History

Pierrick Hymbert 930b178026 server: logs - unified format and --log-format option (#5700 ) * server: logs - always use JSON logger, add add thread_id in message, log task_id and slot_id * server : skip GH copilot requests from logging * server : change message format of server_log() * server : no need to repeat log in comment * server : log style consistency * server : fix compile warning * server : fix tests regex patterns on M2 Ultra * server: logs: PR feedback on log level * server: logs: allow to choose log format in json or plain text * server: tests: output server logs in text * server: logs switch init logs to server logs macro * server: logs ensure value json value does not raised error * server: logs reduce level VERBOSE to VERB to max 4 chars * server: logs lower case as other log messages * server: logs avoid static in general Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * server: logs PR feedback: change text log format to: LEVEL [function_name] message \| additional=data --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>		2024-02-25 13:50:32 +01:00
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features	server: logs - unified format and --log-format option (#5700 )	2024-02-25 13:50:32 +01:00
README.md	server: logs - unified format and --log-format option (#5700 )	2024-02-25 13:50:32 +01:00
requirements.txt	server: concurrency fix + monitoring - add /metrics prometheus compatible endpoint (#5708 )	2024-02-25 13:49:43 +01:00
tests.sh	server: init functional tests (#5566 )	2024-02-24 12:28:55 +01:00

README.md

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 ../../..
mkdir build
cd build
cmake ../
cmake --build . --target server

download required models:
1. ../../../scripts/hf.sh --repo ggml-org/models --file tinyllamas/stories260K.gguf
Start the test: ./tests.sh

It's possible to override some scenario steps values with environment variables:

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/server
DEBUG -> "ON" to enable steps and server verbose mode --verbose
SERVER_LOG_FORMAT_JSON -> if set switch server logs to json format

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

To run a scenario annotated with @bug, start: DEBUG=ON ./tests.sh --no-skipped --tags bug

After changing logic in steps.py, ensure that @bug and @wrong_usage scenario are updated.