Valyu SDK

Connect your AI applications to high-quality proprietary data with Valyu, an AI context engine built by AI Engineers, for AI Engineers.

Why Valyu?

• Ready-to-use RAG Data: All data is returned in Markdown format, optimized for AI consumption
• Multimodal Support: Retrieve text, images, and other data types to provide comprehensive answers
• Pay-per-use: Transparent pricing model where you only pay for what you use
• Hybrid Search: Combine proprietary dataset access with web search capabilities
• Built for AI: Designed specifically for RAG (Retrieval-Augmented Generation) applications

Installation

Install the Valyu SDK using pip:

pip install valyu

Quick Start

Get started in minutes with just a few lines of code:

from valyu import Valyu

# Initialize the Valyu client
valyu = Valyu(api_key="your-api-key")

# Get relevant context for your query
response = valyu.context(
    query="Tell me about ancient civilizations",
    search_type="proprietary",  # Choose between "proprietary" or "public" search
    num_query=5,                # Number of queries to generate
    num_results=3,              # Number of results to return
    max_price=10                # Maximum price willing to pay per thousand queries
)

print(response)

Features

1. Context Enrichment

Enhance your AI applications with relevant context from our proprietary datasets:

# Example: Retrieving context about quantitative finance
response = valyu.context(
    query="What are the latest developments in stochastic volatility models for options pricing?",
    search_type="proprietary",
    num_query=10,
    num_results=5,
    max_price=1  # Price per thousand queries
)

2. Dataset Access

Load complete training/fine-tuning datasets or samples for your AI applications:

from valyu import load_dataset, load_dataset_samples

# Load dataset samples (no API key required)
load_dataset_samples("example_org/example_dataset")

# Load full dataset with API key
load_dataset(api_key="your-api-key", dataset_id="example_org/example_dataset")

Customization Options

• Search Type: Choose between proprietary datasets or public web data
• Query Generation: Control the number of queries generated for better context matching
• Result Volume: Specify the number of results to retrieve
• Cost Control: Set maximum price limits per retrieval
• Data Format: All results are returned in Markdown format, ready for AI consumption

Use Cases

• Enhance RAG applications with high-quality proprietary data
• Access curated datasets across various domains (Finance, Healthcare, Technology, etc.)
• Combine proprietary and public data sources for comprehensive AI responses
• Build domain-specific AI applications with expert knowledge

Getting Started

1. Sign up for a free account at Valyu
2. Get your API key from the dashboard
3. Install the SDK and start building

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Support

For more information and detailed documentation, visit our documentation.