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https://github.com/ggerganov/llama.cpp.git
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* 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
23 lines
794 B
Gherkin
23 lines
794 B
Gherkin
# run with: ./tests.sh --no-skipped --tags wrong_usage
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@wrong_usage
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Feature: Wrong usage of llama.cpp server
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#3969 The user must always set --n-predict option
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# to cap the number of tokens any completion request can generate
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# or pass n_predict/max_tokens in the request.
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Scenario: Infinite loop
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Given a server listening on localhost:8080
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And a model file tinyllamas/stories260K.gguf from HF repo ggml-org/models
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# Uncomment below to fix the issue
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#And 64 server max tokens to predict
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Then the server is starting
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Given a prompt:
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"""
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Go to: infinite loop
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"""
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# Uncomment below to fix the issue
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#And 128 max tokens to predict
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Given concurrent completion requests
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Then the server is idle
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Then all prompts are predicted
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