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	* common: llama_load_model_from_url with libcurl dependency Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
		
			
				
	
	
		
			97 lines
		
	
	
		
			2.4 KiB
		
	
	
	
		
			Gherkin
		
	
	
	
	
	
			
		
		
	
	
			97 lines
		
	
	
		
			2.4 KiB
		
	
	
	
		
			Gherkin
		
	
	
	
	
	
@llama.cpp
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@embeddings
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Feature: llama.cpp server
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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 url https://huggingface.co/ggml-org/models/resolve/main/bert-bge-small/ggml-model-f16.gguf
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    And   a model file ggml-model-f16.gguf
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    And   a model alias bert-bge-small
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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   1024 as ubatch 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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  Scenario: Embedding
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    When embeddings are computed for:
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    """
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    What is the capital of Bulgaria ?
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    """
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    Then embeddings are generated
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  Scenario: OAI Embeddings compatibility
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    Given a model bert-bge-small
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    When an OAI compatible embeddings computation request for:
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    """
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    What is the capital of Spain ?
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    """
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    Then embeddings are generated
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  Scenario: OAI Embeddings compatibility with multiple inputs
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    Given a model bert-bge-small
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    Given a prompt:
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      """
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      In which country Paris is located ?
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      """
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    And a prompt:
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      """
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      Is Madrid the capital of Spain ?
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      """
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    When an OAI compatible embeddings computation request for multiple inputs
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    Then embeddings are generated
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  Scenario: Multi users embeddings
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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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    Given concurrent embedding 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 embeddings are generated
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  Scenario: Multi users OAI compatibility embeddings
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    Given a prompt:
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      """
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      In which country Paris is located ?
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      """
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    And a prompt:
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      """
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      Is Madrid the capital of Spain ?
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      """
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    And a prompt:
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      """
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      What is the biggest US city ?
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      """
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    And a prompt:
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      """
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      What is the capital of Bulgaria ?
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      """
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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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    Then the server is idle
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    Then all embeddings are generated
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  Scenario: All embeddings should be the same
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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 all embeddings are the same
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