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34 lines
1.2 KiB
34 lines
1.2 KiB
2 weeks ago
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# Configuration Overview
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DeepSearcher provides flexible configuration options for all its components. You can customize the following aspects of the system:
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## 📋 Components
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| Component | Purpose | Documentation |
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|-----------|---------|---------------|
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| **LLM** | Large Language Models for query processing | [LLM Configuration](llm.md) |
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| **Embedding Models** | Text embedding for vector retrieval | [Embedding Models](embedding.md) |
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| **Vector Database** | Storage and retrieval of vector embeddings | [Vector Database](vector_db.md) |
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| **File Loader** | Loading and processing various file formats | [File Loader](file_loader.md) |
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| **Web Crawler** | Gathering information from web sources | [Web Crawler](web_crawler.md) |
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## 🔄 Configuration Method
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DeepSearcher uses a consistent configuration approach for all components:
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```python
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from deepsearcher.configuration import Configuration, init_config
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# Create configuration
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config = Configuration()
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# Set provider configurations
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config.set_provider_config("[component]", "[provider]", {"option": "value"})
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# Initialize with configuration
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init_config(config=config)
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```
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For detailed configuration options for each component, please visit the corresponding documentation pages linked in the table above.
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