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import streamlit as st
import os
import json
from datetime import datetime, timedelta
import base64
import pandas as pd
import pydeck as pdk
from paper import (
literature_research_task, outline_task, draft_writing_task,
citation_task, editing_task, chatbot_task,
run_task
)
# st.set_page_config()
st.set_page_config(
page_title="AI Agent for FS",
page_icon="π",
layout="wide",
initial_sidebar_state="expanded"
)
# ------------------------------------------
#
# ------------------------------------------
translations = {
"id": {
"page_title": "Agen AI untuk FS",
"header": "Agen AI untuk FS",
"create_itinerary": "Membuat Laporan FS",
"trip_details": "Rincian",
"origin": "Topic",
"destination": "Judul ",
"travel_dates": "Tanggal selesai",
"duration": "Jumlah halaman (pages)",
"preferences": "Keywords/Focus",
"special_requirements": "Additional Instructions",
"submit": "π Buatkan FS",
"request_details": "Your FS Request",
"from": "Topic",
"when": "Due Date",
"budget": "Paper Type",
"travel_style": "Writing Style",
"live_agent_outputs": "Live Agent Outputs",
"full_itinerary": "Full Paper",
"details": "Details",
"download_share": "Download & Share",
"save_itinerary": "Save Your Paper",
"plan_another_trip": "π Generate Another Paper",
"about": "About",
"how_it_works": "How it works",
"travel_agents": "Research Agents",
"share_itinerary": "Share Your Paper",
"save_for_mobile": "Save for Mobile",
"built_with": "Built with β€οΈ for you",
"itinerary_ready": "Your Research Paper is Ready! π",
"personalized_experience": "Kami telah membuat makalah akademis yang dipersonalisasi berdasarkan masukan Anda. Lihat makalah Anda di bawah ini.",
"agent_activity": "Agent Activity",
"error_origin_destination": "Harap masukkan topik penelitian dan judul makalah",
"your_itinerary_file": "Your Paper File",
"text_format": "Text format - Can be opened in any text editor"
},
"en": {
"page_title": "AI Agent for Academic Research",
"header": "AI Agent for Academic Research",
"create_itinerary": "Generate Your Research Paper",
"trip_details": "Research Details",
"origin": "Research Topic",
"destination": "Paper Title",
"travel_dates": "Due Date",
"duration": "Paper Length (pages)",
"preferences": "Keywords/Focus",
"special_requirements": "Additional Instructions",
"submit": "π Generate My Research Paper",
"request_details": "Your Research Request",
"from": "Topic",
"when": "Due Date",
"budget": "Paper Type",
"travel_style": "Writing Style",
"live_agent_outputs": "Live Agent Outputs",
"full_itinerary": "Full Paper",
"details": "Details",
"download_share": "Download & Share",
"save_itinerary": "Save Your Paper",
"plan_another_trip": "π Generate Another Paper",
"about": "About",
"how_it_works": "How it works",
"travel_agents": "Research Agents",
"share_itinerary": "Share Your Paper",
"save_for_mobile": "Save for Mobile",
"built_with": "Built with β€οΈ for you",
"itinerary_ready": "Your Research Paper is Ready! π",
"personalized_experience": "We've created a personalized academic paper based on your inputs. Explore your paper below.",
"agent_activity": "Agent Activity",
"error_origin_destination": "Please enter both the research topic and paper title.",
"your_itinerary_file": "Your Paper File",
"text_format": "Text format - Can be opened in any text editor"
}
}
def t(key):
lang = st.session_state.get("selected_language", "id")
return translations[lang].get(key, key)
# ---------------------------
#
# ---------------------------
if 'selected_language' not in st.session_state:
st.session_state.selected_language = "id"
# ------------------------------------------
#
# ------------------------------------------
with st.sidebar:
language = st.selectbox(
"Language / Bahasa",
["Indonesia","English"]
)
lang_map = {
"Indonesia": "id",
"English": "en"
}
st.session_state.selected_language = lang_map.get(language, "id")
# ------------------------------------------
#
# ------------------------------------------
st.markdown("""
<style>
:root {
--primary: #3a86ff;
--primary-light: #4895ef;
--primary-dark: #2667ff;
--background: #f8f9fa;
--card-bg: #ffffff;
--text: #212529;
--border: #e9ecef;
}
.main-header {
font-size: 2.5rem;
color: var(--primary-dark);
text-align: center;
margin-bottom: 0.8rem;
font-weight: 700;
}
.modern-card {
background-color: var(--card-bg);
border-radius: 10px;
padding: 1.2rem;
margin-bottom: 1.2rem;
box-shadow: 0 2px 10px rgba(0,0,0,0.05);
border: 1px solid var(--border);
}
</style>
""", unsafe_allow_html=True)
def get_download_link(text_content, filename):
b64 = base64.b64encode(text_content.encode()).decode()
href = f'<a class="download-link" href="data:text/plain;base64,{b64}" download="{filename}"><i>π₯</i> {t("save_itinerary")}</a>'
return href
def display_modern_progress(current_step, total_steps=5):
if 'progress_steps' not in st.session_state:
st.session_state.progress_steps = {
0: {'status': 'pending', 'name': t("trip_details")},
1: {'status': 'pending', 'name': t("about")},
2: {'status': 'pending', 'name': t("live_agent_outputs")},
3: {'status': 'pending', 'name': t("download_share")},
4: {'status': 'pending', 'name': t("full_itinerary")}
}
for i in range(total_steps):
if i < current_step:
st.session_state.progress_steps[i]['status'] = 'complete'
elif i == current_step:
st.session_state.progress_steps[i]['status'] = 'active'
else:
st.session_state.progress_steps[i]['status'] = 'pending'
progress_percentage = (current_step / total_steps) * 100
st.progress(progress_percentage / 100)
st.markdown("<div>Progress: " + str(progress_percentage) + "% completed.</div>")
return progress_percentage
def update_step_status(step_index, status):
if 'progress_steps' in st.session_state and step_index in st.session_state.progress_steps:
st.session_state.progress_steps[step_index]['status'] = status
def run_task_with_logs(task, input_text, log_container, output_container, results_key=None):
log_message = f"π€ Starting {task.agent.role}..."
st.session_state.log_messages.append(log_message)
with log_container:
st.markdown("### " + t("agent_activity"))
for msg in st.session_state.log_messages:
st.markdown(msg)
result = run_task(task, input_text)
if results_key:
st.session_state.results[results_key] = result
log_message = f"β
{task.agent.role} completed!"
st.session_state.log_messages.append(log_message)
with log_container:
st.markdown("### " + t("agent_activity"))
for msg in st.session_state.log_messages:
st.markdown(msg)
with output_container:
st.markdown(f"### {task.agent.role} Output")
st.markdown("<div class='agent-output'>" + result + "</div>", unsafe_allow_html=True)
return result
if 'generated_itinerary' not in st.session_state:
st.session_state.generated_itinerary = None
if 'generation_complete' not in st.session_state:
st.session_state.generation_complete = False
if 'current_step' not in st.session_state:
st.session_state.current_step = 0
if 'results' not in st.session_state:
st.session_state.results = {
"literature_review": "",
"outline": "",
"draft": "",
"citations": "",
"edited": ""
}
if 'log_messages' not in st.session_state:
st.session_state.log_messages = []
if 'form_submitted' not in st.session_state:
st.session_state.form_submitted = False
st.markdown(f"""
<div style="text-align: center;">
<img src="https://img.icons8.com/fluency/96/book.png" width="90">
<h1 class="main-header">{t("header")}</h1>
<p>Hasilkan FS Anda dengan agen yang berbasis AI.</p>
</div>
""", unsafe_allow_html=True)
st.markdown('<hr>', unsafe_allow_html=True)
with st.sidebar:
st.markdown("""
<div style="text-align: center;">
<img src="https://img.icons8.com/fluency/96/book.png" width="80">
<h3>Asisten AI untuk Membuat FS</h3>
<p>FS dibantu AI</p>
</div>
""", unsafe_allow_html=True)
st.markdown('<div class="modern-card">', unsafe_allow_html=True)
st.markdown("### " + t("about"))
st.info("Alat ini menghasilkan FS yang dipersonalisasi berdasarkan masukan Anda. Isi form asumsi, dan biarkan agen spesialis kami menyusun FS Anda!")
st.markdown('</div>', unsafe_allow_html=True)
st.markdown('<div class="modern-card">', unsafe_allow_html=True)
st.markdown("### " + t("how_it_works"))
st.markdown("""
<ol>
<li>Masukkan asumsi selengkap mungkin</li>
<li>AI melakukan persiapan FS</li>
<li>Kemudian menyiapkan outline FS</li>
<li>Buat draf dan edit FS Anda</li>
<li>FS Anda siap diunduh</li>
</ol>
""", unsafe_allow_html=True)
st.markdown('</div>', unsafe_allow_html=True)
if not st.session_state.generation_complete:
st.markdown('<div class="modern-card">', unsafe_allow_html=True)
st.markdown("<h3>" + t("create_itinerary") + "</h3>", unsafe_allow_html=True)
st.markdown("<p>Isi rincian di bawah ini</p>", unsafe_allow_html=True)
instruksi = """
Asumsi-asumsi berikut harus dimasukkan untuk memastikan analisis akurat dan realistis:
1. **Proyeksi Pasar dan Permintaan**
- Pertumbuhan permintaan produk berdasarkan tren pasar.
- Permintaan produk meningkat 5% per tahun.
2. **Tingkat Inflasi dan Suku Bunga**
- Inflasi dan suku bunga untuk proyeksi keuangan.
- Inflasi 3% dan discount rate 10%.
3. **Asumsi Finansial**
- Durasi penggunaan mesin baru sebelum penggantian: 20 tahun.
- Biaya Investasi:
- Harga pembelian mesin baru (termasuk pajak, biaya pengiriman, instalasi) sebesar 33 milyar.
- Biaya pembongkaran dan disposal mesin lama (100 juta).
- Sumber Pendanaan:
- Modal investasi mesin baru dari investor
4. **Ketersediaan Suku Cadang dan Dukungan Teknis**
- Ketersediaan layanan purna jual.
- *Contoh*: Suku cadang tersedia dengan waktu respons 24 jam.
5. **Kebutuhan Tenaga Kerja**
- Jumlah operator yang dibutuhkan.
- *Contoh*: 2 operator per shift untuk mesin baru.
6. **Waktu Henti (Downtime)**
- Estimasi waktu henti selama transisi dan operasi.
- *Contoh*: Downtime instalasi 1 minggu.
7. **Efisiensi Produksi**
- Peningkatan kualitas produk dengan mesin baru.
- Jumlah Produksi Grade #1 (terbaik) meningkat dari 1000 kg/hari menjadi 1200 kg/hari.
- Spesifikasi Mesin Lama:
- Kapasitas produksi 5000 kg per hari.
- Usia mesin 21 tahun, biaya perawatan 17 juta per bulan.
- Konsumsi energi 3 juta per hari.
- Kualitas output grade bagus 50 persen (harga 35 ribu per kg). Grade kurang bagus 50 persen (harga 15 ribu per kg).
- Spesifikasi Mesin Baru:
- Kapasitas produksi 5000 kg per hari.
- Usia mesin 1 tahun, biaya perawatan 7 juta per bulan.
- Konsumsi energi 1 juta per hari.
- Kualitas output grade bagus 80 persen (harga 35 ribu per kg). Grade kurang bagus 20 persen (harga 15 ribu per kg).
8. **Kebutuhan Pelatihan**
- Alur kerja dengan mesin lama dan baru relatif sama: meliputi tahapan produksi teh hitam yaitu: pelayuan, penggilingan, oksidasi, pengeringan, dan sortasi.
- Kebutuhan pelatihan operator untuk mesin baru biayanya 50 juta rupiah (sekali saja) untuk semua tahapan pekerjaan
9. Data Pasar
- **Permintaan Pasar**:
- Volume permintaan teh hitam saat ini dan proyeksi ke depan relative stabil seperti biasanya.
10. Data Lingkungan dan Regulasi
- **Dampak Lingkungan**:
- Emisi karbon atau limbah dari mesin lama vs mesin baru: mesin baru lebih sedikit risiko pencemaran polusi dan limbah.
- **Kepatuhan Regulasi**:
- Standar keamanan pangan atau sertifikasi yang harus dipenuhi (mesin baru lebih mudah memenuhi standar HACCP dan ISO).
11. Data Risiko
- **Risiko Teknis**:
- Bisa dikatakan tidak ada risiko kemungkinan kegagalan mesin baru atau waktu adaptasi yang lama.
- **Risiko Finansial**:
- Fluktuasi harga bahan baku teh atau mesin diperkirakan dalam kendali.
- Ketidakpastian pasar yang memengaruhi penjualan: memang tidak bisa diprediksi sehingga perlu Analisa bila harga jual turun 5 persen dan naik 5 persen.
- **Risiko Operasional**:
- Resistensi dari karyawan terhadap perubahan teknologi: diperkirakan tidak terjadi.
- Gangguan produksi selama transisi penggantian mesin: tidak ada jeda waktu instalasi mesin baru yang menyebabkan turun produksi karena Lokasi yang berbeda mesin lama dan baru.
"""
with st.form("research_form"):
col1, col2 = st.columns(2)
with col1:
research_topic = st.text_input(t("origin"), placeholder="e.g., Feasibility Study penggantian menyeluruh mesin produksi teh hitam", value="Feasibility Study penggantian menyeluruh mesin produksi teh hitam")
paper_title = st.text_input(t("destination"), placeholder="e.g., Penggantian Mesin Produksi Teh Hitam", value="Penggantian Mesin Produksi Teh Hitam")
due_date = st.date_input(t("travel_dates"), min_value=datetime.now())
with col2:
paper_length = st.slider(t("duration"), min_value=5, max_value=50, value=10)
paper_type_options = ["Journal", "Conference", "Thesis", "Review"]
paper_type = st.selectbox(t("budget"), paper_type_options, help="Select the type of paper")
writing_style = st.multiselect(t("travel_style"), options=["Formal", "Technical", "Creative"], default=["Formal"])
additional_instructions = st.text_area(t("special_requirements"), placeholder="Instruksi atau persyaratan tambahan apa pun...", value=instruksi)
keywords = st.text_area(t("preferences"), placeholder="Masukkan kata kunci atau area fokus, dipisahkan dengan koma")
submit_button = st.form_submit_button(t("submit"))
st.markdown('</div>', unsafe_allow_html=True)
if submit_button:
if not research_topic or not paper_title:
st.error(t("error_origin_destination"))
else:
st.session_state.form_submitted = True
st.session_state.research_topic = research_topic
user_input = {
"research_topic": research_topic,
"paper_title": paper_title,
"due_date": due_date.strftime("%Y-%m-%d"),
"paper_length": str(paper_length),
"paper_type": paper_type,
"writing_style": ", ".join(writing_style),
"keywords": keywords,
"additional_instructions": additional_instructions
}
st.session_state.user_input = user_input
input_context = f"""Research Request Details:
Research Topic: {user_input['research_topic']}
Paper Title: {user_input['paper_title']}
Due Date: {user_input['due_date']}
Paper Length: {user_input['paper_length']} pages
Paper Type: {user_input['paper_type']}
Writing Style: {user_input['writing_style']}
Keywords/Focus: {user_input['keywords']}
Additional Instructions: {user_input['additional_instructions']}
"""
llm_language_instructions = {
"en": "Please output the response in English.",
"id": "Please output the response in Bahasa Indonesia."
}
selected_lang = st.session_state.get("selected_language", "id")
language_instruction = llm_language_instructions.get(selected_lang, "Please output the response in Bahasa Indonesia.")
modified_input_context = language_instruction + "\n" + input_context
st.markdown("<div>Sedang memproses...</div>", unsafe_allow_html=True)
st.session_state.current_step = 0
update_step_status(0, 'active')
progress_placeholder = st.empty()
with progress_placeholder.container():
display_modern_progress(st.session_state.current_step)
log_container = st.container()
st.session_state.log_messages = []
output_container = st.container()
st.session_state.results = {}
# Step 1: Literature Research
literature_review = run_task_with_logs(
literature_research_task,
modified_input_context.format(topic=user_input['research_topic'], keywords=user_input['keywords']),
log_container,
output_container,
"literature_review"
)
update_step_status(0, 'complete')
st.session_state.current_step = 1
update_step_status(1, 'active')
with progress_placeholder.container():
display_modern_progress(st.session_state.current_step)
# Step 2: Generate Outline
outline = run_task_with_logs(
outline_task,
modified_input_context.format(topic=user_input['research_topic']),
log_container,
output_container,
"outline"
)
update_step_status(1, 'complete')
st.session_state.current_step = 2
update_step_status(2, 'active')
with progress_placeholder.container():
display_modern_progress(st.session_state.current_step)
# Step 3: Draft Writing
draft = run_task_with_logs(
draft_writing_task,
modified_input_context.format(topic=user_input['research_topic']),
log_container,
output_container,
"draft"
)
update_step_status(2, 'complete')
st.session_state.current_step = 3
update_step_status(3, 'active')
with progress_placeholder.container():
display_modern_progress(st.session_state.current_step)
# Step 4: Citation Generation
citations = run_task_with_logs(
citation_task,
modified_input_context.format(topic=user_input['research_topic']),
log_container,
output_container,
"citations"
)
update_step_status(3, 'complete')
st.session_state.current_step = 4
update_step_status(4, 'active')
with progress_placeholder.container():
display_modern_progress(st.session_state.current_step)
# Step 5: Editing and Polishing
edited = run_task_with_logs(
editing_task,
modified_input_context.format(topic=user_input['research_topic']),
log_container,
output_container,
"edited"
)
update_step_status(4, 'complete')
st.session_state.current_step = 5
with progress_placeholder.container():
display_modern_progress(st.session_state.current_step)
full_paper = f"""Research Paper:
{input_context}
Literature Review:
{literature_review}
Outline:
{outline}
Draft:
{draft}
Citations:
{citations}
Edited Version:
{edited}
"""
st.session_state.generated_itinerary = full_paper
st.session_state.generation_complete = True
date_str = datetime.now().strftime("%Y-%m-%d")
st.session_state.filename = f"{user_input['paper_title'].replace(' ', '_')}_{date_str}_paper.txt"
if st.session_state.generation_complete:
st.markdown(f"""
<div class="modern-card">
<div style="text-align: center;">
<h2>{t("itinerary_ready")}</h2>
<p>{t("personalized_experience")}</p>
</div>
</div>
""", unsafe_allow_html=True)
#
full_paper_tab, details_tab, download_tab, visualization_tab, chatbot_tab = st.tabs([
"ποΈ " + t("full_itinerary"),
"πΌ " + t("details"),
"πΎ " + t("download_share"),
"π Visualization",
"π€ Chatbot"
])
with full_paper_tab:
st.text_area("Your Research Paper", st.session_state.generated_itinerary, height=600)
with details_tab:
agent_tabs = st.tabs(["π Review", "π Outline", "βοΈ Draft", "π Citations", "ποΈ Edited Version"])
with agent_tabs[0]:
st.markdown("### Review")
st.markdown(st.session_state.results.get("literature_review", ""))
with agent_tabs[1]:
st.markdown("### Outline")
st.markdown(st.session_state.results.get("outline", ""))
with agent_tabs[2]:
st.markdown("### Draft")
st.markdown(st.session_state.results.get("draft", ""))
with agent_tabs[3]:
st.markdown("### Citations")
st.markdown(st.session_state.results.get("citations", ""))
with agent_tabs[4]:
st.markdown("### Edited Version")
st.markdown(st.session_state.results.get("edited", ""))
with download_tab:
col1, col2 = st.columns([2, 1])
with col1:
st.markdown("### " + t("save_itinerary"))
st.markdown("Download your FS to access it offline or share with your colleagues.")
st.markdown(f"""
<div style="background-color: #f8f9fa; padding: 15px; border-radius: 10px; margin-top: 20px;">
<h4>{t("your_itinerary_file")}</h4>
<p style="font-size: 0.9rem; color: #6c757d;">{t("text_format")}</p>
</div>
""", unsafe_allow_html=True)
st.markdown("<div>" + get_download_link(st.session_state.generated_itinerary, st.session_state.filename) + "</div>", unsafe_allow_html=True)
st.markdown("### " + t("share_itinerary"))
st.markdown("*Coming soon: Email your paper or share via social media.*")
with col2:
st.markdown("### " + t("save_for_mobile"))
st.markdown("*Coming soon: QR code for easy access on your phone*")
with visualization_tab:
st.markdown("### Visualization")
st.markdown("A conceptual diagram or visualization related to your FS can be displayed here. (Feature under development)")
with chatbot_tab:
st.markdown("### AI Chat")
if "chat_history" not in st.session_state:
st.session_state.chat_history = []
user_message = st.text_input("Input:", key="chat_input")
if st.button("Kirim", key="send_button"):
if user_message:
response = run_task(chatbot_task, user_message)
st.session_state.chat_history.append({
"speaker": "μ¬μ©μ",
"message": user_message,
"time": datetime.now()
})
st.session_state.chat_history.append({
"speaker": "AI",
"message": response,
"time": datetime.now()
})
st.markdown("<div style='max-height:400px; overflow-y:auto; padding:10px; border:1px solid #eaeaea; border-radius:6px;'>", unsafe_allow_html=True)
for chat in st.session_state.chat_history:
time_str = chat["time"].strftime("%H:%M:%S")
st.markdown(f"**{chat['speaker']}** ({time_str}): {chat['message']}")
st.markdown("</div>", unsafe_allow_html=True)
st.markdown("""
<div style="text-align: center; padding: 20px; color: #6c757d; font-size: 0.8rem;">
<p>""" + t("built_with") + """</p>
</div>
""", unsafe_allow_html=True) |