* 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>
