This change:
* fixes rope scaling in the mistral converter
* updates ministral to include llama4 scaling
* includes a new ministral parser for parsing reasoning and tool calling
---------
Co-authored-by: jmorganca <jmorganca@gmail.com>
Adds a temporary global flag to renderers that causes renderers to always
render images as [img]. In a follow up change, we will consider making this
the default, and this flag could eventually be removed
* changing initial status to take into consideration prefill
* Add seperate strings for content and thinking builder
* thinking tests
* remove white space from string before closing think tag
* working (other than tool call is the incorrect order) for tool calls and tools
* Tests work, other than image tags (tests do not go through server) and tools (not in the correct order, but contents are the same)
* testing for qwen3vl parser - toolparser is working
* made changes to JSON tool parser, wraps the TollCallFunction with a TollCall object
* Working parser for thinking models - assumes state of thinking, emits unambiguous content in thinking, does not call tool call in thinking
* changed the parser to start with collecting content
* thinking prefill
* add hasThinkingSupport parameter to parser
* qwen3-vl -> qwen3-vl-instruct for renderer/parser
* Add hasThinkingSupport=false to QwenVLParser
---------
Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
When trimming whitespace at the end of every chunk, we were iterating
backwards over the string byte-by-byte instead of rune-by-rune.
As an example of how this can cause corruption, suppose we have the
multi-byte character ✅ (`"\u2705"`), which is represented in utf-8 as
the three bytes `0xE2 0x9C 0x85`. It happens that `0x85` is NEL, which
passes `unicode.IsSpace()`. Because we were iterating byte-by-byte, this
caused us to mistakenly slice in the middle of the rune, removing `0x85`
and leaving `0xE2 0x9C`, which beyond being the incorrect place to
slice, is not even a valid utf-8 character.
`trailingWhitespaceLen()` was modified to count from the end in a
rune-aware way. Tests with various multibyte unicode characters were
also added.
Fixes: #12414
* init deepseek model file
* temp removal of flash attention implementation
* shapes and proper, can make a pass
* query, key, value have good cosine similarity, but the max diff is a bit high
* Attention block is working! ** with eager for now, have not added the mask line
* Attention block is working! ** with eager for now, have not added the mask line
* working MoE at around 0.95 cosine sim
* added cosine similarity function
* Starting end to end structure
* Trying (and failing) to get rope to work, going to test full thing on tater
* running on tater36... just not the right outputs
* we have the right values for rope... but its still not working?
* chnage Extrapolation Factor to 1
* removed adding residuals twice, removed normalization from shared expert, refactored Norms (Attention, MLP) to be outside the (Attention, MLP) blocks and in the Transformer block instead, add cache setLayer
* Temporary modelfiles for cpu
* change kpass intermediate step to kv, two layer outputs [0,1] look fine
* this calls for 16 chicken nuggets
* whoops
* cleaning up code
* delete stuff we dont need
* getting rid of debug statements for llama cpp
* working with long contexts
* fix long context view error
* reverting some changes I made for files that are not apart of pr
* Added proper tokenizer for deeepseek3
* clean up model and go test
* remove Modelfile
* not passing the tests
* whoops
* how to pass the ci tests
* resolving some of the comments
* rename
* linted and renamed deepseek3 -> deepseek2
* remove name go
* addressed changes - main change was adopting qwen3 naming scheme
* I cannot with linters
* clean up logs
* clean up logs
---------
Co-authored-by: Grace Guo <graceguo@Graces-MBP.localdomain>
Co-authored-by: Grace Guo <graceguo@Graces-MacBook-Pro.local>
Co-authored-by: graceguo <graceguo@tater36.localdomain>
In <https://github.com/ollama/ollama/issues/12357> we that the model
will output tool calls such as
```
<function=shell>
<parameter=command>
pwd && ls -la
</parameter>
</function>
```
We parse this using the approach of transforming into valid xml and then
using an xml parser. While we do transform the function and parameter
names, we weren't escaping the parameter values (which in this example
are invalid since `pwd && ls -la` contains unescaped ampersands).
This has been fixed by first transforming the tags in the same way, and
then walking the transformed string and escaping the text in between the
tags. This also fixes a case where `<` in the middle of a parameter
value would cause an xml parse failure.
Fixes: #12357
with #12181, there's now support for embeddings in ollama engine.
this is done by mutating the architecture and adding _embed when it
detects an embedding model. however this introduced a bug where if
an embedding model was run based on an existing ollama engine model
without an embedding implementation, e.g. llama4, it will pass the
initial arch support check but fail when actually loaded.
there's currently two entrypoints to creating a model. previously this
second entrypoint was necessary because calling model.New would also
load the model. since #11818, this is no longer th case so merge them
to reduce complexity
Now that we have a built-in parser abstraction, which was introduced in
<https://github.com/ollama/ollama/pull/12248>, we can modify our harmony
parser to match this and then get rid of nearly all of the
harmony-specific logic in routes.go. We do have a small amount of
code that turns the parser on by default if the architecture matches and
no other built-in parser was provided.
The built-in parser interface was modified in order to handle harmony's
prefill and tool name translation requirements.
The format qwen3-coder uses is relatively unique, both in rendering and
in parsing. To implement parsing, I wrote a custom parser in similar
style to harmony. For the rendering, I found that the logic would be
much more difficult to follow in a template, so I introduced the concept
of a built-in renderer that uses go code, rather than a template to
generate prompts.
I set us up for future built-in parsers and renderers by making it so
they can be specified in a Modelfile like so:
```
RENDERER "qwen3-coder"
PARSER "qwen3-coder"
```
These need to be provided explicitly because the architecture alone is
not enough to understand what format the model expects to receive, and
what format we expect it to output (e.g., qwen3-coder is `qwen3moe`,
which includes other qwen3-family models as well)
I haven't converted harmony to be one of these "built-ins" yet, since
some of it is in flux with the changes @ParthSareen has been making to
move harmony to the runner. It is likely that many other built-ins will
need to move to the runner as well, but I'm able to slightly defer that
decision since qwen3-coder doesn't have thinking (and therefore doesn't
need to be in the runner to make structured outputs work). I expect to
unify harmony with this approach very soon.
Whether a particular model supports tools or thinking was previously
inferred from templates, but without a template we now also use the
parser itself to declare what it supports. If we have future models that
re-use the same parsing format, but have different capabilities, we'll
want to parameterize them and give them different names to be specified
as a `PARSER`.
Misc changes:
- I worked on the renderer by diffing outputs from the reference
implementation and ours. To make it easier to do this, I extended
<https://github.com/ollama/ollama/pull/11875> to also support
returning the prompt via the openai compat layer
