Building a Chatbot for Interview Preparation using NLP

Contribution Guidelines

• Have a Look at the project structure and folder overview below to understand where to store/upload your contribution
• If you're creating a task, Go to the task folder and create a new folder with the below naming convention and add a README.md with task details and goals to help other contributors understand
  • Task Folder Naming Convention : task-n-taskname.(n is the task number) ex: task-1-data-analysis, task-2-model-deployment etc.
  • Create a README.md with a table containing information table about all contributions for the task.
• If you're contributing for a task, please make sure to store in relavant location and update the README.md information table with your contribution details.
• Make sure your File names(jupyter notebooks, python files, data sheet file names etc) has proper naming to help others in easily identifing them.
• Please restrict yourself from creating unnessesary folders other than in 'tasks' folder (as above mentioned naming convention) to avoid confusion.

Setup & execution instructions

1. Clone the repository onto your local machine

git clone https://github.com/Anas436/Chatbot-for-Interview-Preparation.git

2. Change directory to the newly cloned directory and run the following command to set up the required virtual environment using Conda

conda env create -f environment.yml - Reference

3. Activate the newly created environment

conda activate omdena_hyd_chatbot

4. Rename the .env.example file to .env and populate your HuggingFace Hub API token inside it.

5. Run the streamlit application

streamlit run src/tasks/app-building-task/chatbot.py

Project Structure

├── LICENSE
├── README.md            <- The top-level README for developers/collaborators using this project.
├── reports              <- Folder containing the final reports/results of this project
│   └── README.md        <- Details about final reports and analysis
├── src                  <- Source code folder for this project
│    │
│    ├── data            <- Datasets used and collected for this project
│    │   
│    ├── docs            <- Folder for Task documentations, │Meeting Presentations and task Workflow Documents and Diagrams.
│    │
│    ├── references      <- Data dictionaries, manuals, and all │other explanatory references used 
│    │
│    ├── tasks           <- Master folder for all individual task │folders
│    │
│    ├── visualizations  <- Code and Visualization dashboards │generated for the project
│    │
│    └── results         <- Folder to store Final analysis and │modelling results and code.
├── environment.yml      <- Conda environment file 
├── .env.example         <- Template for an .env file

---

Folder Overview

• Original - Folder Containing old/completed Omdena challenge code.
• Reports - Folder to store all Final Reports of this project
• Data - Folder to Store all the data collected and used for this project
• Docs - Folder for Task documentations, Meeting Presentations and task Workflow Documents and Diagrams.
• References - Folder to store any referneced code/research papers and other useful documents used for this project
• Tasks - Master folder for all tasks
  • All Task Folder names should follow specific naming convention
  • All Task folder names should be in chronologial order (from 1 to n)
  • All Task folders should have a README.md file with task Details and task goals along with an info table containing all code/notebook files with their links and information
  • Update the task-table whenever a task is created and explain the purpose and goals of the task to others.
• Visualization - Folder to store dashboards, analysis and visualization reports
• Results - Folder to store final analysis modelling results for the project.

References

• Local Chapter Links here