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https://github.com/tiennm99/litellm.git
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test: improve flaky test
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@@ -5153,6 +5153,29 @@
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"supports_function_calling": true,
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"supports_tool_choice": true
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},
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"vertex_ai/mistral-small-2503@001": {
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"max_tokens": 8191,
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"max_input_tokens": 32000,
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"max_output_tokens": 8191,
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"input_cost_per_token": 0.000001,
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"output_cost_per_token": 0.000003,
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"litellm_provider": "vertex_ai-mistral_models",
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"supports_function_calling": true,
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"mode": "chat",
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"supports_tool_choice": true
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},
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"vertex_ai/mistral-small-2503": {
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"max_tokens": 128000,
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"max_input_tokens": 128000,
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"max_output_tokens": 128000,
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"input_cost_per_token": 0.000001,
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"output_cost_per_token": 0.000003,
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"litellm_provider": "vertex_ai-mistral_models",
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"mode": "chat",
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"supports_function_calling": true,
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"supports_vision": true,
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"supports_tool_choice": true
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},
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"vertex_ai/jamba-1.5-mini@001": {
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"max_tokens": 256000,
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"max_input_tokens": 256000,
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@@ -1734,6 +1734,7 @@ def test_redis_semantic_cache_completion():
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# test_redis_cache_completion()
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@pytest.mark.flaky(reruns=3)
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@pytest.mark.asyncio
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async def test_redis_semantic_cache_acompletion():
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litellm.set_verbose = True
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@@ -1761,6 +1762,8 @@ async def test_redis_semantic_cache_acompletion():
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)
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print(f"response1: {response1}")
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await asyncio.sleep(2)
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response2 = await litellm.acompletion(
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model="gpt-3.5-turbo",
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messages=[
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