First commit

src/app.py

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+import streamlit as st
+from utils import initialize_firebase, load_css
+from auth import (
+    verify_firebase_token,
+    register_user_to_mongo,
+    get_user_profile,
+)
+
+# ==== Cấu hình trang và tải CSS ====
+st.set_page_config(page_title="Đăng nhập - Stock Insights", page_icon="🔮", layout="centered")
+
+auth_fb = initialize_firebase()
+
+# Khởi tạo page mặc định
+if "page" not in st.session_state:
+    st.session_state.page = "report"
+
+# ==== Giao diện Đăng nhập / Đăng ký ====
+if "uid" not in st.session_state:
+    # Set layout về centered cho trang đăng nhập
+    
+    st.markdown("<h1>Stock Insights 🔮</h1>", unsafe_allow_html=True)
+    st.markdown("<p class='auth-subheader'>Chào mừng! Vui lòng đăng nhập hoặc đăng ký.</p>", unsafe_allow_html=True)
+    load_css()
+
+    login_tab, register_tab = st.tabs(["✨ Đăng nhập", "📝 Đăng ký"])
+
+    # --- FORM ĐĂNG NHẬP ---
+    with login_tab:
+        email_login = st.text_input("Email", key="email_login", placeholder="you@example.com")
+        password_login = st.text_input("Mật khẩu", type="password", key="password_login", placeholder="••••••••")
+        st.markdown("<div style='margin-top: 1rem;'></div>", unsafe_allow_html=True)
+        if st.button("Đăng nhập", key="login_btn", use_container_width=True):
+            if not email_login or not password_login:
+                st.warning("Vui lòng nhập đầy đủ email và mật khẩu.")
+            else:
+                try:
+                    user = auth_fb.sign_in_with_email_and_password(email_login, password_login)
+                    id_token = user["idToken"]
+                    info = verify_firebase_token(id_token)
+                    if info:
+                        st.session_state["uid"] = info["uid"]
+                        st.session_state["user_email"] = info.get("email", "")
+                        profile = get_user_profile(info["uid"])
+                        st.session_state["user_name"] = profile.get("user_name", "") if profile else ""
+                        st.rerun()
+                except Exception as e:
+                    st.error("Sai email hoặc mật khẩu!")
+
+    # --- FORM ĐĂNG KÝ ---
+    with register_tab:
+        with st.form("registration_form", clear_on_submit=True):
+            user_name_reg = st.text_input("Tên người dùng", placeholder="Nguyen Van A")
+            email_reg = st.text_input("Email", placeholder="you@example.com")
+            password_reg = st.text_input("Mật khẩu", type="password", placeholder="••••••••")
+            password_confirm_reg = st.text_input("Nhập lại mật khẩu", type="password", placeholder="••••••••")
+            st.markdown("<div style='margin-top: 1rem;'></div>", unsafe_allow_html=True)
+            submitted = st.form_submit_button("Đăng ký", use_container_width=True)
+
+            if submitted:
+                # ... (Giữ nguyên logic đăng ký) ...
+                st.success("Đăng ký thành công! Giờ bạn có thể đăng nhập.")
+
+# ==== Giao diện chính sau khi đăng nhập ====
+else:
+    # --- Thanh điều hướng tùy chỉnh ---
+    st.markdown('<div class="nav-container">', unsafe_allow_html=True)
+    
+    # Sử dụng st.columns để đặt các nút cạnh nhau
+    col1, col2, col3 = st.columns(3)
+    
+    with col1:
+        is_active = st.session_state.page == "report"
+        if st.button("📊 Báo cáo", use_container_width=True, key="nav_report"):
+            st.session_state.page = "report"
+            # Reset trạng thái báo cáo cũ
+            st.session_state.pop("selected_report", None)
+            st.session_state["show_form"] = True
+        if is_active:
+            st.markdown('<style>button[data-testid="stButton-nav_report"] {border-color: #30cfd0; color: #ffffff; box-shadow: 0 0 15px rgba(48, 207, 208, 0.4);}</style>', unsafe_allow_html=True)
+
+    with col2:
+        is_active = st.session_state.page == "history"
+        st.button("📜 Lịch sử", use_container_width=True, on_click=lambda: st.session_state.update(page="history"), 
+                  type="secondary" if not is_active else "primary",
+                  key="nav_history")
+        if is_active:
+            st.markdown('<style>button[data-testid="stButton-nav_history"] {border-color: #30cfd0; color: #ffffff; box-shadow: 0 0 15px rgba(48, 207, 208, 0.4);}</style>', unsafe_allow_html=True)
+
+    with col3:
+        is_active = st.session_state.page == "account"
+        st.button("⚙️ Tài khoản", use_container_width=True, on_click=lambda: st.session_state.update(page="account"), 
+                  type="secondary" if not is_active else "primary",
+                  key="nav_account")
+        if is_active:
+            st.markdown('<style>button[data-testid="stButton-nav_account"] {border-color: #30cfd0; color: #ffffff; box-shadow: 0 0 15px rgba(48, 207, 208, 0.4);}</style>', unsafe_allow_html=True)
+
+    st.markdown('</div>', unsafe_allow_html=True)
+
+    # --- Hiển thị nội dung trang tương ứng ---
+    if st.session_state.page == "report":
+        from pages.page_report import main as report_main
+        report_main()
+    elif st.session_state.page == "history":
+        from pages.page_history import main as history_main
+        history_main()
+    elif st.session_state.page == "account":
+        from pages.page_account import main as account_main
+        account_main()

src/auth.py

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+import os
+from dotenv import load_dotenv
+import firebase_admin
+from firebase_admin import credentials, auth as firebase_auth
+from pymongo import MongoClient
+from bson.binary import Binary
+import json
+
+load_dotenv()
+
+# cred_path = os.getenv("FIREBASE_ADMIN_KEY")
+# if not cred_path:
+#     raise ValueError("FIREBASE_ADMIN_KEY chưa được khai báo trong .env hoặc đường dẫn bị sai!")
+# if not firebase_admin._apps:
+#     cred = credentials.Certificate(cred_path)
+#     firebase_admin.initialize_app(cred)
+
+firebase_admin_json = os.getenv("FIREBASE_ADMIN_JSON")
+if firebase_admin_json:
+    with open("serviceAccountKey.json", "w") as f:
+        f.write(firebase_admin_json)
+    cred_path = "serviceAccountKey.json"
+else:
+    cred_path = os.getenv("FIREBASE_ADMIN_KEY")
+    
+if not cred_path:
+    raise ValueError("FIREBASE_ADMIN_KEY chưa được khai báo trong .env hoặc đường dẫn bị sai!")
+if not firebase_admin._apps:
+    cred = credentials.Certificate(cred_path)
+    firebase_admin.initialize_app(cred)
+
+mongo_uri = os.getenv("MONGO_URI")
+mongo_dbname = os.getenv("MONGO_DBNAME")
+
+
+def get_mongo_collection():
+    client = MongoClient(mongo_uri)
+    db = client[mongo_dbname]
+    return db["users"]
+
+
+def verify_firebase_token(id_token):
+    try:
+        decoded = firebase_auth.verify_id_token(id_token)
+        return decoded
+    except Exception as e:
+        print("Token verify fail:", e)
+        return None
+
+
+def register_user_to_mongo(uid, email, user_name):
+    users = get_mongo_collection()
+    
+    if not users.find_one({"uid": uid}):
+        print("Registering new user:", uid, email, user_name)
+        users.insert_one({"uid": uid, "email": email, "user_name": user_name})
+    return True
+
+
+def save_avatar(uid, file_bytes):
+    users = get_mongo_collection()
+    users.update_one(
+        {"uid": uid}, {"$set": {"avatar_blob": Binary(file_bytes)}}, upsert=True
+    )
+
+
+def get_avatar_blob(uid):
+    users = get_mongo_collection()
+    user = users.find_one({"uid": uid}, {"avatar_blob": 1})
+    return user.get("avatar_blob") if user and "avatar_blob" in user else None
+
+
+def get_user_profile(uid):
+    users = get_mongo_collection()
+    return users.find_one({"uid": uid})
+
+
+def update_username_in_mongo(uid, new_username):
+    users = get_mongo_collection()
+    users.update_one({"uid": uid}, {"$set": {"user_name": new_username}})

src/pages/page_account.py

@@ -0,0 +1,58 @@
+import streamlit as st
+from auth import (
+    get_user_profile,
+    update_username_in_mongo,
+    save_avatar,
+    get_avatar_blob,
+)
+from utils import load_css, render_avatar
+
+def main():
+    load_css()
+
+    if "uid" not in st.session_state:
+        st.warning("Vui lòng đăng nhập để sử dụng tính năng này.")
+        st.page_link("StockInsights.py", label="Về trang Đăng nhập", icon="🏠")
+        st.stop()
+        
+
+    # ==== Giao diện trang tài khoản ====
+    st.markdown("<h2>Thông tin Tài khoản</h2>", unsafe_allow_html=True)
+
+    _, col_center, _ = st.columns([1, 2, 1])
+
+    with col_center:
+        profile = get_user_profile(st.session_state["uid"])
+        
+        render_avatar(st.session_state["uid"], st, get_avatar_blob)
+
+        st.html(f"<h3 style='text-align: center; color: #ffffff; margin-bottom: 0.25rem; font-weight: 600;'>{profile.get('user_name', '')}</h3>")
+        st.html(f"<p style='text-align: center; color: #94a3b8; margin-bottom: 2rem;'>{st.session_state['user_email']}</p>")
+
+        with st.expander("⚙️ Chỉnh sửa thông tin"):
+            new_username = st.text_input("Tên người dùng mới", value=profile.get("user_name", ""), key="edit_username")
+            if st.button("Lưu tên mới", use_container_width=True, key="save_name"):
+                if new_username:
+                    update_username_in_mongo(st.session_state["uid"], new_username)
+                    st.success("Đã cập nhật tên người dùng!")
+                    st.rerun()
+                else:
+                    st.warning("Tên người dùng không được để trống.")
+            
+            st.markdown("<hr style='margin: 1rem 0; border-color: rgba(100, 116, 139, 0.3);'>", unsafe_allow_html=True)
+            
+            file = st.file_uploader("Thay đổi ảnh đại diện (png, jpg, jpeg)", type=["png", "jpg", "jpeg"])
+            if st.button("Lưu avatar", use_container_width=True, key="save_avatar"):
+                if file:
+                    save_avatar(st.session_state["uid"], file.read())
+                    st.success("Đã lưu avatar!")
+                    st.rerun()
+                else:
+                    st.warning("Hãy chọn ảnh trước khi lưu.")
+
+        st.markdown("<div style='margin-top: 1rem;'></div>", unsafe_allow_html=True)
+
+        if st.button("Đăng xuất", use_container_width=True, key="logout_btn"):
+            st.session_state.clear()
+            st.rerun()
+            #st.switch_page("StockInsights.py")

src/pages/page_history.py

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+import streamlit as st
+# st.set_page_config(page_title="Lịch sử - Stock Insights", page_icon="🔮", layout="centered")
+
+import os
+from pymongo import MongoClient
+from report_generator import show_report
+from utils import load_css
+
+def main():
+    mongo_uri = os.getenv("MONGO_URI")
+    mongo_dbname = os.getenv("MONGO_DBNAME")
+
+    def get_db():
+        client = MongoClient(mongo_uri)
+        db = client[mongo_dbname]
+        return db["reports"]
+
+    reports_history = get_db()
+
+    load_css()
+
+    if "uid" not in st.session_state:
+        st.warning("Vui lòng đăng nhập để sử dụng tính năng này.")
+        st.page_link("StockInsights.py", label="Về trang Đăng nhập", icon="🏠")
+        st.stop()
+
+    # ==== Giao diện trang lịch sử ====
+    st.markdown("<h2>Các báo cáo đã tạo</h2>", unsafe_allow_html=True)
+    search_code = st.text_input("Tìm theo mã cổ phiếu", "").upper()
+
+    query = {"uid": st.session_state["uid"]}
+    if search_code:
+        query["report_data.stock_code"] = {"$regex": f"^{search_code}", "$options": "i"}
+
+    history = list(reports_history.find(query).sort("created_at", -1))
+
+    if history:
+        for item in history:
+            stock_code = item["report_data"]["stock_code"]
+            period = item["report_data"]["report_period"]
+            with st.expander(f"{stock_code}: {period}"):
+                show_report(item["report_data"], item["summary"], item["report_data"]["stock_code"])
+    else:
+        st.info("Chưa có báo cáo nào cả")

src/pages/page_report.py

@@ -0,0 +1,117 @@
+import streamlit as st
+import os
+from pymongo import MongoClient
+import pandas as pd
+from datetime import datetime
+from report_generator import generate_stock_report, show_report
+from utils import load_css, call_genai_summary
+
+def main():
+    mongo_uri = os.getenv("MONGO_URI")
+    mongo_dbname = os.getenv("MONGO_DBNAME")
+
+    def get_db():
+        client = MongoClient(mongo_uri)
+        db = client[mongo_dbname]
+        return db["reports"]
+
+    reports_history = get_db()
+
+
+    load_css()
+
+    if "uid" not in st.session_state:
+        st.warning("Vui lòng đăng nhập để sử dụng tính năng này.")
+        st.page_link("StockInsights.py", label="Về trang Đăng nhập", icon="🏠")
+        st.stop()
+
+    # ==== Giao diện trang báo cáo ===
+    st.markdown("<h2>Báo cáo Cổ phiếu Thông minh</h2>", unsafe_allow_html=True)
+
+    # st.markdown("<div class='report-container'>", unsafe_allow_html=True)
+
+    col_history, col_main = st.columns([1, 3])
+
+    # ===== LEFT: Report History =====
+    with col_history:
+        st.markdown("<h4>Báo cáo đã xem</h4>", unsafe_allow_html=True)
+
+        # Initialize history list
+        if "reports_history_list" not in st.session_state:
+            query = {"uid": st.session_state["uid"]}
+            st.session_state["reports_history_list"] = list(
+                reports_history.find(query).sort("created_at", -1)
+            )
+
+        history = st.session_state["reports_history_list"]
+
+        if not history:
+            st.info("Chưa có báo cáo nào được lưu.")
+        else:
+            for idx, report in enumerate(history):
+                if st.button(
+                    f"{report['report_data'].get('stock_code', 'N/A')} ({report['report_data'].get('report_period', 'N/A')})",
+                    key=f"history_btn_{idx}"
+                ):
+                    # Update the selected report in session state
+                    st.session_state["selected_report"] = report
+                    st.session_state["show_form"] = False  # Hide form when viewing history
+
+    # ===== RIGHT: Report View=====
+    with col_main:
+        if st.session_state.get("selected_report") and not st.session_state.get("show_form", False):
+            selected = st.session_state["selected_report"]
+            show_report(selected["report_data"], selected["summary"], selected["report_data"]["stock_code"])
+            
+            # Tạo báo cáo mới 
+            if st.button("Tạo báo cáo mới", key="new_report_btn"):
+                st.session_state["show_form"] = True
+                st.session_state.pop("selected_report", None)
+                st.rerun()
+        
+        else:
+            with st.form("report_form"):
+                stock_code_input = st.text_input(
+                    "Nhập mã cổ phiếu (ví dụ: VIC, HPG...)", value="HPG").upper()
+
+                col_start, col_end = st.columns(2)
+                with col_start:
+                    start_date = st.date_input(
+                        "Từ ngày", value=pd.to_datetime("2025-05-01"))
+                with col_end:
+                    end_date = st.date_input("Đến ngày", value=datetime.now())
+
+                submitted = st.form_submit_button("Tạo báo cáo", use_container_width=True)
+
+            if submitted and stock_code_input:
+                with st.spinner(f'Đang tổng hợp và phân tích dữ liệu cho mã {stock_code_input}...'):
+                    report_data = generate_stock_report(
+                        stock_code_input, (str(start_date), str(end_date)))
+
+                    if report_data and (report_data["overall_sentiment"]["positive_mentions"] > 0 or report_data["overall_sentiment"]["negative_mentions"] > 0):
+                        summary = call_genai_summary(
+                            report_data, stock_code_input, (str(start_date), str(end_date)))
+                    else:
+                        summary = f"Không tìm thấy đủ dữ liệu nổi bật cho mã **{stock_code_input}** trong khoảng thời gian đã chọn để tạo tóm tắt AI."
+
+                    # Save to MongoDB
+                    inserted_id = reports_history.insert_one({
+                        "uid": st.session_state["uid"],
+                        "report_data": report_data,
+                        "summary": summary,
+                        "created_at": datetime.utcnow()
+                    }).inserted_id
+
+                    # Add new report to top of history
+                    new_report = {
+                        "_id": inserted_id,
+                        "report_data": report_data,
+                        "summary": summary,
+                        "created_at": datetime.utcnow()
+                    }
+                    st.session_state["reports_history_list"].insert(0, new_report)
+
+                    # Show new report
+                    st.session_state["selected_report"] = new_report
+                    st.session_state["show_form"] = False
+                    st.rerun()

src/report_generator.py

@@ -0,0 +1,261 @@
+import sqlite3
+import pandas as pd
+import os
+from datetime import datetime
+import streamlit as st
+
+# def get_db_path():
+#     db_path = "../database/stock_insights.db"
+#     if not os.path.exists(db_path) and os.path.exists("/tmp/stock_insights.db"):
+#         db_path = "/tmp/stock_insights.db"
+#     return db_path
+
+# download from Hugging Face dataset
+def ensure_db():
+    db_path = os.path.join("database", "stock_insights.db")
+    if not os.path.exists(db_path):
+        from huggingface_hub import hf_hub_download
+        os.makedirs("database", exist_ok=True)
+        hf_hub_download(
+            repo_id="PuppetLover/stock_insights",
+            filename="stock_insights.db",
+            repo_type="dataset",
+            local_dir="database",
+            local_dir_use_symlinks=False,
+        )
+
+ensure_db()
+
+def generate_stock_report(stock_code, time_period):
+
+    start_date, end_date = time_period
+    today = datetime.now().date()
+    db_path = os.path.join("database", "stock_insights.db")
+
+    report = {
+        "stock_code": stock_code,
+        "report_period": f"{start_date} to {end_date}"
+    }
+
+    with sqlite3.connect(db_path) as conn:
+        # Tạo bảng tạm relevant_articles
+        conn.execute("DROP TABLE IF EXISTS relevant_articles;")
+        conn.execute("""
+            CREATE TEMP TABLE relevant_articles AS
+            SELECT DISTINCT article_id FROM entities 
+            WHERE entity_text =? 
+              AND entity_type IN ('STOCK', 'COMPANY')
+              AND confidence = 'high'
+              AND article_id IN (
+                  SELECT article_id FROM articles WHERE publish_date BETWEEN ? AND ?
+              );
+        """, (stock_code, start_date, end_date))
+
+        # 1. OVERALL SENTIMENT
+        q_sentences = """
+            SELECT s.sentiment_score, s.sentiment_label, a.publish_date
+            FROM sentences s
+            JOIN articles a ON s.article_id = a.article_id
+            WHERE s.article_id IN (
+                SELECT s2.sentence_id FROM sentences s2
+                WHERE s2.article_id IN (SELECT article_id FROM relevant_articles)
+            )
+            AND s.sentiment_score IS NOT NULL;
+        """
+        df_sent = pd.read_sql_query(q_sentences, conn)
+        
+        if not df_sent.empty:
+            df_sent['publish_date'] = pd.to_datetime(df_sent['publish_date']).dt.date
+            df_sent['days_ago'] = (today - df_sent['publish_date']).apply(lambda x: x.days)
+            df_sent['weight'] = 1 / (df_sent['days_ago'] + 1)
+            weighted_score = (df_sent['sentiment_score'] * df_sent['weight']).sum() / df_sent['weight'].sum()
+            # Chuẩn hóa nhãn sentiment về lower-case
+            df_sent['sentiment_label'] = df_sent['sentiment_label'].str.lower()
+            sentiment_counts = df_sent['sentiment_label'].value_counts().to_dict()
+            trend = "Tích cực" if weighted_score > 0.1 else "Tiêu cực" if weighted_score < -0.1 else "Trung tính"
+        else:
+            weighted_score, sentiment_counts, trend = 0.0, {}, "Không có dữ liệu"
+
+        report["overall_sentiment"] = {
+            "score": weighted_score,
+            "trend": trend,
+            "positive_mentions": sentiment_counts.get("positive", 0),
+            "negative_mentions": sentiment_counts.get("negative", 0),
+            "neutral_mentions": sentiment_counts.get("neutral", 0)
+        }
+
+        # 2. KEY EVENTS, RISKS, PRICE ACTIONS
+        def get_key_entities(entity_type):
+            query = f"""
+                SELECT
+                    e.entity_text,
+                    COUNT(e.entity_id) as count,
+                    AVG(s.sentiment_score) as avg_sentiment
+                FROM entities e
+                JOIN sentences s ON e.sentence_id = s.sentence_id
+                WHERE e.article_id IN (SELECT article_id FROM relevant_articles)
+                  AND e.entity_type =?
+                GROUP BY e.entity_text
+                ORDER BY count DESC
+                LIMIT 5;
+            """
+            df = pd.read_sql_query(query, conn, params=(entity_type,))
+            def score_to_label(score):
+                if score is None: return "N/A"
+                return "Tích cực" if score > 0.1 else "Tiêu cực" if score < -0.1 else "Trung tính"
+            df['sentiment'] = df['avg_sentiment'].apply(score_to_label)
+            return df.to_dict('records')
+
+        report["key_events"] = get_key_entities('EVENT')
+        report["key_price_actions"] = get_key_entities('PRICE_ACTION')
+        report["key_risks_mentioned"] = get_key_entities('RISK')
+
+        # 3. TOP RELATED ENTITIES
+        q_related = """
+            SELECT e.entity_type, e.entity_text
+            FROM entities e
+            WHERE e.article_id IN (SELECT article_id FROM relevant_articles)
+              AND e.entity_text!=?
+              AND e.entity_type IN ('STOCK', 'COMPANY', 'PERSON');
+        """
+        df_related = pd.read_sql_query(q_related, conn, params=(stock_code,))
+        top_related = {}
+        if not df_related.empty:
+            for etype in ['STOCK', 'COMPANY', 'PERSON']:
+                top_related[etype.lower() + 's'] = df_related[df_related['entity_type'] == etype]['entity_text'].value_counts().head(3).index.tolist()
+        report["top_related_entities"] = top_related
+
+        # 4. SOURCE ARTICLES
+        q_articles = """
+            SELECT a.title, a.source_url, s.sentiment_label
+            FROM articles a
+            JOIN sentences s ON a.article_id = s.article_id
+            WHERE a.article_id IN (SELECT article_id FROM relevant_articles)
+            GROUP BY a.article_id
+            ORDER BY a.publish_date DESC
+            LIMIT 5;
+        """
+        df_articles = pd.read_sql_query(q_articles, conn)
+        report["source_articles"] = df_articles.to_dict('records')
+
+    return report
+
+# --- HIỂN THỊ BÁO CÁO ---
+def show_report(report_data, summary, stock_code_input):
+    st.markdown(
+        f"<h3 style='text-align: center; color: #30cfd0; margin-top:2rem;'>Báo cáo Phân tích cho {report_data.get('stock_code', stock_code_input)}</h3>", unsafe_allow_html=True)
+    st.markdown(
+        f"<p style='text-align: center; color: #94a3b8;'>Giai đoạn: {report_data.get('report_period', 'N/A')}</p>", unsafe_allow_html=True)
+
+    st.markdown("#### 🤖 Tóm tắt từ AI")
+    st.info(summary)
+
+    # Tổng quan cảm xúc
+    st.markdown("#### 📊 Tổng quan Cảm xúc")
+    sentiment = report_data['overall_sentiment']
+    score = sentiment['score']
+    trend_color = "normal"
+    if sentiment['trend'] == "Tích cực":
+        trend_color = "normal"
+        if sentiment['trend'] == "Tiêu cực":
+            trend_color = "inverse"
+
+    st.metric(
+        label="Điểm Cảm xúc (có trọng số thời gian)",
+        value=f"{score:.2f}" if score is not None else "N/A",
+        delta=sentiment['trend'],
+        delta_color=trend_color
+    )
+
+    col1, col2, col3 = st.columns(3)
+    col1.metric("👍 Tích cực", sentiment['positive_mentions'])
+    col2.metric("👎 Tiêu cực", sentiment['negative_mentions'])
+    col3.metric("😐 Trung tính", sentiment['neutral_mentions'])
+
+    # Các bảng chi tiết
+    st.markdown("---")
+
+    col_events, col_risks = st.columns(2)
+    with col_events:
+        st.markdown("#### ⚡ Sự kiện Nổi bật")
+        if report_data["key_events"]:
+            # Kiểm tra key thực tế
+            df_events = pd.DataFrame(report_data["key_events"])
+            if 'avg_sentiment' in df_events.columns:
+                df_events = df_events.rename(
+                    columns={'entity_text': 'Sự kiện', 'avg_sentiment': 'Sentiment'})
+                show_cols = ['Sự kiện', 'count', 'Sentiment']
+            elif 'sentiment' in df_events.columns:
+                df_events = df_events.rename(
+                    columns={'entity_text': 'Sự kiện'})
+                show_cols = ['Sự kiện', 'count', 'sentiment']
+            else:
+                df_events = df_events.rename(
+                    columns={'entity_text': 'Sự kiện'})
+                show_cols = ['Sự kiện', 'count']
+            st.dataframe(df_events[show_cols], use_container_width=True)
+        else:
+            st.write("Không có sự kiện nổi bật.")
+
+    with col_risks:
+        st.markdown("#### ⚠️ Rủi ro được đề cập")
+        if report_data["key_risks_mentioned"]:
+            df_risks = pd.DataFrame(report_data["key_risks_mentioned"])
+            if 'avg_sentiment' in df_risks.columns:
+                df_risks = df_risks.rename(
+                    columns={'entity_text': 'Rủi ro', 'avg_sentiment': 'Sentiment'})
+                show_cols = ['Rủi ro', 'count', 'Sentiment']
+            elif 'sentiment' in df_risks.columns:
+                df_risks = df_risks.rename(
+                    columns={'entity_text': 'Rủi ro'})
+                show_cols = ['Rủi ro', 'count', 'sentiment']
+            else:
+                df_risks = df_risks.rename(
+                    columns={'entity_text': 'Rủi ro'})
+                show_cols = ['Rủi ro', 'count']
+            st.dataframe(df_risks[show_cols], use_container_width=True)
+        else:
+            st.write("Không có rủi ro nổi bật.")
+
+    st.markdown("#### 📈 Hành động Giá Chính")
+    if report_data["key_price_actions"]:
+        df_price = pd.DataFrame(report_data["key_price_actions"])
+        if 'avg_sentiment' in df_price.columns:
+            df_price = df_price.rename(
+                columns={'entity_text': 'Hành động giá', 'avg_sentiment': 'Sentiment'})
+            show_cols = ['Hành động giá', 'count', 'Sentiment']
+        elif 'sentiment' in df_price.columns:
+            df_price = df_price.rename(
+                columns={'entity_text': 'Hành động giá'})
+            show_cols = ['Hành động giá', 'count', 'sentiment']
+        else:
+            df_price = df_price.rename(
+                columns={'entity_text': 'Hành động giá'})
+            show_cols = ['Hành động giá', 'count']
+        st.dataframe(df_price[show_cols], use_container_width=True)
+    else:
+        st.write("Không có hành động giá nổi bật.")
+
+    # Thực thể liên quan
+    st.markdown("---")
+    st.markdown("#### 🔗 Các Thực thể Liên quan nhiều nhất")
+    related = report_data['top_related_entities']
+    if any(related.values()):
+        for etype, entities in related.items():
+            if entities:
+                st.markdown(
+                    f"**{etype.replace('_', ' ').title()}:** {', '.join(entities)}")
+    else:
+        st.write("Không tìm thấy thực thể liên quan nổi bật.")
+
+    # Nguồn bài viết
+    st.markdown("---")
+    st.markdown("#### 📰 Nguồn Bài viết Tham khảo")
+    if report_data["source_articles"]:
+        for article in report_data["source_articles"]:
+            st.markdown(
+                f"- [{article['title']}]({article['source_url']}) - *Cảm xúc: {article['sentiment_label']}*")
+    else:
+        st.write("Không có bài viết nào trong khoảng thời gian này.")
+
+    st.markdown("</div>", unsafe_allow_html=True)

src/streamlit_app.py

@@ -1,40 +0,0 @@
-import altair as alt
-import numpy as np
-import pandas as pd
-import streamlit as st
-
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))

src/utils.py

@@ -0,0 +1,176 @@
+import streamlit as st
+import pyrebase
+import os
+import base64
+import json
+import requests
+from dotenv import load_dotenv
+
+load_dotenv()
+
+# ==== Firebase Config & Initialization ====
+def initialize_firebase():
+    """Khởi tạo và trả về các đối tượng Firebase. Sử dụng singleton pattern."""
+    if "firebase_app" not in st.session_state:
+        firebase_config = {
+            "apiKey": os.getenv("FIREBASE_API_KEY"),
+            "authDomain": os.getenv("FIREBASE_AUTH_DOMAIN"),
+            "projectId": os.getenv("FIREBASE_PROJECT_ID"),
+            "storageBucket": os.getenv("FIREBASE_STORAGE_BUCKET"),
+            "messagingSenderId": os.getenv("FIREBASE_MESSAGING_SENDER_ID"),
+            "appId": os.getenv("FIREBASE_APP_ID"),
+            "databaseURL": os.getenv("FIREBASE_DATABASE_URL", ""),
+        }
+        st.session_state.firebase_app = pyrebase.initialize_app(firebase_config)
+    
+    auth_fb = st.session_state.firebase_app.auth()
+    return auth_fb
+
+# ==== CSS Dùng chung ====
+def load_css():
+    """Tải CSS theme Cyberpunk Neon."""
+    st.markdown("""
+    <style>
+        /* === Hide default Streamlit elements === */
+        section[data-testid="stSidebar"] {display: none;}
+        header {visibility: hidden;}
+
+        /* === Main container styling === */
+        .stApp {
+            background-color: #0d1117;
+            color: #c9d1d9;
+        }
+        
+        /* === Main content area styling === */
+        .main .block-container {
+            max-width: 1100px; /* Rộng hơn cho layout mới */
+            padding: 1rem 1.5rem;
+        }
+        .not-logged-in .main .block-container {
+            max-width: 450px;
+        }
+
+        /* === Custom Navigation Bar === */
+        .nav-container {
+            display: flex;
+            justify-content: center;
+            gap: 1rem;
+            margin-bottom: 2rem;
+            padding: 0.5rem;
+            background-color: rgba(30, 41, 59, 0.5);
+            border-radius: 12px;
+            border: 1px solid rgba(100, 116, 139, 0.3);
+        }
+        .nav-container .stButton>button {
+            background: transparent;
+            border: 2px solid transparent;
+            transition: all 0.3s ease;
+            font-weight: 600;
+            color: #94a3b8;
+        }
+        .nav-container .stButton>button:hover {
+            color: #ffffff;
+            border-color: rgba(48, 207, 208, 0.5);
+            box-shadow: none;
+            transform: none; /* FIX: Vô hiệu hóa hiệu ứng transform cho nút nav */
+        }
+        /* Style for the ACTIVE button */
+        .nav-container .stButton>button.active-nav-button {
+            color: #ffffff;
+            border-color: #30cfd0;
+            box-shadow: 0 0 15px rgba(48, 207, 208, 0.4);
+        }
+
+        /* === Card styling with "frosted glass" effect === */
+        div[data-testid="stTabs-panel"], .report-container {
+            background-color: rgba(30, 41, 59, 0.5);
+            backdrop-filter: blur(12px);
+            border-radius: 16px;
+            padding: 2.5rem;
+            box-shadow: 0 8px 32px 0 rgba(0, 0, 0, 0.37);
+            border: 1px solid rgba(100, 116, 139, 0.3);
+        }
+
+        /* === General Button styling === */
+        .stButton>button {
+            border-radius: 8px;
+            border: 1px solid #30cfd0;
+            padding: 12px 20px;
+            color: white;
+            background: linear-gradient(90deg, #30cfd0, #330867);
+            transition: all 0.3s ease-in-out;
+            font-weight: 600;
+        }
+        .stButton>button:hover {
+            box-shadow: 0 0 20px #30cfd0;
+            transform: translateY(-2px);
+        }
+        
+        /* === Input fields styling === */
+        .stTextInput label, .stDateInput label {
+            color: #c9d1d9 !important;
+            font-weight: 600;
+            margin-bottom: 0.5rem;
+        }
+        .stTextInput>div>div>input, .stDateInput>div>div>input {
+            background-color: rgba(15, 23, 42, 0.5);
+            border: 1px solid #64748b;
+            border-radius: 8px;
+            padding: 12px;
+            color: #ffffff;
+        }
+        .stTextInput>div>div>input:focus, .stDateInput>div>div>input:focus {
+            border-color: #30cfd0;
+            box-shadow: 0 0 10px rgba(48, 207, 208, 0.5);
+        }
+
+        /* === Header styling === */
+        h1, h2 {
+            text-align: center;
+            color: #ffffff;
+            font-weight: 700;
+            letter-spacing: 1px;
+            text-shadow: 0 0 10px rgba(48, 207, 208, 0.5);
+        }
+    </style>
+    """, unsafe_allow_html=True)
+
+# ==== Hàm Render Avatar ====
+def render_avatar(uid, container, get_avatar_blob_func):
+    avatar_bytes = get_avatar_blob_func(uid)
+    if avatar_bytes:
+        img_base64 = base64.b64encode(avatar_bytes).decode()
+        avatar_html = f'<img src="data:image/png;base64,{img_base64}" style="border-radius:50%; border:4px solid #30cfd0; width:120px; height:120px; object-fit:cover; box-shadow:0 0 20px rgba(48, 207, 208, 0.5);">'
+    else:
+        avatar_html = """
+            <div style='border-radius:50%; background:linear-gradient(135deg, #30cfd0, #330867);
+                        width:120px; height:120px; display:flex; align-items:center; justify-content:center;
+                        box-shadow:0 0 20px rgba(48, 207, 208, 0.3);'>
+                <span style='font-size:3em; color:#fff;'>👤</span>
+            </div>
+            <div style='margin-top:8px; color:#94a3b8; font-size:0.9em;'>Chưa có avatar</div>
+        """
+    container.html(f"<div style='display:flex; flex-direction:column; align-items:center; margin-bottom: 1rem;'>{avatar_html}</div>")
+
+
+# ==== Hàm gọi Gemini API ====
+def call_genai_summary(report_data, stock_code, time_period):
+    api_key = os.getenv("GEMINI_API_KEY")
+    if not api_key:
+        st.error("Vui lòng cung cấp GEMINI_API_KEY trong file .env")
+        return "Lỗi: Chưa cấu hình API Key."
+        
+    url = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key={api_key}"
+    prompt = f"""
+    Hãy tóm tắt ngắn gọn, chuyên nghiệp về mã cổ phiếu {stock_code} trong giai đoạn {time_period[0]} đến {time_period[1]} dựa trên dữ liệu JSON sau:
+    {json.dumps(report_data, ensure_ascii=False, indent=2)}
+    """
+    payload = {"contents": [{"parts": [{"text": prompt}]}]}
+
+    try:
+        response = requests.post(url, json=payload, timeout=45)
+        response.raise_for_status()
+        data = response.json()
+        return data["candidates"][0]["content"]["parts"][0]["text"]
+    except Exception as e:
+        return f"Lỗi khi gọi Gemini API: {e}"