Overview This project is a Python-based job recommendation system that leverages Google's Generative AI to provide personalized job recommendations for students based on their academic performance, course completion, and other achievements. The system generates tailored job descriptions, salary ranges, and personalized advice, which are then stored in a MongoDB database for easy retrieval and analysis.
Features Personalized Job Recommendations: Generates job descriptions tailored to the student's academic performance and achievements.
AI-Powered: Utilizes Google's Generative AI (gemini-1.5-pro-latest) to create dynamic and relevant job recommendations.
Data Storage: Stores generated job recommendations in a MongoDB database for future reference.
Data Analysis: Uses pandas to display and analyze the stored job recommendations in a tabular format.
Requirements Python 3.x
Required Python libraries:
pandas
pymongo
google-generativeai
MongoDB (local or remote instance)
Installation Clone the repository:
bash Copy git clone https://github.com/your-repo/job-recommendation-generator.git cd job-recommendation-generator Install the required libraries:
bash Copy pip install pandas pymongo google-generativeai Set up MongoDB:
Ensure MongoDB is installed and running locally or provide the connection string for a remote instance.
Update the MongoDB connection string in the notebook if necessary.
Configure Google Generative AI:
Obtain a Google API key and replace the placeholder in the notebook with your actual API key.
Usage Run the Jupyter Notebook:
Open the Gemini-final.ipynb notebook in Jupyter or any compatible environment.
Execute the cells in sequence to install dependencies, configure the AI model, and generate job recommendations.
Input Student Data:
Modify the input_data1 dictionary in the notebook to reflect the student's information, such as course details, attendance, completed modules, and certifications.
Generate Job Recommendations:
The notebook will generate a job recommendation based on the student's profile and store it in the MongoDB database.
View Recommendations:
Use the provided code to retrieve and display the stored job recommendations in a pandas DataFrame.
Example Output The system generates a JSON-structured job recommendation, including:
Job Title
Salary Range
Company Details (Name, Industry, Size, Culture)
Responsibilities
Qualifications
Additional Information
Personalized Advice
Contributing Contributions are welcome! Please fork the repository and submit a pull request with your changes.
Acknowledgments Google Generative AI for providing the AI model.
MongoDB for database storage.
Pandas for data analysis and visualization.