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* Enable Support for Meta LLama-2 Models in Amazon Sagemaker * Improve unit test for invocation layers positioning * Small adjustment, add more unit tests * mypy fixes * Improve unit tests * Update test/prompt/invocation_layer/test_sagemaker_meta.py Co-authored-by: Stefano Fiorucci <44616784+anakin87@users.noreply.github.com> * PR feedback * Add pydocs for newly extracted methods * simplify is_proper_chat_* --------- Co-authored-by: Stefano Fiorucci <44616784+anakin87@users.noreply.github.com> Co-authored-by: anakin87 <stefanofiorucci@gmail.com>
20 lines
880 B
Python
20 lines
880 B
Python
import pytest
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from haystack.nodes.prompt.prompt_model import PromptModelInvocationLayer
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from haystack.nodes.prompt.invocation_layer import HFLocalInvocationLayer, HFInferenceEndpointInvocationLayer
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@pytest.mark.unit
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def test_invocation_layer_order():
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"""
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Checks that the huggingface invocation layer is positioned further down the list of providers
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as they can time out or be slow to respond.
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"""
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invocation_layers = PromptModelInvocationLayer.invocation_layer_providers
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assert HFLocalInvocationLayer in invocation_layers
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assert HFInferenceEndpointInvocationLayer in invocation_layers
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index_hf = invocation_layers.index(HFLocalInvocationLayer) + 1
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index_hf_inference = invocation_layers.index(HFInferenceEndpointInvocationLayer) + 1
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assert index_hf > len(invocation_layers) / 2
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assert index_hf_inference > len(invocation_layers) / 2
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