Module Support

DeepSearcher supports various integration modules including embedding models, large language models, document loaders and vector databases.

📊 Overview

Module Type	Count	Description
Embedding Models	7+	Text vectorization tools
Large Language Models	11+	Query processing and text generation
Document Loaders	5+	Parse and process documents in various formats
Vector Databases	2+	Store and retrieve vector data

🔢 Embedding Models

Support for various embedding models to convert text into vector representations for semantic search.

Provider	Required Environment Variables	Features
Open-source models	None	Locally runnable open-source models
OpenAI	OPENAI_API_KEY	High-quality embeddings, easy to use
VoyageAI	VOYAGE_API_KEY	Embeddings optimized for retrieval
Amazon Bedrock	AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY	AWS integration, enterprise-grade
FastEmbed	None	Fast lightweight embeddings
PPIO	PPIO_API_KEY	Flexible cloud embeddings
Novita AI	NOVITA_API_KEY	Rich model selection

🧠 Large Language Models

Support for various large language models (LLMs) to process queries and generate responses.

Provider	Required Environment Variables	Features
OpenAI	OPENAI_API_KEY	GPT model family
DeepSeek	DEEPSEEK_API_KEY	Powerful reasoning capabilities
XAI Grok	XAI_API_KEY	Real-time knowledge and humor
Anthropic Claude	ANTHROPIC_API_KEY	Excellent long-context understanding
SiliconFlow	SILICONFLOW_API_KEY	Enterprise inference service
PPIO	PPIO_API_KEY	Diverse model support
TogetherAI	TOGETHER_API_KEY	Wide range of open-source models
Google Gemini	GEMINI_API_KEY	Google's multimodal models
SambaNova	SAMBANOVA_API_KEY	High-performance AI platform
Ollama	None	Local LLM deployment
Novita AI	NOVITA_API_KEY	Diverse AI services

📄 Document Loader

Support for loading and processing documents from various sources.

Local File Loaders

Loader	Supported Formats	Required Environment Variables
Built-in Loader	PDF, TXT, MD	None
Unstructured	Multiple document formats	UNSTRUCTURED_API_KEY, UNSTRUCTURED_URL (optional)

Web Crawlers

Crawler	Description	Required Environment Variables/Setup
FireCrawl	Crawler designed for AI applications	FIRECRAWL_API_KEY
Jina Reader	High-accuracy web content extraction	JINA_API_TOKEN
Crawl4AI	Browser automation crawler	Run crawl4ai-setup for first-time use

💾 Vector Database Support

Support for various vector databases for efficient storage and retrieval of embeddings.

Database	Description	Features
Milvus	Open-source vector database	High-performance, scalable
Zilliz Cloud	Managed Milvus service	Fully managed, maintenance-free
Qdrant	Vector similarity search engine	Simple, efficient