server: tests: embeddings, fixed prompt do not exceed n_batch, increase embedding timeout, reduce number of concurrent embeddings
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2 changed files with 6 additions and 5 deletions
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@ -9,7 +9,7 @@ Feature: llama.cpp server
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And 42 as server seed
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And 2 slots
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And 1024 as batch size
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And 4096 KV cache size
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And 2048 KV cache size
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And embeddings extraction
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Then the server is starting
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Then the server is healthy
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@ -87,9 +87,8 @@ Feature: llama.cpp server
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Then the server is idle
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Then all embeddings are generated
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@wip
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Scenario: All embeddings should be the same
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Given 20 fixed prompts
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Given 10 fixed prompts
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And a model bert-bge-small
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Given concurrent OAI embedding requests
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Then the server is busy
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@ -292,9 +292,10 @@ def step_impl(context, n_ga_w):
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def step_prompt_passkey(context):
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context.prompt_passkey = context.text
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@step(u'{n_prompts:d} fixed prompts')
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def step_fixed_prompts(context, n_prompts):
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context.prompts.extend([str(0)*1024 for i in range(n_prompts)])
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context.prompts.extend([str(0)*(context.n_batch if context.n_batch is not None else 512) for i in range(n_prompts)])
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context.n_prompts = n_prompts
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@ -818,7 +819,8 @@ async def request_oai_embeddings(input,
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"input": input,
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"model": model,
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},
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headers=headers) as response:
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headers=headers,
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timeout=3600) as response:
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assert response.status == 200, f"received status code not expected: {response.status}"
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assert response.headers['Access-Control-Allow-Origin'] == origin
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assert response.headers['Content-Type'] == "application/json; charset=utf-8"
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