Embedding Model Configuration
DeepSearcher supports various embedding models to convert text into vector representations for semantic search.
📝 Basic Configuration
config.set_provider_config("embedding", "(EmbeddingModelName)", "(Arguments dict)")
📋 Available Embedding Providers
Provider | Description | Key Features |
---|---|---|
OpenAIEmbedding | OpenAI's text embedding models | High quality, production-ready |
MilvusEmbedding | Built-in embedding models via Pymilvus | Multiple model options |
VoyageEmbedding | VoyageAI embedding models | Specialized for search |
BedrockEmbedding | Amazon Bedrock embedding | AWS integration |
GeminiEmbedding | Google's Gemini embedding | High performance |
GLMEmbedding | ChatGLM embeddings | Chinese language support |
OllamaEmbedding | Local embedding with Ollama | Self-hosted option |
PPIOEmbedding | PPIO cloud embedding | Scalable solution |
SiliconflowEmbedding | Siliconflow's models | Enterprise support |
VolcengineEmbedding | Volcengine embedding | High throughput |
NovitaEmbedding | Novita AI embedding | Cost-effective |
🔍 Provider Examples
OpenAI Embedding
config.set_provider_config("embedding", "OpenAIEmbedding", {"model": "text-embedding-3-small"})
OPENAI_API_KEY
environment variable
Milvus Built-in Embedding
config.set_provider_config("embedding", "MilvusEmbedding", {"model": "BAAI/bge-base-en-v1.5"})
config.set_provider_config("embedding", "MilvusEmbedding", {"model": "jina-embeddings-v3"})
JINAAI_API_KEY
environment variable
VoyageAI Embedding
config.set_provider_config("embedding", "VoyageEmbedding", {"model": "voyage-3"})
VOYAGE_API_KEY
environment variable and pip install voyageai
📚 Additional Providers
Amazon Bedrock
config.set_provider_config("embedding", "BedrockEmbedding", {"model": "amazon.titan-embed-text-v2:0"})
AWS_ACCESS_KEY_ID
and AWS_SECRET_ACCESS_KEY
environment variables and pip install boto3
Novita AI
config.set_provider_config("embedding", "NovitaEmbedding", {"model": "baai/bge-m3"})
NOVITA_API_KEY
environment variable
Siliconflow
config.set_provider_config("embedding", "SiliconflowEmbedding", {"model": "BAAI/bge-m3"})
SILICONFLOW_API_KEY
environment variable
Volcengine
config.set_provider_config("embedding", "VolcengineEmbedding", {"model": "doubao-embedding-text-240515"})
VOLCENGINE_API_KEY
environment variable
GLM
config.set_provider_config("embedding", "GLMEmbedding", {"model": "embedding-3"})
GLM_API_KEY
environment variable and pip install zhipuai
Google Gemini
config.set_provider_config("embedding", "GeminiEmbedding", {"model": "text-embedding-004"})
GEMINI_API_KEY
environment variable and pip install google-genai
Ollama
config.set_provider_config("embedding", "OllamaEmbedding", {"model": "bge-m3"})
pip install ollama
PPIO
config.set_provider_config("embedding", "PPIOEmbedding", {"model": "baai/bge-m3"})
PPIO_API_KEY
environment variable