@llama.cpp Feature: llama.cpp server Background: Server startup Given a server listening on localhost:8080 And a model file stories260K.gguf And a model alias tinyllama-2 And 42 as server seed # KV Cache corresponds to the total amount of tokens # that can be stored across all independent sequences: #4130 # see --ctx-size and #5568 And 32 KV cache size And 1 slots And embeddings extraction And 32 server max tokens to predict And prometheus compatible metrics exposed Then the server is starting Then the server is healthy Scenario: Health Then the server is ready And all slots are idle Scenario Outline: Completion Given a prompt And max tokens to predict And a completion request with no api error Then tokens are predicted matching And prometheus metrics are exposed Examples: Prompts | prompt | n_predict | re_content | n_predicted | | I believe the meaning of life is | 8 | (readgoing)+ | 8 | | Write a joke about AI | 64 | (parkfriendsscaredalways)+ | 32 | Scenario Outline: OAI Compatibility Given a model And a system prompt And a user prompt And max tokens to predict And streaming is Given an OAI compatible chat completions request with no api error Then tokens are predicted matching Examples: Prompts | model | system_prompt | user_prompt | max_tokens | re_content | n_predicted | enable_streaming | | llama-2 | Book | What is the best book | 8 | (Momwhat)+ | 8 | disabled | | codellama70b | You are a coding assistant. | Write the fibonacci function in c++. | 64 | (thankshappybird)+ | 32 | enabled | Scenario: Embedding When embeddings are computed for: """ What is the capital of Bulgaria ? """ Then embeddings are generated Scenario: OAI Embeddings compatibility Given a model tinyllama-2 When an OAI compatible embeddings computation request for: """ What is the capital of Spain ? """ Then embeddings are generated Scenario: OAI Embeddings compatibility with multiple inputs Given a model tinyllama-2 Given a prompt: """ In which country Paris is located ? """ And a prompt: """ Is Madrid the capital of Spain ? """ When an OAI compatible embeddings computation request for multiple inputs Then embeddings are generated Scenario: Tokenize / Detokenize When tokenizing: """ What is the capital of France ? """ Then tokens can be detokenize