HR Agentic Chatbot

This project implements an HR Chatbot using LangChain, MongoDB, OpenAI's language models, and Google APIs. It includes synthetic data generation, embedding creation, and a chatbot interface for querying HR-related information and interacting with Google services.

Table of Contents

1. Prerequisites
2. Installation
3. Configuration
4. Google API Setup
5. Synthetic Data Generation
6. Data Ingestion and Embedding Generation
7. Running the Chatbot
8. Project Structure
9. Contributing
10. License

Prerequisites

• Python 3.8+
• MongoDB
• OpenAI API key
• Google Cloud Platform account
• Git (for version control)

Installation

1. Clone the repository:

   git clone https://github.com/your-username/hr-agentic-chatbot.git
   cd hr-agentic-chatbot

2. Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

3. Install the required packages:

   pip install -r requirements.txt

Configuration

1. Create a .env file in the project root and add the following variables:

   MONGO_URI=your_mongodb_connection_string
   OPENAI_API_KEY=your_openai_api_key
   

2. Replace your_mongodb_connection_string with your actual MongoDB connection string and your_openai_api_key with your OpenAI API key.

Google API Setup

1. Go to the Google Cloud Console.
2. Create a new project or select an existing one.
3. Enable the following APIs for your project:
   • Google Drive API
   • Google Docs API
   • Gmail API
4. Create credentials (OAuth 2.0 Client ID) for a Desktop application:
   • Go to "Credentials" in the left sidebar.
   • Click "Create Credentials" and select "OAuth client ID".
   • Choose "Desktop app" as the application type.
   • Download the client configuration file and rename it to credentials.json.
   • Place credentials.json in the root directory of the project.
5. The first time you run the application, it will prompt you to authorize access:
   • A browser window will open asking you to log in to your Google account.
   • Grant the requested permissions.
   • The application will then create a token.json file in the project root.

Note: Keep credentials.json and token.json secure and do not share them publicly.

Synthetic Data Generation

To generate synthetic data for companies, workforce, and employees:

1. Navigate to the data directory:

   cd data

2. Run the synthetic data generation script:

   python synthetic_data_generation.py

This will create JSON files (companies.json, workforce.json, employees.json) in the data directory.

Data Ingestion and Embedding Generation

To ingest the synthetic data into MongoDB and generate embeddings for employees:

1. Ensure you're in the project root directory.

2. Run the data ingestion script:

   python data/ingestion.py

This script will:

• Read the JSON files from the data directory
• Generate embeddings for employee data using OpenAI's API
• Insert the data (including embeddings) into MongoDB

Running the Chatbot

To start the HR Chatbot:

1. Ensure you're in the project root directory.

2. Run the main script:

   chainlit run app.py

3. Open your web browser and navigate to the URL provided in the terminal (usually http://localhost:8000).

4. Interact with the chatbot through the web interface.

Project Structure

HR_AGENTIC_CHATBOT/
│
├── .chainlit/
├── .files/
├── data/
│   ├── __init__.py
│   ├── companies.json
│   ├── employees.json
│   ├── ingestion.py
│   ├── synthetic_data_generation.py
│   └── workforce.json
│
├── mongodb/
│   ├── __init__.py
│   ├── checkpointer.py
│   └── connect.py
│
├── tools/
│   ├── google_tools.py
│   └── mongodb_tools.py
│
├── .env
├── .gitignore
├── agent.py
├── app.py
├── chainlit.md
├── config.py
├── credentials.json  # Google OAuth 2.0 credentials
├── db_utils.py
├── graph.py
├── README.md
├── requirements.txt
├── temp.py
├── token.json  # Generated after first Google auth
└── utilities.py

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.