The problem: every embedding provider has a different SDK with different bugs. OpenAI has undocumented token limits. VoyageAI's retry logic was broken until September. Cohere breaks downstream libraries every release. LiteLLM's embedding support is minimal.

catsu provides:

- One API for 11 providers (OpenAI, Voyage, Cohere, Jina, Mistral, Gemini, etc.)

- Bundled database of 50+ models with pricing, dimensions, and benchmark scores

- Built-in retry with exponential backoff

- Automatic cost tracking per request

- Full async support

Example:

```python

import catsu

client = catsu.Client()

response = client.embed(model="voyage-3", input="Hello!")

print(f"Cost: ${response.embeddings}")

print(f"Cost: ${response.usage.cost:.6f}")

```

GitHub: https://github.com/chonkie-inc/catsu

We built this at Chonkie (YC X25) because we needed it badly for our chunking library and to easily switch embeddings for our search product. Apache 2.0.