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Merge branch 'main' into meta-ref-vision-fix-2
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commit
2543b54a6a
2 changed files with 23 additions and 9 deletions
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@ -43,7 +43,7 @@ Configuration for this is available at `distributions/ollama/run.yaml`.
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### 3. Use the Llama Stack client SDK
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You can interact with the Llama Stack server using various client SDKs. We will use the Python SDK which you can install using:
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You can interact with the Llama Stack server using various client SDKs. We will use the Python SDK which you can install using the following command. Note that you must be using Python 3.10 or newer:
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```bash
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pip install llama-stack-client
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```
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@ -62,7 +62,7 @@ llama-stack-client models list
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You can test basic Llama inference completion using the CLI too.
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```bash
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llama-stack-client
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llama-stack-client \
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inference chat-completion \
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--message "hello, what model are you?"
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```
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@ -81,14 +81,28 @@ async def agents_stack(request, inference_model, safety_shield):
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inference_models = (
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inference_model if isinstance(inference_model, list) else [inference_model]
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)
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models = [
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# NOTE: meta-reference provider needs 1 provider per model, lookup provider_id from provider config
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model_to_provider_id = {}
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for provider in providers["inference"]:
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if "model" in provider.config:
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model_to_provider_id[provider.config["model"]] = provider.provider_id
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models = []
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for model in inference_models:
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if model in model_to_provider_id:
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provider_id = model_to_provider_id[model]
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else:
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provider_id = providers["inference"][0].provider_id
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models.append(
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ModelInput(
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model_id=model,
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model_type=ModelType.llm,
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provider_id=providers["inference"][i].provider_id,
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provider_id=provider_id,
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)
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for i, model in enumerate(inference_models)
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]
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)
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models.append(
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ModelInput(
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model_id="all-MiniLM-L6-v2",
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