk.download('punkt')
st.set_page_config(
page_title="رزم یار",
page_icon="⚔️",
layout="wide"
)
st.markdown("""
<style>
.stAppHeader.st-emotion-cache-12fmjuu.e4hpqof0 {
background-color: rgba(46,59,46, 0.8) !important;
color: #2e3b2e !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>
@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 style */
::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>رزم‌‌یار‌ ارتش</h1>
<div class="subtitle">دستیارهوشمند ارتش جمهوری اسلامی ایران</div>
</div>
""", unsafe_allow_html=True)
# from transformers import pipeline
# hf_api_key = os.getenv("tavana55")
# model_name = "Qwen/Qwen3-0.6B"
# llm = pipeline("text-generation", model=model_name)
st.markdown("""
<style>
.st-emotion-cache-128upt6.eht7o1d3 {
background-color: rgba(46,59,46, 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>
.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)
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 json
import requests
import streamlit as st
import numpy as np
from langchain.schema import SystemMessage, HumanMessage
from langchain.chat_models import ChatOpenAI
from sklearn.metrics.pairwise import cosine_similarity
llm = ChatOpenAI(
base_url="https://api.together.xyz/v1",
api_key='333ac33f5be91819cb7ade101134d73f5e63d299a964ae290850eeac5d82a8d5',
model="meta-llama/Llama-3.3-70B-Instruct-Turbo",
)
EMBEDDING_FILE = "embeddings.json"
EMBEDDING_MODEL = "intfloat/multilingual-e5-large-instruct"
TOGETHER_API_KEY = "333ac33f5be91819cb7ade101134d73f5e63d299a964ae290850eeac5d82a8d5"
@st.cache_data
def load_embeddings(file_path):
with open(file_path, "r", encoding="utf-8") as f:
return json.load(f)
def get_query_embedding_together(query):
url = "https://api.together.xyz/v1/embeddings"
headers = {
"Authorization": f"Bearer {TOGETHER_API_KEY}",
"accept": "application/json",
"content-type": "application/json"
}
payload = {
"model": EMBEDDING_MODEL,
"input": query
}
response = requests.post(url, headers=headers, json=payload)
response.raise_for_status()
return response.json()["data"][0]["embedding"]
def find_most_similar_chunks(query_embedding, data, top_n=20):
query_vec = np.array(query_embedding).reshape(1, -1)
similarities = []
for item in data:
chunk_vec = np.array(item["embedding"]).reshape(1, -1)
sim = cosine_similarity(query_vec, chunk_vec)[0][0]
similarities.append((item["chunk"], sim))
similarities.sort(key=lambda x: x[1], reverse=True)
return [chunk for chunk, _ in similarities[:top_n]]
def clean_text(text):
import re
return re.sub(r'[^آ-یa-zA-Z0-9۰-۹,.،؟!؛\s]+', '', text)
query = st.chat_input("چطور می‌تونم کمک کنم؟")
if "chat_history" not in st.session_state:
st.session_state.chat_history = []
if query:
thinking = st.empty()
thinking.markdown("⏳ در حال پردازش...")
try:
query_embedding = get_query_embedding_together(query)
data = load_embeddings(EMBEDDING_FILE)
top_chunks = find_most_similar_chunks(query_embedding, data, top_n=20)
context = "\n".join(top_chunks)
prompt = f"""
به سؤال زیر فقط بر اساس اطلاعات موجود در خطوط مرتبط پاسخ بده
از تحلیل، مقدمه‌چینی، توضیح مراحل تفکر، یا حدس شخصی خودداری کن
اگر اطلاعات کافی برای پاسخ دقیق در خطوط مرتبط وجود نداشت، فقط در آن صورت
می‌توانی از دانش عمومی خود استفاده کنی تا یک پاسخ حرفه‌ای و دقیق ارائه دهی
پاسخ باید نهایی، روان، و در حدود 256 تا 1024 کاراکتر باشد اگر در دیتا موجود نبود نزدیک ترین پاسخ به متن
سوال:
{query}
خطوط مرتبط:
{top_chunks}
پاسخ نهایی:
"""
response = llm([
SystemMessage(
content=" تو یک دستیار دقیق هستی که فقط با اطلاعات موجود در متن پاسخ می‌دهی و اگر در متن موجود نبود از شبیه ترین پاسخ به دیتای متن "
),
HumanMessage(content=prompt)
])
final_answer = clean_text(response.content.strip())
except Exception as e:
final_answer = f"❗ خطا: {str(e)}"
thinking.empty()
st.session_state.chat_history.append(("🧑", query))
st.session_state.chat_history.append(("🤖", final_answer))
st.markdown("""
<style>
@import url('https://cdn.fontcdn.ir/Font/Persian/Vazir/Vazir.css');
div.chat-message {
font-family: 'Vazir', sans-serif;
font-size: 16px;
color: white;
background-color: #0d4d31;
padding: 10px;
border-radius: 10px;
margin-bottom: 5px;
}
</style>
""", unsafe_allow_html=True)
st.markdown("---")
for sender, message in st.session_state.chat_history:
st.markdown(f'<div class="chat-message"><strong>{sender}</strong>: {message}</div>', unsafe_allow_html=True)