ShivaPrakash commited on
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Delete app.py

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  1. app.py +0 -164
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- import streamlit as st
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- import pandas as pd
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- import docx
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- import io
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-
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- # Sample data
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- questions = [
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- {"no": 1, "question": "What is the capital of France?", "a": "Paris", "b": "London", "c": "Berlin", "d": "Madrid", "answer": "Paris"},
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- {"no": 2, "question": "What is the largest planet in our solar system?", "a": "Earth", "b": "Mars", "c": "Jupiter", "d": "Saturn", "answer": "Jupiter"},
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- # Add more questions as needed
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- ]
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-
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- text = """Explore pathways to get started with learning and working with Generative AI.Lesson Activities:Introduction (10 minutes):
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- Briefly discuss the history and evolution of AI.
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- Introduce the concept of Generative AI and its different types (e.g., text, image, audio).
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- Showcase examples of Generative AI applications in various industries.
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- Challenges and Opportunities (15 minutes):
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- Discuss the rapid pace of advancements in AI and the resulting confusion.
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- Address ethical concerns and potential biases in AI systems.
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- Explore the vast potential of Generative AI for innovation and problem-solving.
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- The Generative AI Engineer (20 minutes):
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- Define the role and responsibilities of a Generative AI engineer.
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- Explain the skillset required, including machine learning, software engineering, and problem-solving skills.
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- Discuss the importance of bridging the gap between research and practical applications.
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- Getting Started with Generative AI (25 minutes):
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- Provide resources and tools for learning about Generative AI.
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- Introduce popular platforms and frameworks for building AI models.
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- Share tips for building a portfolio and gaining practical experience.
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- Q&A and Discussion (30 minutes):
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- Answer questions from students and address their concerns.
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- Encourage discussion and sharing of ideas.
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- Motivate students to explore and experiment with Generative AI."""
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-
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- # Initialize score
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- score = 0
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- answer = ['','','','','','','','','','']
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- i = 0
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-
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-
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- st.set_page_config(page_title="Dhrona.ai", page_icon="🏹")
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- st.title("🏹 Dhrona.ai 🏹 ")
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- # st.subheader('Your personalized teaching assistant by AI Anamolies')
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-
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- default_title = "This is where title of your for the uploaded lecture gets published"
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- default_lessonplan = "This is where the default lesson plan gets uploaded"
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- default_notes = "This is where the notes get published"
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-
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- ss = st.session_state
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-
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-
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- with st.sidebar:
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- with st.form("config"):
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- st.header("Upload here")
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- yturl = st.text_input('Enter YouTube URL ')
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- st.subheader("or")
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- audiofile = st.file_uploader("Please choose a file")
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- st.subheader("or")
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- driveurl = st.text_input('Enter location of the file')
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- if st.form_submit_button("submit"):
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-
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- if 'youtube.com' in yturl:
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- # transcript = extract_youtube_transcript(url)
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- st.write('Text Summary:')
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- # st.write(transcript)
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- elif audiofile:
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- # transcript = extract_pdf_text(url)
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- st.write('Text Summary:')
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- # st.write(transcript)
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- elif driveurl:
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- # transcript = extract_pdf_text(url)
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- st.write('Text Summary:')
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- # st.write(transcript)
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- else:
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- st.write('Please enter a valid YouTube URL or file URL.')
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-
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- st.info("""
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- [Dhrona.ai](https://github.com/xleven/ai-hackathon-judge) is a personalized teaching assistant
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- built by AI anomalies : [Siddartha](https://github.com/xleven) & [Shiva](https://github.com/langchain-ai/langchain) with [Streamlit](https://streamlit.io).
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- """, icon="ℹ️")
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-
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- st.info("""
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- All you need to do is upload an Youtube url or audio file of your lecture. "Dhron" will give you a detailed, yet crisp notes along with a lesson plan. Once you are done going through the notes, you can test your skills by answering 10 MCQ's
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- """, icon="ℹ️")
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-
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- st.header("Lesson Info")
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- title = st.write(default_title)
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-
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- with st.expander("Lesson Plan"):
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- st.write(f"{default_lessonplan}")
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-
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- with st.expander("Notes"):
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- st.write(f"{default_notes}")
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-
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- # lessonplan = st.text_area("Lesson Plan", default_lessonplan, height=200)
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- # notes = st.text_area("Notes", default_notes, height=600)
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-
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- st.divider()
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-
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- #update your file here
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- file1 = "Notes.txt"
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-
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-
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- # def fileopen(filename):
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- # f = open('MCQ.docx', 'rb')
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- # Load the document
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- # doc_download = text
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- # Close the file
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- # f.close()
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- # Create a BytesIO object to hold the document data
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- # bio = io.BytesIO()
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- # Save the document to the BytesIO object
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- # doc_download.save(bio)
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- # return bio
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-
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-
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- # Reset the BytesIO object's position to the beginning
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-
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- st.subheader("Download your notes here")
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- st.download_button(
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- label="Download Worldfile",
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- data=text.encode('utf-8'),
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- file_name=file1,
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- mime="text/plain",
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- # file_name="example.md",
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- # mime="text/markdown",
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-
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- )
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-
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- st.divider()
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-
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- st.header("Assessment")
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- with st.expander("Lets take the test when ready!!"):
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- # st.write(f"{default_lessonplan}")
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-
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-
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- # Create a form for the quiz
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- with st.form(key='quiz_form'):
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- for question in questions:
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- st.subheader(f"Question {question['no']}: {question['question']}")
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- options = [question['a'], question['b'], question['c'], question['d']]
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- user_answer = st.radio("Select an answer", options, key=f"question_{question['no']}")
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- # st.write(user_answer)
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- answer[i] = user_answer
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- i +=1
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- print(answer)
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- # Submit button to calculate the score
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-
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- if st.form_submit_button("Submit"):
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- i = 0
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- # "entering submit function"
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- # st.write(answer)
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- # st.write(questions)
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- for question in questions:
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- # st.write("Entering for loop")
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- # user_answer = st.radio(key=f"question_{question['no']}")
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- if question['answer'] == answer[i]:
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- # st.write("correct")
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- score += 1
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- else:
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- pass
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- # return score
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- i = i+1
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- # Display the final score outside the form
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- st.header(f"Your score: {score}/{len(questions)}")