Sales Agent using Google ADK

Project Overview

This project implements a conversational Sales Agent using Google's Agent Development Kit (ADK) in Python.

The agent: - Activates when a new lead sends a message, simulating a form submission. - Asks for consent before collecting any information. - Collects specific information through a step-by-step flow: - Age - Country - Interested Product or Service - Handles multiple lead interactions concurrently by managing separate sessions using session IDs. - Saves all collected information into a CSV file (leads.csv). - Sends a follow-up message if a lead does not respond within 10 seconds, simulating a 24-hour delay.

Project Structure

sales-agent/ adk-env/ # Virtual environment agent.py # SalesAgent class logic utils.py # Helper function to update leads.csv simulate_leads.py # Script to automatically simulate lead interaction interactive_test.py # Script to manually interact with the agent leads.csv # Output file where leads are saved README.md # Project documentation

Setup Instructions

1. Clone or download the project files.
2. Create a virtual environment: python -m venv adk-env
3. Activate the virtual environment: adk-env\Scripts\activate
4. Install required dependencies: pip install google-adk pip install aioconsole

How It Works

• External Trigger:
  The agent is activated when a lead sends a message, simulating a form submission.

• Conversational Flow:

  1. The agent greets the user and asks for consent.
  2. If the user agrees, the agent collects information step-by-step.
  3. The collected data is saved in the leads.csv file.

• Multi-Session Handling:
  Each conversation session is handled independently using a unique session ID.

• Follow-Up Handling:
  If the user does not respond within 10 seconds after a question, the agent sends an automatic follow-up reminder.

How to Test

Simulate Leads Automatically

Run the simulation script: python simulate_leads.py This script automatically interacts with the agent to simulate lead form filling.

Manually Interact with the Agent

Run the manual testing script: python interactive_test.py Type your responses manually. If you do not respond to a question within 10 seconds, the agent will automatically send a follow-up message.

Leads Data Example

After the interaction, the leads.csv file will store lead data in the following format:

| leadid | age | country | interest | status | |---------|-----|---------|----------|--------| | manuallead | 25 | Pakistan | Nike Shoes | secured |

Requirements Fulfilled

| Task Requirement | Status | |-------------------|--------| | Use Google ADK in Python | Completed | | Handle multiple lead interactions concurrently | Completed | | Collect specific information step-by-step | Completed | | Activate agent through an external trigger | Completed | | Save collected information into a CSV file | Completed | | Follow up with leads who do not respond | Completed | | Manual and simulation-based testing | Completed |

Conclusion

This project successfully implements a fully functional conversational sales agent that interacts with leads, collects necessary information, saves the data securely, and manages follow-up messaging in case of inactivity, all built using Google's Agent Development Kit in Python.