* server : refactoring (wip)
* server : remove llava/clip objects from build
* server : fix empty prompt handling + all slots idle logic
* server : normalize id vars
* server : code style
* server : simplify model chat template validation
* server : code style
* server : minor
* llama : llama_chat_apply_template support null buf
* server : do not process embedding requests when disabled
* server : reorganize structs and enums + naming fixes
* server : merge oai.hpp in utils.hpp
* server : refactor system prompt update at start
* server : disable cached prompts with self-extend
* server : do not process more than n_batch tokens per iter
* server: tests: embeddings use a real embeddings model (#5908)
* server, tests : bump batch to fit 1 embedding prompt
* server: tests: embeddings fix build type Debug is randomly failing (#5911)
* server: tests: embeddings, use different KV Cache size
* server: tests: embeddings, fixed prompt do not exceed n_batch, increase embedding timeout, reduce number of concurrent embeddings
* server: tests: embeddings, no need to wait for server idle as it can timout
* server: refactor: clean up http code (#5912)
* server : avoid n_available var
ggml-ci
* server: refactor: better http codes
* server : simplify json parsing + add comment about t_last
* server : rename server structs
* server : allow to override FQDN in tests
ggml-ci
* server : add comments
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Co-authored-by: Pierrick Hymbert <pierrick.hymbert@gmail.com>
* server: tests: add models endpoint scenario
* server: /v1/models add some metadata
* server: tests: add debug field in context before scenario
* server: tests: download model from HF, add batch size
* server: tests: add passkey test
* server: tests: add group attention params
* server: do not truncate prompt tokens if self-extend through group attention is enabled
* server: logs: do not truncate log values
* server: tests - passkey - first good working value of nga
* server: tests: fix server timeout
* server: tests: fix passkey, add doc, fix regex content matching, fix timeout
* server: tests: fix regex content matching
* server: tests: schedule slow tests on master
* server: metrics: fix when no prompt processed
* server: tests: self-extend add llama-2-7B and Mixtral-8x7B-v0.1
* server: tests: increase timeout for completion
* server: tests: keep only the PHI-2 test
* server: tests: passkey add a negative test
* 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
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Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* server: monitoring - add /metrics prometheus compatible endpoint
* server: concurrency issue, when 2 task are waiting for results, only one call thread is notified
* server: metrics - move to a dedicated struct
* 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
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Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
