For `/api/show`, a fully missing `model_info` field trips up various
integrators (including a recent Android Studio integration).
The primary source of missing info tends to come from models with a
remote that are also missing other data. It seems better to me to return
an empty `model_info` than making up some other fields within
`model_info` (like saying the architecture is `remote` or something like
that). So this does slightly change `/api/show`'s behavior that possibly
someone is relying on, but it seems more important to ensure the field
is always there (from a quick sampling integrations seem to be robust to
missing fields _within_ it).
Fixes: https://github.com/ollama/ollama/issues/13783
In #13525, I accidentally broke templates' ability to automatically
render tool call function arguments as JSON.
We do need these to be proper maps because we need templates to be able
to call range, which can't be done on custom types.
* preserve tool definition and call JSON ordering
This is another iteration of
<https://github.com/ollama/ollama/pull/12518>, but this time we've
simplified things by relaxing the competing requirements of being
compatible AND order-preserving with templates (vs. renderers). We
maintain backwards compatibility at the cost of not guaranteeing order
for templates. We plan on moving more and more models to renderers,
which have been updated to use these new data types, and additionally
we could add an opt-in way of templates getting an order-preserved list
(e.g., via sibling template vars)
* orderedmap_test: remove testify
* docs: add docs for v1/responses and rework openai compat section
I reworked the examples to be separated by topic and to be fully
runnable (i.e., they now log output instead of just suggesting how a
call might be made).
We now use `<CodeGroup>`s so that each example has a dropdown on the
docs site for users to choose, which makes the examples a lot more
digestible (since you only see approx 1/3 of the code you used to).
I also added a new tool to extract code examples into files so that it's
easier to actually run them and check that they work.
## Example
```shell
go run docs/tools/extract-examples/main.go docs/api/openai-compatibility.mdx
```
Output:
```
Extracting code examples to: /var/folders/vq/wfm2g6k917d3ldzpjdxc8ph00000gn/T/mdx-examples-3271754368
- 01_basic.py
- 01_basic.js
- 01_basic.sh
- 02_responses.py
- 02_responses.js
- 02_responses.sh
- 03_vision.py
- 03_vision.js
- 03_vision.sh
Extracted 9 file(s) to /var/folders/vq/wfm2g6k917d3ldzpjdxc8ph00000gn/T/mdx-examples-3271754368
To run examples:
cd /var/folders/vq/wfm2g6k917d3ldzpjdxc8ph00000gn/T/mdx-examples-3271754368
npm install # for JS examples
then run individual files with `node file.js`, `python file.py`, `bash file.sh`
```
In the future we should consider actually running the examples in CI and
having some sort of acceptance test so we can automatically detect when
our examples break. So this is just a start in that direction.
* Update docs/api/openai-compatibility.mdx
Co-authored-by: Parth Sareen <parth.sareen@ollama.com>
* Update docs/api/openai-compatibility.mdx
Co-authored-by: Parth Sareen <parth.sareen@ollama.com>
---------
Co-authored-by: Parth Sareen <parth.sareen@ollama.com>
On main, the `RENDERER` and `PARSER` fields from the `Modelfile` don't
get propagated to a new model created with a `req.From` parameter. This
is easily triggered via `ollama run qwen3-coder`, then running some save
command like `/save qwen3-coder-custom`.
Added a regression test for this, and then open the config for the
"from" model in order to use its renderer/parser as a default for the
new model. This will fix the CLI and also API-based creates.
Fixes: https://github.com/ollama/ollama/issues/12792
Made it so when api/generate builds up a message array and generates the
prompt it now goes through the same function as `api/chat` for
consistency. This is where we hook the optional built-in renderers to
bypass templates, which was missing for `api/generate` before this
change.
Closes: #12578
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
In #11910 we started sanitizing function names, but we accidentally were
modifying built-ins like `browser.open` to `browser_open`. This was
removing the special prompt rendering for built-ins, but this wasn't
immediately apparent since the models seem to be reasonably good at
remembering the built-ins even when presented with these slightly
renamed version. This fix prevents built-ins from ever being renamed.
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
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
The thinking parser will automatically transition to being a
pass-through if non-whitespace is seen before an opening tag. However,
we weren't clearing the buffer after the first non-whitespace input, so
in practice the first token would be emitted twice.
Added a test that demonstrated this, and then fixed the bug.
0x007e is a tilde and was getting adjusted (+0x00a2) to 0x0120 in the
encode, but then in the decode it was getting adjusted down (-0x0100) to
0x0020. The boundary for the +0x00a2 case has been adjusted to fix this
Fixes: #11966
In <https://github.com/ollama/ollama/issues/11704#issuecomment-3177380197>
I noticed that hyphens in function names could possibly cause the model
to become confused. Later in that issue I found other explanations, but
at a minimum tool names with spaces in them are confusing to the model
because of the prompt format.
In this change I create a mapper that converts arbitrary tool names into
valid typescript identifiers. It's a little overly strict in that it
doesn't allow all unicode characters that might be valid in ts
identifiers, but it's still very permissive. Since mappings aren't
reversible, we must temporarily store this mapping in order to unmap it
if the model comes back with a call. We also handle the case where
multiple mappings collide into the same mapping and append a counter to
the end to make them unique
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
- Both `/api/generate` and `/api/chat` now accept a `"think"`
option that allows specifying whether thinking mode should be on or
not
- Templates get passed this new option so, e.g., qwen3's template can
put `/think` or `/no_think` in the system prompt depending on the
value of the setting
- Models' thinking support is inferred by inspecting model templates.
The prefix and suffix the parser uses to identify thinking support is
also automatically inferred from templates
- Thinking control & parsing is opt-in via the API to prevent breaking
existing API consumers. If the `"think"` option is not specified, the
behavior is unchanged from previous versions of ollama
- Add parsing for thinking blocks in both streaming/non-streaming mode
in both `/generate` and `/chat`
- Update the CLI to make use of these changes. Users can pass `--think`
or `--think=false` to control thinking, or during an interactive
session they can use the commands `/set think` or `/set nothink`
- A `--hidethinking` option has also been added to the CLI. This makes
it easy to use thinking in scripting scenarios like
`ollama run qwen3 --think --hidethinking "my question here"` where you
just want to see the answer but still want the benefits of thinking
models
* strip out thinking tags in message history for qwen3 & r1
This is in advance of "proper" support where we'll make reasoning
configurable and we'll parse out thinking/reasoning tags and provide
them to the caller. These models expect there to be no thinking tags in
the message history, so this should improve quality
* parse model names instead of hacky prefix check
this is in part to "pay" for #10452, which doubled the default context length. The combination isn't fully neutral though, because even though the old 4x2k limit and the new 2x4k limit are memory equivalent, the 1x fallback is larger with 4k
If it's an array, it uses the max value in the array
If array values for head counts becomes more popular, we can consider a
more invasive change like #10225 to calculate more accurate estimates.
Fixes: #9984
* increase default context length to 4096
We lower the default numParallel from 4 to 2 and use these "savings" to
double the default context length from 2048 to 4096.
We're memory neutral in cases when we previously would've used
numParallel == 4, but we add the following mitigation to handle some
cases where we would have previously fallen back to 1x2048 due to low
VRAM: we decide between 2048 and 4096 using a runtime check, choosing
2048 if we're on a one GPU system with total VRAM of <= 4 GB. We
purposefully don't check the available VRAM because we don't want the
context window size to change unexpectedly based on the available VRAM.
We plan on making the default even larger, but this is a relatively
low-risk change we can make to quickly double it.
* fix tests
add an explicit context length so they don't get truncated. The code
that converts -1 from being a signal for doing a runtime check isn't
running as part of these tests.
* tweak small gpu message
* clarify context length default
also make it actually show up in `ollama serve --help`