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* py : add XLMRobertaForSequenceClassification [no ci] * py : fix scalar-tensor conversion [no ci] * py : fix position embeddings chop [no ci] * llama : read new cls tensors [no ci] * llama : add classigication head (wip) [no ci] * llama : add "rank" pooling type ggml-ci * server : add rerank endpoint ggml-ci * llama : aboud ggml_repeat during classification * rerank : cleanup + comments * server : accept /rerank endpoint in addition to /v1/rerank [no ci] * embedding : parse special tokens * jina : support v1 reranker * vocab : minor style ggml-ci * server : initiate tests for later ggml-ci * server : add docs * llama : add comment [no ci] * llama : fix uninitialized tensors * ci : add rerank tests ggml-ci * add reranking test * change test data * Update examples/server/server.cpp Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com> * add `--reranking` argument * update server docs * llama : fix comment [no ci] ggml-ci --------- Co-authored-by: Xuan Son Nguyen <son@huggingface.co> Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com> |
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.. | ||
features | ||
.gitignore | ||
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 |
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"