mirror of
				https://github.com/ggml-org/llama.cpp.git
				synced 2025-11-03 09:22:01 +00:00 
			
		
		
		
	
		
			
				
	
	
		
			103 lines
		
	
	
		
			2.7 KiB
		
	
	
	
		
			Gherkin
		
	
	
	
	
	
			
		
		
	
	
			103 lines
		
	
	
		
			2.7 KiB
		
	
	
	
		
			Gherkin
		
	
	
	
	
	
@llama.cpp
 | 
						|
@parallel
 | 
						|
Feature: Parallel
 | 
						|
 | 
						|
  Background: Server startup
 | 
						|
    Given a server listening on localhost:8080
 | 
						|
    And   a model file tinyllamas/split/stories15M-00001-of-00003.gguf from HF repo ggml-org/models
 | 
						|
    And   a model file test-model-00001-of-00003.gguf
 | 
						|
    And   42 as server seed
 | 
						|
    And   128 as batch size
 | 
						|
    And   256 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
 |