Coding implementation for constructing interactive transcripts and PDF evaluation utilizing the LYZR chatbot framework

!pip set up lyzr youtube-transcript-api fpdf2 ipywidgets
!apt-get replace -qq && apt-get set up -y fonts-dejavu-core

import os
import openai


openai.api_key = os.getenv("OPENAI_API_KEY")
os.environ['OPENAI_API_KEY'] = "YOUR_OPENAI_API_KEY_HERE"

import json
from lyzr import ChatBot
from youtube_transcript_api import YouTubeTranscriptApi, TranscriptsDisabled, NoTranscriptFound, CouldNotRetrieveTranscript
from fpdf import FPDF
from ipywidgets import Textarea, Button, Output, Format
from IPython.show import show, Markdown
import re

def transcript_to_pdf(video_id: str, output_pdf_path: str) -> bool:
    """
    Obtain YouTube transcript (guide or auto) and write it right into a PDF
    utilizing the system-installed DejaVuSans.ttf for full Unicode assist.
    Fastened to deal with lengthy phrases and textual content formatting points.
    """
    attempt:
        entries = YouTubeTranscriptApi.get_transcript(video_id)
    besides (TranscriptsDisabled, NoTranscriptFound, CouldNotRetrieveTranscript):
        attempt:
            entries = YouTubeTranscriptApi.get_transcript(video_id, languages=['en'])
        besides Exception:
            print(f"[!] No transcript for {video_id}")
            return False
    besides Exception as e:
        print(f"[!] Error fetching transcript for {video_id}: {e}")
        return False


    textual content = "n".be a part of(e['text'] for e in entries).strip()
    if not textual content:
        print(f"[!] Empty transcript for {video_id}")
        return False


    pdf = FPDF()
    pdf.add_page()


    font_path = "/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf"
    attempt:
        if os.path.exists(font_path):
            pdf.add_font("DejaVu", "", font_path)
            pdf.set_font("DejaVu", dimension=10)
        else:
            pdf.set_font("Arial", dimension=10)
    besides Exception:
        pdf.set_font("Arial", dimension=10)


    pdf.set_margins(20, 20, 20)
    pdf.set_auto_page_break(auto=True, margin=25)


    def process_text_for_pdf(textual content):
        textual content = re.sub(r's+', ' ', textual content)
        textual content = textual content.change('nn', 'n')


        processed_lines = []
        for paragraph in textual content.break up('n'):
            if not paragraph.strip():
                proceed


            phrases = paragraph.break up()
            processed_words = []
            for phrase in phrases:
                if len(phrase) > 50:
                    chunks = [word[i:i+50] for i in vary(0, len(phrase), 50)]
                    processed_words.prolong(chunks)
                else:
                    processed_words.append(phrase)


            processed_lines.append(' '.be a part of(processed_words))


        return processed_lines


    processed_lines = process_text_for_pdf(textual content)


    for line in processed_lines:
        if line.strip():
            attempt:
                pdf.multi_cell(0, 8, line.encode('utf-8', 'change').decode('utf-8'), align='L')
                pdf.ln(2)
            besides Exception as e:
                print(f"[!] Warning: Skipped problematic line: {str(e)[:100]}...")
                proceed


    attempt:
        pdf.output(output_pdf_path)
        print(f"[+] PDF saved: {output_pdf_path}")
        return True
    besides Exception as e:
        print(f"[!] Error saving PDF: {e}")
        return False

def create_interactive_chat(agent):
    input_area = Textarea(
        placeholder="Sort a query…", format=Format(width="80%", peak="80px")
    )
    send_button = Button(description="Ship", button_style="success")
    output_area = Output(format=Format(
        border="1px stable grey", width="80%", peak="200px", overflow='auto'
    ))


    def on_send(btn):
        query = input_area.worth.strip()
        if not query:
            return
        with output_area:
            print(f">> You: {query}")
            attempt:
                print("<< Bot:", agent.chat(query), "n")
            besides Exception as e:
                print(f"[!] Error: {e}n")


    send_button.on_click(on_send)
    show(input_area, send_button, output_area)

def major():
    video_ids = ["dQw4w9WgXcQ", "jNQXAC9IVRw"]
    processed = []


    for vid in video_ids:
        pdf_path = f"{vid}.pdf"
        if transcript_to_pdf(vid, pdf_path):
            processed.append((vid, pdf_path))
        else:
            print(f"[!] Skipping {vid} — no transcript accessible.")


    if not processed:
        print("[!] No PDFs generated. Please attempt different video IDs.")
        return


    first_vid, first_pdf = processed[0]
    print(f"[+] Initializing PDF-chat agent for video {first_vid}…")
    bot = ChatBot.pdf_chat(
        input_files=[first_pdf]
    )


    questions = [
        "Summarize the transcript in 2–3 sentences.",
        "What are the top 5 insights and why?",
        "List any recommendations or action items mentioned.",
        "Write 3 quiz questions to test comprehension.",
        "Suggest 5 creative prompts to explore further."
    ]
    responses = {}
    for q in questions:
        print(f"[?] {q}")
        attempt:
            resp = bot.chat(q)
        besides Exception as e:
            resp = f"[!] Agent error: {e}"
        responses[q] = resp
        print(f"[/] {resp}n" + "-"*60 + "n")


    with open('responses.json','w',encoding='utf-8') as f:
        json.dump(responses,f,indent=2)
    md = "# Transcript Evaluation Reportnn"
    for q,a in responses.objects():
        md += f"## Q: {q}n{a}nn"
    with open('report.md','w',encoding='utf-8') as f:
        f.write(md)


    show(Markdown(md))


    if len(processed) > 1:
        print("[+] Producing comparability…")
        _, pdf1 = processed[0]
        _, pdf2 = processed[1]
        compare_bot = ChatBot.pdf_chat(
            input_files=[pdf1, pdf2]
        )
        comparability = compare_bot.chat(
            "Evaluate the principle themes of those two movies and spotlight key variations."
        )
        print("[+] Comparability End result:n", comparability)


    print("n=== Interactive Chat (Video 1) ===")
    create_interactive_chat(bot)

if __name__ == "__main__":
    major()