KnowledgeBuilder.py

from pathlib import Path
import speech_recognition as sr
import pdf2image
import gtts
import playsound
from streamlit_ace import st_ace
from PIL import Image
import base64
import streamlit as st
from streamlit_extras.let_it_rain import rain
from tempfile import NamedTemporaryFile
from streamlit_option_menu import option_menu
from streamlit_extras.mandatory_date_range import date_range_picker
import datetime
import os
import textwrap
import google.generativeai as genai
from IPython.display import display
from IPython.display import Markdown
from streamlit_lottie import st_lottie
import requests 
import sys
import io
from streamlit_webrtc import webrtc_streamer, VideoProcessorBase
from youtube_transcript_api import YouTubeTranscriptApi
import time
global s
k=0


os.getenv("AIzaSyBIBVb-0Z0QwaucMGOGy8-j_RM22X-4-lE")
genai.configure(api_key="AIzaSyBIBVb-0Z0QwaucMGOGy8-j_RM22X-4-lE")
t=[ "Python", "Java", "C++", "JavaScript", "Ruby", "PHP", "Swift", "Kotlin", 
    "C#", "Go", "R", "TypeScript", "Scala", "Perl", "Objective-C", "Dart", 
    "Rust", "Haskell", "MATLAB", "SQL", "HTML/CSS", "React", "Angular", "Vue.js", 
    "Node.js", "Django", "Flask", "Spring", "ASP.NET", "Ruby on Rails"]
interview_topics = [
    # Core Python
    "Python fundamentals (syntax, data types, control flow)",
    "Object-oriented programming (OOP) concepts",
    "Data structures (lists, tuples, dictionaries, sets)",
    "Functions and modules",
    "Exception handling",

    # Advanced Python
    "Functional programming paradigms",
    "Decorators and generators",
    "Metaclasses",
    "Concurrency and parallelism",
    "Asynchronous programming",

    # Data Science and Machine Learning
    "NumPy and Pandas",
    "Data cleaning and preprocessing",
    "Exploratory data analysis (EDA)",
    "Machine learning algorithms and models",
    "Model evaluation and deployment",

    # Web Development
    "Django or Flask frameworks",
    "RESTful APIs",
    "Databases (SQL, NoSQL)",
    "Front-end technologies (HTML, CSS, JavaScript)",

    # Software Engineering
    "Design patterns",
    "Algorithms and data structures",
    "Software testing and debugging",
    "Version control (Git)",
    "Code optimization and refactoring",

    # Other
    "Problem-solving and logical reasoning",
    "System design",
    "Project management",
    "Open-source contributions",
    "Soft skills (communication, teamwork, leadership)"
]
st.set_page_config(page_title="KnowledgeBuilder", page_icon='chart_with_upwards_trend', layout="wide", initial_sidebar_state="auto", menu_items=None)
EXAMPLE_NO = 1
is_listening = False
recognizer = sr.Recognizer()
def input_pdf_setup(uploaded_file):
        if uploaded_file is not None:
            ## Convert the PDF to image
            images=pdf2image.convert_from_bytes(uploaded_file.read())
            first_page=images[0]
            # Convert to bytes
            img_byte_arr = io.BytesIO()
            first_page.save(img_byte_arr, format='JPEG')
            img_byte_arr = img_byte_arr.getvalue()

            pdf_parts = [
                {
                    "mime_type": "image/jpeg",
                    "data": base64.b64encode(img_byte_arr).decode()  # encode to base64
                }
            ]
            return pdf_parts
        else:
            raise FileNotFoundError("No file uploaded")
def get_gemini_response1(input,pdf_cotent,prompt):
    model=genai.GenerativeModel('gemini-1.5-flash')
    response=model.generate_content([input,pdf_content[0],prompt])
    return response.text
def example():
    rain(
        emoji="*",
        font_size=54,
        falling_speed=5,
        animation_length="infinite",
    )
def get_gemini_response(question):
    model = genai.GenerativeModel('gemini-pro')
    response = model.generate_content(question)
    return response.text
def load_lottieurl(url: str):
        r = requests.get(url)
        if r.status_code != 200:
            return None
        return r.json() 
def recognize_speech_from_microphone():
    with sr.Microphone() as source:
        while is_listening:
            st.write("Listening...")
            audio = recognizer.listen(source)
            try:
                text = recognizer.recognize_google(audio)
                
                return text
            except sr.UnknownValueError:
                st.error("Google Speech Recognition could not understand audio")
            except sr.RequestError as e:
                st.error(f"Could not request results from Google Speech Recognition service; {e}")
def to_markdown(text):
  text = text.replace('•', '  *')
  return Markdown(textwrap.indent(text, '> ', predicate=lambda _: True))
def get_transcript(video_url):

  # Extract the video ID from the URL
  video_id = video_url.split("=")[1]

  # Create an instance of YouTubeTranscriptApi
  transcript_api = YouTubeTranscriptApi()

  # Get the transcript data
  transcript = transcript_api.get_transcript(video_id)

  return transcript
def pseudo_bold(text):
    bold_text = ''.join(chr(0x1D5D4 + ord(c) - ord('A')) if 'A' <= c <= 'Z' else
                        chr(0x1D5EE + ord(c) - ord('a')) if 'a' <= c <= 'z' else c
                        for c in text)
    return bold_text
def streamlit_menu(example=1):
    if example == 1:
        with st.sidebar:
            selected = option_menu(
                
                menu_title="Knowledge Builder🧠",  # required
                options=["Road Map","Code Editor","Mock Interview","AI Bot","DSA BOT","Hack Bot","Interview Bot"],  # required
                icons=["geo-alt-fill","bi bi-code-slash","bi bi-camera-video-fill","robot"],  # optional
                menu_icon="cast",  # optional
                default_index=0,
            )
        return selected
    if example == 2:
        selected = option_menu(
                menu_title="Knowledge Builder",  # required
                options=["Road Map","Code Editor","Mock Interview","AI Bot"],  # required
                icons=["geo-alt-fill","bi bi-code-slash","bi bi-camera-video-fill","robot"],  # optional
                menu_icon="cast",  # optional
                default_index=0,
            )
        return selected
    if example == 3:
        selected = option_menu(
                menu_title="Knowledge Builder",  # required
                options=["Road Map","Ai bot","Code-editior","Question"],  # required
                icons=["geo-alt-fill","robot","bi bi-code-slash","bi bi-question-diamond-fill"],  # optional
                menu_icon="cast",  # optional
                default_index=0,
            )
        return selected
        return selected
    if example == 4:
        with st.sidebar:
            selected = option_menu(
                menu_title="Main Menu",  # required
                options=["Road Map", "Resume Builder", "Ai bot","ATS-DECTOR"],  # required
                icons=["geo-alt-fill", "file-person-fill", "robot"],  # optional
                menu_icon="cast",  # optional
                default_index=0,                
                # optional
            )
        return selected
selected = streamlit_menu(example=EXAMPLE_NO)
if 'questions' not in st.session_state:
    st.session_state.questions = []
if selected == "Road Map":
    link="https://lottie.host/76509b4e-81b1-4877-9974-1fa506b294b1/ja7bfvhaEb.json"
    l=load_lottieurl(link)
    col1, col2 = st.columns([1,9])  # Create two columns
    with col1:
        st.lottie(l, height=100, width=100)
    with col2:
        st.header(f":rainbow[Get Your Personalised Roadmap]😎🧑‍🏫", divider='rainbow')
    with st.form(key='survey_form'):
        col1, col2 = st.columns(2)  # Create two columns
        with col1:
            text_stack_placeholder = pseudo_bold("Known Tech Stacks")
            text_know = st.multiselect("Tech Stacks You Already Know", t, [], placeholder="choose tech stacks")
        with col2:
            End_Gole = st.multiselect("What is your End Goal ?", t, [], placeholder="choose end goal")    
        col1, col2 ,col3= st.columns(3)  # Create two columns
        with col1:
            year=st.radio("Which year you are in", ("1st year 🥳", "2nd year 😃", "3rd year 😊","4th year  🎓"))
        with col2:
            learning_speed = st.radio("How would you describe your learning speed?", ("Fast learner🚀", "Medium learner🚣‍♀️", "Slow learner🐢"))
        with col3:
            difficulty = st.radio("At what level do you want to learn?", ("Beginner😃🟢", "Intermediate🙂🟡", "Advanced😎🔴"))
        result = date_range_picker("Select a date range")
        submit_button = st.form_submit_button(label='Submit')
    if submit_button:
        with st.spinner("Analyzing..."):
            role = """
            You are a highly skilled AI trained to Make a Proper Roda Map personalised road map for college students  . You are a professional and your Road Map should be constructive and helpful.
            """
            instructions = f"""
            student Name : Ritik
            like the student {text_know} and  it is his end goal to achive after foolwing you road map is {End_Gole}  and the student is a {year}  and his learning spped is {learning_speed} and he want to achive the gola at this levl{difficulty} and this all must be completed in the duration {result}
            Your job is to proved a Proper Road Map and personalised :
            
           
            1. In this section you have to provide me:-
                    in a table format :-
                        1. sno
                        2. topic name for each day
                        3. leet code question name (name of the question) on that at least 2 
                        4. Youtube link to study that 
            2. 
                Give :
                    some likes of youtube  form which take take refreese  both englis and hindi channeld first engilsh and second hindi 
            3. Give :
                some webstie link where he can read rome about the pyhton conetps
            4.
                give:
                    some books name where he can study 
            5.
                any addition imformation you give which will be help full for the studes 
            6.
            Final review:

            At the end give a final review addition tips to while following this road Map. 
            """
            s = role + instructions 
            
            s=get_gemini_response(s)
            st.write(s)
if selected == "AI Bot":
    link="https://lottie.host/364beff7-b5bc-459e-ac28-d26cfa0dfece/FLsJPwNGdK.json"
    l=load_lottieurl(link)
    example()
    col1, col2 = st.columns([2,9])  # Create two columns
    with col1:
        st.lottie(l, height=150, width=150)
    with col2:
        st.header(f"AIBot", divider='rainbow')
    if "messages" not in st.session_state:
        st.session_state["messages"] = [{"role": "assistant", "content": "How can I help you?"}]

    for msg in st.session_state.messages:
        st.chat_message(msg["role"]).write(msg["content"])

    if prompt := st.chat_input():
        st.session_state.messages.append({"role": "user", "content": prompt})
        st.chat_message("user").write(prompt)
        msg=get_gemini_response(prompt)
        st.session_state.messages.append({"role": "assistant", "content": msg})
        st.chat_message("assistant").write(msg)        
if selected=="Code Editor": 
    link="https://lottie.host/d6e55231-a53c-4d19-a142-d71320fcd9a7/hbFKIhu1KA.json"
    l=load_lottieurl(link)
    col1, col2 = st.columns([1,9])  # Create two columns
    with col1:
        st.lottie(l, height=100, width=100)
    with col2:
        st.header(f":rainbow[Code Editor]👨‍💻", divider='rainbow')      
    python_code = """def sum_of_list(l):
        print(sum(l))
sum_of_list([5,3,4,4])"""
    java_code = """public class SumOfList {
        public static void main(String[] args) {
            int[] numbers = {5, 3, 4, 4};
            int sum = 0;
            for (int number : numbers) {
                sum += number;
            }
            System.out.println(sum);
        }
    }"""
    cpp_code = """#include <iostream>

    using namespace std;

    int main() {
        int numbers[] = {5, 3, 4, 4};
        int sum = 0;
        for (int i = 0; i < sizeof(numbers) / sizeof(numbers[0]); i++) {
            sum += numbers[i];
        }
        cout << sum << endl;
        return 0;
    }"""

    # Select language
    selected_lang = st.sidebar.selectbox("Language", ["Python", "Java", "C++"])

    # Set session state
    st.session_state["selected_lang"] = selected_lang
    s=""
    with st.container(border=True):
        with st.container(border=True):
            if selected_lang == "Python":
                editor_content = st_ace(value=python_code, language='python', theme='monokai', keybinding='vscode', font_size=14,key='run-code')
            elif selected_lang == "Java":
                editor_content = st_ace(value=java_code, language='java', theme='monokai', keybinding='vscode', font_size=14)
            elif selected_lang == "C++":
                editor_content = st_ace(value=cpp_code, language='cpp', theme='monokai', keybinding='vscode', font_size=14)
            else:
                st.write("Unsupported language selected.")
        with st.container(border=True):  
            col1, col2, col3, col4= st.columns([1,1,1,2])
            with col1:
                if st.button("Debug My code ",type="primary", help="Debug your code",use_container_width=True):
                    s="Debug  my code  "+str(editor_content)+"explain where I have done wrong and correcty and write the whole correct code again "
                    s=get_gemini_response(s)
                    #st.write(s)                   
            with col2:
                if st.button("Explain whole Code",type="primary", help="Explain the Code",use_container_width=True):
                    s="Explain  my code  "+str(editor_content)+"explain where I have done wrong and exaplin like you are explain to a noob"
                    s=get_gemini_response(s)        
            with col3:
                if st.button("Time Complexity",type="primary", help="Time complexity",use_container_width=True):
                    s="Tell the time COmplextiy   "+str(editor_content)+"explain who the time complixity is correct "
                    s=get_gemini_response(s)
                    #st.write(s)
            with col4:

                p=st.multiselect("Convert Code into", ["C++","Python","Java"], [], placeholder="Choose Language")
                if p:
                    s="convert  the  whole code into the language "+str(p)+str(editor_content)+"explain"
                    s=get_gemini_response(s)
        
        with st.container(border=True): 
            col1, col2 = st.columns([6,1])  
            with col1:
                text_input = st.text_input("This is a placeholder",
        key="placeholder",)
            with col2:
                if st.button("🎤 Mic",type="primary", help="Speeck Now",use_container_width=True):
                    is_listening = True
                    voice_input = recognize_speech_from_microphone()
                    if voice_input:
                        text_input = voice_input  
                    is_listening = False
            
                
        
    if editor_content:
        output = io.StringIO()
        sys.stdout = output
        try:
            exec(editor_content)
        except Exception as e:
            # Capture any exceptions
            st.error(f"Error: {e}")
        finally:
            # Reset stdout
            sys.stdout = sys.__stdout__

        # Display the captured output
        st.write("### Code Output")
        st.text("The Output of the above code is : "+output.getvalue())

    # Display the captured input
    if text_input:
        st.success(f"You said: {text_input}")
        s="here is python code "+str(editor_content)+"so please do the change like this "+text_input+"and give me the wole answer in python only dont give me it in any english owrd explin it all in comments only "

        s=get_gemini_response(s)
        s=s[9:-3]
        
        editor_content = st_ace(value=str(s), language='python', theme='monokai', keybinding='vscode', font_size=14)
    
    st.write(s)
if selected == "Mock Interview":
    link="https://lottie.host/299688b5-e6b2-48ad-b2e9-2fa14b1fb117/TXqg2APXpL.json"
    l=load_lottieurl(link)
    col1, col2 = st.columns([1,9])  # Create two columns
    with col1:
        st.lottie(l, height=100, width=100)
    with col2:
        st.header(f":rainbow[Mock Interview]💻💻", divider='rainbow')
    with st.container(border=True):  
        col1, col2 = st.columns([1,1])   

        with col1:
            with st.container(border=True):    
                text = st.multiselect("Which topic you want to practice ",interview_topics,[],placeholder="Choose the topic")
                video_link = st.text_input(" Enter the video link",placeholder="Enter the url")    
                uploaded_file=st.file_uploader("Upload your study Material (PDF)",type=["pdf"])
                geratequestion=st.button("Generate question",type="primary", help="Gerate your question",use_container_width=True)
                button=st.button("🎤Speak now",type="primary", help="Speak Now",use_container_width=True)
        with col2:
            with st.container(border=True):
                webrtc_streamer(key="sample") 
                ques=st.multiselect("Type of Question ? ", ["MCQ","Codding","Oral"], [], placeholder="Choose Language")
    s=""
    text_input=""
    if geratequestion:
            if video_link :    
                transcript = get_transcript(video_link)
                s=""
                for segment in transcript:
                    try:
                        s=s+f"{segment['text']}"
                        #print(f"{segment['text']}")
                    except KeyError:
                        print(f"Segment with missing end time: Text: {segment['text']}")
                s=s+str(text)
                s=s+"this is tracprit of yout which i have studing now form this ask me best  question based on the tracrpit  it should be type keep in mind only give qusetion "+str(ques)
                s=get_gemini_response(s)
            if text:
                s=str(text)+"from  this is of topic yout which i have studing now form this ask me 1 question ask me best  question based on the tracrpit  it should be type keep in mind only give queston "+str(ques)
                s=get_gemini_response(s)
            if uploaded_file:
                if uploaded_file is not None:
                    st.write("PDF Uploaded Successfully")
                    pdf_content=input_pdf_setup(uploaded_file) 
                    s=get_gemini_response1("from the content make a question",pdf_content,"ask me best  question based on the tracrpit  it should be type keep in mind only give question" +str(ques))
            st.session_state["q"]= s
    
    if button:
            is_listening = True
            voice_input = recognize_speech_from_microphone()
            st.write(st.session_state["q"])
            if voice_input:
                is_listening = False
                text_input = voice_input
                  
        
            
    if s:
        st.write(s)
        k=s
    if text_input:
        st.success(f"You said: {text_input}") 
        s="the given question is"+str(st.session_state["q"] )+"And the answer is given is "+ text_input +" this is my question and my answer now you give me the coorect answer and also write give me the score for my anwer  out of 10 give me the number  it is a interview also tell how can i improve and be littlebe strict"
        
        s=get_gemini_response(s)
        st.write(s)
    
if selected== "DSA BOT":
    link="https://lottie.host/299688b5-e6b2-48ad-b2e9-2fa14b1fb117/TXqg2APXpL.json"
    l=load_lottieurl(link)
    col1, col2 = st.columns([1,9])  # Create two columns
    with col1:
        st.lottie(l, height=100, width=100)
    with col2:
        st.header(f":rainbow[DSA BOT]💻💻", divider='rainbow')
    with st.container(border=True):  
        col1, col2 = st.columns([1,1])

        st.title("dsabot")
        api_key = "OCxIwjhQg0XLtO6IuEiTj22h8iajR3hd"
        external_user_id = "rehan"
        query = st.text_input("Query")

        if st.button("Submit Query"):
            # Create Chat Session
            create_session_url = "https://api.on-demand.io/chat/v1/sessions"
            headers = {"apikey": api_key}
            body = {"pluginIds": ["plugin-1726249854"], "externalUserId": external_user_id}
            
            response = requests.post(create_session_url, headers=headers, json=body)
            session_data = response.json()
            session_id = session_data['data']['id']
            
            # Submit Query
            submit_query_url = f"https://api.on-demand.io/chat/v1/sessions/{session_id}/query"
            query_body = {
                "endpointId": "predefined-openai-gpt4o",
                "query": query,
                "pluginIds": ["plugin-1712327325", "plugin-1713962163", "plugin-1726249854"],
                "responseMode": "sync"
            }
            
            query_response = requests.post(submit_query_url, headers=headers, json=query_body)
            query_result = query_response.json()
            
            # Display the result
            st.write("Response:", query_result["data"]["answer"])

    
if selected == "Interview Bot":
    link="https://lottie.host/299688b5-e6b2-48ad-b2e9-2fa14b1fb117/TXqg2APXpL.json"
    l=load_lottieurl(link)
    col1, col2 = st.columns([1,9])  # Create two columns
    with col1:
        st.lottie(l, height=100, width=100)
    with col2:
        st.header(f":rainbow[Interview Bot]💻💻", divider='rainbow')
    with st.container(border=True):
        col1, col2 = st.columns([1,1])
        
            
    # Streamlit UI for input
    st.title("INTERVIEW CHATBOT")
    api_key = "ZaIl7Ba3E1BzvgA6Xh7RtD0AWMSafZYN"
    external_user_id = "abhishek"
    query = st.text_input("Query")

    if st.button("Submit Query"):
        # Create Chat Session
        create_session_url = "https://api.on-demand.io/chat/v1/sessions"
        headers = {"apikey": api_key}
        body = {"pluginIds": ["plugin-1726251563"], "externalUserId": external_user_id}
        
        response = requests.post(create_session_url, headers=headers, json=body)
        session_data = response.json()
        session_id = session_data['data']['id']
        
        # Submit Query
        submit_query_url = f"https://api.on-demand.io/chat/v1/sessions/{session_id}/query"
        query_body = {
            "endpointId": "predefined-openai-gpt4o",
            "query": query,
            "pluginIds": ["plugin-1712327325", "plugin-1713962163", "plugin-1726249854"],
            "responseMode": "sync"
        }
        
        query_response = requests.post(submit_query_url, headers=headers, json=query_body)
        query_result = query_response.json()
        
        # Display the result
        st.write("Response:", query_result["data"]["answer"])