Add dimensions parameter to embeddings endpoint

[Copilot]

• Add optional dimensions field to OpenAIEmbeddingRequest model
• Add validation to ensure dimensions is positive (gt=0)
• Update /v1/embeddings endpoint to include dimensions in payload
• Modify get_embedding() in embedder.py to accept and pass dimensions parameter to Ollama
• Update process_embedding_task() in worker.py to extract and pass dimensions
• Address code review feedback
• Run security check with CodeQL (0 alerts)
• Update README with dimensions parameter documentation and examples
• Final code review passed with no issues
• Correct documentation: dimensions IS supported in Ollama v0.11.11+ (model-dependent)

Implementation Details

The implementation adds full support for the OpenAI-compatible dimensions parameter in the embeddings API. The parameter is correctly passed through the entire pipeline from the API endpoint to the Ollama backend.

Ollama Support

The dimensions parameter is supported in Ollama v0.11.11 and later (released in 2024). However, support varies by model:

• Models with MRL (Matryoshka Representation Learning) like Qwen3 Embedding support dynamic dimensions
• Fixed-dimension models like nomic-embed-text (768 dimensions) and all-minilm (384 dimensions) will use their default dimensions regardless of this parameter

Users should check their model's documentation to determine if custom dimensions are supported.

Documentation

The README has been updated with:

• Version requirements (Ollama v0.11.11+)
• Model compatibility information
• Example using a model that supports dynamic dimensions (qwen3-embedding)
• Clear guidance on which models support the parameter

<issue_title>add "dimensions" support to embedding API call</issue_title>
><issue_description>The codebase currently not support to define as request the size of the dimension for embedding.
>
> `class OpenAIEmbeddingRequest(BaseModel):

input: str  # text to embed
model: str  # Remove default value

`</issue_description>
>
> ## Comments on the Issue (you are @copilot in this section)
>
>
>

Original prompt

---

This section details on the original issue you should resolve

<issue_title>add "dimensions" support to embedding API call</issue_title>
<issue_description>The codebase currently not support to define as request the size of the dimension for embedding.

class OpenAIEmbeddingRequest(BaseModel): input: str # text to embed model: str # Remove default value </issue_description>

Comments on the Issue (you are @copilot in this section)

• Fixes add "dimensions" support to embedding API call #5

---

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[gszecsenyi]

I send this request:

curl -X POST http://localhost:8000/v1/embeddings \ -H "Authorization: Bearer your-secret-token" \ -H "Content-Type: application/json" \ -d '{"input": "Hello world", "model": "nomic-embed-text", "dimensions":1}'

But I still got 768 dimensions. Can you check @copilot, why?

[Copilot]

I send this request:

`curl -X POST http://localhost:8000/v1/embeddings
...

The nomic-embed-text model always outputs 768-dimensional embeddings - it doesn't support the dimensions parameter. Ollama's API doesn't officially support dynamic dimension sizing for most models.

The implementation correctly passes the parameter through to Ollama, but it has no effect because:

1. nomic-embed-text has a fixed 768-dimension output
2. Ollama's embedding API doesn't honor the dimensions parameter for standard models

Only models with Matryoshka Representation Learning (MRL) capability can support dimension reduction, and even then, Ollama doesn't expose this through the API - you'd need to manually truncate the embeddings after retrieval.

If you need smaller embeddings, consider:

• Using a model with naturally smaller dimensions (e.g., all-minilm with 384 dimensions)
• Post-processing embeddings to truncate them manually
• Using a different embedding service that supports dimension control

The parameter implementation is correct for API compatibility with OpenAI, but it won't affect Ollama's output with current models.

[gszecsenyi]

@copilot based on this doc, ollama supports: https://docs.ollama.com/api/openai-compatibility

[Copilot]

@copilot based on this doc, ollama supports: https://docs.ollama.com/api/openai-compatibility

You're absolutely right! I apologize for the incorrect information. Ollama does support the dimensions parameter as of version v0.11.11 (released in 2024).

The implementation is correct and will work with:

• Ollama v0.11.11 or later
• Models that support dynamic dimensions (e.g., Qwen3 Embedding with MRL support)

However, nomic-embed-text has fixed 768 dimensions and won't change its output based on the dimensions parameter. To test the feature, use a model with MRL (Matryoshka Representation Learning) support like Qwen3 Embedding.

I've updated the documentation in commit 98dfc94 to correctly reflect that Ollama supports this parameter (model-dependent).

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• docs.ollama.com
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