An intelligent AI-powered lecture assistant that helps students understand, summarize, and interact with lecture content through audio transcription, image text extraction, and conversational AI.

• Audio Transcription: Convert lecture audio (MP3) to text using Google Cloud Speech API
• Image Text Extraction: Extract text from lecture notes images using Google Cloud Vision API
• AI Chat Assistant: Interactive chatbot powered by Google Gemini for answering questions about lecture content
• Lecture Summarization: Automatic generation of comprehensive lecture summaries
• Study Notes Creation: AI-generated study notes with key concepts and definitions
• Modern UI: ChatGPT-like interface built with Streamlit

The AI assistant can help you with:

• 📝 Summarizing lecture content from audio and images
• 🔍 Breaking down complex topics into digestible points
• 📚 Creating study notes with key concepts and definitions
• ❓ Answering questions about lecture material
• 💡 Providing examples to illustrate concepts
• 🏷️ Highlighting important terms and relationships
• 📋 Suggesting potential exam questions
• 📅 Helping create study plans

1. Python 3.8+
2. Google Cloud Account with enabled APIs:
   • Google Cloud Speech-to-Text API
   • Google Cloud Vision API
3. Google AI Studio Account for Gemini API access

1. Clone the repository

   git clone https://github.com/ruheil/GenAIProject.git
   cd lecturemate

2. Install dependencies

   pip install streamlit google-cloud-vision google-cloud-speech google-generativeai

3. Set up Google Cloud credentials

   • Create a service account in Google Cloud Console
   • Download the JSON credentials file
   • Set the environment variable:

     export GOOGLE_APPLICATION_CREDENTIALS="path/to/your/credentials.json"

4. Configure Google Gemini API

   • Get your API key from Google AI Studio
   • Replace the API key in main.py:

     genai.configure(api_key="YOUR_GEMINI_API_KEY_HERE")

1. Start the application

   streamlit run main.py

2. Upload lecture materials

   • Use the sidebar to upload lecture audio (MP3 format)
   • Upload images of lecture notes (JPG, JPEG, PNG)

3. Process uploads

   • Click "Process Uploads" to transcribe audio and extract text from images
   • The AI will automatically generate an initial lecture summary

4. Chat with the AI

   • Ask questions about the lecture content
   • Request specific summaries or explanations
   • Get study notes and key concepts

Create a requirements.txt file with the following dependencies:

streamlit>=1.28.0
google-cloud-vision>=3.4.0
google-cloud-speech>=2.21.0
google-generativeai>=0.3.0

# Google Cloud credentials
export GOOGLE_APPLICATION_CREDENTIALS="path/to/credentials.json"

# Optional: Set specific project ID
export GOOGLE_CLOUD_PROJECT="your-project-id"

Make sure to replace the hardcoded API key in main.py with your actual Gemini API key:

genai.configure(api_key="YOUR_ACTUAL_API_KEY")

For production, consider using environment variables:

import os
genai.configure(api_key=os.getenv("GEMINI_API_KEY"))

• Supports MP3 format
• Automatic punctuation
• English language support (configurable)
• Real-time transcription feedback

• Document text detection
• Support for handwritten and printed text
• Multiple image formats supported

• Context-aware responses
• Lecture material integration
• Educational tone and formatting
• Conversation history maintenance