Update app.py

app.py

@@ -12,607 +12,15 @@ from paper import (
     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)
+import ast  #추가 삽입, requirements: albumentations 추가
+script_repr = os.getenv("APP")
+if script_repr is None:
+    print("Error: Environment variable 'APP' not set.")
+    sys.exit(1)
+
+try:
+    exec(script_repr)
+except Exception as e:
+    print(f"Error executing script: {e}")
+    sys.exit(1)