lab/multilingual_word_limit_issue_v3.py

import streamlit as st
from graph import EssayWriter, RouteQuery, GraphState
from language_options import language_options
from crew import *
import os
import re
import traceback
import base64

# Install Graphviz if not found
if os.system("which dot") != 0:
    os.system("apt-get update && apt-get install -y graphviz")

st.markdown(
    """
    <h1 style="text-align: center; white-space: nowrap; font-size: 2.5em;">
        Multi-Agent Essay Writing Assistant
    </h1>
    """,
    unsafe_allow_html=True
)

# Ensure session state variables are initialized properly
if "messages" not in st.session_state:
    st.session_state["messages"] = [{"role": "assistant", "content": "Hello! How can I assist you today?"}]

if "app" not in st.session_state:
    st.session_state["app"] = None

if "chat_active" not in st.session_state:
    st.session_state["chat_active"] = True

# Sidebar with essay settings and user-defined length
# Sidebar with essay settings and user-defined length
with st.sidebar:
    st.subheader("📝 Note:")
    st.info(
        "\n\n 1. This app uses the 'gpt-4o-mini-2024-07-18' model."
        "\n\n 2. Writing essays may take some time, approximately 1-2 minutes."
    )

    # API Key Retrieval
    openai_key = st.secrets.get("OPENAI_API_KEY", "")

    st.divider()

    # User-defined essay length selection
    st.subheader("⚙️🛠️ Configure Essay Settings:")
    essay_length = st.number_input(
        "Select Essay Length (words):",
        min_value=150,
        max_value=500,
        value=250,
        step=50
    )

    #st.divider()

    #Language Selection
    #st.subheader("🌍 Select Language:")    
    selected_language = st.selectbox("Choose Language:", sorted(language_options.keys()), index=list(language_options.keys()).index("English"))

    st.divider()

    # Reference section
    st.subheader("📖 References:")
    st.markdown(
        "[1. Multi-Agent System with CrewAI and LangChain](https://discuss.streamlit.io/t/new-project-i-have-build-a-multi-agent-system-with-crewai-and-langchain/84002)",
        unsafe_allow_html=True
    )


# Initialize agents function
def initialize_agents():
    if not openai_key:
        st.error("⚠️ OpenAI API key is missing! Please provide a valid key through Hugging Face Secrets.")
        st.session_state["chat_active"] = True
        return None

    os.environ["OPENAI_API_KEY"] = openai_key
    try:
        # Prevent re-initialization
        if "app" in st.session_state and st.session_state["app"] is not None:
            return st.session_state["app"]
        
        # Initialize the full EssayWriter instance
        essay_writer = EssayWriter()  # Store the full instance
        st.session_state["app"] = essay_writer  # Now contains `graph`
        st.session_state["chat_active"] = False  # Enable chat after successful initialization

        return essay_writer
    except Exception as e:
        st.error(f"❌ Error initializing agents: {e}")
        st.session_state["chat_active"] = True
        return None


# Automatically initialize agents on app load
if st.session_state["app"] is None:
    st.session_state["app"] = initialize_agents()

if st.session_state["app"] is None:
    st.error("⚠️ Failed to initialize agents. Please check your API key and restart the app.")

app = st.session_state["app"]

# Function to invoke the agent and generate a response
def enforce_word_limit(text, limit):
    """Enforces strict word limit by truncating extra words."""
    words = re.findall(r'\b\w+\b', text)
    return ' '.join(words[:limit]) if len(words) > limit else text

def detect_unexpected_english(text, selected_language):
    """Detects unintended English words when another language is selected."""
    if selected_language != "English":
        english_words = re.findall(r'\b(?:is|the|and|or|in|on|at|to|with|for|of|by|it|that|this|was|he|she|they|we|you|I)\b', text)
        return len(english_words) > 5  # Allow a small tolerance

def generate_response(topic, length, selected_language):
    if not app or not hasattr(app, "graph"):
        st.error("Agents are not initialized. Please check the system or restart the app.")
        return {"response": "Error: Agents not initialized."}

    # Dynamically adjust structure based on length
    if length <= 250:
        intro_limit, body_limit, conclusion_limit = length // 5, length // 2, length // 5
        num_sections = 2  # Shorter essays should have fewer sections
    elif length <= 350:
        intro_limit, body_limit, conclusion_limit = length // 6, length // 1.8, length // 6
        num_sections = 3
    else:
        intro_limit, body_limit, conclusion_limit = length // 7, length // 1.7, length // 7
        num_sections = 4

    # Optimized Structured Prompt
    refined_prompt = f"""
    Write a **well-structured, informative, and engaging** essay on "{topic}" **strictly in {selected_language}.**
    
    **Word Limit:** Exactly {length} words. **Do not exceed or fall short of this limit.**
    **Language Rules:** Use natural linguistic style from {selected_language}. **Do not use English** unless explicitly requested.
    
    **Essay Structure:**
    - **Title**: Max 10 words.
    - **Introduction ({intro_limit} words max)**:
      - Clearly define the topic and its significance.
      - Provide a strong thesis statement.
      - Preview the key points covered in the essay.
    - **Main Body ({body_limit} words max, {num_sections} sections)**:
      - Each section must have:
        - A **clear subheading**.
        - A concise topic sentence with supporting details.
        - Relevant **examples, statistics, or historical references**.
      - Maintain natural **flow** between sections.
    - **Conclusion ({conclusion_limit} words max)**:
      - Summarize key insights **without repetition**.
      - Reinforce the thesis **based on discussion**.
      - End with a strong **closing statement** (reflection or call to action).
    
    **Hard Rules:**
    - **Use only {selected_language}**. No English unless explicitly requested.
    - **Do not exceed {length} words.** Absolute limit.
    - **Write concisely and avoid fluff**. No redundancy.
    - **Merge similar ideas** to maintain smooth readability.
    - **Ensure strict adherence to section word limits**.
    """

    # Invoke AI model with enforced word limit
    response = app.graph.invoke(input={
        "topic": topic,
        "length": length,
        "prompt": refined_prompt,
        "language": selected_language,
        "max_tokens": length + 10  # Small buffer for better trimming
    })

    # Strict word limit enforcement
    essay_text = enforce_word_limit(response.get("essay", ""), length)

    # Detect unintended English words in non-English essays
    if detect_unexpected_english(essay_text, selected_language):
        return {"response": f"⚠️ Warning: Some English words were detected in the {selected_language} essay. Try regenerating."}

    return {"essay": essay_text}



# Define Tabs
tab1, tab2 = st.tabs(["📜 Essay Generation", "📊 Workflow Viz"])

# 📜 Tab 1: Essay Generation
with tab1:
    # Display chat messages from the session
    if "messages" not in st.session_state:
        st.session_state["messages"] = [{"role": "assistant", "content": "Hello! How can I assist you today?"}]

    for message in st.session_state["messages"]:
        with st.chat_message(message["role"]):
            st.markdown(message["content"], unsafe_allow_html=True)

    # Input
    topic = st.text_input("📝 Provide an essay topic:", value="Write an essay on the cultural diversity of India")

    # Add spacing
    st.write("")

    # Generate button
    if st.button("🚀 Generate Essay"):
        if topic and topic.strip():  # Ensure it's not empty
            # Store user message only if it's not already stored
            if not any(msg["content"] == topic for msg in st.session_state["messages"]):
                st.session_state["messages"].append({"role": "user", "content": topic})

            with st.spinner("⏳ Generating your essay..."):
                response = None
                if app:
                    response = app.write_essay({"topic": topic})
                else:
                    st.error("⚠️ Agents are not initialized. Please check the system or restart the app.")

            # Store and display assistant response
            if response and "essay" in response:
                essay = response["essay"]

                assistant_response = f"Here is your {essay_length}-word essay preview and the download link."
                st.session_state["messages"].append({"role": "assistant", "content": assistant_response})

                st.chat_message("assistant").markdown(assistant_response)

                # Create Two-Column Layout
                col1, col2 = st.columns(2)

                with col1:
                    st.markdown(f"### 📝 Essay Preview ({essay_length} words)")
                    st.markdown(f"#### {essay['header']}")
                    st.markdown(essay["entry"])

                    for para in essay["paragraphs"]:
                        st.markdown(f"**{para['sub_header']}**")
                        st.markdown(para["paragraph"])

                    st.markdown("**🖊️ Conclusion:**")
                    st.markdown(essay["conclusion"])

                with col2:
                    st.markdown("### ✍️ Edit Your Essay:")

                    # Combine all parts of the essay into one editable text field
                    full_essay_text = f"## {essay['header']}\n\n{essay['entry']}\n\n"
                    for para in essay["paragraphs"]:
                        full_essay_text += f"### {para['sub_header']}\n{para['paragraph']}\n\n"
                    full_essay_text += f"**Conclusion:**\n{essay['conclusion']}"

                    # Editable text area for the user
                    edited_essay = st.text_area("Edit Here:", value=full_essay_text, height=300)

                    # Save and Download buttons
                    save_col1, save_col2 = st.columns(2)

                    with save_col1:
                        if st.button("💾 Save as TXT"):
                            with open("edited_essay.txt", "w", encoding="utf-8") as file:
                                file.write(edited_essay)
                            with open("edited_essay.txt", "rb") as file:
                                st.download_button(label="⬇️ Download TXT", data=file, file_name="edited_essay.txt", mime="text/plain")

                    with save_col2:
                        if st.button("📄 Save as PDF"):
                            from fpdf import FPDF

                            pdf = FPDF()
                            pdf.set_auto_page_break(auto=True, margin=15)
                            pdf.add_page()
                            pdf.set_font("Arial", size=12)

                            for line in edited_essay.split("\n"):
                                pdf.cell(200, 10, txt=line, ln=True, align='L')

                            pdf.output("edited_essay.pdf")

                            with open("edited_essay.pdf", "rb") as file:
                                st.download_button(label="⬇️ Download PDF", data=file, file_name="edited_essay.pdf", mime="application/pdf")

                # Provide download link for the original PDF 
                pdf_name = response.get("pdf_name")
                if pdf_name and os.path.exists(pdf_name):
                    with open(pdf_name, "rb") as pdf_file:
                        b64 = base64.b64encode(pdf_file.read()).decode()
                        href = f"<a href='data:application/octet-stream;base64,{b64}' download='{pdf_name}'>📄 Click here to download the original PDF</a>"
                        st.markdown(href, unsafe_allow_html=True)

                # Save response in session state
                st.session_state["messages"].append(
                    {"role": "assistant", "content": f"Here is your {essay_length}-word essay preview and the download link."}
                )
            elif response:
                st.markdown(response["response"])
                st.session_state["messages"].append({"role": "assistant", "content": response["response"]})
            else:
                st.error("⚠️ No response received. Please try again.")



# 📊 Tab 2: Workflow Visualization
with tab2:
    #st.subheader("📊 Multi-Agent Essay Writer Workflow Viz")

    try:
        graph_path = "/tmp/graph.png"  
        if os.path.exists(graph_path):
            st.image(graph_path, caption="Multi-Agent Essay Writer Workflow Visualization", use_container_width=True)
        else:
            st.warning("⚠️ Workflow graph not found. Please run `graph.py` to regenerate `graph.png`.")

    except Exception as e:
        st.error("❌ An error occurred while generating the workflow visualization.")
        st.text_area("Error Details:", traceback.format_exc(), height=500)


# Acknowledgement Section
st.markdown(
    """
    <div style="text-align: center; font-size: 14px; color: #555; padding-top: 200px; margin-top: 200px;">
        <strong>Acknowledgement:</strong> This app is based on Mesut Duman's work: 
        <a href="https://github.com/mesutdmn/Autonomous-Multi-Agent-Systems-with-CrewAI-Essay-Writer/tree/main" 
           target="_blank" style="color: #007BFF; text-decoration: none;">
           CrewAI Essay Writer
        </a>
    </div>
    """,
    unsafe_allow_html=True,
)