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Author SHA1 Message Date
Wen Zhou
4bca4af3e4
refactor: set proper name for embedding all-minilm:l6-v2 and update to use "starter" in detailed_tutorial (#2627)
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# What does this PR do?
<!-- Provide a short summary of what this PR does and why. Link to
relevant issues if applicable. -->
- we are using `all-minilm:l6-v2` but the model we download from ollama
is `all-minilm:latest`
  latest: https://ollama.com/library/all-minilm:latest 1b226e2802db
  l6-v2: https://ollama.com/library/all-minilm:l6-v2 pin 1b226e2802db
- even currently they are exactly the same model but if
[all-minilm:l12-v2](https://ollama.com/library/all-minilm:l12-v2) is
updated, "latest" might not be the same for l6-v2.
- the only change in this PR is pin the model id in ollama
- also update detailed_tutorial with "starter" to replace deprecated
"ollama".

<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->

## Test Plan
<!-- Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.* -->
```
>INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct"
>llama stack build --run --template ollama --image-type venv
...
Build Successful!
You can find the newly-built template here: /home/wenzhou/zdtsw-forking/lls/llama-stack/llama_stack/templates/ollama/run.yaml
....
 - metadata:                                                                                                                                  
     embedding_dimension: 384                                                                                                                 
   model_id: all-MiniLM-L6-v2                                                                                                                 
   model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType                                                                 
   - embedding                                                                                                                                
   provider_id: ollama                                                                                                                        
   provider_model_id: all-minilm:l6-v2  
   ...
```
test
```
>llama-stack-client inference chat-completion --message "Write me a 2-sentence poem about the moon"
           INFO:httpx:HTTP Request: GET http://localhost:8321/v1/models "HTTP/1.1 200 OK"
INFO:httpx:HTTP Request: POST http://localhost:8321/v1/openai/v1/chat/completions "HTTP/1.1 200 OK"
OpenAIChatCompletion(
    id='chatcmpl-04f99071-3da2-44ba-a19f-03b5b7fc70b7',
    choices=[
        OpenAIChatCompletionChoice(
            finish_reason='stop',
            index=0,
            message=OpenAIChatCompletionChoiceMessageOpenAIAssistantMessageParam(
                role='assistant',
                content="Here is a 2-sentence poem about the moon:\n\nSilver crescent in the midnight sky,\nLuna's gentle face, a beauty to the eye.",
                name=None,
                tool_calls=None,
                refusal=None,
                annotations=None,
                audio=None,
                function_call=None
            ),
            logprobs=None
        )
    ],
    created=1751644429,
    model='llama3.2:3b-instruct-fp16',
    object='chat.completion',
    service_tier=None,
    system_fingerprint='fp_ollama',
    usage={'completion_tokens': 33, 'prompt_tokens': 36, 'total_tokens': 69, 'completion_tokens_details': None, 'prompt_tokens_details': None}
)
```

---------

Signed-off-by: Wen Zhou <wenzhou@redhat.com>
2025-07-06 09:07:37 +05:30
Sébastien Han
0d0b8d2be1
ci: use ollama container image with loaded models (#2410)
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# What does this PR do?

Instead of downloading the models each time we now have a single Ollama
container that is baked with the models pulled and ready to use.

This will remove the CI flakiness on model pulling.

Signed-off-by: Sébastien Han <seb@redhat.com>
2025-06-06 12:08:20 +02:00