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525213d2f5
* server: tests: init scenarios - health and slots endpoints - completion endpoint - OAI compatible chat completion requests w/ and without streaming - completion multi users scenario - multi users scenario on OAI compatible endpoint with streaming - multi users with total number of tokens to predict exceeds the KV Cache size - server wrong usage scenario, like in Infinite loop of "context shift" #3969 - slots shifting - continuous batching - embeddings endpoint - multi users embedding endpoint: Segmentation fault #5655 - OpenAI-compatible embeddings API - tokenize endpoint - CORS and api key scenario * server: CI GitHub workflow --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
78 lines
2.0 KiB
Gherkin
78 lines
2.0 KiB
Gherkin
@llama.cpp
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Feature: Parallel
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Background: Server startup
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Given a server listening on localhost:8080
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And a model file stories260K.gguf
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And a model alias tinyllama-2
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And 42 as server seed
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And 64 KV cache size
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And 2 slots
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And continuous batching
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Then the server is starting
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Then the server is healthy
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Scenario Outline: Multi users completion
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Given a prompt:
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"""
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Write a very long story about AI.
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"""
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And a prompt:
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"""
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Write another very long music lyrics.
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"""
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And <n_predict> max tokens to predict
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Given concurrent completion requests
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Then the server is busy
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Then the server is idle
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And all slots are idle
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Then all prompts are predicted with <n_predict> tokens
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Examples:
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| n_predict |
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| 128 |
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Scenario Outline: Multi users OAI completions compatibility
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Given a system prompt You are a writer.
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And a model tinyllama-2
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Given a prompt:
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"""
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Write a very long book.
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"""
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And a prompt:
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"""
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Write another a poem.
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"""
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And <n_predict> max tokens to predict
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And streaming is <streaming>
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Given concurrent OAI completions requests
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Then the server is busy
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Then the server is idle
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Then all prompts are predicted with <n_predict> tokens
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Examples:
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| streaming | n_predict |
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| disabled | 128 |
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| enabled | 64 |
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Scenario: Multi users with total number of tokens to predict exceeds the KV Cache size #3969
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Given a prompt:
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"""
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Write a very long story about AI.
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"""
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And a prompt:
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"""
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Write another very long music lyrics.
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"""
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And a prompt:
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"""
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Write a very long poem.
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"""
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And a prompt:
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"""
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Write a very long joke.
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"""
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And 128 max tokens to predict
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Given concurrent completion requests
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Then the server is busy
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Then the server is idle
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Then all prompts are predicted
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