from transformers import pipeline
from gift_finder_model import GiftFinderModel

model = GiftFinderModel()

# Example conversation
conversation = """
USER: I need to find a gift for my brother's birthday. He's in his 20s and loves playing basketball and video games. I don't want to spend more than $50.
ASSISTANT: I'd be happy to help you find a birthday gift for your brother who loves basketball and video games within your $50 budget.
"""

result = model.process_conversation(conversation)
print(result)

Output Example

{
  "extracted_data": {
    "occasion": "birthday",
    "recipient_relationship": "brother",
    "recipient_age": "young adult",
    "recipient_interests": "basketball and video games",
    "budget": "moderate"
  },
  "gift_search_query": "birthday gift for brother who enjoys basketball and video games under $50"
}

Using with SerpAPI for Real Product Recommendations

python

from gift_finder_api import GiftFinderAPI

# Initialize the API
api = GiftFinderAPI()

# Get recommendations with real product search
recommendations = api.get_gift_recommendations(
    conversation="...",
    num_recommendations=5,
    search_api_key="your_serpapi_key"  # Pass your SerpAPI key here
)

# Display recommendations
for rec in recommendations:
    print(f"{rec['name']} - {rec['price']}")
    print(f"{rec['description']}")
    print(f"{rec['url']}")

mehdirben/gift-finder

Gift Finder Model

Model Description

SerpAPI Integration

Usage

Output Example

Using with SerpAPI for Real Product Recommendations

mehdirben/
gift-finder