GitLab

* Fix embeddings memory corruption

The patch was leading to a buffer overrun corruption.  Once removed though, parallism
in server.cpp lead to hitting an assert due to slot/seq IDs being >= token count.  To
work around this, only use slot 0 for embeddings.

* Fix embed integration test assumption

The token eval count has changed with recent llama.cpp bumps (0.3.5+)

For simplicity, perform parallelization of embedding requests in the API handler instead of offloading this to the subprocess runner. This keeps the scheduling story simpler as it builds on existing parallel requests, similar to existing text completion functionality.

* add prompt tokens to embed response

* rm slog

* metrics

* types

* prompt n

* clean up

* reset submodule

* update tests

* test name

* list metrics

Make sure if something goes wrong spawning the process, the user gets
enough info to be able to try to self correct, or at least file a bug
with details so we can fix it.  Once the process starts, we immediately
change back to the recommended setting to prevent the blocking dialog.
This ensures if the model fails to load (OOM, unsupported model type,
etc.) the process will exit quickly and we can scan the stdout/stderr
of the subprocess for the reason to report via API.

* Initial Batch Embedding

* Revert "Initial Batch Embedding"

This reverts commit c22d54895a280b54c727279d85a5fc94defb5a29.

* Initial Draft

* mock up notes

* api/embed draft

* add server function

* check normalization

* clean up

* normalization

* playing around with truncate stuff

* Truncation

* Truncation

* move normalization to go

* Integration Test Template

* Truncation Integration Tests

* Clean up

* use float32

* move normalize

* move normalize test

* refactoring

* integration float32

* input handling and handler testing

* Refactoring of legacy and new

* clear comments

* merge conflicts

* touches

* embedding type 64

* merge conflicts

* fix hanging on single string

* refactoring

* test values

* set context length

* clean up

* testing clean up

* testing clean up

* remove function closure

* Revert "remove function closure"

This reverts commit 55d48c6ed17abe42e7a122e69d603ef0c1506787.

* remove function closure

* remove redundant error check

* clean up

* more clean up

* clean up

* Use common prefix to select slot

* actually report `longest`

* openai compatibility

* Revert "openai compatibility"

This reverts commit d3f98a811e00fc497d889c8c45b0cfec5b64690c.

* remove erroneous subtraction of prompt cache

* Do not shift context for sliding window models

* truncate prompt > 2/3 tokens

* only target gemma2

* fix embedding by adding fixes from llama.cpp upstream

* remove assert

---------
Co-authored-by: Jesper Ek <deadbeef84@gmail.com>

* Revert "use `int32_t` for call to tokenize (#4738)"

This reverts commit 763bb65d.

* Revert "vocab only"

This reverts commit bf54c845.

* Revert "use ffi for tokenizing/detokenizing"

This reverts commit 26a00a04.

This doesn't expose a UX yet, but wires the initial server portion
of progress reporting during load

* feat: enable flash attention if supported

* feat: enable flash attention if supported

* feat: enable flash attention if supported

* feat: add flash_attn support

* Bump llama.cpp to b2761

* Adjust types for bump

* parse wide argv characters on windows

* cleanup

* move cleanup to end of `main`

This should resolve a number of memory leak and stability defects by allowing
us to isolate llama.cpp in a separate process and shutdown when idle, and
gracefully restart if it has problems.  This also serves as a first step to be
able to run multiple copies to support multiple models concurrently.

The release just before ggml-cuda.cu refactoring