Configuration Overview

DeepSearcher provides flexible configuration options for all its components. You can customize the following aspects of the system:

📋 Components

Component	Purpose	Documentation
LLM	Large Language Models for query processing	LLM Configuration
Embedding Models	Text embedding for vector retrieval	Embedding Models
Vector Database	Storage and retrieval of vector embeddings	Vector Database
File Loader	Loading and processing various file formats	File Loader
Web Crawler	Gathering information from web sources	Web Crawler

🔄 Configuration Method

DeepSearcher uses a consistent configuration approach for all components:

from deepsearcher.configuration import Configuration, init_config

# Create configuration
config = Configuration()

# Set provider configurations
config.set_provider_config("[component]", "[provider]", {"option": "value"})

# Initialize with configuration
init_config(config=config)

For detailed configuration options for each component, please visit the corresponding documentation pages linked in the table above.