🧠 Embedding Providers
Generate vector representations of text for semantic search, clustering, and AI applications
EmbeddingFramework supports multiple embedding providers, allowing you to generate vector representations of text for semantic search, clustering, and other AI applications.
🧠 Supported Providers¶
1️⃣ OpenAI Embeddings¶
- State-of-the-art embeddings for text and code.
- Requires an OpenAI API key.
Example:
from embeddingframework.adapters.openai_embedding_adapter import OpenAIEmbeddingAdapter
provider = OpenAIEmbeddingAdapter(api_key="YOUR_OPENAI_API_KEY")
embeddings = provider.embed_texts(["Hello world", "EmbeddingFramework is awesome!"])
🔄 Adding New Providers¶
EmbeddingFramework is designed to be extensible.
To add a new provider:
1. Create a new adapter class in embeddingframework/adapters/.
2. Inherit from the base embedding adapter.
3. Implement the embed_texts method.