* fix(reasoning): stop prefilled <think> from swallowing tag-less answers
When a chat template injects the thinking start token into the prompt (so
DetectThinkingStartToken returns e.g. "<think>"), the model's output begins
inside a reasoning block and carries only the closing tag. The non-jinja
autoparser fallback (peg-native "pure content" mode, issue #9985) prepends the
start token so the extractor can pair it with the model's </think>.
But on a COMPLETE response that contains no closing tag, the model answered
directly with no reasoning at all. Prepending the start token there manufactures
an unclosed block that swallows the entire answer into reasoning, leaving the
OpenAI `content` field empty. This breaks short/direct answers — session names,
JSON summaries, any terse completion where the model skips the think block —
which come back with empty content. Regression surfaced by #9991, which added
the defensive prefill extraction to the complete-response paths.
Add reasoning.ExtractReasoningComplete: it only honors a prefilled start token
when the response actually contains the matching closing tag (proof a reasoning
block exists). Genuine reasoning tags already in the content still extract;
tag-less content stays content. Apply it at every complete-response site
(applyAutoparserOverride, realtime, openresponses). The streaming per-token
extractor is intentionally left on ExtractReasoningWithConfig — mid-stream an
as-yet-unclosed block is legitimate and must surface as reasoning deltas.
Also adds reasoning.ClosingTokenForStart and hoists the default reasoning tag
pairs to package scope so both helpers share one source of truth.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* test(reasoning): cover the enable_thinking=false non-thinking-mode regression
Adds the end-to-end case that actually broke session summaries / auto-titles
and was not covered before: a request with enable_thinking=false against a
<think>-capable model. In non-thinking mode the model emits no reasoning block,
so llama.cpp's autoparser returns ChatDeltas with content set and
reasoning_content empty (verified against stock llama-server: same model with
chat_template_kwargs.enable_thinking=false returns reasoning_content=null,
content="hello"). thinkingStartToken is still "<think>" because it is detected
per-model from the enable_thinking=true render, so the old code prepended it and
swallowed the answer. The test fails without the ExtractReasoningComplete gate.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* fix(openresponses): populate Content and accept bare {role,content} items (#10039)
Fixesmudler/LocalAI#10039 — `/v1/responses` silently returned empty
output on any model whose YAML doesn't include a Go-side
`template.chat_message` block.
Three cooperating bugs:
* `convertORInputToMessages` populated only `StringContent` for string
input and for the `input.Instructions` system message, leaving the
`Content` (any) field nil.
* `TemplateMessages` gated all fallback content-rendering branches on
`Content != nil && StringContent != ""` — but every branch in that
function consumes `StringContent`, not `Content`. The `&&` silently
dropped messages that had StringContent set and Content nil, producing
an empty prompt that the 5× empty-retry guard then turned into a
200 OK with `output: []`.
* The array-input branch of `convertORInputToMessages` dispatched on
`itemMap["type"]` with no default, dropping bare `{role, content}`
items emitted by the OpenAI Python SDK helper
`client.responses.create(input=[{...}])`.
Fix:
* Set both `Content` and `StringContent` in the two openresponses
message-construction sites that only set one.
* Treat a bare `{role, content}` item (no `type`) as
`type: "message"` for OpenAI-SDK compatibility.
* Gate `TemplateMessages` fallback rendering on `StringContent != ""`,
which is what every downstream branch in that function actually
reads.
Regression test added to `evaluator_test.go` covering the fallback
path (no `ChatMessage` template) with a StringContent-only message,
both with and without a role mapping.
* test(openresponses): guard Content population and ToProto path (#10039)
Add regression tests for the two seams the original fix touched but
left uncovered:
* convertORInputToMessages must populate both Content and StringContent
for plain string input and for bare {role, content} array items (the
OpenAI SDK shape that omits the type discriminator). Both are
functional reds against the pre-fix code.
* Messages.ToProto reads Content, not StringContent — this is the path
UseTokenizerTemplate backends (imported GGUFs) take. The cases pin
that contract so a future regression on the producer side is caught.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
When LocalAI templates a thinking model outside of jinja (the default for
the qwen3 gallery family), llama.cpp's chat parser falls back to a
"pure content" PEG parser that dumps the entire raw response into
ChatDelta.Content with an empty ReasoningContent. The Go side then
trusted that content verbatim and overrode tokenCallback's
correctly-split reasoning, so <think>...</think> blocks ended up in the
OpenAI `content` field. Regression from v4.0.0 introduced when the
autoparser ChatDeltas path was added (#9224).
The override now runs Go-side reasoning extraction defensively when the
autoparser delivered content but no reasoning. The streaming worker
gains a sticky preferAutoparser flag that flips on the first chunk
where the autoparser classified reasoning_content; until then we use
the streaming Go-side extractor. Realtime mirrors the non-streaming
fallback. When the autoparser already populated ReasoningContent we
trust it untouched, so jinja-enabled installs are not regressed.
gallery/qwen3.yaml now enables use_jinja, letting the autoparser
classify <think> natively for all 20+ qwen3 family entries that share
this template.
Fixes#9985
Assisted-by: Claude:opus-4-7 [Read] [Edit] [Bash] [Write]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* fix(anthropic): use SetFunctionCallNameString for specific tool forcing
* fix(openai/realtime): use SetFunctionCallNameString for specific tool forcing
* fix(openresponses): use SetFunctionCallNameString for specific tool forcing
Upstream llama.cpp (PR #21962) switched the server-side mtmd media
marker to a random per-server string and removed the legacy
"<__media__>" backward-compat replacement in mtmd_tokenizer. The
Go layer still emitted the hardcoded "<__media__>", so on the
non-tokenizer-template path the prompt arrived with a marker mtmd
did not recognize and tokenization failed with "number of bitmaps
(1) does not match number of markers (0)".
Report the active media marker via ModelMetadataResponse.media_marker
and substitute the sentinel "<__media__>" with it right before the
gRPC call, after the backend has been loaded and probed. Also skip
the Go-side multimodal templating entirely when UseTokenizerTemplate
is true — llama.cpp's oaicompat_chat_params_parse already injects its
own marker and StringContent is unused in that path. Backends that do
not expose the field keep the legacy "<__media__>" behavior.
The C++ PEG parser needs a few tokens to identify the reasoning format
(e.g. "<|channel>thought\n" for Gemma 4). During this warm-up, the gRPC
layer was sending raw partial tag tokens to Go, which leaked into the
reasoning field.
- Clear reply.message in gRPC when autoparser is active but has no diffs
yet, matching llama.cpp server behavior of only emitting classified output
- Prefer C++ autoparser chat deltas for reasoning/content in all streaming
paths, falling back to Go-side extraction for backends without autoparser
(e.g. vLLM)
- Override non-streaming no-tools result with chat delta content when available
- Guard PrependThinkingTokenIfNeeded against partial tag prefixes during
streaming accumulation
- Reorder default thinking tokens so <|channel>thought is checked before
<|think|> (Gemma 4 templates contain both)
* feat: add distributed mode (experimental)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix data races, mutexes, transactions
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactorings
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fixups
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix events and tool stream in agent chat
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* use ginkgo
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(cron): compute correctly time boundaries avoiding re-triggering
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* enhancements, refactorings
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* do not flood of healthy checks
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* do not list obvious backends as text backends
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* tests fixups
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Drop redundant healthcheck
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* enhancements, refactorings
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat: wire min_p
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat: inferencing defaults
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(refactor): re-use iterative parser
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore: generate automatically inference defaults from unsloth
Instead of trying to re-invent the wheel and maintain here the inference
defaults, prefer to consume unsloth ones, and contribute there as
necessary.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore: apply defaults also to models installed via gallery
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore: be consistent and apply fallback to all endpoint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(openresponses): do not omit required fields summary and id
* fix(openresponses): ensure ORItemParam.Summary is never null
Normalize Summary to an empty slice at serialization chokepoints
(sendSSEEvent, bufferEvent, buildORResponse) so it always serializes
as [] instead of null.
Closes#9047
* feat(functions): add peg-based parsing
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat: support returning toolcalls directly from backends
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore: do run PEG only if backend didn't send deltas
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat: add standalone and agentic functionalities
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* expose agents via responses api
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* debug
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* retry instead of re-computing a response
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(openresponses): support reasoning blocks
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* allow to disable reasoning, refactor common logic
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Add option to only strip reasoning
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Add configurations for custom reasoning tokens
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
