What is Objective Search API
Objective is an AI-native search platform designed to integrate the best of search technologies with modern developer ergonomics. It provides a layer of intelligence that helps businesses optimize for their goals, enabling powerful user experiences across various applications. The platform is trusted by leading companies and offers features like automated relevance evaluation, AI-powered finetuning, and transparent embedding management.
How to Use Objective Search API
- Initialize the Client: Use the Objective Client with your API key.
- Upsert Objects: Add or update objects in the object store.
- Create Index: Define the index type and fields for search.
- Search: Perform searches using queries and retrieve results.
Example:
from objective import Client as ObjectiveClient
client = ObjectiveClient(api_key="YOUR_API_KEY")
objects = [
{
"product_name": "Nike Free Run 208",
"detail_description": "Built for the trail or the road, Free Run 208’s ...",
"product_photo": "https:// ... 8272302349.png",
"categories": ["footwear","athletic"]
}
]
client.object_store.upsert_objects(objects)
index = client.indexes.create_index(
index_type="multimodal",
fields={
"searchable": ["product_name", "detail_description"],
"crawlable": ["product_photo"]
}
)
index.search(
query="trail running shoes",
object_fields="*"
)
Use Cases of Objective Search API
Objective is used to build retail search experiences that understand semantic meaning and image content, product discovery with "search by vibe," and RAG & conversational agents powered by flexible semantic search. It is ideal for companies looking to enhance their search capabilities without building infrastructure from scratch.
Features of Objective Search API
-
Automated Relevance Evaluation
Automatically evaluate the relevance of your search indexes, allowing for validation and experimentation at scale.
-
AI-powered Finetuning
Generate simulated search queries and training data to automatically finetune your indexes, improving search accuracy.
-
Transparent Embedding Management
Search indexes react to data updates in real-time, handling embedding and transformations seamlessly.
-
Ensemble Models
Combine best-of-breed technologies and blended models to deliver superior search experiences.