When processing a prompt, we look for image tags of the form
[img-0], which are inserted by the Ollama server process.
However, this can cause errors if the original prompt has these
tags - typically an image not found error is returned.
This changes tag searching behavior to be similar to the 0.3.x
series, which will largely avoid these problems. However,they can
still happen when input text with these tags is used with image
models. The correct solution is to escape the tags but this is a
larger issue with special sequences in general so this is an
incremental fix that should avoid the problem for the majority
of cases.
This also makes it easier to truncate long inputs the same as
shifting but does not actually implement it. This type of
truncation has a trade off between quality and time to first
token.
If there are no avilable slots for new sequences then a request
will not be added to the processing queue but will continue on
to wait for a response that never comes. Besides never giving a
response to the request, this prevents the model from being
unloaded due to the outstanding request.
To prevent this, there are semaphores that prevent more requests
from being processed than there are slots - one in the Ollama
server and one in the runner.
- The Ollama server one works but it is not designed to protect
the runner's data internal structures and the runner can return a
final response before clearing its data structures.
- The internal runner semaphore has similar behavior where it
can release the semaphore when it issues a response. This is
wrong - it should only release the semaphore after it has
cleared the data structure.
In addition, we should return an error if a slot is not found
rather than deadlocking in the event we ever get to this spot.
Fixes#7779
Users get confused by "Failed to acquire semaphore" error="context canceled"
messages in the logs, which are actually clients giving up. While there could be
a legitimate hang bug in the system, sometimes this is just short client timeouts
with an overloaded system, so this should help users understand what's going on
better.
Previous versions of the runner would truncate inputs to the context
window before beginning processing. The main processing loop relied
on this behavior if the context needed to be shifted later (due to
token generation). If truncation did not occur then invariants
would be broken, causing crashes or infinite loops.
Later versions attempted to fix these bugs and make the logic less
subtle so that all inputs could be handled. Truncation was removed
to make things consistent.
However, truncation is much faster than processing and shifting, so
removing it caused performance problems when the input vastly exceeded
the context size. This restores the input truncation as a performance
optimization while keeping the more robust processing logic.
Fixes#7762
We need to track which tokens are in the cache ourselves. We currently
add tokens to the cache tracker when we add them to batch but they are
not actually in the cache until we call Decode. This can cause
confusion when we are shifting the cache.
Avoids "could not find a KV slot for the batch" issues.
Bug #7545
We try to recover from errors by dropping the tokens that caused the
problem and re-trying. However, dropping the tokens is not correct
and continuing often leads to infinite loops. To avoid, this we
end the sequence if such a condition is detected, which is also
surprising.
At this point, it is better to just report the error. This will make
it easier to find problems and the alternatives are perhaps even more
surprising to users.
This is not a very satisfactory solution either - we should isolate
the error and return it to the user without killing the whole process.
However, this is an incremental step and consistent with most other
failures (which either manifest as abort() or panic).
Fragmentation of the KV cache can occur due to cache shifting or
different sequences getting processed. Decode uses a heuristic to
decide if it should defrag. However, this heuristic isn't 100%
accurate, so decoding can sometimes fail by surprise.
For these cases, if decode indicates that there is no KV cache space,
we should defrag and then try again.
This is a partial revert of 8a35bb92
"runner.go: Increase survivability of main processing loop", removing
the panic handler.
Although we want to avoid errors taking down the runner, we also
should make the user aware of problems when they happen. In the
future, we can restructure things so both parts are true.
Currently, if an error occurs during the prep stages (such as
tokenizing) of a single request, it will only affect that request.
However, if an error happens during decoding, it can take down the
entire runner.
Instead, it's better to drop the tokens that triggered the error and try to
keep going. However, we also need to stop when we run out of tokens,
otherwise, this just causes an infinite loop. This is likely the cause
of at least some of the hanging issues that have been reported.
Bug #7573
It's possible to get prompts that consist entirely of whitespace -
this is most likely to happen when generating embeddings. Currently,
we will trim this away, leaving an empty prompt, which will then
generate an error.
Generating embeddings from whitespace should not trigger an error,
as this may break pipelines. It's better to just leave the whitespace
in place and process what we are given. This is consistent with
past versions of Ollama.
Bug #7578
NUM_PARALEL is currently enforced by the Ollama server process - it
will only issue requests to the runner if the maximum number of
concurrent requests has not been exceeded. Although this should
be sufficient, it is good for the runner to protect its own data
structures. Currently, if too many requests get through to the
runner, they will just get stuck and never return.
This may help with reports of Ollama hanging, though it is unclear
how it would actually occur.
Bug #7573
The structure of the accounting for KV cache shifting was carried
over from the old runner but it now doesn't feel natural with the new
runner. There are a number of invariants that should hold true but
are difficult to reason about. There is at least one bug report
that would imply that the invariants are not holding.
This reduces the number of implicit assumptions and is more forgiving
of unexpected situations. It also improves behavior around which input
tokens are kept when truncation occurs.
Bug #7545
Check for NULL return values from llama.cpp in more places and
convert them into Go errors, which should make debugging easier
in the future rather than having hidden surprises in our data
structures.
Mllama has large embeddings (100 MB per image) and each embedding is
represented as 1 token when passed to llama.cpp. Batches are pre-
allocated for the size of the tokens times the batch size, so this
results in allocations of over 50 GB at the default batch size.
On some systems, these mallocs will fail.
Since an image is represented as a single token and mllama doesn't
support more than 1 image per request, we only need to allocate a
batch size of 1, which is much more reasonable. In addition, for
non-multimodal models, we don't need to allocate the embedding
batches at all.
Fixes#7464
Currently if an input has embeddings at any point then we will set
cross attention to true from the beginning. This means that any
tokens before the embeddings are sent will incorrectly have cross
attention layers applied.
This only sets cross attention when we have an embedding, either
previously in this sequence or in the cache. It also makes cross
attention capable of supporting parallelism at the runner level,
though the mllama implementation doesn't support that yet.
-Update mllama to take the cross attention state as embeddings in
a batch, more similar to how Llava handles it. This improves
integration with the input cache.
-Pass locations in a prompt for embeddings using tags similar to Llava.
-Abstract interface to vision models so the main runner accesses Clip
and Mllama similarly
Co-authored-by: Michael Yang <mxyng@pm.me>
This will no longer error if built with regular gcc on windows. To help
triage issues that may come in related to different compilers, the runner now
reports the compier used by cgo.
* Switch over to clang for deepseek on windows
The patch for deepseek requires clang on windows. gcc on windows
has a buggy c++ library and can't handle the unicode characters
* Fail fast with wrong compiler on windows
Avoid users mistakenly building with GCC when we need clang
Llama.cpp sometimes returns NULL as a return value to report an
error. We should explicitly check for this and convert it to a Go
error rather than putting NULL in our data structures and waiting
for it to blow up later.
On windows ensure windows version define is properly set for rocm.
Remove duplicate rocm arch flags.
Resolve wildcards in the targets so parallel builds don't race.
Use readlink to resolve rocm dependencies since wildcards omit libelf
Keep windows rocm deps aligned with unified packaging model
We check for partial unicode characters and accumulate them before
sending. However, when we did send, we still sent each individual piece
separately, leading to broken output. This combines everything into
a single group, which is also more efficient.
This also switches to the built-in check for valid unicode characters,
which is stricter. After this, we should never send back an invalid
sequence.
Fixes#7290
* fix(ext_server): Port llama.cpp sampling refactors to ext_server
This was a fairly large changeset. I closely followed the changes here:
df270ef745
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(server.cpp): Refactor server.cpp logging for llama.cpp overhaul
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Bump llama.cpp to the latest master with `granite` support
This does not yet have granite MoE support, but that can come in a
follow up PR
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(patches): Update all patches (except solar-pro) to work with bumped llama.cpp
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(solar): Update solar patch for llama.cpp bump
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat(llama.cpp): Bump llama.cpp for granitemoe support
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat(llama.cpp): Bump llama.cpp for granitemoe support
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(solar): Update the solar-pro patch for latest llama.cpp bump
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat(llama.cpp): Bump to the latest master of llama.cpp
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(patches): Update all patches for latest bump
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat(llama): Always run sync.sh from the right directory
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llama/patches): Update llama patches
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat(llama)!: Rough sync with llama.cpp submodule
There are a number of changes that will need to be propagated to llama.go
before any of this works!
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llama/patches): Add a patch and update for missing ggml-impl.h include
This include is where the ggml_cgraph struct is defined. It is included in
many of the .c files to define the forward declartion in ggml.h. It seems
that with the subset of code included here, the import was somehow lost (or
out-of-order) when building, so adding this include to llama.cpp fixes the
missing definition.
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llama/sync): Add missing ggml-cpu-impl.h copy-over in sync.sh
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llama): Add missing log.cpp
This was added as part of the logging overhaul done in llama.cpp
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llama): Overhaul use of sampling module for llama.cpp changes
The changes here reflect the changes made in the big llama.cpp sampling PR
https://github.com/ggerganov/llama.cpp/pull/9294
The sampling functionality is now broken into the base interface
(llama_sampler) and the generation implementation (gpt_sampler). The
changes here reflect that. Since the sampling.h/sampling.cpp code uses c++
STL headers, the sampling_ext.[h|cpp] wrapper is maintained to allow go to
access a pure-C interface.
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llama): Fix the impl of SampleTokenGreedy for new sampling
I don't think this method is currently used, so it could probably just be
removed so that all sampling goes through the GPT interface, but in the
interest of doing no harm, this should keep the method working as expected.
Branch: IBMGraniteArchitectureSupport
* fix(llama): Remove unused SampleTokenGreedy
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(sync): Remove bash-specific change to sync.sh
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* chore(gofumpt): Format on llama.go to pass linting
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llm): Fix missing <thread> include in ext_server
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llama): Remove TODO about grammar_first
This feature was not used/needed previously so should be fine without
plumbing it through now.
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llama): Better naming for sampling wrapper and args
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llama): Fix patch 05 to use new wrapper api and re-sync
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* runner: Flush pending responses before returning
If there are any pending reponses (such as from potential stop
tokens) then we should send them back before ending the sequence.
Otherwise, we can be missing tokens at the end of a response.
Fixes#6707
* fix(llama/sampling): Use gpt_sampler with a forward declaration
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llama): Remove unnecessary patch for gguf impl header
This was caused by an earlier mistake in the embeddings patch that was
dereferencing the pointer instead of using the wrapper API.
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llm): Remove use of deprecated --log-disable flag
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
---------
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Having v11 support hard-coded into the cgo settings causes warnings
for newer Xcode versions. This should help keep the build clean for users
building from source with the latest tools, while still allow us to target
the older OS via our CI processes.
When a single token contains both text to be return and a stop
sequence, this causes an out of bounds error when we update the
cache to match our text. This is because we currently assume that
the removing the stop sequence will consume at least one token.
This also inverts the logic to deal with positive numbers, rather
than a value to be subtracted, which is easier to reason about.
Fixes#7153
