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* server: tests: init scenarios - health and slots endpoints - completion endpoint - OAI compatible chat completion requests w/ and without streaming - completion multi users scenario - multi users scenario on OAI compatible endpoint with streaming - multi users with total number of tokens to predict exceeds the KV Cache size - server wrong usage scenario, like in Infinite loop of "context shift" #3969 - slots shifting - continuous batching - embeddings endpoint - multi users embedding endpoint: Segmentation fault #5655 - OpenAI-compatible embeddings API - tokenize endpoint - CORS and api key scenario * server: CI GitHub workflow --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
47 lines
2.1 KiB
Markdown
47 lines
2.1 KiB
Markdown
# Server tests
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Python based server tests scenario using [BDD](https://en.wikipedia.org/wiki/Behavior-driven_development) 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 using [aiohttp](https://docs.aiohttp.org/en/stable/client_reference.html), [asyncio](https://docs.python.org/fr/3/library/asyncio.html) 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. 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. download required models:
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1. `../../../scripts/hf.sh --repo ggml-org/models --file tinyllamas/stories260K.gguf`
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3. 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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- `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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### 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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To run a scenario annotated with `@bug`, start:
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`DEBUG=ON ./tests.sh --no-skipped --tags bug`
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After changing logic in `steps.py`, ensure that `@bug` and `@wrong_usage` scenario are updated.
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