Create app.py

app.py

@@ -0,0 +1,618 @@
+import streamlit as st
+import os
+import json
+from datetime import datetime, timedelta
+import base64
+import pandas as pd
+import pydeck as pdk
+import requests
+from paper import (
+    literature_research_task, outline_task, draft_writing_task,
+    citation_task, editing_task, chatbot_task,
+    run_task
+)
+
+# Add web search functionality
+def brave_search(query, count=10):
+    """
+    Perform a web search using Brave Search API
+    """
+    api_key = os.getenv("SEARCH_API")
+    if not api_key:
+        return "Error: Brave Search API key not found. Please set the SEARCH_API environment variable."
+    
+    url = "https://api.search.brave.com/res/v1/web/search"
+    headers = {
+        "Accept": "application/json",
+        "Accept-Encoding": "gzip",
+        "X-Subscription-Token": api_key
+    }
+    params = {
+        "q": query,
+        "count": count
+    }
+    
+    try:
+        response = requests.get(url, headers=headers, params=params)
+        response.raise_for_status()
+        
+        results = response.json()
+        formatted_results = []
+        
+        for result in results.get("web", {}).get("results", []):
+            formatted_results.append({
+                "title": result.get("title", ""),
+                "url": result.get("url", ""),
+                "description": result.get("description", "")
+            })
+        
+        return formatted_results
+    except Exception as e:
+        return f"Search error: {str(e)}"
+
+# st.set_page_config()는 다른 Streamlit 함수보다 가장 먼저 실행되어야 합니다.
+st.set_page_config(
+    page_title="Your AI Agent for Academic Research",
+    page_icon="📚",
+    layout="wide",
+    initial_sidebar_state="expanded"
+)
+
+# ------------------------------------------
+# 다국어 지원 (영어/한국어 예시)
+# ------------------------------------------
+translations = {
+    "en": {
+         "page_title": "Your AI Agent for Academic Research",
+         "header": "Your 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": "🚀 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": "🔄 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 ❤️ for you",
+         "itinerary_ready": "Your Research Paper is Ready! 🎉",
+         "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",
+         "web_search": "Web Search",
+         "search_placeholder": "Search for academic papers, journals, or information...",
+         "search_button": "Search",
+         "search_results": "Search Results"
+    },
+    "ko": {
+         "page_title": "당신의 학술 연구 AI 에이전트",
+         "header": "당신의 학술 연구 AI 에이전트",
+         "create_itinerary": "논문 생성",
+         "trip_details": "연구 세부사항",
+         "origin": "연구 주제",
+         "destination": "논문 제목",
+         "travel_dates": "제출 기한",
+         "duration": "논문 분량 (페이지)",
+         "preferences": "키워드/주요 초점",
+         "special_requirements": "추가 지시사항",
+         "submit": "🚀 나의 논문 생성",
+         "request_details": "연구 요청 정보",
+         "from": "주제",
+         "when": "제출 기한",
+         "budget": "논문 종류",
+         "travel_style": "작성 스타일",
+         "live_agent_outputs": "실시간 에이전트 결과",
+         "full_itinerary": "전체 논문",
+         "details": "세부사항",
+         "download_share": "다운로드 및 공유",
+         "save_itinerary": "논문 저장",
+         "plan_another_trip": "🔄 다른 논문 생성",
+         "about": "소개",
+         "how_it_works": "작동 방식",
+         "travel_agents": "연구 에이전트",
+         "share_itinerary": "논문 공유",
+         "save_for_mobile": "모바일 저장",
+         "built_with": "당신을 위해 ❤️ 만들어졌습니다",
+         "itinerary_ready": "논문이 준비되었습니다! 🎉",
+         "personalized_experience": "입력하신 정보를 바탕으로 맞춤형 논문이 생성되었습니다. 아래에서 논문을 확인하세요.",
+         "agent_activity": "에이전트 활동",
+         "error_origin_destination": "연구 주제와 논문 제목을 모두 입력하세요.",
+         "your_itinerary_file": "논문 파일",
+         "text_format": "텍스트 형식 - 모든 텍스트 편집기에서 열 수 있습니다.",
+         "web_search": "웹 검색",
+         "search_placeholder": "학술 논문, 저널 또는 정보 검색...",
+         "search_button": "검색",
+         "search_results": "검색 결과"
+    }
+}
+
+def t(key):
+    lang = st.session_state.get("selected_language", "en")
+    return translations[lang].get(key, key)
+
+# ---------------------------
+# 세션 초기화
+# ---------------------------
+if 'selected_language' not in st.session_state:
+    st.session_state.selected_language = "en"
+
+# ------------------------------------------
+# 사이드바에 언어 선택 위젯 추가
+# ------------------------------------------
+with st.sidebar:
+    language = st.selectbox(
+        "Language / 언어",
+        ["English", "한국어"]
+    )
+    lang_map = {
+        "English": "en",
+        "한국어": "ko"
+    }
+    st.session_state.selected_language = lang_map.get(language, "en")
+    
+    # Add web search component to sidebar
+    st.markdown('<div class="modern-card">', unsafe_allow_html=True)
+    st.markdown("### " + t("web_search"))
+    search_query = st.text_input(t("search_placeholder"), key="search_query")
+    search_button = st.button(t("search_button"))
+    
+    if search_button and search_query:
+        with st.spinner("Searching..."):
+            search_results = brave_search(search_query)
+            if isinstance(search_results, str) and "error" in search_results.lower():
+                st.error(search_results)
+            else:
+                st.success(f"Found {len(search_results)} results")
+                st.session_state.search_results = search_results
+    
+    if 'search_results' in st.session_state and st.session_state.search_results:
+        st.markdown(f"### {t('search_results')}")
+        for i, result in enumerate(st.session_state.search_results[:5]):
+            st.markdown(f"**{i+1}. [{result['title']}]({result['url']})**")
+            st.markdown(f"{result['description']}")
+            st.markdown("---")
+    st.markdown('</div>', unsafe_allow_html=True)
+
+# ------------------------------------------
+# UI 시작
+# ------------------------------------------
+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>📥</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"🤖 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)
+    
+    # Enhance with web search if needed
+    if "include_search" in input_text.lower():
+        search_query = task.agent.role + " about " + st.session_state.research_topic
+        search_results = brave_search(search_query, count=5)
+        
+        if not isinstance(search_results, str):  # If not error message
+            search_info = "\n\nWeb Search Results for reference:\n"
+            for i, result in enumerate(search_results):
+                search_info += f"{i+1}. {result['title']} - {result['url']}\n"
+                search_info += f"   {result['description']}\n\n"
+            
+            input_text += search_info
+            log_message = f"🔍 Added web search results for {search_query}"
+            st.session_state.log_messages.append(log_message)
+    
+    result = run_task(task, input_text)
+    if results_key:
+        st.session_state.results[results_key] = result
+    log_message = f"✅ {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>Generate your personalized research paper with AI-powered academic agents.</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>Your AI Academic Research Assistant</h3>
+        <p>AI-Powered Paper Generation</p>
+    </div>
+    """, unsafe_allow_html=True)
+    st.markdown('<div class="modern-card">', unsafe_allow_html=True)
+    st.markdown("### " + t("about"))
+    st.info("This tool generates a personalized academic research paper based on your inputs. Fill in the form and let our specialized agents craft your paper!")
+    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>Enter your research details</li>
+        <li>AI conducts literature research</li>
+        <li>Generate a paper outline</li>
+        <li>Draft and edit your paper</li>
+        <li>Download your final paper</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>Fill in the details below to generate your research paper.</p>", unsafe_allow_html=True)
+    
+    with st.form("research_form"):
+        col1, col2 = st.columns(2)
+        with col1:
+            research_topic = st.text_input(t("origin"), placeholder="e.g., Deep Learning in Healthcare")
+            paper_title = st.text_input(t("destination"), placeholder="e.g., Advances in Deep Learning for Medical Diagnosis")
+            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="Any additional instructions or requirements...")
+        keywords = st.text_area(t("preferences"), placeholder="Enter keywords or focus areas, separated by commas")
+        
+        # Add option to include web search
+        include_search = st.checkbox("Include web search for latest references", value=True)
+        
+        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,
+                "include_search": "include_search" if include_search else ""
+            }
+            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']}
+{user_input['include_search']}
+"""
+            llm_language_instructions = {
+                "en": "Please output the response in English.",
+                "ko": "한국어로 출력해 주세요."
+            }
+            selected_lang = st.session_state.get("selected_language", "en")
+            language_instruction = llm_language_instructions.get(selected_lang, "Please output the response in English.")
+            modified_input_context = language_instruction + "\n" + input_context
+            
+            st.markdown("<div>Processing your request...</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)
+    
+    # 탭 생성 (전체 논문, 세부 정보, 다운로드/공유, 시각화, 챗봇)
+    full_paper_tab, details_tab, download_tab, visualization_tab, chatbot_tab = st.tabs([
+        "🗒️ " + t("full_itinerary"),
+        "💼 " + t("details"),
+        "💾 " + t("download_share"),
+        "📊 Visualization",
+        "🤖 챗봇 인터페이스"
+    ])
+    
+    with full_paper_tab:
+        st.text_area("Your Research Paper", st.session_state.generated_itinerary, height=600)
+    
+    with details_tab:
+        agent_tabs = st.tabs(["📚 Literature Review", "📝 Outline", "✍️ Draft", "🔗 Citations", "🖋️ Edited Version"])
+        with agent_tabs[0]:
+            st.markdown("### Literature 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 research paper 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 research paper can be displayed here. (Feature under development)")
+    
+    with chatbot_tab:
+        st.markdown("### AI 챗봇 인터페이스")
+        if "chat_history" not in st.session_state:
+            st.session_state.chat_history = []
+        
+        user_message = st.text_input("메시지를 입력하세요:", key="chat_input")
+        if st.button("전송", key="send_button"):
+            if user_message:
+                # Add option to search when chatting
+                if "search" in user_message.lower() or "find" in user_message.lower() or "look up" in user_message.lower():
+                    search_results = brave_search(user_message, count=3)
+                    if not isinstance(search_results, str):
+                        search_context = f"I found some information that might help:\n\n"
+                        for i, result in enumerate(search_results):
+                            search_context += f"{i+1}. {result['title']} - {result['url']}\n"
+                            search_context += f"   {result['description']}\n\n"
+                        
+                        enhanced_prompt = f"{user_message}\n\nSearch context: {search_context}"
+                        response = run_task(chatbot_task, enhanced_prompt)
+                    else:
+                        response = run_task(chatbot_task, user_message)
+                else:
+                    response = run_task(chatbot_task, user_message)
+                
+                st.session_state.chat_history.append({
+                    "speaker": "사용자",
+                    "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)