`ollama-python` does not expose the `name` field returned by `/api/tags`

[Wu2406]

Environment

• ollama: 0.11.4
• ollama-python: 0.5.3
• Python: 3.10
• OS: Windows 10

Background

I downloaded a GGUF file locally and created a model with a custom Modelfile:

FROM ./qwen3-embedding-0.6b-q8_0.gguf

After running:

ollama create Qwen3-Embedding:0.6B -f Modelfile

the CLI confirms the model is correctly registered:

ollama show Qwen3-Embedding:0.6B
  Model
    architecture        qwen3
    parameters          595.78M
    context length      32768
    embedding length    1024
    quantization        Q8_0

  Capabilities
    embedding

The REST endpoint /api/tags returns the expected JSON, including the name field:

{
  "models": [
    {
      "name": "Qwen3-Embedding:0.6B",
      "model": "Qwen3-Embedding:0.6B",
      "modified_at": "2025-08-13T21:02:21.918215+08:00",
      "size": 639150858,
      "digest": "43f15..........0112",
      "details": {
        "parent_model": "",
        "format": "gguf",
        "family": "qwen3",
        "families": ["qwen3"],
        "parameter_size": "595.78M",
        "quantization_level": "Q8_0"
      }
    }
  ]
}

Problem

When I use the official ollama-python client:

from ollama import Client
client = Client(host="http://localhost:11434")
models = client.list()["models"]
print(models)

the returned objects do not contain the name attribute, only:

[Model(
  model='Qwen3-Embedding:0.6B',
  modified_at=datetime.datetime(...),
  digest='43f15..........0112',
  size=639150858,
  details=ModelDetails(...)
)]

This breaks downstream libraries (e.g. mem0) that rely on:

# site-packages\mem0\embeddings\ollama.py
local_models = self.client.list()["models"]
if not any(model.get("model") == self.config.model for model in local_models):
    self.client.pull(self.config.model)

Because model.get("model") is None, the condition always evaluates to True, leading to unnecessary pulls or runtime errors.

Question

Is this discrepancy intentional, or am I missing a configuration step when importing a local GGUF?
Could the ollama-python SDK expose the same name field that the REST API already provides?

Thank you for your time and for maintaining this great project!

[Wu2406]

Follow-up: name field missing from ollama._types.ListResponse.Model in ollama-python

Root-cause investigation

After opening the issue I did a quick local audit and can confirm the mismatch is inside the SDK itself, not in Ollama’s REST layer.

1. The HTTP endpoint /api/tags does return

   {
     "models": [
       { "name": "Qwen3-Embedding:0.6B", ... }
     ]
   }

2. However, the ListResponse type defined in
   site-packages/ollama/_types.py (line 463) only maps the following fields:

   class ListResponse(SubscriptableBaseModel):
     class Model(SubscriptableBaseModel):
       model: Optional[str] = None
       modified_at: Optional[datetime] = None
       digest: Optional[str] = None
       size: Optional[ByteSize] = None
       details: Optional[ModelDetails] = None

3. In _client.py, list() calls

   self._request(ListResponse, 'GET', '/api/tags')

   The JSON is deserialized into the Model sub-class above, so any extra keys (like name) are silently dropped by Pydantic.

Minimal repro

from ollama import Client
client = Client(host="http://localhost:11434")
print(client.list().models[0].dict())
# -> {'model': 'Qwen3-Embedding:0.6B', 'modified_at': ..., 'digest': ..., 'size': ..., 'details': {...}}
# 'name' is missing

Proposed fix

Add a single optional field to ListResponse.Model:

class Model(SubscriptableBaseModel):
  name: Optional[str] = None   # ← keep parity with /api/tags
  model: Optional[str] = None
  modified_at: Optional[datetime] = None
  digest: Optional[str] = None
  size: Optional[ByteSize] = None
  details: Optional[ModelDetails] = None

This is a non-breaking change (defaults to None) and restores 1-to-1 compatibility with the REST API.

Pull request

Based on the findings above, I've implemented this code change and verified its functionality. I've also submitted a pull request. Whenever you have a moment, I would be grateful if you could kindly take a look.

Here is my pull request link: #563