diff --git a/.env b/.env new file mode 100644 index 0000000..21a41de --- /dev/null +++ b/.env @@ -0,0 +1,7 @@ +API-KEY="AIzaSyAk-vG70jpxWB17WnpOxqDtAdagBA1a9kg" +FIREBASE_PROJECT_ID="profile-data-dde0a" +FIREBASE_PRIVATE_KEY_ID="39b3f7d7d7bb9b4c7dcca432da4ee788328e1f64" +FIREBASE_PRIVATE_KEY="-----BEGIN PRIVATE KEY-----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\nudZmstCQ8c7EcKQpAYK1lA==\n-----END PRIVATE KEY-----\n" +FIREBASE_CLIENT_EMAIL="firebase-adminsdk-723lh@profile-data-dde0a.iam.gserviceaccount.com" +FIREBASE_CLIENT_ID="115904305166207640044" +FIREBASE_CLIENT_X509_CERT_URL="https://www.googleapis.com/oauth2/v1/certs" \ No newline at end of file diff --git a/KnowledgeBuilder.py b/KnowledgeBuilder.py new file mode 100644 index 0000000..609006e --- /dev/null +++ b/KnowledgeBuilder.py @@ -0,0 +1,625 @@ +from pathlib import Path +import speech_recognition as sr +import pdf2image +import gtts +import pandas as pd +import json +import traceback +from dotenv import load_dotenv +from src.mcqgenerator.utils import read_file, get_table_data +from src.mcqgenerator.logger import logging +import streamlit as st +from src.mcqgenerator.MCQGenerator import generate_evaluate_chain +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 +from util.common import get_gemini_response,get_leetcode_data,get_gemini_response1,load_lottieurl +import time + +global s +k=0 +genai.configure(api_key=os.getenv("API-KEY")) +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='src/Logo College.png', layout="wide", initial_sidebar_state="auto", menu_items=None) +if "`current_theme`" not in st.session_state: + st.session_state.current_theme = "light" +current_dir = Path(__file__).parent if "__file__" in locals() else Path.cwd() +css_file = current_dir / "src" / "main.css" +with open(css_file) as f: + st.markdown("".format(f.read()), unsafe_allow_html=True) + +st.markdown(""" + +""", unsafe_allow_html=True) +EXAMPLE_NO = 1 +is_listening = False +recognizer = sr.Recognizer() +with open(r"Response.json", 'r') as file: + RESPONSE_JSON = json.load(file) +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 example(): + rain( + emoji="*", + font_size=40, + falling_speed=7, + animation_length="infinite", + ) + +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 get_transcript(video_url): + video_id = video_url.split("=")[1] + transcript_api = YouTubeTranscriptApi() + 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","Mock Interview","Code Editor"], # required + icons=["geo-alt-fill","bi bi-camera-video-fill","bi bi-code-slash"], # 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 + +def main(): + link="https://lottie.host/299688b5-e6b2-48ad-b2e9-2fa14b1fb117/TXqg2APXpL.json" + l=load_lottieurl(link) + col1, col2 = st.columns([1,9]) + with col1: + st.lottie(l, height=100, width=100) + with col2: + st.header(f":rainbow[Mock Interview]💻💻", divider='rainbow') + if 'quiz_data' not in st.session_state: + st.session_state.quiz_data = None + if 'user_answers' not in st.session_state: + st.session_state.user_answers = {} + if 'quiz_submitted' not in st.session_state: + st.session_state.quiz_submitted = False + if 'score' not in st.session_state: + st.session_state.score = 0 + if 'show_error' not in st.session_state: + st.session_state.show_error = False + + def process_quiz_data(quiz_json): + """Convert the nested JSON structure to a more manageable format""" + processed_data = [] + quiz_dict = json.loads(quiz_json) if isinstance(quiz_json, str) else quiz_json + + for question_num, question_data in quiz_dict.items(): + processed_question = { + 'question_num': question_num, + 'mcq': question_data['mcq'], + 'options': question_data['options'], + 'correct': question_data['correct'] + } + processed_data.append(processed_question) + + return processed_data + + def calculate_score(): + correct_answers = 0 + total_questions = len(st.session_state.quiz_data) + for i, question in enumerate(st.session_state.quiz_data): + user_answer = st.session_state.user_answers.get(i) + if user_answer and user_answer != 'Select an option': + correct_answer = question['correct'] + if user_answer[0] == correct_answer: # Compare just the letter + correct_answers += 1 + return correct_answers, total_questions + + def check_answers_complete(): + """Check if all questions have been answered""" + total_questions = len(st.session_state.quiz_data) + answered_questions = sum(1 for ans in st.session_state.user_answers.values() + if ans != 'Select an option') + return answered_questions == total_questions + + # Fi le upload and quiz generation section + if not st.session_state.quiz_data: + with st.container(border=True): + col1, col2 = st.columns([1,1]) + with col1: + with st.form("user_inputs"): + + text = st.text_input("Which topic you want to learn",placeholder="Enter the topic") + video_link = st.text_input(" Enter the video link",placeholder="Enter the url") + uploaded_file = st.file_uploader("Upload a PDF or txt file") + mcq_count = 5 + subject = "resume" + tone = "Simple" + button = st.form_submit_button("Create MCQs") + + if video_link: + video_link=get_transcript(video_link) + if button and uploaded_file is not None and mcq_count and subject and tone: + with st.spinner("loading..."): + try: + + text2 = read_file(uploaded_file) + response = generate_evaluate_chain({ + "text": text2, + "number": mcq_count, + "subject": subject, + "tone": tone, + "response_json": json.dumps(RESPONSE_JSON) + }) + + except Exception as e: + traceback.print_exception(type(e), e, e.__traceback__) + st.error(e) + else: + if isinstance(response, dict): + quiz_json_start = response['quiz'].find('{') + quiz_json_end = response['quiz'].rfind('}') + 1 + quiz_json = response['quiz'][quiz_json_start:quiz_json_end] + if quiz_json: + try: + processed_quiz_data = process_quiz_data(quiz_json) + st.session_state.quiz_data = processed_quiz_data + st.session_state.review = response.get("review", "") + except Exception as e: + st.error(f"Error processing quiz data: {str(e)}") + else: + st.error("No valid quiz data found") + if button and text : + with st.spinner("loading..."): + try: + + response = generate_evaluate_chain({ + "text": text, + "number": mcq_count, + "subject": subject, + "tone": tone, + "response_json": json.dumps(RESPONSE_JSON) + }) + + except Exception as e: + traceback.print_exception(type(e), e, e.__traceback__) + st.error(e) + else: + if isinstance(response, dict): + quiz_json_start = response['quiz'].find('{') + quiz_json_end = response['quiz'].rfind('}') + 1 + quiz_json = response['quiz'][quiz_json_start:quiz_json_end] + if quiz_json: + try: + processed_quiz_data = process_quiz_data(quiz_json) + st.session_state.quiz_data = processed_quiz_data + st.session_state.review = response.get("review", "") + except Exception as e: + st.error(f"Error processing quiz data: {str(e)}") + else: + st.error("No valid quiz data found") + if button and video_link : + with st.spinner("loading..."): + try: + + response = generate_evaluate_chain({ + "text": video_link, + "number": mcq_count, + "subject": subject, + "tone": tone, + "response_json": json.dumps(RESPONSE_JSON) + }) + + except Exception as e: + traceback.print_exception(type(e), e, e.__traceback__) + st.error(e) + else: + if isinstance(response, dict): + quiz_json_start = response['quiz'].find('{') + quiz_json_end = response['quiz'].rfind('}') + 1 + quiz_json = response['quiz'][quiz_json_start:quiz_json_end] + if quiz_json: + try: + processed_quiz_data = process_quiz_data(quiz_json) + st.session_state.quiz_data = processed_quiz_data + st.session_state.review = response.get("review", "") + except Exception as e: + st.error(f"Error processing quiz data: {str(e)}") + else: + st.error("No valid quiz data found") + + with col2: + with st.container(border=True): + webrtc_streamer(key="sample") + ques=st.multiselect("Type of Question ? ", ["MCQ","Codding","Oral"], [], placeholder="Choose Language") + + if st.session_state.quiz_data is not None and not st.session_state.quiz_submitted: + st.subheader("Answer the following questions:") + + # Display error message if needed + if st.session_state.show_error: + st.error("Please answer all questions before submitting.") + st.session_state.show_error = False + + with st.form("quiz_form"): + for i, question in enumerate(st.session_state.quiz_data): + st.markdown(f"**Q{i+1}. {question['mcq']}**") + + # Create a list of options in the format "a) option_text" + options = [f"{opt_key}) {opt_value}" + for opt_key, opt_value in question['options'].items()] + + # Add an initial empty option to prevent default selection + options = options + + selected_option = st.radio( + f"select an option ", + options, + key=f"q_{i}", + index=0 # Set default to first option (Select an option) + ) + + st.session_state.user_answers[i] = selected_option + + submit_quiz = st.form_submit_button("Submit Quiz") + if submit_quiz: + if check_answers_complete(): + st.session_state.quiz_submitted = True + else: + st.session_state.show_error = True + st.experimental_rerun() + + + if st.session_state.quiz_submitted: + correct_answers, total_questions = calculate_score() + st.session_state.score = (correct_answers / total_questions) * 100 + + st.subheader("Quiz Results") + st.write(f"Your Score: {st.session_state.score:.2f}%") + st.write(f"Correct Answers: {correct_answers}/{total_questions}") + + st.subheader("Detailed Review") + for i, question in enumerate(st.session_state.quiz_data): + st.markdown(f"**Q{i+1}. {question['mcq']}**") + + # Display all options + for opt_key, opt_value in question['options'].items(): + if opt_key == question['correct']: + st.markdown(f"- {opt_key}) {opt_value} ✓ (Correct Answer)") + elif opt_key == st.session_state.user_answers[i][0]: # Compare with first character of answer + st.markdown(f"- {opt_key}) {opt_value} ❌ (Your Answer)") + else: + st.markdown(f"- {opt_key}) {opt_value}") + + st.markdown("---") + + def reset_quiz(): + st.session_state.quiz_data = None + st.session_state.user_answers = {} + st.session_state.quiz_submitted = False + st.session_state.score = 0 + st.session_state.show_error = False + if st.button("Start New Quiz"): + reset_quiz() + + + +selected = streamlit_menu(example=EXAMPLE_NO) +if 'questions' not in st.session_state: + st.session_state.questions = [] + +if selected == "Road Map": + example() + 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=="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 + + 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": + main() + + diff --git a/README.md b/README.md index e088c0a..42486fe 100644 --- a/README.md +++ b/README.md @@ -1 +1,3 @@ -# Compare \ No newline at end of file +# CollegeBuddy + +#dfasd \ No newline at end of file diff --git a/Recording 2024-08-03 001234.mp4 b/Recording 2024-08-03 001234.mp4 new file mode 100644 index 0000000..10ec964 Binary files /dev/null and b/Recording 2024-08-03 001234.mp4 differ diff --git a/Response.json b/Response.json new file mode 100644 index 0000000..6463ff5 --- /dev/null +++ b/Response.json @@ -0,0 +1,32 @@ +{ + "1": { + "mcq": "multiple choice question", + "options": { + "a": "choice here", + "b": "choice here", + "c": "choice here", + "d": "choice here" + }, + "correct": "correct answer" + }, + "2": { + "mcq": "multiple choice question", + "options": { + "a": "choice here", + "b": "choice here", + "c": "choice here", + "d": "choice here" + }, + "correct": "correct answer" + }, + "3": { + "mcq": "multiple choice question", + "options": { + "a": "choice here", + "b": "choice here", + "c": "choice here", + "d": "choice here" + }, + "correct": "correct answer" + } +} \ No newline at end of file diff --git a/data/AbhiCV.pdf b/data/AbhiCV.pdf new file mode 100644 index 0000000..14777d6 Binary files /dev/null and b/data/AbhiCV.pdf differ diff --git a/data/sree.pdf b/data/sree.pdf new file mode 100644 index 0000000..98a73cf Binary files /dev/null and b/data/sree.pdf differ diff --git a/instance/video-meeting.db b/instance/video-meeting.db new file mode 100644 index 0000000..0c2eddc Binary files /dev/null and b/instance/video-meeting.db differ diff --git a/logs/01_02_2025_09_09_05.log b/logs/01_02_2025_09_09_05.log new file mode 100644 index 0000000..e69de29 diff --git a/logs/01_02_2025_15_15_14.log b/logs/01_02_2025_15_15_14.log new file mode 100644 index 0000000..d8c61f6 --- /dev/null +++ b/logs/01_02_2025_15_15_14.log @@ -0,0 +1,204 @@ +[2025-01-02 15:14:02,030] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:14:02,056] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:14:02,116] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:14:02,253] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:14:02,253] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:14:02,317] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 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'Helvetica' not found. +[2025-01-02 15:53:13,958] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:53:13,959] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:53:15,175] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:53:15,176] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:53:15,224] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:53:15,225] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:53:15,324] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:53:15,324] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:53:15,325] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:55:31,284] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:55:31,286] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:55:31,305] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:55:31,350] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:55:31,350] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:55:31,387] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:55:31,644] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:55:31,645] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:55:31,645] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:55:31,691] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 15:55:31,691] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:00,234] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:00,240] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:00,285] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:00,285] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:00,372] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:00,373] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:00,374] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:01,892] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:01,893] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:01,936] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:01,937] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:02,034] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:02,034] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:02,036] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:58,203] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:58,217] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:58,322] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:58,323] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:58,507] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:58,507] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:23:58,508] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:24:03,320] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:24:03,321] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:24:03,399] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:24:03,400] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:24:03,584] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:24:03,586] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 16:24:03,586] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. diff --git a/logs/01_02_2025_18_18_11.log b/logs/01_02_2025_18_18_11.log new file mode 100644 index 0000000..c68ee26 --- /dev/null +++ b/logs/01_02_2025_18_18_11.log @@ -0,0 +1,135 @@ +[2025-01-02 19:14:44,123] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:14:44,155] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:14:44,310] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:14:44,310] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:14:44,527] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:14:44,527] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:14:44,532] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:14:47,317] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:14:47,326] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:14:47,421] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:14:47,422] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:14:47,612] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:14:47,612] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:14:47,613] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:52:12,622] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:52:12,634] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:52:12,667] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:52:12,753] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:52:12,753] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:52:12,799] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:52:13,098] 1371 matplotlib.font_manager - WARNING - 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matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:16,284] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:16,364] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:16,366] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:16,366] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:16,387] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:16,387] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:28,564] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:28,564] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:28,580] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:28,624] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:28,624] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:28,654] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:28,803] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:28,804] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:28,804] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:28,863] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:28,864] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:42,321] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:42,322] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:42,338] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:42,460] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:42,460] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:42,509] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:42,594] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:42,594] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:42,597] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:42,669] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:56:42,669] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:57:36,949] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:57:36,950] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:57:36,962] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:57:36,988] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:57:36,988] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:57:37,002] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:57:37,085] 1371 matplotlib.font_manager - WARNING - 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matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:57:51,088] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:57:51,167] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:57:51,168] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:57:51,168] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:57:51,193] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:57:51,193] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:01,474] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:01,476] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:01,488] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:01,525] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:01,525] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:01,542] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:01,633] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:01,634] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:01,634] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:01,659] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:01,659] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:13,134] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:13,135] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:13,145] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:13,170] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:13,170] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:13,182] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:13,250] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:13,251] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:13,251] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:13,274] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:13,274] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:21,884] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:21,888] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:21,902] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:21,933] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:21,933] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:21,946] 1371 matplotlib.font_manager - WARNING - findfont: Font family 'Helvetica' not found. +[2025-01-02 19:58:22,049] 1371 matplotlib.font_manager - WARNING - 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OpenStreetMap contributors, ODbL 1.0. http://osm.org/copyright", "osm_type": "way", "osm_id": 244524327, "lat": "22.188424400000002", "lon": "113.5435057449533", "class": "leisure", "type": "park", "place_rank": 24, "importance": 0.303230229325644, "addresstype": "park", "name": "\u4e9e\u99ac\u5587\u524d\u5730 Pra\u00e7a de Ferreira do Amaral", "display_name": "\u4e9e\u99ac\u5587\u524d\u5730 Pra\u00e7a de Ferreira do Amaral, \u65b0\u53e3\u5cb8\u586b\u6d77\u5340 Zona de Aterros do Porto Exterior, Grand Beach, S\u00e9, Municipality of Macau, Macau, China", "boundingbox": ["22.1878619", "22.1889405", "113.5429242", "113.5440887"]}] \ No newline at end of file diff --git a/pages/styles/main.css b/pages/styles/main.css new file mode 100644 index 0000000..8bbe45d --- /dev/null +++ b/pages/styles/main.css @@ -0,0 +1,27 @@ +@import url('https://fonts.googleapis.com/css2?family=Readex+Pro:wght@300;400;500;600;700&display=swap'); + + +* {font-family: 'Readex Pro';} + + +a { + text-decoration: none; + color: white !important; + font-weight: 500; +} + +a:hover { + color: #55d336 !important; + text-decoration: none; +} +body { + background-image: linear-gradient(to right, #f06b6b, #ffdb58); + background-size: 100% 100%; + background-attachment: fixed; + } +ul {list-style-type: none;} + +hr { + margin-top: 0px; + margin-bottom: 5%; +} diff --git "a/pages/\360\237\227\203\357\270\217JobHackHub.py" "b/pages/\360\237\227\203\357\270\217JobHackHub.py" new file mode 100644 index 0000000..46c6eec --- /dev/null +++ "b/pages/\360\237\227\203\357\270\217JobHackHub.py" @@ -0,0 +1,245 @@ +from pathlib import Path +from streamlit_ace import st_ace +from PIL import Image +import streamlit as st +from streamlit_option_menu import option_menu +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 +import pandas as pd +import numpy as np +import matplotlib.pyplot as plt +import seaborn as sns +import plotly.express as px +import speech_recognition as sr +from streamlit_extras.echo_expander import echo_expander +from bs4 import BeautifulSoup +global s +k=0 +st.set_page_config(page_title="KnowledgeBuilder", page_icon='src/Logo College.png', layout="wide", initial_sidebar_state="auto", menu_items=None) +EXAMPLE_NO = 1 +recognizer = sr.Recognizer() +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: + st.write("Listening...") + audio = recognizer.listen(source) + try: + text = recognizer.recognize_google(audio) + st.success(f"You said: {text}") + 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 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="Job Portal 💼", # required + options=["Hackthons", "Jobs", "Exams","Lectures"], # required + icons=["bi bi-bag", "bi bi-bag-check-fill", "bi bi-book",], # optional + menu_icon="cast", # optional + default_index=0, + ) + return selected + if example == 2: + 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, + ) + return selected + if example == 3: + 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 + 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 +def hactkon(): + url = 'https://hack2skill.com/dashboard/' + hackathons = [] + response = requests.get(url) + if response.status_code == 200: + soup = BeautifulSoup(response.content, 'html.parser') + + # Find cards containing hackathon details + card_elements = soup.find_all('div', class_='card') # Assuming card structure + + for card in card_elements: + # Extract data from within each card + name_element = card.find('div', class_='card-body') # Customize selector if needed + name = name_element.get_text(strip=True) if name_element else None + + description_element = card.find('p') # Adjust selector if necessary + description = description_element.get_text(strip=True) if description_element else None + + mode_element = card.find('span', class_='text-success') # Adapt for your mode class + mode = mode_element.get_text(strip=True) if mode_element else None + + image_element = card.find('img', class_='card-img-top') # Modify based on image element + image_url = image_element.get('src') if image_element else None + + # Create and append hackathon dictionary + hackathons.append({ + 'name': name, + 'description': description, + 'mode': mode, + 'image_url': image_url + }) + else: + print(f"Failed to retrieve the webpage. Status code: {response.status_code}") + + return hackathons +selected = streamlit_menu(example=EXAMPLE_NO) +if 'questions' not in st.session_state: + st.session_state.questions = [] +if selected == "Hackthons": + hackathons=hactkon() + st.title("Hackathons Listings") + + # Create columns for each hackathon + for hackathon in hackathons[:]: + col1, col2, col3 = st.columns([1, 2, 1]) + + # Column 1: Image + with col1: + st.image(hackathon["image_url"], use_container_width=True) + + # Column 2: Details + with col2: + s=hackathon["name"] + k=hackathon['description'][:5] + st.header(s[:s.find(k)]) + + with st.expander("Read more"): + st.write(f"**Description :** {hackathon['description']}") + st.write(hackathon["mode"]) + + + # Column 3: Apply button + with col3: + if st.button("Apply Now", key=hackathon["name"]): + pass + + st.markdown("---") + + # Main content of the Streamlit app + st.write("Explore and apply to the latest hackathons listed above.") +if selected == "Jobs": + + # Sample data + hackathons = [ + { + "name": "Hackathon 1", + "image_url": "https://via.placeholder.com/150", + "timeline": "Jan 1, 2024 - Jan 3, 2024", + "prizes": "1st: $1000, 2nd: $500", + "details": "This is a brief description of Hackathon 1." + }, + { + "name": "Hackathon 2", + "image_url": "https://via.placeholder.com/150", + "timeline": "Feb 10, 2024 - Feb 12, 2024", + "prizes": "1st: $2000, 2nd: $1000", + "details": "This is a brief description of Hackathon 2." + }, + { + "name": "Hackathon 3", + "image_url": "https://via.placeholder.com/150", + "timeline": "Mar 15, 2024 - Mar 17, 2024", + "prizes": "1st: $3000, 2nd: $1500", + "details": "This is a brief description of Hackathon 3." + } + ] + + # Title of the app + st.title("Hackathon Listings") + + # Create columns for each hackathon + for hackathon in hackathons: + col1, col2, col3 = st.columns([1, 2, 1]) + + # Column 1: Image + with col1: + st.image(hackathon["image_url"], use_column_width=True) + + # Column 2: Details + with col2: + st.header(hackathon["name"]) + st.write(f"**Timeline:** {hackathon['timeline']}") + st.write(f"**Prizes:** {hackathon['prizes']}") + st.write(hackathon["details"]) + + # Column 3: Apply button + with col3: + st.button("Apply Now", key=hackathon["name"]) + + st.markdown("---") + + # Main content of the Streamlit app + st.write("Explore and apply to the latest hackathons listed above.") +if selected == "Exams": + + st.title("💬 Chatbot") + + 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 == "Lectures": + + pass \ No newline at end of file diff --git "a/pages/\360\237\247\221\342\200\215\360\237\217\253ProfileBuilder.py" "b/pages/\360\237\247\221\342\200\215\360\237\217\253ProfileBuilder.py" new file mode 100644 index 0000000..3372cb6 --- /dev/null +++ "b/pages/\360\237\247\221\342\200\215\360\237\217\253ProfileBuilder.py" @@ -0,0 +1,1341 @@ +import subprocess +import plotly.express as px +from datetime import date +from pathlib import Path +import shutil +import speech_recognition as sr +import pdf2image +import gtts +import sqlite3 +import re +import pandas as pd +import streamlit.components.v1 as components +from local_components import card_container +import json +import traceback +import calplot +from dotenv import load_dotenv +import PIL +import PyPDF2 +import re +from streamlit_ace import st_ace +from PIL import Image +import streamlit_shadcn_ui as ui +import base64 +from bs4 import BeautifulSoup +from datetime import datetime +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 google.generativeai as genai +import matplotlib.pyplot as plt +from IPython.display import display +from local_components import card_container +from IPython.display import Markdown +from streamlit_lottie import st_lottie +import requests +import sys +import io +import time +import plotly.graph_objects as go +from util.common import get_gemini_response,get_leetcode_data,get_gemini_response1,load_lottieurl +from util.leetcode import get_leetcode_data1, RQuestion, skills, let_Badges, graph,get_active_days_for_users,get_active_days,get_ratings_for_users,get_leetcode_contest_rating +from util.codeforces import get_user_data, get_contest_data +from util.github import run_gitleaks, count_lines_of_code, clone_and_count_lines, is_repo_processed, get_all_user_repos, update_progress_file +from util.login import add_user, authenticate_user, is_valid_password,listofuser,list_profiles,listofcollege,totalusers +import firebase_admin +from firebase_admin import credentials +from firebase_admin import db +import time + +if not firebase_admin._apps: + + service_account_info = { + "type": "service_account", + "project_id": os.environ.get("FIREBASE_PROJECT_ID"), + "private_key_id": os.environ.get("FIREBASE_PRIVATE_KEY_ID"), + "private_key": "-----BEGIN PRIVATE KEY-----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\nudZmstCQ8c7EcKQpAYK1lA==\n-----END PRIVATE KEY-----\n", # Important: handle newlines + "client_email": os.environ.get("FIREBASE_CLIENT_EMAIL"), + "client_id": os.environ.get("FIREBASE_CLIENT_ID"), + "auth_uri": "https://accounts.google.com/o/oauth2/auth", + "token_uri": "https://oauth2.googleapis.com/token", + "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs", + "client_x509_cert_url": os.environ.get("FIREBASE_CLIENT_X509_CERT_URL"), + "universe_domain": "googleapis.com" + } + cred = credentials.Certificate(service_account_info) + firebase_admin.initialize_app(cred, { + 'databaseURL': "https://profile-data-dde0a-default-rtdb.firebaseio.com/" + }) + +global s +k=0 +api_key=os.getenv("API-KEY") +genai.configure(api_key=os.getenv("API-KEY")) +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"] + +EXAMPLE_NO = 1 + + +st.set_page_config(page_title="KnowledgeBuilder", page_icon='src/Logo College.png', layout="wide", initial_sidebar_state="auto", menu_items=None) +if "current_theme" not in st.session_state: + st.session_state.current_theme = "light" + +def process_data(data): + rows = [] + for category, topics in data.items(): + for topic in topics: + rows.append( + {"Category": category.capitalize(), "Topic": topic["tagName"], "Problems Solved": topic["problemsSolved"]} + ) + return pd.DataFrame(rows) +def streamlit_menu(example=1): + if example == 1: + with st.sidebar: + selected = option_menu( + menu_title="Profile - Builder ", # required + options=["Register","Dashboard", "1vs1","LinkedIn Profile","collage","ATS Detector"], # required + icons=["bi bi-person-lines-fill","bi bi-border-all", "bi bi-binoculars-fill", "bi bi-linkedin","bi bi-envelope-at","bi bi-file-person"], # optional + menu_icon="cast", # optional + + default_index=0, + ) + return selected + +selected = streamlit_menu(example=EXAMPLE_NO) + +if 'questions' not in st.session_state: + st.session_state.questions = [] + + +if selected == "Register": + global username + with st.container(border=True): + st.title("Login / Signup") + option = st.selectbox("Login/Signup/Update", ["Sign up", "Login","Update"]) + + if option == "Sign up": + # Input fields + username = st.text_input("Username", placeholder="Enter your username (must be unique)") + password = st.text_input("Password", placeholder="Enter your password", type="password") + with st.container(): + col1, col2 = st.columns(2) + + with col1: + st.subheader("Profile Information") + codechef_id = st.text_input("CodeChef ID", placeholder="Enter your CodeChef username") + leetcode_id = st.text_input("LeetCode ID", placeholder="Enter your LeetCode username") + github_id = st.text_input("GitHub ID", placeholder="Enter your GitHub username") + codeforces_id = st.text_input("Codeforces ID", placeholder="Enter your Codeforces username") + + with col2: + st.subheader("Additional Information") + predefined_colleges = ["LPU","MIT", "Stanford", "Harvard", "IIT", "Other"] + selected_college = st.selectbox("College/School", predefined_colleges) + if selected_college == "Other": + college = st.text_input("Enter your College/School name") + else: + college = selected_college + + category = st.selectbox("Category", ["Student", "Professional", "Other"]) + + # Submit button + if st.button("Create my account"): + if username and password and college: + # Validate password + password_error = is_valid_password(password) + if password_error: + st.error(password_error) + else: + try: + add_user(username, password, codechef_id, leetcode_id, github_id, codeforces_id, college, category,db) + st.success("Account created successfully!") + except sqlite3.IntegrityError: + st.error("This username is already registered. Please use a different username.") + else: + st.error("Username, Password, and College are required!") + + elif option == "Login": + # Input fields for login + st.subheader("Login") + username = st.text_input("Username", placeholder="Enter your username for login") + password = st.text_input("Password", placeholder="Enter your password", type="password") + + # Login button + if st.button("Login"): + if username and password: + user = authenticate_user(username, password) + if user: + st.success(f"Welcome back, {username}!") + st.write("Your Profile Information:") + st.write(f"- **CodeChef ID:** {user[3]}") + st.write(f"- **LeetCode ID:** {user[4]}") + st.write(f"- **GitHub ID:** {user[5]}") + st.write(f"- **Codeforces ID:** {user[6]}") + st.write(f"- **College/School:** {user[7]}") + st.write(f"- **Category:** {user[8]}") + else: + st.error("Invalid username or password.") + else: + st.error("Both fields are required!") + +if selected == "Dashboard": + + link="https://lottie.host/02515adf-e5f1-41c8-ab4f-8d07af1dcfb8/30KYw8Ui2q.json" + Username = "Sreecharan9484" + cUsername="Sreecharan9484" + st.session_state["Username"] = Username + st.session_state["cUsername"]= cUsername + l=load_lottieurl(link) + + col1, col2 = st.columns([1.3,9]) + + + if st.session_state["Username"] and st.session_state["cUsername"]: + response = requests.get(f'https://www.codechef.com/users/{st.session_state["cUsername"]}') + if response.status_code != 200: + print(f"Failed to retrieve the page. Status code: {response.status_code}") + else: + soup = BeautifulSoup(response.text, 'html.parser') + user_info = {} + user_name_tag = soup.find('div', class_='user-details-container').find('h1') + user_name = user_name_tag.get_text(strip=True) if user_name_tag else "N/A" + user_info['Name'] = user_name + country_tag = soup.find('span', class_='user-country-name') + country = country_tag.get_text(strip=True) if country_tag else "N/A" + user_info['Country'] = country + rating_graph_section = soup.find('section', class_='rating-graphs rating-data-section') + rating_widget = soup.find('div', class_='widget-rating') + rating_number = rating_widget.find('div', class_='rating-number') + ratingc = rating_number.text.strip() if rating_number else None + #print(ratingc) + if rating_graph_section: + contest_participated_div = rating_graph_section.find('div', class_='contest-participated-count') + if contest_participated_div: + no_of_contests = contest_participated_div.find('b').get_text(strip=True) + #print(f"No. of Contests Participated: {no_of_contests}") + #print(user_info) + else: + print("No. of Contests Participated information not found.") + data = get_leetcode_data(st.session_state["Username"]) + user_profile = data['userProfile'] + contest_info = data['userContestRanking'] + ko=[] + for stat in user_profile['submitStats']['acSubmissionNum']: + ko=ko+[stat['count']] + with col1: + st.lottie(l, height=100, width=100) + with col2: + st.header(f":rainbow[Student Dashboard]👧👦", divider='rainbow') + with st.container(border=True): + + cols = st.columns([1,3,2.5,2.5]) + with cols[0]: + image = st.image(user_profile['profile']['userAvatar']) + + # Apply CSS to make the image circular + st.markdown( + """ + + """, + unsafe_allow_html=True, + ) + + # Create a link around the image + image_html = f'' + st.markdown(image_html, unsafe_allow_html=True) + with cols[1]: + z=user_info['Name'] + ui.metric_card(title="Name", content=z, description="", key="card1") + with cols[2]: + if contest_info['topPercentage']: + ui.metric_card(title="Top Percentage", content=contest_info['topPercentage'], description="", key="card2") + else: + ui.metric_card(title="Top Percentage", content=0, description="", key="card2") + with cols[3]: + ui.metric_card(title="Rating", content=user_profile['profile']['ranking'], description="", key="card3") + + + cols3=st.columns([1.5,1]) + with st.container(border=True): + with cols3[0]: + + # Data + total_questions = ko[0] + easy_questions = ko[1] + medium_questions = ko[2] + hard_questions = ko[3] + + # Calculate percentages + easy_percent = (easy_questions / total_questions) * 100 + medium_percent = (medium_questions / total_questions) * 100 + hard_percent = (hard_questions / total_questions) * 100 + + # Create columns for layout + col1, col3 = st.columns([3, 1]) + + # Display total questions + + with col1: + ui.metric_card(title="Total Question ", content=ko[0], key="card9") + + # Display pie chart + + fig, ax = plt.subplots() + ax.pie([easy_percent, medium_percent, hard_percent], + labels=["Easy", "Medium", "Hard"], + autopct="%1.1f%%", + startangle=140) + ax.axis("equal") # Equal aspect ratio for a circular pie chart + st.pyplot(fig) + + # Display difficulty counts + with col3: + ui.metric_card(title="Easy ", content=ko[1], key="card12") + ui.metric_card(title="Medium", content=ko[2], key="card10") + ui.metric_card(title="Hard ", content=ko[3], key="card11") + + with st.container(border=True): + with cols3[1]: + data1 = { + "No of contest": [contest_info['attendedContestsCount'], no_of_contests, 1], + "category": ["LeetCode", "CodeChef", "Codeforces"] + } + + # Vega-Lite specification for the bar graph + vega_spec = { + "mark": { + "type": "bar", + "cornerRadiusEnd": 4 + }, + "encoding": { + "x": { + "field": "category", + "type": "nominal", + "axis": { + "labelAngle": 0, + "title": None, # Hides the x-axis title + "grid": False # Removes the x-axis grid + } + }, + "y": { + "field": "No of contest", + "type": "quantitative", + "axis": { + "title": None # Hides the y-axis title + } + }, + "color": {"value": "#000000"}, + }, + "data": { + "values": [ + {"category": "LeetCode", "No of contest": contest_info['attendedContestsCount']}, + {"category": "Code Shef", "No of contest": no_of_contests}, + {"category": "Codeforces", "No of contest": 1} + ] + } + } + # Display the bar graph in Streamlit + with card_container(key="chart"): + st.vega_lite_chart(vega_spec, use_container_width=True) + + with st.container(border=True): + col1a, col2b= st.columns([1,1]) + with st.container(border=True): + with col1a: + with st.container(border=True): + st.write("This is resent Question You Did") + for language_data in data['matchedUser']['languageProblemCount']: + st.write(f"{language_data['languageName']}: {language_data['problemsSolved']}") + + with st.container(border=True): + with col2b: + with st.container(border=True): + header = [ "Question Name", "Timestamp"] + def format_timestamp(timestamp): + dt_object = datetime.datetime.fromtimestamp(int(timestamp)) + return dt_object.strftime("%Y-%m-%d %I:%M %p") # AM/PM format + processed_data = [] + for submission in data['recentAcSubmissionList']: + formatted_date = format_timestamp(submission['timestamp']) + processed_data.append([ submission['title'], formatted_date]) + df = pd.DataFrame(processed_data, columns=["Question Name", "Timestamp"]) + st.write(df) + + # Display table in Streamlit + + + + a, b,c = st.columns([1,4,1]) + rating = ratingc + total_contests = no_of_contests + rank = 1007 + divisio = "Starters 142" + date = date.today() + # Left column + data = { + "1704067200": 1, "1704153600": 1, "1704240000": 1, "1704326400": 1, "1704412800": 1, + "1704585600": 15, "1705190400": 1, "1705536000": 1, "1705708800": 3, "1705881600": 2, + "1705968000": 2, "1706313600": 2, "1706659200": 2, "1707264000": 1, "1707350400": 1, + "1711497600": 2, "1711929600": 6, "1712016000": 3, "1712361600": 2, "1712707200": 6, + "1712793600": 2, "1712880000": 1, "1713139200": 3, "1713225600": 3, "1713312000": 2, + "1713398400": 1, "1713571200": 1, "1716940800": 3, "1717027200": 2, "1717113600": 3, + "1717200000": 1, "1717286400": 11, "1717459200": 3, "1717718400": 4, "1718841600": 9, + "1718928000": 3, "1719100800": 1, "1719187200": 2, "1719273600": 5, "1719360000": 1, + "1719446400": 2, "1719705600": 1, "1719792000": 7, "1719878400": 6, "1719964800": 4, + "1720051200": 4, "1720137600": 1, "1720224000": 7, "1720310400": 3, "1720483200": 5, + "1720569600": 5, "1722211200": 1, "1722297600": 1, "1722384000": 1, "1690934400": 2, + "1691107200": 2, "1691193600": 3, "1694390400": 1, "1694822400": 1, "1694908800": 1, + "1696723200": 7, "1696982400": 2, "1697328000": 5, "1697414400": 1, "1702512000": 4, + "1703289600": 7, "1703721600": 3, "1703808000": 3, "1703894400": 1, "1703980800": 3 + } + + # Convert the data to a DataFrame + df = pd.DataFrame(list(data.items()), columns=['Timestamp', 'Count']) + df['Date'] = pd.to_datetime(df['Timestamp'].astype(int), unit='s') + df.set_index('Date', inplace=True) + daily_counts = df['Count'].resample('D').sum().fillna(0) + + # Create the calendar plot with a brighter colormap + cmap = 'plasma' # or 'viridis', 'inferno', etc. + fig, ax = calplot.calplot(daily_counts, cmap=cmap, figsize=(12, 6),colorbar=False) + + + # Display the plot in Streamlit + st.pyplot(fig) + with a: + st.metric(label="Rating", value=rating) + st.metric(label="Total Contests", value=total_contests) + st.metric(label="Rank", value=rank) + with b: + data = { + 'Week': ['Week 1', 'Week 2', 'Week 3', 'Week 4', 'Week 5'], + 'Rating': [3.5, 4.0, 4.5, 4.2, 4.8] + } + df = pd.DataFrame(data) + fig = go.Figure() + fig.add_trace(go.Scatter( + x=df['Week'], + y=df['Rating'], + mode='lines+markers', + name='Rating', + line=dict(color='royalblue', width=2), + marker=dict(color='royalblue', size=8) + )) + fig.update_layout( + title='Weekly Ratings', + xaxis_title='Week', + yaxis_title='Rating', + plot_bgcolor='white', + font=dict(size=14), + xaxis=dict( + showline=True, + showgrid=False, + showticklabels=True, + linecolor='black', + linewidth=2, + ticks='outside', + tickfont=dict( + family='Arial', + size=12, + color='black', + ), + ), + yaxis=dict( + showline=True, + showgrid=True, + showticklabels=True, + linecolor='black', + linewidth=2, + ticks='outside', + tickfont=dict( + family='Arial', + size=12, + color='black', + ), + ) + ) + st.plotly_chart(fig) + with c: + st.subheader("Division") + st.write(f"{divisio}") + st.subheader("Date") + st.write(date) + + # Chart (using your preferred charting library) + # ... + + st.markdown(""" +
+

No of question in each topic

+
+ """, unsafe_allow_html=True) + data = { + "Arrays": 106, + "String": 35, + "HashMap and Set": 30, + "Dynamic Programming": 28, + "Sorting": 26, + "Math": 22, + "Two Pointers": 21, + "Matrix": 16, + "Binary Search": 16, + "Trees": 14 + } + st.table(pd.DataFrame(data, index=["Count"])) + # Convert data to a Pandas DataFrame + df = pd.DataFrame.from_dict(data, orient='index', columns=['Count']) + + # Create the bar graph with custom colors + fig, ax = plt.subplots() + df.plot(kind='bar', color=['red','blue'], ax=ax) # Set color to 'skyblue' + ax.set_title('Topic Counts', color='darkblue') + ax.set_xlabel('Topic', color='gray') + ax.set_ylabel('Count', color='gray') + ax.tick_params(axis='x', rotation=45) # Rotate x-axis labels for better readability + + linkedin_embed_code = """ + + """ + linkedin_embed_code2 = """ + + """ + # Embed the LinkedIn post in the Streamlit app + with st.container(border=True): + col1, col2 = st.columns([1,1]) + with st.container(border=True): + with col1: + components.html(linkedin_embed_code, height=1200) # Adjust height as needed + with st.container(border=True): + with col2: + components.html(linkedin_embed_code2, height=1200) # Adjust height as needed + st.pyplot(fig) + + + else: + st.write("## Write Your UserName") + +if selected == "ATS Detector": + + 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") + lott=load_lottieurl("https://lottie.host/6a18ec99-538f-48b7-b9f1-85549bfbc5e1/n6lDQ3tHy2.json") + col1, col2,clo3= st.columns([2,5,1]) + with col2: + st.header(f"Applicant Tracking System ", divider='rainbow') + with col1: + if lott: + st_lottie(lott, key="ad", height="150px",width="150px") + else: + st.error("Failed to load Lottie animation.") + with clo3 : + pass + with st.container(border=True): + input_text=st.text_area("Job Description : ",key="input") + uploaded_file=st.file_uploader("Upload your resume (PDF)",type=["pdf"]) + if uploaded_file is not None: + st.write("PDF Uploaded Successfully") + col1, col2 ,col3,clo4= st.columns([2,2.5,2,2]) # Create two columns + with col1: + pass + with col2: + + submit1 = st.button("Tell Me About the Resume",type="primary", help="Know your resume",use_container_width=True) + with col3: + submit3 = st.button("Percentage match",type="primary", help="Percentage match",use_container_width=True) + with clo4: + pass + + #submit2 = st.button("How Can I Improvise my Skills") + + + + input_prompt1 = """ + You are an experienced Technical Human Resource Manager,your task is to review the provided resume against the job description. + Please share your professional evaluation on whether the candidate's profile aligns with the role. + Highlight the strengths and weaknesses of the applicant in relation to the specified job requirements. + """ + + input_prompt3 = """ + You are an skilled ATS (Applicant Tracking System) scanner with a deep understanding of data science and ATS functionality, + your task is to evaluate the resume against the provided job description. give me the percentage of match if the resume matches + the job description. First the output should come as percentage and then keywords missing and last final thoughts. + """ + + if submit1: + if uploaded_file is not None: + pdf_content=input_pdf_setup(uploaded_file) + response=get_gemini_response1(input_prompt1,pdf_content,input_text) + st.subheader("The Repsonse is") + st.write(response) + else: + st.write("Please uplaod the resume") + + elif submit3: + if uploaded_file is not None: + pdf_content=input_pdf_setup(uploaded_file) + response=get_gemini_response1(input_prompt3,pdf_content,input_text) + st.subheader("The Repsonse is") + st.write(response) + else: + st.write("Please uplaod the resume") + +if selected == "LinkedIn Profile": + + def extract_text_from_pdf(file): + pdf_reader = PyPDF2.PdfReader(file) + text = "" + for page in pdf_reader.pages: + text += page.extract_text() + "\n" + return text + + link="https://lottie.host/a2aa0932-646a-40a0-9638-4634d3a77c89/MU89CSP8h1.json" + l=load_lottieurl(link) + col1, col2 = st.columns([1.3,9]) # Create two columns + with col1: + st.lottie(l, height=100, width=100) + with col2: + st.header(f":rainbow[Linkdin Profile Builder]👧👦", divider='rainbow') + with st.container(border=True): + col1, col2 = st.columns(2) + with col1: + # PDF upload + uploaded_image = st.file_uploader("Upload an image file", type=["png", "jpg", "jpeg"]) + if uploaded_image is not None: + with st.container(border=True): + st.image(uploaded_image, caption="Uploaded Image", use_container_width=True) + uploaded_file = st.file_uploader("Upload a PDF file", type=["pdf"]) + if uploaded_file is not None: + text2 = extract_text_from_pdf(uploaded_file) + # Job role selection + job_roles = [ + "Software Engineer", + "Data Scientist", + "Product Manager", + "Designer", + "Front-end Developer", + "Back-end Developer", + "Full-stack Developer", + "Mobile App Developer", + "DevOps Engineer", + "Quality Assurance Engineer", + "Data Analyst", + "Business Intelligence Analyst", + "Machine Learning Engineer", + "Data Engineer", + "Product Owner", + "Product Marketing Manager", + "Project Manager", + "Scrum Master", + "UX Researcher", + "IT Project Manager", + "Machnical Engineer", + ] + # selected_role = st.selectbox("Select your job role", job_roles) + selected_role = st.text_input("Which topic you want to learn",placeholder="Enter the topic") + # Display selected job role + with col2: + # Video upload + st.video(r"Recording 2024-08-03 001234.mp4") + + with st.container(border=True): + st.markdown(":grey[Click the button to analyze the image]") + know = st.button("ANALYZE", + type="primary", help="Analyze the LinkedIn proflie",use_container_width=True) + if know: + + st.caption("Powerd by Gemini Pro Vision") + img_=uploaded_image + img = PIL.Image.open(img_) + def get_analysis(prompt, image): + import google.generativeai as genai + genai.configure(api_key=api_key) + + # Set up the model + generation_config = { + "temperature": 0.9, + "top_p": 0.95, + "top_k": 40, + "max_output_tokens": 5000, + } + + safety_settings = [ + { + "category": "HARM_CATEGORY_HARASSMENT", + "threshold": "BLOCK_MEDIUM_AND_ABOVE" + }, + { + "category": "HARM_CATEGORY_HATE_SPEECH", + "threshold": "BLOCK_MEDIUM_AND_ABOVE" + }, + { + "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", + "threshold": "BLOCK_MEDIUM_AND_ABOVE" + }, + { + "category": "HARM_CATEGORY_DANGEROUS_CONTENT", + "threshold": "BLOCK_MEDIUM_AND_ABOVE" + } + ] + + model = genai.GenerativeModel(model_name="gemini-1.5-flash", + generation_config=generation_config, + safety_settings=safety_settings) + + response = model.generate_content([prompt, image]) + + return response.text + role = """ + You are a highly skilled AI trained to review LinikedIn profile photos and provide feedback on their quality. You are a professional and your feedback should be constructive and helpful. + """ + instructions = """ + You are provided with an image file depicting a LinkedIn profile photo. + + Your job is to proved a structured report analyzing the image based on the following criteria: + + 1. Resolution and Clarity: + + Describe the resolution and clarity of the image. Tell the user whether the image is blurry or pixelated, making it difficult to discern the features. If the image is not clear, suggest the user to upload a higher-resolution photo. + (provide a confidence score for this assessment.) + + 2. Professional Appearance: + + Analyse the image and describe the attire of the person in the image. Tell what he/she is wearing. If the attire is appropriate for a professional setting, tell the user that their attire is appropriate for a professional setting. If the attire is not appropriate for a professional setting, tell the user that their attire might not be suitable for a professional setting. If the attire is not appropriate for a professional setting, suggest the user to wear more formal clothing for their profile picture. Also include background in this assessment. Describe the background of the person. If the background is simple and uncluttered, tell the user about it, that it is allowing the focus to remain on them. If the background is not good, tell the user about it. If the background is not suitable, suggest the user to use a plain background or crop the image to remove distractions. + (provide a confidence score for this assessment.) + + 3. Face Visibility: + + Analyse the image and describe the visibility of the person's face. If the face is clearly visible and unobstructed, tell the user that their face is clearly visible and unobstructed. If the face is partially covered by any objects or hair, making it difficult to see the face clearly, tell the user about it. Also tell where the person is looking. If the person is looking away, suggest the user to look into the camera for a more direct connection. + (provide a confidence score for this assessment.) + + 4. Appropriate Expression: + + Describe the expression of the person in the image. If the expression is friendly and approachable, tell the user about it. If the expression is overly serious, stern, or unprofessional, tell the user user about it. If the expression is not appropriate, suggest the user to consider a more relaxed and natural smile for a more approachable look. + (provide a confidence score for this assessment.) + + 5. Filters and Distortions: + + Describe the filters and distortions applied to the image. If the image appears natural and unaltered, tell the user about it. If the image appears to be excessively filtered, edited, or retouched, tell the user about it. If the image is excessively filtered, edited, or retouched, suggest the user to opt for a natural-looking photo for a more genuine impression. + (provide a confidence score for this assessment.) + + 6. Single Person and No Pets: + + Describe the number of people and pets in the image. If the image contains only the user, tell the user about it. If the image contains multiple people or pets, tell the user about it. If the image contains multiple people or pets, suggest the user to crop the image to remove distractions. + (provide a confidence score for this assessment.) + + Final review: + + At the end give a final review on whether the image is suitable for a LinkedIn profile photo. Also the reason for your review. + """ + output_format = """ + Your report should be structured like shown in triple backticks below: + + ``` + **1. Resolution and Clarity:**\n[description] (confidence: [confidence score]%) + + **2. Professional Appearance:**\n[description] (confidence: [confidence score]%) + + **3. Face Visibility:**\n[description] (confidence: [confidence score]%) + + **4. Appropriate Expression:**\n[description] (confidence: [confidence score]%) + + **5. Filters and Distortions:**\n[description] (confidence: [confidence score]%) + + **6. Single Person and No Pets:**\n[description] (confidence: [confidence score]%) + + **Final review:**\n[your review] + ``` + + You should also provide a confidence score for each assessment, ranging from 0 to 100. + + Don't copy the above text. Write your own report. + + And always keep your output in this format. + + For example: + + **1. Resolution and Clarity:**\n[Your description and analysis.] (confidence: [score here]%) + + **2. Professional Appearance:**\n[Your description and analysis.] (confidence: [socre here]%) + + **3. Face Visibility:**\n[Your description and analysis.] (confidence: [score her]%) + + **4. Appropriate Expression:**\n[Your description and analysis.] (confidence: [score here]%) + + **5. Filters and Distortions:**\n[Your description and analysis.] (confidence: [score here]%) + + **6. Single Person and No Pets:**\n[Your description and analysis.] (confidence: [score here]%) + + **Final review:**\n[Your review] + + """ + prompt = role + instructions + output_format + image_parts = [ + { + "mime_type": "image/jpeg", + "data": img + } + ] + + with st.container(border=True): + st.markdown(":grey[Click the button to analyze the image]") + + + # show spinner while generating + with st.spinner("Analyzing..."): + + try: + # get the analysis + analysis = get_analysis(prompt, img) + except Exception as e: + st.error(f"An error occurred: {e}") + + else: + + # find all the headings that are enclosed in ** ** + headings = re.findall(r"\*\*(.*?)\*\*", analysis) + + # find all the features that are after ** and before (confidence + features = re.findall(r"\*\*.*?\*\*\n(.*?)\s\(", analysis) + + # find all the confidence scores that are after (confidence: and before %) + confidence_scores = re.findall(r"\(confidence: (.*?)\%\)", analysis) + + # find the final review which is after the last confidence score like this: + # (confidence: 50%)\n\n(.*?) + + st.subheader(":blue[LinkedIn] Profile Photo Analyzer", divider="gray") + for i in range(6): + + st.divider() + + st.markdown(f"**{headings[i]}**\n\n{features[i]}") + + # show progress bar + st.progress(int(confidence_scores[i]), text=f"confidence score: {confidence_scores[i]}") + + st.divider() + st.divider() + st.divider() + text2 = extract_text_from_pdf(uploaded_file) + st.subheader(":blue[LinkedIn] Skills Analyzer", divider="gray") + s=f"""Take on the role of a skilled HR professional. Analyze the provided candidate text ({text2}) and compare the candidate's skills to the required skills for the specified job profile ({selected_role}). Identify the top 5 most relevant skills required for the job and determine the candidate's skill gap.Calculate a percentage match based on the overlap between the candidate's skills and the required skills. + """+"""Output the results in the following format: + 1. skils Methoned By user: + 2. Top Skills Required: {skill1}, {skill2}, {skill3}, {skill4}, {skill5} + 3. Candidate's Skill Gap: {missing_skills} + 4 .Role Match Percentage: {percentage} + tell we what you think about the skills of the useres + """ + + st.write(get_gemini_response(s)) + + st.divider() + st.divider() + st.divider() + st.subheader(":blue[LinkedIn] Certificates Analyzer", divider="gray") + s=f"""Take on the role of a skilled HR professional. Analyze the provided candidate text ({text2}) and compare the candidate's Certifications to the required Certifications for the specified job profile ({selected_role}). Identify the top 5 most relevant skills required for the job and determine the candidate's skill gap.Calculate a percentage match based on the overlap between the candidate's skills and the required skills. + """+"""Output the results in the following format: + 1. Certifications Methoned By user: + 2. Top Certifications Required: {skill1}, {skill2}, {skill3}, {skill4}, {skill5} + 3. Candidate's Certifications Gap: {missing_skills} + 4 .Role Match Percentage: {percentage} + tell we what you think about the Certifications of the useres + """ + st.write(get_gemini_response(s)) + + st.divider() + st.divider() + st.divider() + st.subheader(":blue[LinkedIn] Headline Analyzer", divider="gray") + s=f"""Take on the role of a skilled HR professional. Analyze the provided candidate text ({text2}) and compare the candidate's Headline to the required Headline for the specified job profile ({selected_role}). Identify the top 5 most relevant skills required for the job and determine the candidate's skill gap.Calculate a percentage match based on the overlap between the candidate's skills and the required skills. + """+"""Output the results in the following format: + 1. Headline Methoned By user: + 2. Suugest some more text by annalysis: {Headline1}, {Headline2}, {Headline3}, {Headline4}, {Headline5} + 3. Candidate's Headline Gap (missing words): {missing_words} + 4 .Role Match Percentage: {percentage} + tell we what you think about the Headline of the useres + """ + st.write(get_gemini_response(s)) + st.divider() + st.divider() + st.divider() + st.subheader(":blue[LinkedIn] Summary Analyzer", divider="gray") + s=f"""Take on the role of a skilled HR professional. Analyze the provided candidate text ({text2}) and compare the candidate's Summary to the required Summary for the specified job profile ({selected_role}). Identify the top 5 most relevant skills required for the job and determine the candidate's skill gap.Calculate a percentage match based on the overlap between the candidate's skills and the required skills. + """+"""Output the results in the following format: + 1. Summary Methoned By user: + + 2. Candidate's Summary Gap: {missing_skills} + 3 .Role rating you give: {percentage} + tell we what you think about the Summary of the useres + """ + st.write(get_gemini_response(s)) + + + st.divider() + st.divider() + st.divider() + st.subheader(":blue[LinkedIn] Education Analyzer", divider="gray") + s=f"""Take on the role of a skilled HR professional. Analyze the provided candidate text ({text2}) and compare the candidate's Education to the required Education for the specified job profile ({selected_role}). Identify the top 5 most relevant skills required for the job and determine the candidate's skill gap.Calculate a percentage match based on the overlap between the candidate's skills and the required skills. + """+"""Output the results in the following format: + 1. Education Methoned By user: + + 2. Candidate's Education Gap: {missing_skills} + 3 .Role rating you give: {percentage} + tell we what you think about the Education of the useres + """ + st.write(get_gemini_response(s)) + st.divider() + st.divider() + st.divider() + + with st.container(border=True): + pass + +if selected=="1vs1": + link="https://lottie.host/02515adf-e5f1-41c8-ab4f-8d07af1dcfb8/30KYw8Ui2q.json" + l=load_lottieurl(link) + col1, col2 = st.columns([1.3,9]) + with col1: + st.lottie(l, height=100, width=100) + with col2: + st.header(f":rainbow[Compare with your friend]👧👦", divider='rainbow') + + ans=listofuser(db) + left,right=st.columns(2) + your_id,friends_id="","" + with left: + your_id = st.multiselect("What is your ?", ans, [], placeholder="Select Your's Id") + with right: + friends_id = st.multiselect("What is your friend's?", ans, [], placeholder="Select Your Friend's Id") + + if your_id and friends_id: + + your_id = list_profiles(your_id[0],db) + friends_id = list_profiles(friends_id[0],db) + + your_data = get_leetcode_data1(your_id[5]) + friend_data = get_leetcode_data1(friends_id[5]) + your_RQuestion=RQuestion(your_id[5], limit=50) + friend_RQuestion=RQuestion(friends_id[5], limit=50) + your_let_Badges=let_Badges(your_id[5]) + friend_let_Badges=let_Badges(friends_id[5]) + your_skils=skills(your_id[5]) + friend_skils=skills(friends_id[5]) + your_graph=graph(your_id[5]) + friend_graph=graph(friends_id[5]) + my_df = process_data(your_skils) + friends_df = process_data(friend_skils) + link="https://lottie.host/3de1b5f0-49df-47f6-8a9b-21d9830c1810/IxEWj5DLSb.json" + + l=load_lottieurl(link) + col1, col2 = st.columns([1.3,9]) + with col1: + st.lottie(l, height=100, width=100) + with col2: + st.header("Coding Platform analyzer 💻💻", divider=True) + your, midle, friend = st.columns([1.6,0.1, 1.6]) + with your: + user_profile = your_data['userProfile'] + contest_info = your_data['userContestRanking'] + ko=[] + for stat in user_profile['submitStats']['acSubmissionNum']: + ko=ko+[stat['count']] + cols = st.columns([1,2.9]) + with cols[0]: + image = st.image(user_profile['profile']['userAvatar']) + st.markdown( + """ + + """, + unsafe_allow_html=True, + ) + + # Create a link around the image + image_html = f'' + st.markdown(image_html, unsafe_allow_html=True) + with cols[1]: + z=your_data['userProfile']['username'] + ui.metric_card(title="User Name", content=z, description="", key="card1") + perc,ratong = st.columns([1,1]) + with perc: + ui.metric_card(title="Top Percentage", content=contest_info['topPercentage'], description="Great🥰", key="card2") + with ratong: + ui.metric_card(title="Rating", content=user_profile['profile']['ranking'], description="Good😁", key="card3") + st.header("Easy-Medium-Hard😊😑😥", divider=True) + total_questions = ko[0] + easy_questions = ko[1] + medium_questions = ko[2] + hard_questions = ko[3] + # Calculate percentages + easy_percent = (easy_questions / total_questions) * 100 + medium_percent = (medium_questions / total_questions) * 100 + hard_percent = (hard_questions / total_questions) * 100 + # Display total questions + col1, col3 = st.columns([3, 1]) + with col1: + ui.metric_card(title="Total Question ", content=ko[0], key="card9") + + # Display pie chart + + fig, ax = plt.subplots() + ax.pie([easy_percent, medium_percent, hard_percent], + labels=["Easy", "Medium", "Hard"], + autopct="%1.1f%%", + startangle=140) + ax.axis("equal") # Equal aspect ratio for a circular pie chart + st.pyplot(fig) + + # Display difficulty counts + with col3: + ui.metric_card(title="Easy ", content=ko[1], key="card12") + ui.metric_card(title="Medium", content=ko[2], key="card10") + ui.metric_card(title="Hard ", content=ko[3], key="card11") + + st.header("SkillTracker🤹‍♂️🦾", divider=True) + categories = list(my_df["Category"].unique()) + selected_categories = st.multiselect("Select Categories for Your Data", categories, default=categories, key="my_categories") + + # Filter and Sort Data + filtered_my_df = my_df[my_df["Category"].isin(selected_categories)] + sorted_my_df = filtered_my_df.sort_values(by="Problems Solved", ascending=False) + + # Bar Chart + + fig, ax = plt.subplots(figsize=(6, 4)) + for category in sorted_my_df["Category"].unique(): + category_data = sorted_my_df[sorted_my_df["Category"] == category] + ax.bar(category_data["Topic"], category_data["Problems Solved"], label=category) + + ax.set_ylabel("Problems Solved") + ax.set_xlabel("Topic") + ax.set_title("Your Problems Solved (Sorted)") + ax.legend() + plt.xticks(rotation=90, ha="right") + st.pyplot(fig) + # Detailed Data + st.subheader("Detailed Data View") + st.dataframe(sorted_my_df) + language_data = your_data['matchedUser']['languageProblemCount'] + language_df = pd.DataFrame(language_data) + language_df.columns = ["Language", "Problems Solved"] + st.header("Questions per Language🤠", divider=True) + st.table(language_df) + header = [ "Question Name", "Timestamp"] + def format_timestamp(timestamp): + dt_object = datetime.datetime.fromtimestamp(int(timestamp)) + return dt_object.strftime("%Y-%m-%d %I:%M %p") # AM/PM format + processed_data = [] + for submission in your_RQuestion: + formatted_date = format_timestamp(submission['timestamp']) + processed_data.append([ submission['title'], formatted_date]) + df = pd.DataFrame(processed_data, columns=["Question Name", "Timestamp"]) + st.header("Your Recent Question😊📕📅",divider=True) + st.write(df) + st.header("Badges 💫🌟",divider=True) + total_badges = len(your_let_Badges["matchedUser"]["badges"]) + with st.expander(f"Total Badges: {total_badges}"): + # Create three columns + col1, col2, col3 = st.columns(3) + + # Iterate over badges and distribute them to columns + for i, badge in enumerate(your_let_Badges["matchedUser"]["badges"]): + if i % 3 == 0: + with col1: + st.write(f"**{badge['displayName']}**") + st.image(badge['medal']['config']["iconGif"], width=100) + elif i % 3 == 1: + with col2: + st.write(f"**{badge['displayName']}**") + st.image(badge['medal']['config']["iconGif"], width=100) + else: + with col3: + st.write(f"**{badge['displayName']}**") + st.image(badge['medal']['config']["iconGif"], width=100) + st.header("Graph 📊📈📉",divider=True) + data=your_graph['matchedUser']['userCalendar']['submissionCalendar'] + data = json.loads(data) + df = pd.DataFrame(list(data.items()), columns=['Timestamp', 'Count']) + df['Date'] = pd.to_datetime(df['Timestamp'].astype(int), unit='s') + df.set_index('Date', inplace=True) + daily_counts = df['Count'].resample('D').sum().fillna(0) + cmap = 'plasma' + fig, ax = calplot.calplot(daily_counts, cmap=cmap, figsize=(12, 6),colorbar=False) + st.pyplot(fig) + with midle: + st.markdown(""" + + +
+ """, unsafe_allow_html=True) + + with friend: + user_profile = friend_data['userProfile'] + contest_info = friend_data['userContestRanking'] + ko=[] + for stat in user_profile['submitStats']['acSubmissionNum']: + ko=ko+[stat['count']] + cols = st.columns([1,2.9]) + with cols[0]: + image = st.image(user_profile['profile']['userAvatar']) + st.markdown( + """ + + """, + unsafe_allow_html=True, + ) + + # Create a link around the image + image_html = f'' + st.markdown(image_html, unsafe_allow_html=True) + with cols[1]: + z=friend_data['userProfile']['username'] + ui.metric_card(title="User Name", content=z, description="", key="card24") + perc,ratong = st.columns([1,1]) + with perc: + ui.metric_card(title="Top Percentage", content=contest_info['topPercentage'], description="Great🥰", key="card26") + with ratong: + ui.metric_card(title="Rating", content=user_profile['profile']['ranking'], description="Good😁", key="card36") + st.header("Easy-Medium-Hard😊😑😥", divider=True) + total_questions = ko[0] + easy_questions = ko[1] + medium_questions = ko[2] + hard_questions = ko[3] + easy_percent = (easy_questions / total_questions) * 100 + medium_percent = (medium_questions / total_questions) * 100 + hard_percent = (hard_questions / total_questions) * 100 + col1, col3 = st.columns([3, 1]) + with col1: + ui.metric_card(title="Total Question ", content=ko[0], key="card94") + fig, ax = plt.subplots() + ax.pie([easy_percent, medium_percent, hard_percent], + labels=["Easy", "Medium", "Hard"], + autopct="%1.1f%%", + startangle=140) + ax.axis("equal") # Equal aspect ratio for a circular pie chart + st.pyplot(fig) + + # Display difficulty counts + with col3: + ui.metric_card(title="Easy ", content=ko[1], key="card124") + ui.metric_card(title="Medium", content=ko[2], key="card104") + ui.metric_card(title="Hard ", content=ko[3], key="card114") + + st.header("SkillTracker🤹‍♂️🦾", divider=True) + + categories = list(friends_df["Category"].unique()) + selected_categories = st.multiselect("Select Categories for Friends' Data", categories, default=categories, key="friends_categories") + + # Filter and Sort Data + filtered_friends_df = friends_df[friends_df["Category"].isin(selected_categories)] + sorted_friends_df = filtered_friends_df.sort_values(by="Problems Solved", ascending=False) + + # Bar Chart + + fig, ax = plt.subplots(figsize=(6, 4)) + for category in sorted_friends_df["Category"].unique(): + category_data = sorted_friends_df[sorted_friends_df["Category"] == category] + ax.bar(category_data["Topic"], category_data["Problems Solved"], label=category) + + ax.set_ylabel("Problems Solved") + ax.set_xlabel("Topic") + ax.set_title("Friends' Problems Solved (Sorted)") + ax.legend() + plt.xticks(rotation=90, ha="right") + st.pyplot(fig) + + # Detailed Data + st.subheader("Detailed Data View") + st.dataframe(sorted_friends_df) + + + + + language_data = friend_data['matchedUser']['languageProblemCount'] + language_df = pd.DataFrame(language_data) + language_df.columns = ["Language", "Problems Solved"] + st.header("Questions per Language🤠", divider=True) + st.table(language_df) + + header = [ "Question Name", "Timestamp"] + def format_timestamp(timestamp): + dt_object = datetime.datetime.fromtimestamp(int(timestamp)) + return dt_object.strftime("%Y-%m-%d %I:%M %p") # AM/PM format + processed_data = [] + + + for submission in friend_RQuestion: + formatted_date = format_timestamp(submission['timestamp']) + processed_data.append([ submission['title'], formatted_date]) + df = pd.DataFrame(processed_data, columns=["Question Name", "Timestamp"]) + + st.header("Your Recent Question😊📕📅",divider=True) + st.write(df) + total_badges = len(friend_let_Badges["matchedUser"]["badges"]) + + # Create the expander + + st.header("Badges 💫🌟",divider=True) + with st.expander(f"Total Badges: {total_badges}"): + # Create three columns + col1, col2, col3 = st.columns(3) + + # Iterate over badges and distribute them to columns + for i, badge in enumerate(friend_let_Badges["matchedUser"]["badges"]): + if i % 3 == 0: + with col1: + st.write(f"**{badge['displayName']}**") + st.image(badge['medal']['config']["iconGif"], width=100) + elif i % 3 == 1: + with col2: + st.write(f"**{badge['displayName']}**") + st.image(badge['medal']['config']["iconGif"], width=100) + else: + with col3: + st.write(f"**{badge['displayName']}**") + st.image(badge['medal']['config']["iconGif"], width=100) + + st.header("Graph 📊📈📉",divider=True) + data=friend_graph['matchedUser']['userCalendar']['submissionCalendar'] + data= json.loads(data) + df = pd.DataFrame(list(data.items()), columns=['Timestamp', 'Count']) + + df['Date'] = pd.to_datetime(df['Timestamp'].astype(int), unit='s') + df.set_index('Date', inplace=True) + daily_counts1 = df['Count'].resample('D').sum().fillna(0) + cmap = 'plasma' + fig3, ax = calplot.calplot(daily_counts1, cmap=cmap, figsize=(12, 6),colorbar=False) + st.pyplot(fig3) + codeforce_your=your_id[2] + codeforce_friend=friends_id[2] + codechef_username_your=your_id[1] + codechef_username_friend=friends_id[1] + + + + with your: + + st.header("Codeforces and Codechef ",divider=True) + data=get_user_data(codeforce_your) + # last_online_time = datetime.utcfromtimestamp(data["lastOnlineTimeSeconds"]).strftime('%Y-%m-%d %H:%M:%S') + # registration_time = datetime.utcfromtimestamp(data["registrationTimeSeconds"]).strftime('%Y-%m-%d %H:%M:%S') + st.image(data["avatar"], caption="User's Avatar", width=100) + st.subheader(f"Username: {data['handle']}") + + # Display Rating and Rank + st.write(f"**Rank:** {data['rank']}") + st.write(f"**Max Rank:** {data['maxRank']}") + st.write(f"**Rating:** {data['rating']}") + st.write(f"**Max Rating:** {data['maxRating']}") + + # Display Friend Count and Contribution + st.write(f"**Friend Count:** {data['friendOfCount']}") + st.write(f"**Contribution:** {data['contribution']}") + + + with midle: + st.markdown(""" + + +
+ """, unsafe_allow_html=True) + + with friend: + st.header("Codeforces and Codechef ",divider=True) + + data=get_user_data(codeforce_friend) + # last_online_time = datetime.utcfromtimestamp(data["lastOnlineTimeSeconds"]).strftime('%Y-%m-%d %H:%M:%S') + # registration_time = datetime.utcfromtimestamp(data["registrationTimeSeconds"]).strftime('%Y-%m-%d %H:%M:%S') + st.image(data["avatar"], caption="User's Avatar", width=100) + st.subheader(f"Username: {data['handle']}") + + # Display Rating and Rank + st.write(f"**Rank:** {data['rank']}") + st.write(f"**Max Rank:** {data['maxRank']}") + st.write(f"**Rating:** {data['rating']}") + st.write(f"**Max Rating:** {data['maxRating']}") + + # Display Friend Count and Contribution + st.write(f"**Friend Count:** {data['friendOfCount']}") + st.write(f"**Contribution:** {data['contribution']}") + +if selected=="collage": + ans=listofcollege(db) + your_id = st.multiselect("which Collage ?", ans, [], placeholder="Select Your's Id") + + if your_id: + usernames=totalusers(your_id[0],4) + user_ratings = get_ratings_for_users(usernames) + st.write(user_ratings) + for user, rating in user_ratings.items(): + if rating is not None: + st.write(f"{user}'s contest rating: {rating}") + else: + st.write(f"Could not retrieve contest rating for {user}") + active_days_list = get_active_days_for_users(usernames) + + if active_days_list: + for username, days in active_days_list: + st.write(f"{username}: {days} active days in 2024") + else: + st.write("Error fetching active days for some users.") + + diff --git a/profiles/profile_data.sql b/profiles/profile_data.sql new file mode 100644 index 0000000..147f7f9 --- /dev/null +++ b/profiles/profile_data.sql @@ -0,0 +1,17 @@ +use profiles; +CREATE TABLE user_profiles ( + id INT AUTO_INCREMENT PRIMARY KEY, + name VARCHAR(255) NOT NULL, + leetcode_username VARCHAR(255), + codechef_username VARCHAR(255), + github_username VARCHAR(255), + codeforces_username VARCHAR(255) +); +-- Insert new rows into the user_profiles table +INSERT INTO user_profiles (name, leetcode_username, codechef_username, github_username, codeforces_username) +VALUES +('Sree Charan', 'sreecharna9484', 'sreecharna9484', 'SreeCharan1234', 'sreecharna9484'), +('ykgupta2411', 'ykgupta2411', 'ykgupta2411', 'ykgupta2411', 'ykgupta2411'); + +-- Query the data to verify +SELECT * FROM user_profiles; diff --git a/progress.csv b/progress.csv new file mode 100644 index 0000000..26f9814 --- /dev/null +++ b/progress.csv @@ -0,0 +1 @@ +User,Repo,Lines of Code,Language diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..385a741 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,45 @@ +firebase-admin +google-cloud-firestore +SpeechRecognition +google-generativeai +python-dotenv +streamlit +streamlit-ace +streamlit-extras +pdf2image +gtts +pillow +google.generativeai +IPython +streamlit-lottie +requests +youtube-transcript-api +streamlit-option-menu +streamlit-webrtc +pandas +plotly +Pillow +GitPython +beautifulsoup4 +matplotlib +seaborn +spacy +streamlit_shadcn_ui +langchain +PyPDF2 +faiss-cpu +poppler-utils +requests_html +streamlit-on-Hover-tabs +httpx-oauth +firebase-admin +streamlit-authenticator +calplot +langchain_google_genai +langchain-community +numpy +aiortc +flask +flask-socketio +streamlit_chat +mysql-connector-python diff --git a/src/ATS.json b/src/ATS.json new file mode 100644 index 0000000..3598fb9 --- /dev/null +++ b/src/ATS.json @@ -0,0 +1,5289 @@ +{ + "v": "5.12.1", + "fr": 60, + "ip": 0, + "op": 360, + "w": 500, + "h": 500, + "nm": "Person Creative", + "ddd": 0, + "assets": [ + { + "id": "comp_0", + "nm": "Tabs&Mouse", + "fr": 60, + "layers": [ + { + "ddd": 0, + "ind": 1, + "ty": 4, + "nm": "Mouse", + "sr": 1, + "ks": { + "o": { + "a": 0, + "k": 100, + "ix": 11 + }, + "r": { + "a": 1, + "k": [ + { + "i": { + "x": [ + 0.227 + ], + "y": [ + 1 + ] + }, + "o": { + "x": [ + 0.904 + ], + "y": [ + 0 + ] + }, + "t": 0, + "s": [ + 82 + ] + }, + { + "i": { + 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+ background-image: linear-gradient(to right, #f06b6b, #ffdb58); + background-size: 100% 100%; + background-attachment: fixed; + } +ul {list-style-type: none;} + +hr { + margin-top: 0px; + margin-bottom: 5%; +} diff --git a/src/mcqgenerator/.env b/src/mcqgenerator/.env new file mode 100644 index 0000000..ce0ecac --- /dev/null +++ b/src/mcqgenerator/.env @@ -0,0 +1 @@ +API-KEY="AIzaSyAk-vG70jpxWB17WnpOxqDtAdagBA1a9kg" diff --git a/src/mcqgenerator/MCQGenerator.py b/src/mcqgenerator/MCQGenerator.py new file mode 100644 index 0000000..c0713fa --- /dev/null +++ b/src/mcqgenerator/MCQGenerator.py @@ -0,0 +1,54 @@ +import os +import json +import PyPDF2 +import pandas as pd +import traceback +from dotenv import load_dotenv +from src.mcqgenerator.utils import read_file, get_table_data +from src.mcqgenerator.logger import logging +import langchain_google_genai as genai +from langchain.prompts import PromptTemplate +from langchain.chains import LLMChain, SequentialChain + +load_dotenv() + +api_key=os.getenv("API-KEY") +llm = genai.ChatGoogleGenerativeAI(google_api_key=api_key, model="gemini-pro") + +template=""" +Text:{text} +You are an expert MCQ maker. Given the above text, it is your job to \ +create a quiz of {number} multiple choice questions for {subject} students in {tone} tone. +Make sure the questions are not repeated and check all the questions to be conforming the text as well. +Make sure to format your response like RESPONSE_JSON below and use it as a guide. \ +Ensure to make {number} MCQs +### RESPONSE_JSON +{response_json} + +""" + +quiz_generation_prompt = PromptTemplate( + input_variables=["text", "number", "subject", "tone", "response_json"], + template=template + ) + +quiz_chain = LLMChain(llm=llm, prompt=quiz_generation_prompt, output_key="quiz", verbose=True) + +template2=""" +You are an expert english grammarian and writer. Given a Multiple Choice Quiz for {subject} students.\ +You need to evaluate the complexity of the question and give a complete analysis of the quiz. Only use at max 50 words for complexity analysis. +if the quiz is not at per with the cognitive and analytical abilities of the students,\ +update the quiz questions which needs to be changed and change the tone such that it perfectly fits the student abilities +Quiz_MCQs: +{quiz} + +Check from an expert English Writer of the above quiz: +""" + +quiz_evaluation_prompt=PromptTemplate(input_variables=["subject", "quiz"], template=template2) + +review_chain = LLMChain(llm=llm, prompt=quiz_evaluation_prompt, output_key="review", verbose=True) + +generate_evaluate_chain = SequentialChain(chains=[quiz_chain, review_chain], input_variables=["text", "number", "subject", "tone", "response_json"], + output_variables=["quiz", "review"], verbose=True) + diff --git a/src/mcqgenerator/__init__.py b/src/mcqgenerator/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/src/mcqgenerator/__pycache__/MCQGenerator.cpython-312.pyc b/src/mcqgenerator/__pycache__/MCQGenerator.cpython-312.pyc new file mode 100644 index 0000000..86294ad Binary files /dev/null and b/src/mcqgenerator/__pycache__/MCQGenerator.cpython-312.pyc differ diff --git a/src/mcqgenerator/__pycache__/MCQGenerator.cpython-39.pyc b/src/mcqgenerator/__pycache__/MCQGenerator.cpython-39.pyc new file mode 100644 index 0000000..277b04a Binary files /dev/null and b/src/mcqgenerator/__pycache__/MCQGenerator.cpython-39.pyc differ diff --git a/src/mcqgenerator/__pycache__/__init__.cpython-312.pyc b/src/mcqgenerator/__pycache__/__init__.cpython-312.pyc new file mode 100644 index 0000000..f9b8b78 Binary files /dev/null and b/src/mcqgenerator/__pycache__/__init__.cpython-312.pyc differ diff --git a/src/mcqgenerator/__pycache__/__init__.cpython-39.pyc b/src/mcqgenerator/__pycache__/__init__.cpython-39.pyc new file mode 100644 index 0000000..b4e4637 Binary files /dev/null and b/src/mcqgenerator/__pycache__/__init__.cpython-39.pyc differ diff --git a/src/mcqgenerator/__pycache__/logger.cpython-312.pyc b/src/mcqgenerator/__pycache__/logger.cpython-312.pyc new file mode 100644 index 0000000..f4d8368 Binary files /dev/null and b/src/mcqgenerator/__pycache__/logger.cpython-312.pyc differ diff --git a/src/mcqgenerator/__pycache__/logger.cpython-39.pyc b/src/mcqgenerator/__pycache__/logger.cpython-39.pyc new file mode 100644 index 0000000..4a7ae63 Binary files /dev/null and b/src/mcqgenerator/__pycache__/logger.cpython-39.pyc differ diff --git a/src/mcqgenerator/__pycache__/utils.cpython-312.pyc b/src/mcqgenerator/__pycache__/utils.cpython-312.pyc new file mode 100644 index 0000000..3d6682f Binary files /dev/null and b/src/mcqgenerator/__pycache__/utils.cpython-312.pyc differ diff --git a/src/mcqgenerator/__pycache__/utils.cpython-39.pyc b/src/mcqgenerator/__pycache__/utils.cpython-39.pyc new file mode 100644 index 0000000..cbba3d9 Binary files /dev/null and b/src/mcqgenerator/__pycache__/utils.cpython-39.pyc differ diff --git a/src/mcqgenerator/logger.py b/src/mcqgenerator/logger.py new file mode 100644 index 0000000..661cf3c --- /dev/null +++ b/src/mcqgenerator/logger.py @@ -0,0 +1,15 @@ +import logging +import os +from datetime import datetime + +LOG_FILE=f"{datetime.now().strftime('%m_%d_%Y_%H_%H_%S')}.log" + +log_path=os.path.join(os.getcwd(), "logs") +os.makedirs(log_path, exist_ok=True) + +LOG_FILEPATH=os.path.join(log_path, LOG_FILE) + +logging.basicConfig(level=logging.INFO, + filename=LOG_FILEPATH, + format="[%(asctime)s] %(lineno)d %(name)s - %(levelname)s - %(message)s" + ) \ No newline at end of file diff --git a/src/mcqgenerator/utils.py b/src/mcqgenerator/utils.py new file mode 100644 index 0000000..20757f5 --- /dev/null +++ b/src/mcqgenerator/utils.py @@ -0,0 +1,49 @@ +import os +import json +import PyPDF2 +import traceback + +def read_file(file): + if file.name.endswith(".pdf"): + try: + pdf_reader=PyPDF2.PdfReader(file) + text="" + for page in pdf_reader.pages: + text+=page.extract_text() + return text + + except Exception as e: + raise Exception("error reading the PDF file") + + elif file.name.endswith(".txt"): + return file.read().decode("utf-8") + + else: + raise Exception( + "unsupported file format only pdf and text file supported" + ) + +def get_table_data(quiz_str): + try: + # convert the quiz from a str to dict + quiz_dict=json.loads(quiz_str) + quiz_table_data=[] + + #iterate over the quiz dictionary and extract the required information + for key, value in quiz_dict.items(): + mcq=value["mcq"] + options=" || ".join( + [ + f"{option} -> {option_value}" for option, option_value in value["options"].items() + ] + ) + + correct=value["correct"] + quiz_table_data.append({"MCQ": mcq, "Choices": options, "Correct": correct}) + + return quiz_table_data + + except Exception as e: + traceback.print_exception(type(e), e, e.__traceback__) + return False + diff --git a/src/style.css b/src/style.css new file mode 100644 index 0000000..ae60a06 --- /dev/null +++ b/src/style.css @@ -0,0 +1,76 @@ +section[data-testid='stSidebar'] { + background-color: #111; + flex-shrink: unset !important; + +} + +@media(hover:hover) and (min-width: 600px) and (max-width: 769px){ + + header[data-testid="stHeader"] { + display:none; + } + + section[data-testid='stSidebar'] { + height: 100%; + min-width:95px !important; + width: 95px !important; + margin-left: 305px; + position: relative; + z-index: 1; + top: 0; + left: 0; + background-color: #111; + overflow-x: hidden; + transition: 0.5s ease; + padding-top: 60px; + white-space: nowrap; + } + + section[data-testid='stSidebar']:hover{ + min-width: 330px !important; + } + + button[kind="header"] { + display: none; + } + + div[data-testid="collapsedControl"]{ + display: none; + } + +} + +@media(hover: hover) and (min-width: 769px){ + + header[data-testid="stHeader"] { + display:none; + } + + section[data-testid='stSidebar'] { + height: 100%; + min-width:95px !important; + width: 95px !important; + transform:translateX(0px); + position: relative; + z-index: 1; + top: 0; + left: 0; + background-color: #111; + overflow-x: hidden; + transition: 0.5s ease; + padding-top: 60px; + white-space: nowrap; + } + + section[data-testid='stSidebar']:hover{ + min-width: 330px !important; + } + + button[kind="header"] { + display: none; + } + + div[data-testid="collapsedControl"]{ + display: none; + } +} \ No newline at end of file diff --git a/test.py b/test.py new file mode 100644 index 0000000..a04e4ad --- /dev/null +++ b/test.py @@ -0,0 +1,143 @@ +# import requests + +def get_active_days(username): + """Fetches and returns total active days for a given LeetCode username in 2024. + + Args: + username (str): The username of the LeetCode user. + + Returns: + list: A list containing two elements: + - The username (str) + - The total active days in 2024 (int) if successful, or None otherwise. + """ + + url = "https://leetcode.com/graphql" + query = """ + query userProfileCalendar($username: String!, $year: Int) { + matchedUser(username: $username) { + userCalendar(year: $year) { + totalActiveDays + } + } + } + """ + + variables = { + "username": username, + "year": 2024 + } + + try: + response = requests.post(url, json={'query': query, 'variables': variables}) + data = response.json() + + if 'errors' in data: + print("Error:", data['errors']) + return None + + total_active_days = data['data']['matchedUser']['userCalendar']['totalActiveDays'] + return [username, total_active_days] + + except requests.exceptions.RequestException as e: + print("Error making request:", e) + return None + +def get_active_days_for_users(usernames): + """Calculates total active days for a list of LeetCode usernames in 2024. + + Args: + usernames (list): A list of LeetCode usernames. + + Returns: + list: A list of lists, where each inner list contains: + - The username (str) + - The total active days in 2024 (int) if successful, or None otherwise. + """ + + results = [] + for username in usernames: + active_days = get_active_days(username) + if active_days: + results.append(active_days) + + return results +# # Example usage +# usernames = ["sreecharan9484", "ykgupta2411", "Tauhid_Neyaz"] # Replace with your usernames +active_days_list = get_active_days_for_users(usernames) + +if active_days_list: + for username, days in active_days_list: + print(f"{username}: {days} active days in 2024") +else: + print("Error fetching active days for some users.") + + + +import requests + +def get_leetcode_contest_rating(username): + + + url = "https://leetcode.com/graphql" + query = """ + query userContestRankingInfo($username: String!) { + userContestRanking(username: $username) { + rating + } + } + """ + variables = {"username": username} + + try: + response = requests.post(url, json={'query': query, 'variables': variables}) + data = response.json() + + if 'errors' in data: + print(f"Error for {username}:", data['errors']) + return None + + contest_ranking = data['data']['userContestRanking'] + + if contest_ranking is None: # Handle cases where user has no rating + print(f"{username} has no contest rating.") + return None + + rating = contest_ranking.get('rating') + if rating is None: + print(f"Rating data is missing for {username}") + return None + + return rating + + except requests.exceptions.RequestException as e: + print(f"Request error for {username}:", e) + return None + except (KeyError, TypeError) as e: + print(f"Data processing error for {username}:", e) + return None + + +def get_ratings_for_users(usernames): + """Retrieves contest ratings for a list of usernames. + + Args: + usernames (list): A list of LeetCode usernames. + + Returns: + dict: A dictionary where keys are usernames and values are their ratings (or None if an error occurred or no rating exists). + """ + ratings = {} + for username in usernames: + rating = get_leetcode_contest_rating(username) + ratings[username] = rating + return ratings + +usernames = ["sreecharan9484", "ykgupta2411", "Tauhid_Neyaz"] # Replace with actual usernames +user_ratings = get_ratings_for_users(usernames) + +for user, rating in user_ratings.items(): + if rating is not None: + print(f"{user}'s contest rating: {rating}") + else: + print(f"Could not retrieve contest rating for {user}") diff --git a/test2.py b/test2.py new file mode 100644 index 0000000..1bfe2fb --- /dev/null +++ b/test2.py @@ -0,0 +1,120 @@ +import firebase_admin +from firebase_admin import credentials +from firebase_admin import db +import time +import streamlit as st +from google.cloud import firestore +# Replace with your Firebase project credentials (service account key JSON file) +cred = credentials.Certificate("a.json") + +# Initialize the Firebase Admin SDK +firebase_admin.initialize_app(cred, { + 'databaseURL': "https://profile-data-dde0a-default-rtdb.firebaseio.com/" # Replace with your database URL +}) + + + +def create_user(username, password, codechef_id, leet_id, github_id, codeforces_id, college, category): + + try: + users_ref = db.reference("users") + new_user_ref = users_ref.push() + user_data = { + "username": username, + "password": password, + "codechef_id": codechef_id, + "leet_id": leet_id, + "github_id": github_id, + "codeforces_id": codeforces_id, + "college": college, + "category": category + } + new_user_ref.set(user_data) + print(f"User created with ID: {new_user_ref.key}") + return new_user_ref.key + except Exception as e: + print(f"Error creating user: {e}") + return None + +def listofuser(db): + """Retrieves all users from Firebase and returns a list of usernames.""" + try: + users_ref = db.reference("users") + users_snapshot = users_ref.get() + + if users_snapshot: + user_data = [] + for user_id, user_info in users_snapshot.items(): # Iterate through user IDs and data + user_data.append(user_info["username"]) # Append username to the list + return user_data + else: + print("No users found in the database.") + return [] # Return an empty list if no users are found + + except Exception as e: + print(f"Error retrieving users: {e}") + return [] +print(listofuser(db)) +# if __name__ == "__main__": +# #users_input = get_user_input() +# insert_users_from_input([["TUHID", "Sree@1234", "sreecharan9484", "sreecharan9484", "SreeCharan1234", "sreecharan9484","LPU","Student"]]) +# print("Finished inserting users.") + +#create_user("a","a","a","a","a","a","a","a") +def list_profiles(username): #rt for real time database + """Retrieves a user profile from the Realtime Database based on username.""" + try: + ref = db.reference('/users') + users = ref.get() + + if users: + for user_id, user_data in users.items(): + if user_data.get('username') == username: + # Convert the dictionary values to a list + profile_list = list(user_data.values()) + return profile_list # Return the list + + return None + + except Exception as e: + print(f"Error retrieving profile: {e}") + return None + +def authenticate_user(username, password): + """Authenticates a user against Firebase.""" + try: + users_ref = db.reference("users") + users_snapshot = users_ref.get() + + if users_snapshot: + for user_id, user_data in users_snapshot.items(): + if user_data.get("username") == username and user_data.get("password") == password: + print(f"User '{username}' authenticated successfully. User ID: {user_id}") + return user_data # Return the user data if authenticated + print(f"Authentication failed for user '{username}'.") + return None # Return None if authentication fails + else: + print("No users found in the database.") + return None + + except Exception as e: + print(f"Error during authentication: {e}") + return None +authenticate_user("Sree Charan" ,"Sree@1234") + + +# if __name__ == "__main__": +# usernames = get_all_users() +# if usernames: +# print("List of usernames:", usernames) +#print(list_profiles("Sree Charan")) +def listofcollege(db): + users_ref = db.reference('users') + users_data = users_ref.get() + colleges = set() + for user_id, user_data in users_data.items(): + if 'college' in user_data: + colleges.add(user_data['college']) + return list(colleges) + +print("List of Colleges:", listofcollege(db)) \ No newline at end of file diff --git a/test3.py b/test3.py new file mode 100644 index 0000000..c9653de --- /dev/null +++ b/test3.py @@ -0,0 +1,77 @@ +import streamlit as st +import firebase_admin +from firebase_admin import credentials, firestore # Import for Firestore + +# -- Firebase configuration (replace with your credentials) -- +cred = credentials.Certificate("a.json") +firebase_admin.initialize_app(cred, { + 'databaseURL': "https://profile-data-dde0a-default-rtdb.firebaseio.com/" # Replace with your database URL +}) + +# -- Firestore client initialization (for scalability) -- +db = firestore.client() # Initialize Firestore client + +def create_user(username, password, codechef_id, leet_id, github_id, codeforces_id, college, category): + """ + Creates a new user in the Firebase Realtime Database (or Firestore) and returns the user ID. + + Args: + username (str): Username for the new user. + password (str): User's password (consider hashing for security). + codechef_id (str): User's CodeChef ID (optional). + leet_id (str): User's LeetCode ID (optional). + github_id (str): User's GitHub ID (optional). + codeforces_id (str): User's Codeforces ID (optional). + college (str): User's college name (optional). + category (str): User's category (optional). + + Returns: + str: The ID of the newly created user, or None on error. + """ + + try: + # Choose either Realtime Database (commented out) or Firestore + # users_ref = db.reference("users") # Use for Realtime Database + users_collection = db.collection("users") # Use for Firestore + + # Generate a unique ID (consider UUID for better distribution) + new_user_ref = users_collection.document() # Use for Firestore + + user_data = { + "username": username, + "password": password, # Consider hashing before storing + "codechef_id": codechef_id, + "leet_id": leet_id, + "github_id": github_id, + "codeforces_id": codeforces_id, + "college": college, + "category": category + } + + # Use either set() for Realtime Database (commented out) or add() for Firestore + # new_user_ref.set(user_data) # Use for Realtime Database + new_user_ref.set(user_data) # Use for Firestore + + st.success(f"User created with ID: {new_user_ref.id}") # Use for Firestore + return new_user_ref.id # Use for Firestore + + except Exception as e: + st.error(f"Error creating user: {e}") + return None + +st.title("Create User") + +username = st.text_input("Username") +password = st.text_input("Password", type="password") +codechef_id = st.text_input("CodeChef ID (optional)") +leet_id = st.text_input("LeetCode ID (optional)") +github_id = st.text_input("GitHub ID (optional)") +codeforces_id = st.text_input("Codeforces ID (optional)") +college = st.text_input("College (optional)") +category = st.text_input("Category (optional)") + +if st.button("Create User"): + user_id = create_user(username, password, codechef_id, leet_id, github_id, codeforces_id, college, category) + + if user_id: + st.success(f"User created successfully! User ID: {user_id}") \ No newline at end of file diff --git a/user.csv b/user.csv new file mode 100644 index 0000000..0db7639 --- /dev/null +++ b/user.csv @@ -0,0 +1,4 @@ +1,1,Sree@1234,sd,gh,hg,hg +2,Sree Charan,Sree@1234,sreecharan9484,sreecharan9484,SreeCharan1234,sreecharan9484 +4,tu,listofcollege3,tle0tauhid,Tauhid_Neyaz,tleTauhid,tleTauhid +3,ykgupta2411,ykgupta2411,ykgupta2411,ykgupta2411,ykgupta2411,ykgupta2411 \ No newline at end of file diff --git a/user_data.db b/user_data.db new file mode 100644 index 0000000..f489609 Binary files /dev/null and b/user_data.db differ diff --git a/users_data.csv b/users_data.csv new file mode 100644 index 0000000..00b4e1d --- /dev/null +++ b/users_data.csv @@ -0,0 +1,5 @@ +username,password,codechef_id,leet_id,github_id,codeforces_id +Sree@1234,Sree@1234,sd,gh,hg,hg +Sree Charan,Sree@1234,sreecharan9484,sreecharan9484,SreeCharan1234,sreecharan9484 +tu,listofcollege3,tle0tauhid,Tauhid_Neyaz,tleTauhid,tleTauhid +ykgupta2411,ykgupta2411,ykgupta2411,ykgupta2411,ykgupta2411,ykgupta2411 diff --git a/util/__pycache__/codeforces.cpython-312.pyc b/util/__pycache__/codeforces.cpython-312.pyc new file mode 100644 index 0000000..fb35072 Binary files /dev/null and b/util/__pycache__/codeforces.cpython-312.pyc differ diff --git a/util/__pycache__/common.cpython-312.pyc b/util/__pycache__/common.cpython-312.pyc new file mode 100644 index 0000000..07e17a0 Binary files /dev/null and b/util/__pycache__/common.cpython-312.pyc differ diff --git a/util/__pycache__/github.cpython-312.pyc b/util/__pycache__/github.cpython-312.pyc new file mode 100644 index 0000000..0a0ae16 Binary files /dev/null and b/util/__pycache__/github.cpython-312.pyc differ diff --git a/util/__pycache__/leetcode.cpython-312.pyc b/util/__pycache__/leetcode.cpython-312.pyc new file mode 100644 index 0000000..ebdedf0 Binary files /dev/null and b/util/__pycache__/leetcode.cpython-312.pyc differ diff --git a/util/__pycache__/login.cpython-312.pyc b/util/__pycache__/login.cpython-312.pyc new file mode 100644 index 0000000..6a1118a Binary files /dev/null and b/util/__pycache__/login.cpython-312.pyc differ diff --git a/util/codechef.py b/util/codechef.py new file mode 100644 index 0000000..e69de29 diff --git a/util/codeforces.py b/util/codeforces.py new file mode 100644 index 0000000..904edd3 --- /dev/null +++ b/util/codeforces.py @@ -0,0 +1,34 @@ +import streamlit as st +import requests +import matplotlib.pyplot as plt +def get_user_data(handle): + base_api_url = "https://codeforces.com/api/" + url = f"{base_api_url}user.info?handles={handle}" + response = requests.get(url) + if response.status_code == 200: + return response.json()["result"][0] + else: + st.error(f"Error: {response.text}") + return None + +def get_contest_data(handle): + base_api_url = "https://codeforces.com/api/" + url = f"{base_api_url}user.rating?handle={handle}" + response = requests.get(url) + if response.status_code == 200: + return response.json() + else: + st.error(f"Error: {response.text}") + return None + +def get_submission_data(handle): + base_api_url = "https://codeforces.com/api/" + url = f"{base_api_url}user.status?handle={handle}" + response = requests.get(url) + if response.status_code == 200: + return response.json()["result"] + else: + st.error(f"Error: {response.text}") + return None + + diff --git a/util/common.py b/util/common.py new file mode 100644 index 0000000..2c6dde2 --- /dev/null +++ b/util/common.py @@ -0,0 +1,79 @@ + +import google.generativeai as genai +import PyPDF2 +import pdf2image +import requests +def get_leetcode_data(username): + url = "https://leetcode.com/graphql" + query = """ + query getLeetCodeData($username: String!) { + userProfile: matchedUser(username: $username) { + username + profile { + userAvatar + reputation + ranking + } + submitStats { + acSubmissionNum { + difficulty + count + } + totalSubmissionNum { + difficulty + count + } + } + } + userContestRanking(username: $username) { + attendedContestsCount + rating + globalRanking + totalParticipants + topPercentage + } + recentSubmissionList(username: $username) { + title + statusDisplay + lang + } + matchedUser(username: $username) { + languageProblemCount { + languageName + problemsSolved + } + } + recentAcSubmissionList(username: $username, limit: 15) { + id + title + titleSlug + timestamp + } + + } + + """ + variables = { + "username": username + } + response = requests.post(url, json={'query': query, 'variables': variables}) + data = response.json() + + if 'errors' in data: + print("Error:", data['errors']) + return None + + return data['data'] +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 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() diff --git a/util/github.py b/util/github.py new file mode 100644 index 0000000..603c79a --- /dev/null +++ b/util/github.py @@ -0,0 +1,94 @@ +import os +import shutil +import streamlit as st +import requests +import pandas as pd +import plotly.express as px +from PIL import Image +from git import Repo +from urllib.request import urlopen +from bs4 import BeautifulSoup +import json +import matplotlib.pyplot as plt +import subprocess +import sys + +def run_gitleaks(user, repo): + repo_url = f'https://github.com/{user}/{repo}.git' + output_file = f"{user}_secrets.txt" + + cmd = f"chmod +x /app/cmc/gitleaks && /app/cmc/gitleaks --repo-url={repo_url} --report={output_file}" + subprocess.run(cmd, shell=True) + + +def count_lines_of_code(repo_path, ext): + total = 0 + for path, dirs, files in os.walk(repo_path): + for name in files: + st.write(name) + if name.endswith(ext): + try: + with open(os.path.join(path, name)) as f: + total += sum(1 for line in f if line.strip() != '') + except Exception as e: + total =total + return total + +def clone_and_count_lines(user, repo, ext): + repo_url = f'https://github.com/{user}/{repo}' + + local_path = f'temp/{repo}' + Repo.clone_from(repo_url, local_path) + + lines = count_lines_of_code(local_path, ext) + + #shutil.rmtree(local_path) + # you can add this in the file code after deplyoment in the streamlit ok + + return lines + +def update_progress_file(filename, repo_name): + with open(filename, 'a') as f: + f.write(repo_name + '\n') + +def is_repo_processed(filename, repo_name): + if not os.path.exists(filename): + st.write("File not found") + return False + with open(filename, 'r') as f: + lines = f.read().splitlines() + return repo_name in lines + + + + + # For wide layout +def get_all_user_repos(user): + page = 1 + repos = [] + + while True: + response = requests.get(f'https://github.com/{user}?page={page}&tab=repositories') + + if response.status_code != 200: + break + + soup = BeautifulSoup(response.text, 'html.parser') + repo_elements = soup.find_all('a', itemprop='name codeRepository') + + if not repo_elements: # If no more repos found, stop looping + break + + page_repos = [repo.text.strip() for repo in repo_elements] + repos.extend(page_repos) + + page += 1 + + return repos + +def get_user_repos(user): + repo_names = get_all_user_repos(user) + df = pd.DataFrame(repo_names, columns=['repo_name']) + df['repo_size'] = [len(name) for name in df['repo_name']] + + return df diff --git a/util/leetcode.py b/util/leetcode.py new file mode 100644 index 0000000..3d67896 --- /dev/null +++ b/util/leetcode.py @@ -0,0 +1,339 @@ +import requests +import json + +def RQuestion(username, limit=50): + + + url = f"https://leetcode.com/graphql" + headers = { + "Content-Type": "application/json" + } + + query = """ + query recentAcSubmissions($username: String!, $limit: Int!) { + recentAcSubmissionList(username: $username, limit: $limit) { + id + title + titleSlug + timestamp + } + } + """ + + variables = { + "username": username, + "limit": limit + } + + response = requests.post(url, json={"query": query, "variables": variables}, headers=headers) + + if response.status_code == 200: + data = json.loads(response.text) + return data["data"]["recentAcSubmissionList"] + else: + return f"Error fetching data: {response.text}" + +def skills(username): + query = """ + query skillStats($username: String!) { + matchedUser(username: $username) { + tagProblemCounts { + advanced { + tagName + tagSlug + problemsSolved + } + intermediate { + tagName + tagSlug + problemsSolved + } + fundamental { + tagName + tagSlug + problemsSolved + } + } + } + } + """ + + variables = {"username": username} + + url = "https://leetcode.com/graphql" # Replace with the actual GraphQL API endpoint + headers = {"Content-Type": "application/json"} + + response = requests.post(url, json={"query": query, "variables": variables}, headers=headers) + + if response.status_code == 200: + data = json.loads(response.text) + return data['data']['matchedUser']['tagProblemCounts'] + else: + print(f"Error fetching data: {response.text}") + return None + +def get_leetcode_data1(username): + url = "https://leetcode.com/graphql" + query = """ + + query getLeetCodeData($username: String!) { + userProfile: matchedUser(username: $username) { + username + profile { + userAvatar + reputation + ranking + } + submitStats { + acSubmissionNum { + difficulty + count + } + totalSubmissionNum { + difficulty + count + } + } + } + userContestRanking(username: $username) { + attendedContestsCount + rating + globalRanking + totalParticipants + topPercentage + } + recentSubmissionList(username: $username) { + title + statusDisplay + lang + } + matchedUser(username: $username) { + languageProblemCount { + languageName + problemsSolved + } + } + + } + + + """ + variables = { + "username": username, + "year": 2024 + } + response = requests.post(url, json={'query': query, 'variables': variables}) + data = response.json() + if 'errors' in data: + print("Error:", data['errors']) + return None + + + return data['data'] + +def let_Badges(username): + url = "https://leetcode.com/graphql" + + query=""" + query userBadges($username: String!) { + matchedUser(username: $username) { + badges { + id + name + shortName + displayName + icon + hoverText + medal { + slug + config { + iconGif + iconGifBackground + } + } + creationDate + category + } + upcomingBadges { + name + icon + progress + } + } +} + +""" + + + variables = { + "username": username, + "year": 2024 + } + response = requests.post(url, json={'query': query, 'variables': variables}) + data = response.json() + if 'errors' in data: + print("Error:", data['errors']) + return None + + + return data['data'] + +def graph(username): + url = "https://leetcode.com/graphql" + query=""" + + +query userProfileCalendar($username: String!, $year: Int) { + matchedUser(username: $username) { + userCalendar(year: $year) { + activeYears + streak + totalActiveDays + dccBadges { + timestamp + badge { + name + icon + } + } + submissionCalendar + } + } +} + """ + + + + + variables = { + "username": username, + "year": 2024 + } + response = requests.post(url, json={'query': query, 'variables': variables}) + + data = response.json() + if 'errors' in data: + print("Error:", data['errors']) + return None + + + return data['data'] + +def get_leetcode_contest_rating(username): + + + url = "https://leetcode.com/graphql" + query = """ + query userContestRankingInfo($username: String!) { + userContestRanking(username: $username) { + rating + } + } + """ + variables = {"username": username} + + try: + response = requests.post(url, json={'query': query, 'variables': variables}) + data = response.json() + + if 'errors' in data: + print(f"Error for {username}:", data['errors']) + return None + + contest_ranking = data['data']['userContestRanking'] + + if contest_ranking is None: # Handle cases where user has no rating + print(f"{username} has no contest rating.") + return None + + rating = contest_ranking.get('rating') + if rating is None: + print(f"Rating data is missing for {username}") + return None + + return rating + + except requests.exceptions.RequestException as e: + print(f"Request error for {username}:", e) + return None + except (KeyError, TypeError) as e: + print(f"Data processing error for {username}:", e) + return None + +def get_ratings_for_users(usernames): + """Retrieves contest ratings for a list of usernames. + + Args: + usernames (list): A list of LeetCode usernames. + + Returns: + dict: A dictionary where keys are usernames and values are their ratings (or None if an error occurred or no rating exists). + """ + ratings = {} + for username in usernames: + rating = get_leetcode_contest_rating(username) + ratings[username] = rating + return ratings + +def get_active_days(username): + """Fetches and returns total active days for a given LeetCode username in 2024. + + Args: + username (str): The username of the LeetCode user. + + Returns: + list: A list containing two elements: + - The username (str) + - The total active days in 2024 (int) if successful, or None otherwise. + """ + + url = "https://leetcode.com/graphql" + query = """ + query userProfileCalendar($username: String!, $year: Int) { + matchedUser(username: $username) { + userCalendar(year: $year) { + totalActiveDays + } + } + } + """ + + variables = { + "username": username, + "year": 2024 + } + + try: + response = requests.post(url, json={'query': query, 'variables': variables}) + data = response.json() + + if 'errors' in data: + print("Error:", data['errors']) + return None + + total_active_days = data['data']['matchedUser']['userCalendar']['totalActiveDays'] + return [username, total_active_days] + + except requests.exceptions.RequestException as e: + print("Error making request:", e) + return None + +def get_active_days_for_users(usernames): + """Calculates total active days for a list of LeetCode usernames in 2024. + + Args: + usernames (list): A list of LeetCode usernames. + + Returns: + list: A list of lists, where each inner list contains: + - The username (str) + - The total active days in 2024 (int) if successful, or None otherwise. + """ + + results = [] + for username in usernames: + active_days = get_active_days(username) + if active_days: + results.append(active_days) + + return results diff --git a/util/login.py b/util/login.py new file mode 100644 index 0000000..e819dbc --- /dev/null +++ b/util/login.py @@ -0,0 +1,127 @@ +# Function to insert data into the database +from firebase_admin import db + + +def add_user(username, password, codechef_id, leet_id, github_id, codeforces_id, college, category,db): + + try: + + users_ref = db.reference("users") + new_user_ref = users_ref.push() + user_data = { + "username": username, + "password": password, + "codechef_id": codechef_id, + "leet_id": leet_id, + "github_id": github_id, + "codeforces_id": codeforces_id, + "college": college, + "category": category + } + new_user_ref.set(user_data) + print(f"User created with ID: {new_user_ref.key}") + return new_user_ref.key + except Exception as e: + print(f"Error creating user: {e}") + return None + +# Function to authenticate a user during login +def authenticate_user(username, password): + """Authenticates a user against Firebase.""" + try: + users_ref = db.reference("users") + users_snapshot = users_ref.get() + + if users_snapshot: + for user_id, user_data in users_snapshot.items(): + if user_data.get("username") == username and user_data.get("password") == password: + print(f"User '{username}' authenticated successfully. User ID: {user_id}") + return user_data # Return the user data if authenticated + print(f"Authentication failed for user '{username}'.") + return None # Return None if authentication fails + else: + print("No users found in the database.") + return None + + except Exception as e: + print(f"Error during authentication: {e}") + return None +# Password validation function +def is_valid_password(password): + if len(password) < 8: + return "Password must be at least 8 characters long." + if not any(char.isdigit() for char in password): + return "Password must contain at least one number." + return None + + +def list_profiles(username,db): #rt for real time database + """Retrieves a user profile from the Realtime Database based on username.""" + try: + ref = db.reference('/users') + users = ref.get() + + if users: + for user_id, user_data in users.items(): + if user_data.get('username') == username: + # Convert the dictionary values to a list + profile_list = list(user_data.values()) + return profile_list # Return the list + + return None + + except Exception as e: + print(f"Error retrieving profile: {e}") + return None + +def listofcollege(db): + users_ref = db.reference('users') + users_data = users_ref.get() + colleges = set() + for user_id, user_data in users_data.items(): + if 'college' in user_data: + colleges.add(user_data['college']) + return list(colleges) + + +def totalusers(college_name,n): + try: + conn = sqlite3.connect('user_data.db') # Replace with your database name + cursor = conn.cursor() + cursor.execute("SELECT * FROM users WHERE college = ?", (college_name,)) + results = cursor.fetchall() + + college_names = [] + for college in results: + college_names.append(college[n]) + + return college_names + + except sqlite3.Error as e: + print(f"SQLite error: {e}") + return [] + + finally: + if conn: + conn.close() + + + +def listofuser(db): + """Retrieves all users from Firebase and returns a list of usernames.""" + try: + users_ref = db.reference("users") + users_snapshot = users_ref.get() + + if users_snapshot: + user_data = [] + for user_id, user_info in users_snapshot.items(): # Iterate through user IDs and data + user_data.append(user_info["username"]) # Append username to the list + return user_data + else: + print("No users found in the database.") + return [] # Return an empty list if no users are found + + except Exception as e: + print(f"Error retrieving users: {e}") + return [] # Return an empty list in case of error