mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-25 22:08:46 +01:00
9731134296
* server: tests: add models endpoint scenario * server: /v1/models add some metadata * server: tests: add debug field in context before scenario * server: tests: download model from HF, add batch size * server: tests: add passkey test * server: tests: add group attention params * server: do not truncate prompt tokens if self-extend through group attention is enabled * server: logs: do not truncate log values * server: tests - passkey - first good working value of nga * server: tests: fix server timeout * server: tests: fix passkey, add doc, fix regex content matching, fix timeout * server: tests: fix regex content matching * server: tests: schedule slow tests on master * server: metrics: fix when no prompt processed * server: tests: self-extend add llama-2-7B and Mixtral-8x7B-v0.1 * server: tests: increase timeout for completion * server: tests: keep only the PHI-2 test * server: tests: passkey add a negative test
147 lines
3.6 KiB
Gherkin
147 lines
3.6 KiB
Gherkin
@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 embeddings extraction
|
|
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
|
|
|
|
Scenario: Multi users embeddings
|
|
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.
|
|
"""
|
|
Given concurrent embedding requests
|
|
Then the server is busy
|
|
Then the server is idle
|
|
Then all embeddings are generated
|
|
|
|
Scenario: Multi users OAI compatibility embeddings
|
|
Given a prompt:
|
|
"""
|
|
In which country Paris is located ?
|
|
"""
|
|
And a prompt:
|
|
"""
|
|
Is Madrid the capital of Spain ?
|
|
"""
|
|
And a prompt:
|
|
"""
|
|
What is the biggest US city ?
|
|
"""
|
|
And a prompt:
|
|
"""
|
|
What is the capital of Bulgaria ?
|
|
"""
|
|
And a model tinyllama-2
|
|
Given concurrent OAI embedding requests
|
|
Then the server is busy
|
|
Then the server is idle
|
|
Then all embeddings are generated
|