Morph + Weaviate
Morph serves code and text embedding models behind an OpenAI-compatible API. Weaviate integrates with Morph's embedding endpoint so you can vectorize and search data using Morph-hosted models directly from your Weaviate instance.
Morph's own documentation labels the Embedding API as legacy and planned for deprecation. Check the current status in Morph's documentation before you build on this integration.
Integrations with Morph
Embedding models for vector search
Morph exposes embedding models over an OpenAI-compatible /v1/embeddings API at https://api.morphllm.com.
Weaviate integrates with Morph's embedding models through the text2vec-morph vectorizer module. Configure a vector index to use a Morph model and Weaviate generates embeddings for imports, vector searches, and hybrid searches automatically.
Morph embedding integration page
Summary
This integration lets you use Morph's hosted embedding models from Weaviate without managing inference infrastructure yourself.
Get started
Generate an API key in the Morph dashboard, then supply it to Weaviate through the MORPH_APIKEY environment variable or the X-Openai-Api-Key request header. The header name is shared with the OpenAI integration, because Morph requests are built by the same OpenAI-compatible client inside Weaviate. Then see the embedding integration page:
Questions and feedback
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