Commit Graph

182 Commits

Author SHA1 Message Date
Georgi Gerganov
31f2d03f1b
server : enable continuous batching by default 2024-03-22 11:16:43 +02:00
Olivier Chafik
5b7b0ac8df
json-schema-to-grammar improvements (+ added to server) (#5978)
* json: fix arrays (disallow `[,1]`)

* json: support tuple types (`[number, string]`)

* json: support additionalProperties (`{[k: string]: [string,number][]}`)

* json: support required / optional properties

* json: add support for pattern

* json: resolve $ref (and support https schema urls)

* json: fix $ref resolution

* join: support union types (mostly for nullable types I think)

* json: support allOf + nested anyOf

* json: support any (`{}` or `{type: object}`)

* json: fix merge

* json: temp fix for escapes

* json: spaces in output and unrestricted output spaces

* json: add typings

* json:fix typo

* Create ts-type-to-grammar.sh

* json: fix _format_literal (json.dumps already escapes quotes)

* json: merge lit sequences and handle negatives

{"type": "string", "pattern": "^({\"question\": \"[^\"]+\", \"response\": \"[^\"]+\"}\\n)+$"}

* json: handle pattern repetitions

* Update json-schema-to-grammar.mjs

* Create regex-to-grammar.py

* json: extract repeated regexp patterns to subrule

* Update json-schema-to-grammar.py

* Update json-schema-to-grammar.py

* Update json-schema-to-grammar.py

* json: handle schema from pydantic Optional fields

* Update json-schema-to-grammar.py

* Update json-schema-to-grammar.py

* Update ts-type-to-grammar.sh

* Update ts-type-to-grammar.sh

* json: simplify nullable fields handling

* json: accept duplicate identical rules

* json: revert space to 1 at most

* json: reuse regexp pattern subrules

* json: handle uuid string format

* json: fix literal escapes

* json: add --allow-fetch

* json: simplify range escapes

* json: support negative ranges in patterns

* Delete commit.txt

* json: custom regex parser, adds dot support & JS-portable

* json: rm trailing spaces

* Update json-schema-to-grammar.mjs

* json: updated server & chat `( cd examples/server && ./deps.sh )`

* json: port fixes from mjs to python

* Update ts-type-to-grammar.sh

* json: support prefixItems alongside array items

* json: add date format + fix uuid

* json: add date, time, date-time formats

* json: preserve order of props from TS defs

* json: port schema converter to C++, wire in ./server

* json: nits

* Update json-schema-to-grammar.cpp

* Update json-schema-to-grammar.cpp

* Update json-schema-to-grammar.cpp

* json: fix mjs implementation + align outputs

* Update json-schema-to-grammar.mjs.hpp

* json: test C++, JS & Python versions

* json: nits + regen deps

* json: cleanup test

* json: revert from c++17 to 11

* json: nit fixes

* json: dirty include for test

* json: fix zig build

* json: pass static command to std::system in tests (fixed temp files)

* json: fix top-level $refs

* json: don't use c++20 designated initializers

* nit

* json: basic support for reserved names `{number:{number:{root:number}}}`

* Revamp test cmake to allow args (WORKING_DIRECTORY needed for JSON test)

* json: re-ran server deps.sh

* json: simplify test

* json: support mix of additional props & required/optional

* json: add tests for some expected failures

* json: fix type=const in c++, add failure expectations for non-str const&enum

* json: test (& simplify output of) empty schema

* json: check parsing in test + fix value & string refs

* json: add server tests for OAI JSON response_format

* json: test/fix top-level anyOf

* json: improve grammar parsing failures

* json: test/fix additional props corner cases

* json: fix string patterns (was missing quotes)

* json: ws nit

* json: fix json handling in server when there's no response_format

* json: catch schema conversion errors in server

* json: don't complain about unknown format type in server if unset

* json: cleaner build of test

* json: create examples/json-schema-pydantic-example.py

* json: fix date pattern

* json: move json.hpp & json-schema-to-grammar.{cpp,h} to common

* json: indent 4 spaces

* json: fix naming of top-level c++ function (+ drop unused one)

* json: avoid using namespace std

* json: fix zig build

* Update server.feature

* json: iostream -> fprintf

* json: space before & refs for consistency

* json: nits
2024-03-21 11:50:43 +00:00
Pierrick Hymbert
d01b3c4c32
common: llama_load_model_from_url using --model-url (#6098)
* common: llama_load_model_from_url with libcurl dependency

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-17 19:12:37 +01:00
slaren
f30ea47a87
llama : add pipeline parallelism support (#6017)
* llama : add pipeline parallelism support for batch processing with multiple CUDA GPUs

ggml-ci

* server : add -ub, --ubatch-size parameter

* fix server embedding test

* llama : fix Mamba inference for pipeline parallelism

Tested to work correctly with both `main` and `parallel` examples.

* llama : limit max batch size to n_batch

* add LLAMA_SCHED_MAX_COPIES to configure the number of input copies for pipeline parallelism
default increase to 4 (from 2)

changing this value may improve performance for some systems, but increases memory usage

* fix hip build

* fix sycl build (disable cpy_tensor_async)

* fix hip build

* llama : limit n_batch and n_ubatch to n_ctx during context creation

* llama : fix norm backend

* batched-bench : sync after decode

* swiftui : sync after decode

* ggml : allow ggml_get_rows to use multiple threads if they are available

* check n_ubatch >= n_tokens with non-casual attention

* llama : do not limit n_batch to n_ctx with non-casual attn

* server : construct batch with size of llama_n_batch

* ggml_backend_cpu_graph_compute : fix return value when alloc fails

* llama : better n_batch and n_ubatch comment

* fix merge

* small fix

* reduce default n_batch to 2048

---------

Co-authored-by: Francis Couture-Harpin <git@compilade.net>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-13 18:54:21 +01:00
Xuan Son Nguyen
99b71c068f
Server: Use multi-task for embeddings endpoint (#6001)
* use multitask for embd endpoint

* specify types

* remove redundant {"n_predict", 0}
2024-03-13 11:39:11 +01:00
Xuan Son Nguyen
caa106d4e0
Server: format error to json (#5961)
* server: format error to json

* server: do not crash on grammar error

* fix api key test case

* revert limit max n_predict

* small fix

* correct coding style

* update completion.js

* launch_slot_with_task

* update docs

* update_slots

* update webui

* update readme
2024-03-11 10:56:41 +01:00
Minsoo Cheong
332bdfd798
server : maintain chat completion id for streaming responses (#5988)
* server: maintain chat completion id for streaming responses

* Update examples/server/utils.hpp

* Update examples/server/utils.hpp

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-11 10:09:32 +02:00
Pierrick Hymbert
621e86b331
server: benchmark: chat/completions scenario and other llm servers comparison (#5941)
* server: bench: Init a bench scenario with K6
See #5827

* server: bench: EOL EOF

* server: bench: PR feedback and improved k6 script configuration

* server: bench: remove llamacpp_completions_tokens_seconds as it include prompt processing time and it's misleading

server: bench: add max_tokens from SERVER_BENCH_MAX_TOKENS

server: bench: increase truncated rate to 80% before failing

* server: bench: fix doc

* server: bench: change gauge custom metrics to trend

* server: bench: change gauge custom metrics to trend
server: bench: add trend custom metrics for total tokens per second average

* server: bench: doc add an option to debug http request

* server: bench: filter dataset too short and too long sequences

* server: bench: allow to filter out conversation in the dataset based on env variable

* server: bench: fix assistant message sent instead of user message

* server: bench: fix assistant message sent instead of user message

* server : add defrag thold parameter

* server: bench: select prompts based on the current iteration id not randomly to make the bench more reproducible

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-09 23:41:49 +01:00
Georgi Gerganov
77d1ac7e00
server : print chat template info 2024-03-09 22:04:00 +02:00
Georgi Gerganov
58308a0ecc
server : fix metrics init (#5964) 2024-03-09 17:34:15 +02:00
SeungWon Jeong
fb215c3832
server : normalize embeddings (#5956)
* output normalize embedding in '/v1/embeddings'

* common : reuse llama_embd_normalize

* common : better normalize impl

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-09 14:27:58 +02:00
Alexey Parfenov
0db32beaf0
server : fix passing prompt as tokens (#5955)
* server: fix passing prompt as tokens

* Update examples/server/server.cpp

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-09 13:16:53 +02:00
Georgi Gerganov
9674aaf35c
server : simplify logic for empty prompts (#5953) 2024-03-09 12:34:18 +02:00
Xuan Son Nguyen
950ba1ab84
Server: reorganize some http logic (#5939)
* refactor static file handler

* use set_pre_routing_handler for validate_api_key

* merge embedding handlers

* correct http verb for endpoints

* fix embedding response

* fix test case CORS Options

* fix code style
2024-03-09 11:27:53 +01:00
Gabe Goodhart
e1fa9569ba
server : add SSL support (#5926)
* add cmake build toggle to enable ssl support in server

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* add flags for ssl key/cert files and use SSLServer if set

All SSL setup is hidden behind CPPHTTPLIB_OPENSSL_SUPPORT in the same
way that the base httlib hides the SSL support

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* Update readme for SSL support in server

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* Add LLAMA_SERVER_SSL variable setup to top-level Makefile

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

---------

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
2024-03-09 11:57:09 +02:00
Pierrick Hymbert
fd72d2d2a5
server: tests: add truncated prompt tests, better kv cache size (#5933)
* server: tests: add truncated prompt tests, better size

* server, tests : update regex

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-09 11:30:04 +02:00
compilade
c2101a2e90
llama : support Mamba Selective State Space Models (#5328)
* mamba : begin working on support for Mamba SSM

* mamba : begin figuring out how to (ab)use the kv cache for Mamba

* mamba : recurrent inference almost works, but incoherent

* mamba : recurrent inference WORKS!!!

* convert : optionally use d_conv and d_state from config.json for Mamba

* mamba : refactor recurrent conv, resulting in 20% perf increase

It's still slower than I'd like, but I did not really optimize `ggml_exp` yet.

I also refactored `ggml_exp` to work with tensors with more than 2 dimensions.

* ggml : parallelize ggml_exp

This results in 8% faster token generation for Mamba-130M.

* mamba : simplify the conv step with a self-overlapping view

Turns out the conv_state can be made smaller by one column.
Note that this breaks existing GGUFs of Mamba,
because the key_value_length field is tied to the conv_state size.

Convolution with a self-overlapping view is cool!
And it's much simpler than what I initially thought would be necessary
to make the convolution step work with more than 1 token at a time.

Next step is to make the SSM step work on batches of tokens too,
and thus I need to figure out a way to make a parallel selective scan
which will keep the ssm_state small and won't make it bigger
by a factor of (n_layer * batch_size).

* llama : fix Mamba KV self size wrongly displaying as f16 instead of f32

Relatedly, I also tried to see if other types than f32 worked for the states,
but they don't, because of the operators used.
It's probably better anyway to keep lots of precision there,
since the states are small anyway.

* mamba : fix self-overlapping view depth stride

* mamba : handle batches of more than 1 token

This means running Mamba no longer crashes when using the default settings!
And probably also slightly faster prompt processing.
Both batched and non-batched processing yield the same output.

Previously, the state was not cleared when starting a sequence.
Next step is to make the KV cache API work as expected for Mamba models.

* ggml: add ggml_ssm_scan to help with parallel selective scan

If the selective scan was implemented without a custom operator,
there would be waaay too many nodes in the graph. For example,
for Mamba-130M, with a batch size of 512 (the default),
a naive selective scan could add at least 24*512=12288 nodes,
which is more than LLAMA_MAX_NODES (8192),
and that's only for the smallest Mamba model.
So it's much cleaner with a custom operator.
Not sure about the name, though.

* ggml : in ggml_ssm_scan, merge multiple rows in the same vec operation

This will help with performance on CPU if ggml_vec_mul_f32
and ggml_vec_add_f32 are ever optimized with SIMD.

* mamba : very basic quantization support

Mostly works, but there is currently no difference
between the variants of a k-quant (e.g. Q4_K_S and Q4_K_M are the same).
Most of the SSM-specific weights can be kept in f32 without affecting
the size that much, since they are relatively small.
(the linear projection weights are responsible for most of Mamba's size)

Too much quantization seems to make the state degrade quite fast, and
the model begins to output gibberish.
It seems to affect bigger models to a lesser extent than small models,
but I'm not sure by how much.

Experimentation will be needed to figure out which weights are more important
for the _M (and _L?) variants of k-quants for Mamba.

* convert : fix wrong name for layer norm weight of offical Mamba models

I was using Q-bert/Mamba-* models before, which have a slighlty different
naming scheme for the weights.
(they start with "model.layers" instead of "backbone.layers")

* mamba : fuse more steps of the SSM scan in the ggml_ssm_scan operator

This increases performance on CPU by around 30% for prompt processing,
and by around 20% for text generation.

However, it also makes the ggml_exp and ggml_soft_plus operators unused.
Whether or not they should be kept will be decided later.

* convert : for Mamba, also consider the "MambaLMHeadModel" arch name

It's the name of the class of the official implementation,
though they don't use it (yet) in the "architectures" field of config.json

* mamba : fix vocab size problems with official models

The perplexity was waaaay to high for models with a non-round vocab size.
Not sure why, but it needed to be fixed in the metadata.

Note that this breaks existing GGUF-converted Mamba models,
but **only if** the vocab size was not already rounded.

* ggml : remove ggml_exp and ggml_soft_plus

They did not exist anyway outside of this branch,
and since ggml_ssm_scan fused operations together, they are unused.
It's always possible to bring them back if needed.

* mamba : remove some useless comments

No code change.

* convert : fix flake8 linter errors

* mamba : apply suggestions from code review

* mamba : remove unecessary branch for row-wise ssm_state and C multiplication

It was previously done to avoid permuting when only one token is processed
at a time (like when generating text), but permuting is cheap,
and dynamically changing the compute graph is not future-proof.

* ggml : in ggml_ssm_scan, use more appropriate asserts

* ggml : rename the destination pointer in ggml_compute_forward_ssm_scan_f32

* mamba : multiple sequences, but one at a time

This is a step towards making this Mamba implementation usable
with the server example (the way the system prompt is kept when clearing
the client slots will need to be changed before this can work, though).

The KV cache size for this kind of model is tied to the maximum number
of sequences kept at any single time.
For now, this number is obtained from n_parallel (plus one,
to have an extra sequence to dedicate to the system prompt),
but there might be a better way to do this which won't also
make the main example use 2 cells even if only 1 is really used.
(for this specific case, --parallel 0 helps)

Simultaneous sequence processing will probably require changes to
ggml_ssm_scan, and possibly a new operator for the conv step.

* mamba : support llama_kv_cache_seq_cp

This (mis)uses the logic around K shifts, because tokens in a state
can't be shifted anyway, and because inp_K_shift has the right shape and type.
Using ggml_get_rows is a nice way to do copies, but copy chains can't work.
Fortunately, copy chains don't really seem to be used in the examples.

Each KV cell is dedicated to the sequence ID corresponding to its own index.

* mamba : use a state mask

It's cleaner than the previous heuristic of
checking for the pos of the first token in the batch.

inp_KQ_mask could not be re-used for this, because it has the wrong shape
and because it seems more suited to the next step of
simultaneous sequence processing (helping with the problem of
remembering which token belongs to which sequence(s)/state(s)).

* llama : replace the usage of n_ctx with kv_self.size in many places

* mamba : use n_tokens directly instead of n_tok

* mamba : in comments, properly refer to KV cells instead of slots

* mamba : reduce memory usage of ggml_ssm_scan

From 290.37 MiB to 140.68 MiB of CPU compute buffer size
with Mamba 3B with a batch size of 512.

The result tensor of ggml_ssm_scan was previously a big part
of the CPU compute buffer size. To make it smaller,
it does not contain the intermediate ssm states anymore.
Both y and the last ssm state are combined in the result tensor,
because it seems only a single tensor can be returned by an operator
with the way the graph is built.

* mamba : simultaneous sequence processing

A batch can now contain tokens from multiple sequences.

This is necessary for at least the parallel example, the server example,
and the HellaSwag test in the perplexity example.

However, for this to be useful, uses of llama_kv_cache_seq_rm/cp
will need to be changed to work on whole sequences.

* ggml : add ggml_ssm_conv as a new operator for the conv step of Mamba

This operator makes it possible to use and update the correct states
for each token of the batch in the same way as ggml_ssm_scan.
Other solutions which use existing operators would need loops which would
add too many nodes to the graph (at least the ones I thought of).

Using this operator further reduces the size of the CPU compute buffer
from 140.68 MiB to 103.20 MiB with Mamba 3B with a batch size of 512.
And (at least on CPU), it's a bit faster than before.

Note that "ggml_ssm_conv" is probably not the most appropriate name,
and it could be changed if a better one is found.

* llama : add inp_s_seq as a new input tensor

The most convenient implementation to select the correct state (for Mamba)
for each token is to directly get the correct index from a tensor.
This is why inp_s_seq is storing int32_t and not floats.

The other, less convenient way to select the correct state would be
to have inp_KQ_mask contain 1.0f for each state used by a token
and 0.0f otherwise. This complicates quickly fetching the first used
state of a token, and is also less efficient because a whole row
of the mask would always need to be read for each token.

Using indexes makes it easy to stop searching when there are
no more sequences for a token, and the first sequence assigned
is always very quickly available (it's the first element of each row).

* mamba : support llama_kv_cache_seq_cp copy chains

* mamba : support shifting and dividing the kv cache pos

* mamba : make the server and parallel examples work with whole sequences

A seq_id is dedicated to the system prompt in both cases.

* llama : make llama_kv_cache_seq_rm return whether it succeeded or not

* mamba : dedicate an input tensor for state copy indices

This is cleaner and makes it easier to adapt when/if token positions
(and by extension, inp_K_shift) are no longer integers.

* mamba : adapt perplexity, batched, and batched-bench examples

* perplexity : limit the max number of sequences

This adapts to what the loaded model can provide.

* llama : add llama_n_max_seq to get the upper limit for seq_ids

Used by the perplexity example.

* batched : pass n_parallel to the model's context params

This should have been there already, but it wasn't.

* batched-bench : reserve sequences to support Mamba

* batched-bench : fix tokens being put in wrong sequences

Generation quality isn't what's measured in there anyway,
but at least using the correct sequences avoids using non-consecutive
token positions.

* mamba : stop abusing attention metadata

This breaks existing converted-to-GGUF Mamba models,
but will allow supporting mixed architectures like MambaFormer
without needing to break Mamba models.

This will also allow changing the size of Mamba's states
without having to reconvert models in the future.
(e.g. using something else than d_conv - 1 columns for the conv_states
 will not require breaking existing converted Mamba models again)

* gguf-py : add new KV metadata key-value pairs for Mamba

* llama : add new metadata key-value pairs for Mamba

* llama : guard against divisions by zero when n_head is 0

* mamba : rename "unlimited" KV cache property to "recurrent"

* mamba : more correctly update the "used" field of the KV cache

* ggml : in ggml_ssm_scan, use a threshold for soft_plus

This is how the official Mamba implementation does it,
and it's also what torch.nn.Softplus does.

* convert : for Mamba, fallback to internal NeoX tokenizer

The resulting models are exactly the same
as if the tokenizer.json and tokenizer_config.json of GPT-NeoX were there.

* mamba : support state saving and restoring

* ggml : implicitly pass src tensors through dst for Mamba-related ops

* mamba : clarify some comments

* server : fix cache_tokens not getting correctly resized

Otherwise, when the "we have to evaluate at least 1 token" special case
was triggered, an extra token was kept in cache_tokens even if it was
removed from the KV cache.

For Mamba, this caused useless prompt reprocessing when the previous
request triggered the above case.

* convert-hf : support new metadata keys for Mamba

For the models available at
https://huggingface.co/collections/state-spaces/transformers-compatible-mamba-65e7b40ab87e5297e45ae406

* mamba : rename metadata to be more similar to transformers library

This breaks existing converted-to-GGUF models,
but the metadata names are more "standard".

* mamba : support mamba-*-hf models

These models share their token_embd.weight with their output.weight

* mamba : add missing spaces

This is purely a formatting change.

* convert-hf : omit output.weight when identical with token_embd.weight

Only for Mamba for now, but it might be relevant for other models eventually.
Most Mamba models actually share these two tensors, albeit implicitly.

* readme : add Mamba to supported models, and add recent API changes

* mamba : move state_seq and state_mask views outside layer loop

A few tensors were also missing `struct` in front of `ggml_tensor`.
2024-03-08 17:31:00 -05:00
Pierrick Hymbert
76e868821a
server: metrics: add llamacpp:prompt_seconds_total and llamacpp:tokens_predicted_seconds_total, reset bucket only on /metrics. Fix values cast to int. Add Process-Start-Time-Unix header. (#5937)
Closes #5850
2024-03-08 12:25:04 +01:00
Georgi Gerganov
af37fd8b30
server : fix EOS token detection with disabled cache (#5938) 2024-03-08 12:40:02 +02:00
Minsoo Cheong
55a2a900ff
server : add /v1/completions endpoint (#5914)
* add-`/v1/completions`-endpoint

* add legacy comment to `/completion` endpoint
2024-03-07 12:42:39 +02:00
Georgi Gerganov
2002bc96bf
server : refactor (#5882)
* 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

---------

Co-authored-by: Pierrick Hymbert <pierrick.hymbert@gmail.com>
2024-03-07 11:41:53 +02:00
Georgi Gerganov
29ae62d2ae
llama : fix embeddings (#5796)
* llama : fix embeddings

ggml-ci

* llama : do not use KV cache for non-causal models

ggml-ci

* embeddings : fix llama_batch_init arg

* llama : add pooling switch

* llama : distinguish token vs sequence embeddings

ggml-ci

* llama : assert pooling tensor

* llama : simplify causal mask condition

ggml-ci

* llama : assert input batch with pooling enabled

* readme : update API changes list
2024-03-04 22:31:20 +02:00
Xuan Son Nguyen
4ffcdce2ff
add alias for chat template (#5858) 2024-03-04 12:22:08 +01:00
Pierrick Hymbert
8ef969afce
server : init http requests thread pool with --parallel if set (#5836) 2024-03-03 09:48:36 +02:00
Pierrick Hymbert
9731134296
server: tests: passkey challenge / self-extend with context shift demo (#5832)
* 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
2024-03-02 22:00:14 +01:00
Pierrick Hymbert
3ab8b3a92e
llama : cleanup unused mmq flags (#5772)
* cleanup unused --no-mul-mat-q,-nommq, -mmq, --mul-mat-q, mul_mat_q

* remove: mul_mat_q in compare llama bench and usage

* update llama-bench

---------

Co-authored-by: slaren <slarengh@gmail.com>
2024-03-01 13:39:06 +02:00
Pierrick Hymbert
5cb02b4a01
server: allow to override threads server pool with --threads-http (#5794) 2024-03-01 10:08:08 +01:00
Georgi Gerganov
f105471ef6
server : fix newlines in help (#5785) 2024-03-01 09:59:43 +02:00
Xuan Son Nguyen
052051d8ae
Server: normalize naming (#5779)
* server: normalize naming

* fix spacing
2024-02-29 21:42:11 +01:00
Xuan Son Nguyen
a693bea1e6
server : hit Ctrl+C twice to exit (#5734)
* server: twice ctrl+C to exit

* std::atomic_flag

* sigint: message

* sigint: stderr

* Update examples/server/server.cpp

Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>

---------

Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
2024-02-28 10:55:37 +02:00
Jorge A
efc72253f7
server : add "/chat/completions" alias for "/v1/...` (#5722)
* Add "/chat/completions" as alias for "/v1/chat/completions"

* merge to upstream master

* minor : fix trailing whitespace

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-02-28 10:39:15 +02:00
Xuan Son Nguyen
b11a93df41
fix server hangs on empty prompt (#5733) 2024-02-26 23:15:48 +01:00
Georgi Gerganov
bf08e00643
llama : refactor k-shift implementation + KV defragmentation (#5691)
* llama : refactor k-shift implementation

ggml-ci

* llama : rename llama_kv_cache_seq_shift to llama_kv_cache_seq_add

* llama : cont k-shift refactoring + normalize type names

ggml-ci

* minor : fix MPI builds

* llama : reuse n_rot from the build context

ggml-ci

* llama : revert enum name changes from this PR

ggml-ci

* llama : update llama_rope_type

* llama : add comment about rope values

* llama : fix build

* passkey : apply kv cache updates explicitly

ggml-ci

* llama : change name to llama_kv_cache_update()

* llama : add llama_kv_cache_seq_pos_max()

* passkey : fix llama_kv_cache_seq_pos_max() usage

* llama : some llama_kv_cell simplifications

* llama : add llama_kv_cache_compress (EXPERIMENTAL)

* llama : add alternative KV cache merging (EXPERIMENTAL)

* llama : add llama_kv_cache_defrag

* llama : comments

* llama : remove llama_kv_cache_compress

will add in a separate PR

ggml-ci

* llama : defragment via non-overlapping moves

* llama : ggml_graph based defrag implementation

ggml-ci

* llama : switch the loop order in build_defrag

* llama : add comments
2024-02-25 22:12:24 +02:00
compilade
f7625019c5
server : fix crash when system prompt is bigger than batch size (#5714)
The system prompt is now decoded in batches.

* server : fix off-by-one n_past when start of prompt matches whole cache

The tokens right after the matching part would otherwise skip a pos value.
2024-02-25 20:43:50 +02:00
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
Pierrick Hymbert
d52d7819b8
server: concurrency fix + monitoring - add /metrics prometheus compatible endpoint (#5708)
* 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
2024-02-25 13:49:43 +01:00
Georgi Gerganov
ab336a9d5e
code : normalize enum names (#5697)
* coda : normalize enum names

ggml-ci

* code : cont

* code : cont
2024-02-25 12:09:09 +02:00
Pierrick Hymbert
9e359a4f47
server: continue to update other slots on embedding concurrent request (#5699)
* server: #5655 - continue to update other slots on embedding concurrent request.

* server: tests: add multi users embeddings as fixed

* server: tests: adding OAI compatible embedding concurrent endpoint

* server: tests: adding OAI compatible embedding with multiple inputs
2024-02-24 19:16:04 +01:00
Pierrick Hymbert
525213d2f5
server: init functional tests (#5566)
* 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>
2024-02-24 12:28:55 +01:00
AlpinDale
fd43d66f46
server : add KV cache quantization options (#5684) 2024-02-23 21:31:54 +02:00
Xuan Son Nguyen
a46f50747b
server : fallback to chatml, add AlphaMonarch chat template (#5628)
* server: fallback to chatml

* add new chat template

* server: add AlphaMonarch to test chat template

* server: only check model template if there is no custom tmpl

* remove TODO
2024-02-22 10:33:24 +02:00
Jared Van Bortel
89febfed93
examples : do not assume BOS when shifting context (#5622) 2024-02-21 10:33:54 -05:00
Pierrick Hymbert
1ecea255eb
server: health: fix race condition on slots data using tasks queue (#5634)
* server: health: fix race condition on slots data using tasks queue

* server: health:
    * include_slots only if slots_endpoint
    * fix compile warning task.target_id not initialized.
2024-02-21 15:47:48 +01:00
CJ Pais
6560bed3f0
server : support llava 1.6 (#5553)
* server: init working 1.6

* move clip_image to header

* remove commented code

* remove c++ style from header

* remove todo

* expose llava_image_embed_make_with_clip_img

* fix zig build
2024-02-20 21:07:22 +02:00
Xuan Son Nguyen
9c405c9f9a
Server: use llama_chat_apply_template (#5593)
* server: use llama_chat_apply_template

* server: remove trailing space

* server: fix format_chat

* server: fix help message

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* server: fix formatted_chat

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-02-20 15:58:27 +01:00
Pierrick Hymbert
c0a8c6db37
server : health endpoint configurable failure on no slot (#5594) 2024-02-20 09:48:19 +02:00
Robey Holderith
5ee99c32f5
common, server : surface min_keep as its own parameter (#5567)
* Feature - surface min_keep as its own parameter

* Updated README with min_keep param
2024-02-18 21:11:16 +02:00
Pierrick Hymbert
c145f8a132
server : slots monitoring endpoint (#5550) 2024-02-18 19:39:57 +02:00
Pierrick Hymbert
e75c6279d1
server : enhanced health endpoint (#5548)
* server: enrich health endpoint with available slots, return 503 if not slots are available

* server: document new status no slot available in the README.md
2024-02-18 18:31:28 +02:00
Pierrick Hymbert
36376abe05
server : --n-predict option document and cap to max value (#5549)
* server: document --n-predict

* server: ensure client request cannot override n_predict if set

* server: fix print usage LF in new --n-predict option
2024-02-18 18:30:09 +02:00