mirror of
https://github.com/ggerganov/llama.cpp.git
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faf69d4237
* common : do not add null tokens during warmup ggml-ci * llama : check that the input tokens are valid ggml-ci * tests : fix batch size of bert model ggml-ci
100 lines
2.7 KiB
Gherkin
100 lines
2.7 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 bert-bge-small.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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# the bert-bge-small model has context size of 512
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# since the generated prompts are as big as the batch size, we need to set the batch size to 512
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# ref: https://huggingface.co/BAAI/bge-small-en-v1.5/blob/5c38ec7c405ec4b44b94cc5a9bb96e735b38267a/config.json#L20
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And 512 as batch size
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And 512 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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