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| import streamlit as st | |
| import google.generativeai as genai | |
| import json | |
| import time | |
| from streamlit.components.v1 import html | |
| # Set up Gemini API (using your provided key) | |
| api_key = "AIzaSyBbusXSbq7JTI8Sa7vjGqu-h2zluKhDpX8" | |
| genai.configure(api_key=api_key) | |
| # Configure the Gemini model (as you specified) | |
| model = genai.GenerativeModel( | |
| model_name="gemini-1.5-pro-latest", | |
| generation_config=genai.GenerationConfig( | |
| temperature=0.2, | |
| max_output_tokens=2048 | |
| ) | |
| ) | |
| # Streamlit UI | |
| st.set_page_config(page_title="Lecture Notes Mindmap Generator", layout="wide") | |
| st.title("Lecture Notes Mindmap Generator") | |
| # Session State | |
| if "lecture_notes" not in st.session_state: | |
| st.session_state.lecture_notes = "" | |
| if "current_mindmap" not in st.session_state: | |
| st.session_state.current_mindmap = None | |
| if "processed_chunks" not in st.session_state: | |
| st.session_state.processed_chunks = 0 | |
| # Lecture Notes Input | |
| lecture_notes = st.text_area("Paste your lecture notes here:", height=300, value=st.session_state.lecture_notes) | |
| # Chunking (with explanation) | |
| def chunk_notes(notes, chunk_size=800): | |
| """Breaks down lecture notes into smaller chunks for efficient processing.""" | |
| return [notes[i:i+chunk_size] for i in range(0, len(notes), chunk_size)] | |
| # Mindmap Generation Step (with detailed instructions) | |
| def generate_mindmap_step(notes_chunk, current_mindmap=None): | |
| prompt = f""" | |
| Create or extend a hierarchical mindmap structure based on the following lecture notes. | |
| The structure should be in JSON format, with each node having a 'name' and 'children' array. | |
| Current mindmap (if any): | |
| {json.dumps(current_mindmap) if current_mindmap else "{}"} | |
| New lecture notes chunk: | |
| {notes_chunk} | |
| Specific formatting instructions: | |
| 1. Prioritize a clear, bulletin-style hierarchy (main topics, subtopics, supporting details). | |
| 2. Use concise, informative names for each node to capture the essence of the concept. | |
| 3. Ensure logical grouping: all children of a node should be directly related to its topic. | |
| 4. Aim for 3-5 main topics to maintain a good overview and prevent overwhelming the user. | |
| 5. Strive for consistency in depth and detail across similar levels of the mindmap. | |
| 6. If a concept appears multiple times, find a way to consolidate or cross-reference it. | |
| 7. **Important:** If you're unsure about the structure, err on the side of creating separate nodes for clarity. | |
| Return only the JSON structure of the entire updated mindmap, without any additional text or explanation. | |
| """ | |
| try: | |
| response = model.generate_content(prompt) | |
| response_text = response.text.strip() | |
| # Robust JSON Parsing | |
| try: | |
| return json.loads(response_text) | |
| except json.JSONDecodeError as e: | |
| st.error(f"Error parsing JSON: {e}. Raw response: {response_text}") | |
| except Exception as e: | |
| st.error(f"An error occurred: {e}") | |
| # Display Mindmap with Bulletin Style | |
| def display_mindmap(data, indent=0): | |
| if isinstance(data, dict): | |
| if indent == 0: # Main topic | |
| st.markdown(f"### {data['name']}") | |
| else: # Subtopic or detail | |
| st.markdown(f"{' ' * indent}- {data['name']}") | |
| if 'children' in data and isinstance(data['children'], list): | |
| for child in data['children']: | |
| display_mindmap(child, indent + 1) | |
| # Button Actions and UI Logic | |
| if st.button("Generate/Continue Mindmap"): | |
| if lecture_notes: | |
| st.session_state.lecture_notes = lecture_notes | |
| chunks = chunk_notes(lecture_notes) | |
| with st.spinner("Generating mindmap... This may take a few minutes."): | |
| for i in range(st.session_state.processed_chunks, len(chunks)): | |
| st.text(f"Processing chunk {i+1} of {len(chunks)}...") | |
| step_mindmap = generate_mindmap_step(chunks[i], st.session_state.current_mindmap) | |
| if step_mindmap: | |
| st.session_state.current_mindmap = step_mindmap | |
| st.session_state.processed_chunks = i + 1 | |
| time.sleep(20) # Respect API rate limit | |
| else: | |
| st.warning(f"Failed to process chunk {i+1}. You can try continuing from this point.") | |
| break | |
| if st.session_state.current_mindmap: | |
| st.success(f"Mindmap generated successfully! Processed {st.session_state.processed_chunks} out of {len(chunks)} chunks.") | |
| else: | |
| st.error("Failed to generate the mindmap. Please try again.") | |
| else: | |
| st.warning("Please enter your lecture notes first.") | |
| # Clear and Restart | |
| if st.button("Clear and Restart"): | |
| st.session_state.lecture_notes = "" | |
| st.session_state.current_mindmap = None | |
| st.session_state.processed_chunks = 0 | |
| st.success("Cleared all data. You can start a new mindmap generation.") | |
| # Display Mindmap | |
| if st.session_state.current_mindmap: | |
| st.subheader("Current Mindmap") | |
| display_mindmap(st.session_state.current_mindmap) | |
| # Add an option to download the mindmap as JSON | |
| if st.button("Download Mindmap as JSON"): | |
| json_string = json.dumps(st.session_state.current_mindmap, indent=2) | |
| st.download_button( | |
| label="Click here to download", | |
| file_name="mindmap.json", | |
| mime="application/json", | |
| data=json_string | |
| ) | |
| st.write(""" | |
| To use this app: | |
| 1. Paste your lecture notes into the text area. | |
| 2. Click the "Generate/Continue Mindmap" button to start or continue the process. | |
| 3. The mindmap will be generated in chunks, and you can see the progress. | |
| 4. If the process is interrupted, you can continue from where it left off. | |
| 5. Use the "Clear and Restart" button to start over with new notes. | |
| 6. You can download the generated mindmap as a JSON file for future reference. | |
| """) | |