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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.