GitLab

* 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>

This makes the core openai compat layer independent of the middleware
that adapts it to our particular gin routes

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

* feat: add field to truncate embeddings

* add openai embeddings for dimensions

We were missing passing along thinking if content was nil (as opposed
to empty string)

Also added a test for content not being passed, which was the real cause
of <https://github.com/ollama/ollama/issues/11704>, since with the way
`Content` is typed, not passing it and empty string are distinct

Added support for converting both `name` and `tool_call_id` fields,
which different clients might provide. `name` is a legacy field from the
OpenAI completions API. For `tool_call_id` we inspect previous messages
and look for a matching tool call ID and grab its name

Issue: https://github.com/ollama/ollama/issues/11704

Previously our OpenAI chat completions compat layer assumed that tool
calls and content would never be provided together, but this is not a
correct assumption. Content is only optional when tool calls are
present, but tool calls and content can be provided together

Fixes: https://github.com/ollama/ollama/issues/11704

afaik gpt-oss is the first model that meaningfully transforms tool
function definitions in its template. We found that relatively common
definitions that include `anyOf` were not working because the template
was assuming that types were always defined via a `type` field.

anyOf allows for fully recursive types, so I exposed a
`toTypeScriptType()` function to handle this recursive logic in go and
keep the templates cleaner. The gpt-oss templates will need to be
updated to use this.

We should keep building out our function definition support to more
fully support the parts of json schema that make sense for this use
case, but in the meantime this will unblock some users (e.g., zed's
ollama integration w/ gpt-oss). Probably the most urgent is proper array
support

* bf16

* tests

* gpt-oss

* enable gptoss for engine

* rough estimate

* convert to mxfp4

* handle safetensors U8

* clamp glu/linear

* update tokenizer

* MXFP4 support

This implements the Open Compute Microscaling (MX) FP4 format
as a tensor type with backend implementations focusing
on mulmat and mulmatid on CPU, CUDA, and Metal.

* Unit tests for MXFP4 support

This exercises various operations and shapes on both CPU and GPU (if detected
on the system)

* cuda graph

* unit test adjustments

* cuda: optimize memory access

Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4

* mac: fix crash on old macos versions

cblas_sgemm is only supported on v13.3 and up, however bf16 is
only supported on v14+ so we were falling back to ggml-blas and
crashing on bf16 tensors.  Checking for the function being null
seems to be the simplest way to condittionally avoid registering the
backend.

* server: Minimum context length for gptoss

This model requires a minimum context length of 8192 to function
effectively. Users can set higher values through all normal mechanisms
but lower values will be silently reset.

* ggml: Multiply by numParallel for gptoss sliding window

When computing the graph size estimate, the context size is already
multiplied by numParallel so estimates reflect that. However, since
sliding window models use a smaller, fixed context size, they need
to manually take numParallel into account.

* gpt-oss integration

includes harmony parser and thinking levels, etc.

* fix sync

* fix tests

* fix lint

---------
Co-authored-by: Daniel Hiltgen <daniel@ollama.com>
Co-authored-by: Jesse Gross <jesse@ollama.com>
Co-authored-by: Devon Rifkin <drifkin@drifkin.net>

Co-authored-by: Richard Lyons <frob@cloudstaff.com>

---------
Co-authored-by: Parth Sareen <parth.sareen@ollama.com>

Both interface{} and any (which is just an alias for interface{} introduced in Go 1.18) represent the empty interface that all types satisfy.

* openai: return usage as final chunk for streams

---------
Co-authored-by: ParthSareen <parth.sareen@ollama.com>

Previously we decoded and re-encoded JSON schemas during validation,
which served no purpose since json.RawMessage already validates JSON
syntax. Worse, the re-encoding lost field ordering from the original
schema, which affects inference quality during step-by-step reasoning.

While fixing this ordering issue by using json.RawMessage directly,
testing revealed that schema_to_grammar (from llama.cpp) also fails to
preserve field order during grammar generation. This appears to be the
root cause of inference degradation.

This change prevents us from mangling the user's original schema order,
but we still need to address the ordering issue in schema_to_grammar.
That will be a separate change.

Updates #7978

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

The writeError takes a code argument which is no longer used. Remove it for clarity.

* simplify input output

* direct comp

* in line image

* rm error pointer type

* update response testing

* lint

* add prompt tokens to embed response

* rm slog

* metrics

* types

* prompt n

* clean up

* reset submodule

* add tokens to v1/embeddings

* separate usage

* hot fix

* backend stream support

* clean up

* finish reason

* move to openai

* distinguish error forwarding

* more coverage

* rm comment

* reopen pr

* tools

* remove tc from stream for now

* ID and Function

* openai expects arguments to be a string (#5739)

* mutually exclusive content and tool calls

* clean up

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

* add suffix

* remove todo

* remove TODO

* add to test

* rm outdated prompt tokens info md

* fix test

* fix test

* OpenAI v1 models

* Empty List Testing

* Add back envconfig

* v1/models docs

* Remove Docs

* OpenAI batch embed compatibility

* merge conflicts

* integrate with api/embed

* ep

* merge conflicts

* request tests

* rm resp test

* merge conflict

* merge conflict

* test fixes

* test fn renaming

* input validation for empty string

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

* OpenAI v1 models

* Refactor Writers

* Add Test

Co-Authored-By: Attila Kerekes

* Credit Co-Author
Co-Authored-By: Attila Kerekes <439392+keriati@users.noreply.github.com>

* Empty List Testing

* Use Namespace for Ownedby

* Update Test

* Add back envconfig

* v1/models docs

* Use ModelName Parser

* Test Names

* Remove Docs

* Clean Up

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

* Add Middleware for Chat and List

* Testing Cleanup

* Test with Fatal

* Add functionality to chat test

* Support image input for OpenAI chat

* Decoding

* Fix message processing logic

* openai vision test

* type errors

* clean up

* redundant check

* merge conflicts

* merge conflicts

* merge conflicts

* flattening and smaller image

* add test

* support python and js SDKs and mandate prefixing

* clean up

---------
Co-authored-by: Attila Kerekes <439392+keriati@users.noreply.github.com>
Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>