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* py : type-check all Python scripts with Pyright * server-tests : use trailing slash in openai base_url * server-tests : add more type annotations * server-tests : strip "chat" from base_url in oai_chat_completions * server-tests : model metadata is a dict * ci : disable pip cache in type-check workflow The cache is not shared between branches, and it's 250MB in size, so it would become quite a big part of the 10GB cache limit of the repo. * py : fix new type errors from master branch * tests : fix test-tokenizer-random.py Apparently, gcc applies optimisations even when pre-processing, which confuses pycparser. * ci : only show warnings and errors in python type-check The "information" level otherwise has entries from 'examples/pydantic_models_to_grammar.py', which could be confusing for someone trying to figure out what failed, considering that these messages can safely be ignored even though they look like errors. |
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.. | ||
features | ||
README.md | ||
requirements.txt | ||
tests.sh |
Server tests
Python based server tests scenario using BDD and behave:
- issues.feature Pending issues scenario
- parallel.feature Scenario involving multi slots and concurrent requests
- security.feature Security, CORS and API Key
- server.feature Server base scenario: completion, embedding, tokenization, etc...
Tests target GitHub workflows job runners with 4 vCPU.
Requests are using aiohttp, asyncio based http client.
Note: If the host architecture inference speed is faster than GitHub runners one, parallel scenario may randomly fail.
To mitigate it, you can increase values in n_predict
, kv_size
.
Install dependencies
pip install -r requirements.txt
Run tests
- Build the server
cd ../../..
cmake -B build -DLLAMA_CURL=ON
cmake --build build --target llama-server
- Start the test:
./tests.sh
It's possible to override some scenario steps values with environment variables:
variable | description |
---|---|
PORT |
context.server_port to set the listening port of the server during scenario, default: 8080 |
LLAMA_SERVER_BIN_PATH |
to change the server binary path, default: ../../../build/bin/llama-server |
DEBUG |
"ON" to enable steps and server verbose mode --verbose |
SERVER_LOG_FORMAT_JSON |
if set switch server logs to json format |
N_GPU_LAYERS |
number of model layers to offload to VRAM -ngl --n-gpu-layers |
Run @bug, @wip or @wrong_usage annotated scenario
Feature or Scenario must be annotated with @llama.cpp
to be included in the default scope.
@bug
annotation aims to link a scenario with a GitHub issue.@wrong_usage
are meant to show user issue that are actually an expected behavior@wip
to focus on a scenario working in progress@slow
heavy test, disabled by default
To run a scenario annotated with @bug
, start:
DEBUG=ON ./tests.sh --no-skipped --tags bug --stop
After changing logic in steps.py
, ensure that @bug
and @wrong_usage
scenario are updated.
./tests.sh --no-skipped --tags bug,wrong_usage || echo "should failed but compile"