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( """

Multi-Agent Essay Writing Assistant

""", 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"📄 Click here to download the original PDF" 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( """
Acknowledgement: This app is based on Mesut Duman's work: CrewAI Essay Writer
""", unsafe_allow_html=True, )