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parallel.feature
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@llama.cpp
@parallel
Feature: Parallel
Background: Server startup
Given a server listening on localhost:8080
And a model file tinyllamas/stories260K.gguf from HF repo ggml-org/models
And 42 as server seed
And 512 as batch size
And 64 KV cache size
And 2 slots
And continuous batching
Then the server is starting
Then the server is healthy
Scenario Outline: Multi users completion
Given a prompt:
"""
Write a very long story about AI.
"""
And a prompt:
"""
Write another very long music lyrics.
"""
And <n_predict> max tokens to predict
Given concurrent completion requests
Then the server is busy
Then the server is idle
And all slots are idle
Then all prompts are predicted with <n_predict> tokens
Examples:
| n_predict |
| 128 |
Scenario Outline: Multi users OAI completions compatibility
Given a system prompt You are a writer.
And a model tinyllama-2
Given a prompt:
"""
Write a very long book.
"""
And a prompt:
"""
Write another a poem.
"""
And <n_predict> max tokens to predict
And streaming is <streaming>
Given concurrent OAI completions requests
Then the server is busy
Then the server is idle
Then all prompts are predicted with <n_predict> tokens
Examples:
| streaming | n_predict |
| disabled | 128 |
| enabled | 64 |
Scenario Outline: Multi users OAI completions compatibility no v1
Given a system prompt You are a writer.
And a model tinyllama-2
Given a prompt:
"""
Write a very long book.
"""
And a prompt:
"""
Write another a poem.
"""
And <n_predict> max tokens to predict
And streaming is <streaming>
Given concurrent OAI completions requests no v1
Then the server is busy
Then the server is idle
Then all prompts are predicted with <n_predict> tokens
Examples:
| streaming | n_predict |
| disabled | 128 |
| enabled | 64 |
Scenario: Multi users with total number of tokens to predict exceeds the KV Cache size #3969
Given a prompt:
"""
Write a very long story about AI.
"""
And a prompt:
"""
Write another very long music lyrics.
"""
And a prompt:
"""
Write a very long poem.
"""
And a prompt:
"""
Write a very long joke.
"""
And 128 max tokens to predict
Given concurrent completion requests
Then the server is busy
Then the server is idle
Then all prompts are predicted