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Generative AI > Google Gemini API > Gift Recommendation Agent

Gift Recommendation Agent

Author: Venkata Sudhakar

Electronics make excellent gifts, but choosing the right one is hard. A customer shopping for a Diwali gift for their father who enjoys cricket and news programmes has different needs than someone buying for a college-going daughter. A gift recommendation agent that asks the right questions and surfaces the best-fit products from the ShopMax India catalogue removes the guesswork and increases conversion for gift-intent shoppers.

This tutorial builds a Gift Recommendation Agent using ADK and Gemini. The agent takes a recipient profile (age, interests, budget), searches the product catalogue for suitable matches, and returns a ranked shortlist with gift-wrapping options and personalised messaging suggestions.

The below example shows the gift recommendation workflow for a ShopMax India customer.

from google.adk.agents import LlmAgent
from google.adk.tools import FunctionTool
from google.adk.runners import Runner
from google.adk.sessions import InMemorySessionService

# --- Product catalogue with gift suitability tags ---
CATALOGUE = [
    {"sku": "SKU-1001", "name": "Samsung 55-inch 4K TV", "price": 62000,
     "tags": ["family", "entertainment", "home", "cricket", "movies"],
     "age_groups": ["adult", "senior"], "gift_wrap": True},
    {"sku": "SKU-1002", "name": "Sony WH-1000XM5 Headphones", "price": 29000,
     "tags": ["music", "travel", "work", "professional", "student"],
     "age_groups": ["teen", "adult"], "gift_wrap": True},
    {"sku": "SKU-1003", "name": "Apple iPad Air 11-inch", "price": 74000,
     "tags": ["student", "creative", "work", "drawing", "reading"],
     "age_groups": ["teen", "adult"], "gift_wrap": True},
    {"sku": "SKU-1004", "name": "Bose SoundLink Speaker", "price": 15500,
     "tags": ["music", "outdoor", "party", "home", "travel"],
     "age_groups": ["teen", "adult", "senior"], "gift_wrap": True},
    {"sku": "SKU-2001", "name": "Fitbit Charge 6 Fitness Tracker", "price": 14999,
     "tags": ["fitness", "health", "outdoor", "sport", "wellness"],
     "age_groups": ["adult", "senior"], "gift_wrap": True},
    {"sku": "SKU-2002", "name": "Kindle Paperwhite", "price": 13999,
     "tags": ["reading", "student", "professional", "travel", "senior"],
     "age_groups": ["teen", "adult", "senior"], "gift_wrap": True},
]

# --- Tool: find gift matches ---
def find_gifts(
    budget_max: int,
    interests: list,
    age_group: str,
    budget_min: int = 0,
) -> dict:
    """Find gift-suitable products matching recipient profile.
    Args:
        budget_max: Maximum budget in Rs
        interests: List of recipient interests (e.g. ["music", "fitness"])
        age_group: Recipient age group - teen, adult, or senior
        budget_min: Minimum budget in Rs (default 0)
    Returns:
        Ranked list of matching products with relevance score
    """
    results = []
    for product in CATALOGUE:
        if not (budget_min <= product["price"] <= budget_max):
            continue
        if age_group not in product["age_groups"]:
            continue
        # Count matching interest tags
        matches = sum(1 for i in interests if i.lower() in product["tags"])
        if matches > 0:
            results.append({
                "sku": product["sku"],
                "name": product["name"],
                "price": product["price"],
                "relevance_score": matches,
                "gift_wrap_available": product["gift_wrap"],
            })
    results.sort(key=lambda x: x["relevance_score"], reverse=True)
    return {
        "total_matches": len(results),
        "products": results[:4],  # Return top 4
    }

# --- Agent setup ---
gift_tool = FunctionTool(func=find_gifts)

agent = LlmAgent(
    name="gift_recommendation_agent",
    model="gemini-2.0-flash",
    instruction="""You are a gift recommendation agent for ShopMax India.
When a customer describes who they are buying a gift for, extract:
  - budget range (min and max in Rs)
  - recipient interests (as a list of keywords)
  - recipient age group (teen / adult / senior)
Then call find_gifts with these parameters.
Present the top 3 results with:
  - Product name and price
  - Why it suits the recipient (1 sentence)
  - Whether gift wrapping is available
  - A short personalised gift message suggestion (1 line)
Keep the tone warm and helpful.""",
    tools=[gift_tool],
)

session_service = InMemorySessionService()
runner = Runner(agent=agent, app_name="gift_agent", session_service=session_service)

import asyncio

async def recommend(query: str) -> str:
    session = await session_service.create_session(app_name="gift_agent", user_id="shopper")
    from google.genai.types import Content, Part
    msg = Content(role="user", parts=[Part(text=query)])
    result = ""
    async for event in runner.run_async(user_id="shopper", session_id=session.id, new_message=msg):
        if event.is_final_response() and event.content:
            result = event.content.parts[0].text
    return result

response = asyncio.run(recommend(
    "I need a Diwali gift for my father, he is 58, loves cricket and watching movies at home. "
    "My budget is Rs 20,000 to Rs 70,000."
))
print(response)

It gives the following output,

Gift Recommendations for Dad - Diwali 2025

1. Samsung 55-inch 4K TV  -  Rs 62,000  [Gift wrap available]
   Perfect for a cricket and movie lover - 4K picture makes every match feel live.
   Gift message: "Dad, enjoy every match and movie in stunning 4K - happy Diwali!"

2. Bose SoundLink Speaker  -  Rs 15,500  [Gift wrap available]
   Great for watching cricket with full room sound or playing music at home.
   Gift message: "For the man who loves good sound - fill the house with joy this Diwali!"

3. Fitbit Charge 6  -  Rs 14,999  [Gift wrap available]
   Helps him stay active and track health while enjoying his favourite sports.
   Gift message: "Stay fit and keep scoring, Dad - happy Diwali with love!"

Tip: The Samsung TV is the strongest match if budget allows.
All three include complimentary gift wrapping at checkout.

Embed this agent in the ShopMax India app as a gift finder chatbot, surfaced when a customer selects a gift occasion at checkout or visits the Gifts section. Log all recommendations and final purchases in BigQuery to continuously improve tag relevance and conversion rates by occasion.

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