Leebr Data ConsultingandIgor Okulist
033df86b69
* server : preserve context checkpoints across slot save/restore Append the checkpoints after the packed server_tokens payload added in #26640 and count them in n_written / n_read, so a restored slot can still roll back to a checkpoint instead of re-processing the whole prompt. * server : drop draft checkpoint data that does not match the draft context Restoring a slot saved with a different draft KV cache type aborted in load_dft(). Test-load one draft checkpoint on restore and drop the draft data if it does not fit, instead of crashing. Adds a regression test. Co-authored-by: Igor Okulist <okigan@gmail.com> * server : harden the checkpoint appendix of slot save files Bound each blob size by the bytes left in the file before allocating, open the file with UTF-8 paths on Windows like the llama state payload, fall back to full prompt re-processing when a checkpoint restored from a slot file fails to load, and replace the 1024 count cap by keeping the last n_ctx_checkpoints while reading. * server : report an incomplete checkpoint appendix as a failed slot save Return an error to the client when the appendix cannot be written, like a failed payload write, and make the oversized-blob test declare a size that cannot be allocated, so an unbounded allocation fails the test. * server : reject an empty target state in the checkpoint appendix A saved checkpoint always holds a target state, an empty blob would roll back without restoring anything. Also log with the slot id, and load the draft test model from the HF cache instead of a second download. * common : return bool from checkpoint load_tgt / load_dft A checkpoint restored from a slot file falls back to full prompt re-processing when it fails to load, a checkpoint created in memory still aborts. --------- Co-authored-by: Igor Okulist <okigan@gmail.com>
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
- Build the server
cd ../../..
cmake -B build
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 |
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 development:
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.