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* Include unified vision layers in memory prediction

For newer vision models with a single gguf, include
the projection estimates.

* Adjust CLI to handle both styles of vision model metadata

* Wire up new tokenizers for new engine

If we're loading the new engine, utilize the new model
text processor instead of calling into cgo wrappers for
llama.cpp.  This also cleans up some tech debt from the
older tokenization flow for the C++ server which was
no longer used.

This also adjusts the grammar handling logic to pass
through to the new engine instead of utilizing the cgo
schema to grammar call.

* Lay foundation for auto selection of new engine

This provides integration with the new Ollama engine
(58245413 next ollama runner (#7913)) and the rest of the Ollama
infrastructure such as the runner and Ollama server.

In addition, it also builds out the KV cache infrastructure to
support requirements of how Ollama runs models such as:
 - Parallel processing
 - Memory management for defragmentation and shifting
 - Multi-modal modals

Both old and new engines continue to be supported. By default, only
the old engine is used. To enable the new engine:

Start the server with the OLLAMA_NEW_ENGINE environment variable set:
OLLAMA_NEW_ENGINE=1 ./ollama serve

Start a model that is supported by the Ollama engine. This one is Llama 3.1 8b Q4_K_M:
./ollama run jessegross/llama3.1

Replaces `POST /api/create` to use JSON instead of a Modelfile.

This is a breaking change.

Fixes #7944

* llama: wire up builtin runner

This adds a new entrypoint into the ollama CLI to run the cgo built runner.
On Mac arm64, this will have GPU support, but on all other platforms it will
be the lowest common denominator CPU build.  After we fully transition
to the new Go runners more tech-debt can be removed and we can stop building
the "default" runner via make and rely on the builtin always.

* build: Make target improvements

Add a few new targets and help for building locally.
This also adjusts the runner lookup to favor local builds, then
runners relative to the executable, and finally payloads.

* Support customized CPU flags for runners

This implements a simplified custom CPU flags pattern for the runners.
When built without overrides, the runner name contains the vector flag
we check for (AVX) to ensure we don't try to run on unsupported systems
and crash.  If the user builds a customized set, we omit the naming
scheme and don't check for compatibility.  This avoids checking
requirements at runtime, so that logic has been removed as well.  This
can be used to build GPU runners with no vector flags, or CPU/GPU
runners with additional flags (e.g. AVX512) enabled.

* Use relative paths

If the user checks out the repo in a path that contains spaces, make gets
really confused so use relative paths for everything in-repo to avoid breakage.

* Remove payloads from main binary

* install: clean up prior libraries

This removes support for v0.3.6 and older versions (before the tar bundle)
and ensures we clean up prior libraries before extracting the bundle(s).
Without this change, runners and dependent libraries could leak when we
update and lead to subtle runtime errors.

Adds structured outputs to chat endpoint
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Co-authored-by: Michael Yang <mxyng@pm.me>
Co-authored-by: Hieu Nguyen <hieunguyen1053@outlook.com>

After a user pushes their model it is not clear what to do next. Add a link
to the output of `ollama push` that tells the user where their model can now
be found.

In the past the ollama.com server would return a JWT that contained
information about the user being authenticated. This was used to return
different error messages to the user. This is no longer possible since the
token used to authenticate does not contain information about the user
anymore. Removing this code that no longer works.

Follow up changes will improve the error messages returned here, but good to
clean up first.

This avoids emitting the progress indicators to stderr, and the interactive
prompts to the output file or pipe.  Running "ollama run model > out.txt"
now exits immediately, and "echo hello | ollama run model > out.txt"
produces zero stderr output and a typical response in out.txt

If we're not writing out to a terminal, avoid setting the console mode
on windows, which corrupts the output file.

Co-authored-by: jmorganca <jmorganca@gmail.com>
Co-authored-by: Michael Yang <mxyng@pm.me>
Co-authored-by: Jesse Gross <jesse@ollama.com>

fixes line wrapping on long texts

With the new very large parameter models, some users are willing to wait for
a very long time for models to load.

Provide a mechanism for users to set aside an amount of VRAM on each GPU
to make room for other applications they want to start after Ollama, or workaround
memory prediction bugs

* Fix typo and improve readability

Summary:
* Rename updatAvailableMenuID to updateAvailableMenuID
* Replace unused cmd parameter with _ in RunServer function
* Fix typos in comments

(cherry picked from commit 5b8715f0b04773369e8eb1f9e6737995a0ab3ba7)

* Update api/client.go
Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>

---------
Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>

The OLLAMA_MAX_VRAM env var was a temporary workaround for OOM
scenarios.  With Concurrency this was no longer wired up, and the simplistic
value doesn't map to multi-GPU setups.  Users can still set `num_gpu`
to limit memory usage to avoid OOM if we get our predictions wrong.

* Check exists projtype

* Maintain Ordering