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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
68 lines
2.8 KiB
Markdown
68 lines
2.8 KiB
Markdown
# Server tests
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Python based server tests scenario using [BDD](https://en.wikipedia.org/wiki/Behavior-driven_development)
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and [behave](https://behave.readthedocs.io/en/latest/):
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* [issues.feature](./features/issues.feature) Pending issues scenario
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* [parallel.feature](./features/parallel.feature) Scenario involving multi slots and concurrent requests
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* [security.feature](./features/security.feature) Security, CORS and API Key
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* [server.feature](./features/server.feature) Server base scenario: completion, embedding, tokenization, etc...
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Tests target GitHub workflows job runners with 4 vCPU.
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Requests are
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using [aiohttp](https://docs.aiohttp.org/en/stable/client_reference.html), [asyncio](https://docs.python.org/fr/3/library/asyncio.html)
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based http client.
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Note: If the host architecture inference speed is faster than GitHub runners one, parallel scenario may randomly fail.
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To mitigate it, you can increase values in `n_predict`, `kv_size`.
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### Install dependencies
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`pip install -r requirements.txt`
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### Run tests
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1. Build the server
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```shell
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cd ../../..
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mkdir build
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cd build
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cmake ../
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cmake --build . --target server
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```
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2. Start the test: `./tests.sh`
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It's possible to override some scenario steps values with environment variables:
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| variable | description |
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|--------------------------|------------------------------------------------------------------------------------------------|
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| `PORT` | `context.server_port` to set the listening port of the server during scenario, default: `8080` |
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| `LLAMA_SERVER_BIN_PATH` | to change the server binary path, default: `../../../build/bin/server` |
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| `DEBUG` | "ON" to enable steps and server verbose mode `--verbose` |
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| `SERVER_LOG_FORMAT_JSON` | if set switch server logs to json format |
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| `N_GPU_LAYERS` | number of model layers to offload to VRAM `-ngl --n-gpu-layers` |
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### Run @bug, @wip or @wrong_usage annotated scenario
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Feature or Scenario must be annotated with `@llama.cpp` to be included in the default scope.
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- `@bug` annotation aims to link a scenario with a GitHub issue.
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- `@wrong_usage` are meant to show user issue that are actually an expected behavior
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- `@wip` to focus on a scenario working in progress
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- `@slow` heavy test, disabled by default
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To run a scenario annotated with `@bug`, start:
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```shell
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DEBUG=ON ./tests.sh --no-skipped --tags bug
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```
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After changing logic in `steps.py`, ensure that `@bug` and `@wrong_usage` scenario are updated.
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```shell
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./tests.sh --no-skipped --tags bug,wrong_usage || echo "should failed but compile"
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```
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