Files
llama.cpp/tools/server/tests
Yann Follet 31d0ff1869 server / ranking : add sorting and management of top_n (#16403)
* server / ranking : add sorting and management of top_n

* Make the retro compatible if no top_n will return
all results

here is a script to make some test

```script

URL=${1:-http://127.0.0.1:8181}

curl "$URL/v1/rerank" -H "Content-Type: application/json" \
 -d '{ "model": "M", "query": "What is the recipe to make bread ?",
 "return_text" : true,
 "texts" : true,
 "top_n": 6,
 "documents": [
 "voici la recette pour faire du pain, il faut de la farine de l eau et du levain et du sel",
 "it is a bear",
 "bread recipe : floor, water, yest, salt",
 "The giant panda (Ailuropoda melanoleuca), sometimes called a panda bear or simply panda, is a bear species endemic to China.",
 "here is the ingedients to bake bread : 500g floor, 350g water, 120g fresh refresh yest, 15g salt",
 "recipe to make cookies : floor, eggs, water, chocolat",
 "here is the recipe to make bread : 500g floor, 350g water, 120g fresh refresh yest, 15g salt",
 "il fait tres beau aujourd hui",
 "je n ai pas faim, je ne veux pas manger",
 "je suis a paris"
 ] }' | jq
```

* use resize() instead for(...)

* simplify top_n init since no need to return error

result to test :

./tests.sh unit/test_rerank.py -v -x
==================================================== test session starts =====================================================
platform linux -- Python 3.12.3, pytest-8.3.5, pluggy-1.6.0 -- /home/yann/dev/yann/llama.cpp/tools/server/tests/test/bin/python3
cachedir: .pytest_cache
rootdir: /home/yann/dev/yann/llama.cpp/tools/server/tests
configfile: pytest.ini
plugins: anyio-4.11.0
collected 8 items

unit/test_rerank.py::test_rerank PASSED                                                                                [ 12%]
unit/test_rerank.py::test_rerank_tei_format PASSED                                                                     [ 25%]
unit/test_rerank.py::test_invalid_rerank_req[documents0] PASSED                                                        [ 37%]
unit/test_rerank.py::test_invalid_rerank_req[None] PASSED                                                              [ 50%]
unit/test_rerank.py::test_invalid_rerank_req[123] PASSED                                                               [ 62%]
unit/test_rerank.py::test_invalid_rerank_req[documents3] PASSED                                                        [ 75%]
unit/test_rerank.py::test_rerank_usage[Machine learning is-A machine-Learning is-19] PASSED                            [ 87%]
unit/test_rerank.py::test_rerank_usage[Which city?-Machine learning is -Paris, capitale de la-26] PASSED               [100%]

===================================================== 8 passed in 4.31s ======================================================

* add rerank top_n unit test

here is the result :

./tests.sh unit/test_rerank.py -v -x
=================================================================== test session starts ===================================================================
platform linux -- Python 3.12.3, pytest-8.3.5, pluggy-1.6.0 -- /home/yann/dev/yann/llama.cpp/tools/server/tests/test/bin/python3
cachedir: .pytest_cache
rootdir: /home/yann/dev/yann/llama.cpp/tools/server/tests
configfile: pytest.ini
plugins: anyio-4.11.0
collected 16 items

unit/test_rerank.py::test_rerank PASSED                                                                                                             [  6%]
unit/test_rerank.py::test_rerank_tei_format PASSED                                                                                                  [ 12%]
unit/test_rerank.py::test_invalid_rerank_req[documents0] PASSED                                                                                     [ 18%]
unit/test_rerank.py::test_invalid_rerank_req[None] PASSED                                                                                           [ 25%]
unit/test_rerank.py::test_invalid_rerank_req[123] PASSED                                                                                            [ 31%]
unit/test_rerank.py::test_invalid_rerank_req[documents3] PASSED                                                                                     [ 37%]
unit/test_rerank.py::test_rerank_usage[Machine learning is-A machine-Learning is-19] PASSED                                                         [ 43%]
unit/test_rerank.py::test_rerank_usage[Which city?-Machine learning is -Paris, capitale de la-26] PASSED                                            [ 50%]
unit/test_rerank.py::test_rerank_top_n[None-4] PASSED                                                                                               [ 56%]
unit/test_rerank.py::test_rerank_top_n[2-2] PASSED                                                                                                  [ 62%]
unit/test_rerank.py::test_rerank_top_n[4-4] PASSED                                                                                                  [ 68%]
unit/test_rerank.py::test_rerank_top_n[99-4] PASSED                                                                                                 [ 75%]
unit/test_rerank.py::test_rerank_tei_top_n[None-4] PASSED                                                                                           [ 81%]
unit/test_rerank.py::test_rerank_tei_top_n[2-2] PASSED                                                                                              [ 87%]
unit/test_rerank.py::test_rerank_tei_top_n[4-4] PASSED                                                                                              [ 93%]
unit/test_rerank.py::test_rerank_tei_top_n[99-4] PASSED                                                                                             [100%]

=================================================================== 16 passed in 8.84s ===================================================================

* editor config check fix
2025-10-11 16:39:04 +03:00
..

Server tests

Python based server tests scenario using pytest.

Tests target GitHub workflows job runners with 4 vCPU.

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

  1. Build the server
cd ../../..
cmake -B build
cmake --build build --target llama-server
  1. 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 to enable steps and server verbose mode --verbose
N_GPU_LAYERS number of model layers to offload to VRAM -ngl --n-gpu-layers
LLAMA_CACHE by default server tests re-download models to the tmp subfolder. Set this to your cache (e.g. $HOME/Library/Caches/llama.cpp on Mac or $HOME/.cache/llama.cpp on Unix) to avoid this

To run slow tests (will download many models, make sure to set LLAMA_CACHE if needed):

SLOW_TESTS=1 ./tests.sh

To run with stdout/stderr display in real time (verbose output, but useful for debugging):

DEBUG=1 ./tests.sh -s -v -x

To run all the tests in a file:

./tests.sh unit/test_chat_completion.py -v -x

To run a single test:

./tests.sh unit/test_chat_completion.py::test_invalid_chat_completion_req

Hint: You can compile and run test in single command, useful for local developement:

cmake --build build -j --target llama-server && ./tools/server/tests/tests.sh

To see all available arguments, please refer to pytest documentation

Debugging external llama-server

It can sometimes be useful to run the server in a debugger when invesigating test failures. To do this, the environment variable DEBUG_EXTERNAL=1 can be set which will cause the test to skip starting a llama-server itself. Instead, the server can be started in a debugger.

Example using gdb:

$ gdb --args ../../../build/bin/llama-server \
    --host 127.0.0.1 --port 8080 \
    --temp 0.8 --seed 42 \
    --hf-repo ggml-org/models --hf-file tinyllamas/stories260K.gguf \
    --batch-size 32 --no-slots --alias tinyllama-2 --ctx-size 512 \
    --parallel 2 --n-predict 64

And a break point can be set in before running:

(gdb) br server.cpp:4604
(gdb) r
main: server is listening on http://127.0.0.1:8080 - starting the main loop
srv  update_slots: all slots are idle

And then the test in question can be run in another terminal:

(venv) $ env DEBUG_EXTERNAL=1 ./tests.sh unit/test_chat_completion.py -v -x

And this should trigger the breakpoint and allow inspection of the server state in the debugger terminal.