`GoogleGenAiChatModel` and `GoogleGenAiStreamingChatModel` expose a
fixed set of generation options through their builders. When the
underlying Google Gen AI Java SDK adds a new `GenerateContentConfig`
option, it cannot be used through the integration until a matching
builder method is added and released.
This adds an escape hatch,
`generateContentConfigCustomizer(Consumer<GenerateContentConfig.Builder>)`,
on both chat model builders:
```java
GoogleGenAiChatModel.builder()
.modelName("gemini-2.5-flash")
.generateContentConfigCustomizer(config -> config.responseLogprobs(true).logprobs(5))
.build();
```
The customizer is applied after the integration has populated the config
(generation parameters, tools, system instruction, etc.) and just before
it is built, so a caller can set any SDK option (including ones not yet
exposed here) or override an existing value, while the per-request tools
and system instruction are preserved.
This addresses the configuration side of the suggestion from the
integration review in #4658. The response side of that discussion
already shipped as `GoogleGenAiChatResponseMetadata.rawResponse()`; this
adds the matching request side, which isn't in the module yet.
A note on the chosen shape: the review mentioned accepting a
`GenerateContentConfig` object directly. That does not work well here,
because tools and the system instruction are derived per request, so a
model-level config object would drop them. A customizer applied to the
already-assembled builder keeps them intact and still lets a caller
reach any SDK option. If you'd prefer a different shape (for example
accepting a full config object), or a different method name, I'm happy
to adjust.
Scope: this covers the sync and streaming chat models.
`GoogleGenAiBatchChatModel` is left as is; happy to extend the same
option to it in a follow-up if that's wanted.
Addresses #4658
### Changes
- `GoogleGenAiConfigBuilder`: add a static `applyCustomizer(config,
customizer)` that returns the config unchanged when the customizer is
`null`, otherwise re-opens it via `toBuilder()`, applies the customizer,
and rebuilds. `buildConfig` is left untouched, so current callers
(including `GoogleGenAiBatchChatModel`) are unaffected.
- `GoogleGenAiChatModel` and `GoogleGenAiStreamingChatModel`: add the
`generateContentConfigCustomizer(...)` builder option, and run the
assembled config through `applyCustomizer` just before the request.
- Docs: a "customizing the `GenerateContentConfig`" section in
`google-genai.md`.
- Unit tests: `applyCustomizer` is applied, can override a value set by
the builder, preserves tools, and is a no-op when `null`; plus a
chat-path test (offline, no network) proving the model actually invokes
the customizer while assembling the request.
- Integration tests (`GOOGLE_AI_GEMINI_API_KEY`-gated, like the rest of
this module): a live call on both the sync and streaming model with a
customizer set, asserting the request goes through (the customized
config reaches the transport without breaking the request).
### Testing
`mvn -pl langchain4j-google-genai test` -> 124 passing, 0 failures. The
two new ITs are key-gated and were run against `gemini-2.5-flash` (both
pass). `spotless:check` passes.
### Checklist
- [x] No breaking changes (additive; the new option defaults to no-op).
- [x] Unit tests added (apply, override, preserve tools, null no-op).
- [x] Integration tests added on both models (live call with a
customizer).
- [x] Applied to both the sync and streaming chat models.
- [x] Ran the module build and tests locally (green) + spotless.
---------
Co-authored-by: Dmytro Liubarskyi <ljubarskij@gmail.com>
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## Issue
<!-- Please specify the ID of the issue this PR is addressing. For
example: "Closes #1234" or "Fixes #1234" -->
Closes #
## Change
This work has been inspired by the discussion in this issue on the
quarkus-langchain4j extension
https://github.com/quarkiverse/quarkus-langchain4j/issues/2638
However the task of improving the Human-in-the-Loop suspension is
something that we already discussed and that in my opinion belong mostly
to the langchain4j implementation.
This pull request:
- Adds the ability to suspend an agentic system when human input is
required, checkpoint its state to a persistent store, and resume it
later — even after a process restart or crash. Users choose the behavior
by returning either a `SuspendedResponse` (suspend and release the
thread) or a `PendingResponse` (block and wait in-process) from their
human-in-the-loop handler.
- Supports nested and parallel suspension points within the same
workflow, each independently resumable by response ID.
- Provides a `completePendingResponse(value)` convenience method on
`AgenticScope` for the common single-response case.
- Works with both the programmatic API (`HumanInTheLoop.builder()`) and
the declarative `@HumanInTheLoop` annotation.
You can find more details on how this works giving a look to the updated
documentation.
## General checklist
<!-- Please double-check the following points and mark them like this:
[X] -->
- [X] There are no breaking changes (API, behaviour)
- [X] I have added unit and/or integration tests for my change
- [X] The tests cover both positive and negative cases
- [X] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [ ] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green
- [ ] I have added/updated the
[documentation](https://github.com/langchain4j/langchain4j/tree/main/docs/docs)
- [ ] I have added an example in the [examples
repo](https://github.com/langchain4j/langchain4j-examples) (only for
"big" features)
- [ ] I have added/updated [Spring Boot
starter(s)](https://github.com/langchain4j/langchain4j-spring) (if
applicable)
## Checklist for adding new maven module
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have added my new module in the root `pom.xml` and
`langchain4j-bom/pom.xml`
## Checklist for adding new embedding store integration
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreIT` that extends
from either `EmbeddingStoreIT` or `EmbeddingStoreWithFilteringIT`
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreRemovalIT` that
extends from `EmbeddingStoreWithRemovalIT`
## Checklist for changing existing embedding store integration
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have manually verified that the
`{NameOfIntegration}EmbeddingStore` works correctly with the data
persisted using the latest released version of LangChain4j
---------
Co-authored-by: Dmytro Liubarskyi <ljubarskij@gmail.com>
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## Issue
<!-- Please specify the ID of the issue this PR is addressing. For
example: "Closes #1234" or "Fixes #1234" -->
Closes#5760
## Change
The `@A2AClientAgent` annotation previously required `a2aServerUrl` as a
compile-time string literal, making it impossible to configure the URL
per environment (dev, staging, production).
This PR adds an `@A2AServerUrlSupplier` companion annotation — a static
method that returns the URL at agent construction time — following the
same supplier pattern already used by `@McpClientSupplier` for
`@McpClientAgent`.
It also bumps the A2A client to the latest `1.1.0.Final` version.
## General checklist
<!-- Please double-check the following points and mark them like this:
[X] -->
- [X] There are no breaking changes (API, behaviour)
- [X] I have added unit and/or integration tests for my change
- [X] The tests cover both positive and negative cases
- [X] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [ ] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green
- [ ] I have added/updated the
[documentation](https://github.com/langchain4j/langchain4j/tree/main/docs/docs)
- [ ] I have added an example in the [examples
repo](https://github.com/langchain4j/langchain4j-examples) (only for
"big" features)
- [ ] I have added/updated [Spring Boot
starter(s)](https://github.com/langchain4j/langchain4j-spring) (if
applicable)
## Checklist for adding new maven module
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have added my new module in the root `pom.xml` and
`langchain4j-bom/pom.xml`
## Checklist for adding new embedding store integration
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreIT` that extends
from either `EmbeddingStoreIT` or `EmbeddingStoreWithFilteringIT`
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreRemovalIT` that
extends from `EmbeddingStoreWithRemovalIT`
## Checklist for changing existing embedding store integration
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have manually verified that the
`{NameOfIntegration}EmbeddingStore` works correctly with the data
persisted using the latest released version of LangChain4j
## Issue
No dedicated issue. This implements the optional follow-up explicitly
suggested by the author of #5465 in the merged commit message:
> "For full parity, these four types could also gain a `jsonSchema()`
(as `Integer`/`Long`/`Float`/`Double` have) to support structured
outputs. I left that out to keep this PR focused on the
parsing-consistency bug ..."
## Change
`IntegerOutputParser`, `LongOutputParser`, `FloatOutputParser` and
`DoubleOutputParser` implement `jsonSchema()`, which lets them
participate in structured outputs (`RESPONSE_FORMAT_JSON_SCHEMA`). Their
sibling numeric parsers `ByteOutputParser`, `ShortOutputParser`,
`BigIntegerOutputParser` and `BigDecimalOutputParser` did not, so they
fell back to the default `Optional.empty()`.
This PR adds `jsonSchema()` to the four remaining numeric parsers,
mirroring the existing implementations:
- `Byte`, `Short`, `BigInteger` → `"integer"` schema with an integer
`value` property (same as `Integer`/`Long`)
- `BigDecimal` → `"number"` schema with a number `value` property (same
as `Float`/`Double`)
New unit tests (`json_schema()`) were added to each of the four parser
tests, following the existing test style. Also updated
`ServiceOutputParserTest.jsonSchema()` to reflect the new support (moved
the four types from "not supported" assertions to "present" assertions).
## General checklist
- [ ] There are no breaking changes (API, behaviour) — purely additive;
the default was `Optional.empty()`, now returns a schema
- [X] I have added unit and/or integration tests for my change
- [X] The tests cover both positive and negative cases
- [X] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [X] I have manually run all the unit and integration tests in the core
and main modules — ran the full `service/output` test suite (including
`ServiceOutputParserTest`) + `spotless:check` passes
- [x] I have added/updated the documentation — not applicable (internal
parser behaviour)
- [ ] I have added an example in the examples repo — not applicable
- [ ] I have added/updated Spring Boot starter(s) — not applicable
## Verification
```
mvn -pl langchain4j test -Dtest='ByteOutputParserTest,ShortOutputParserTest,BigIntegerOutputParserTest,BigDecimalOutputParserTest,ServiceOutputParserTest'
# all tests pass
mvn -pl langchain4j spotless:check
# BUILD SUCCESS
```
---------
Co-authored-by: gus.guo <gus.guo@tec-do.com>
Co-authored-by: Dmytro Liubarskyi <ljubarskij@gmail.com>
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## Issue
<!-- Please specify the ID of the issue this PR is addressing. For
example: "Closes #1234" or "Fixes #1234" -->
Closes #
## Change
<!-- Please describe the changes you made. -->
## General checklist
<!-- Please double-check the following points and mark them like this:
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- [X] There are no breaking changes (API, behaviour)
- [X] I have added unit and/or integration tests for my change
- [X] The tests cover both positive and negative cases
- [X] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [ ] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green
- [ ] I have added/updated the
[documentation](https://github.com/langchain4j/langchain4j/tree/main/docs/docs)
- [ ] I have added an example in the [examples
repo](https://github.com/langchain4j/langchain4j-examples) (only for
"big" features)
- [ ] I have added/updated [Spring Boot
starter(s)](https://github.com/langchain4j/langchain4j-spring) (if
applicable)
## Checklist for adding new maven module
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have added my new module in the root `pom.xml` and
`langchain4j-bom/pom.xml`
## Checklist for adding new embedding store integration
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreIT` that extends
from either `EmbeddingStoreIT` or `EmbeddingStoreWithFilteringIT`
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreRemovalIT` that
extends from `EmbeddingStoreWithRemovalIT`
## Checklist for changing existing embedding store integration
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have manually verified that the
`{NameOfIntegration}EmbeddingStore` works correctly with the data
persisted using the latest released version of LangChain4j
---------
Co-authored-by: Dmytro Liubarskyi <ljubarskij@gmail.com>
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## Issue
<!-- Please specify the ID of the issue this PR is addressing. For
example: "Closes #1234" or "Fixes #1234" -->
Closes #
## Change
Agentic patterns define a `beforeCall` method that didn't have a
counterpart in the declarative API. With this pull request I also added
a new `writeStateIfAbsent` method on the `AgenticScope` and tried to
clarify a bit the documentation of the declarative API itself.
## General checklist
<!-- Please double-check the following points and mark them like this:
[X] -->
- [X] There are no breaking changes (API, behaviour)
- [X] I have added unit and/or integration tests for my change
- [X] The tests cover both positive and negative cases
- [X] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [ ] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green
- [x] I have added/updated the
[documentation](https://github.com/langchain4j/langchain4j/tree/main/docs/docs)
- [ ] I have added an example in the [examples
repo](https://github.com/langchain4j/langchain4j-examples) (only for
"big" features)
- [ ] I have added/updated [Spring Boot
starter(s)](https://github.com/langchain4j/langchain4j-spring) (if
applicable)
## Checklist for adding new maven module
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have added my new module in the root `pom.xml` and
`langchain4j-bom/pom.xml`
## Checklist for adding new embedding store integration
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreIT` that extends
from either `EmbeddingStoreIT` or `EmbeddingStoreWithFilteringIT`
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreRemovalIT` that
extends from `EmbeddingStoreWithRemovalIT`
## Checklist for changing existing embedding store integration
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have manually verified that the
`{NameOfIntegration}EmbeddingStore` works correctly with the data
persisted using the latest released version of LangChain4j
---------
Co-authored-by: Dmytro Liubarskyi <ljubarskij@gmail.com>
## Issue
Progresses #3916
## Change
Adds `MistralAiBatchChatModel`, an implementation of the core
`BatchChatModel` interface for the
[Mistral Batch API](https://docs.mistral.ai/capabilities/batch/), which
processes many chat requests
asynchronously at 50% of the standard per-token price. It follows the
existing
`GoogleAiGeminiBatchChatModel`, so both providers expose the same
`submit` / `retrieve` / `cancel` /
`list` surface.
Each `ChatRequest` is built through the same path `MistralAiChatModel`
uses (`createMistralAiRequest`),
so per-request parameters (temperature, tools, response format, etc.)
behave identically in a batch and
in a single call. Requests are submitted inline, so no separate file
upload is needed; once a job
completes, its results are downloaded from the `output_file` /
`error_file` and re-sorted back to
submission order using generated `custom_id`s. Mistral's job statuses
map onto the core `BatchState`:
| Mistral status | `BatchState` |
|---|---|
| `QUEUED` | `PENDING` |
| `RUNNING`, `CANCELLATION_REQUESTED` | `RUNNING` |
| `SUCCESS` | `SUCCEEDED` |
| `FAILED` | `FAILED` |
| `TIMEOUT_EXCEEDED` | `EXPIRED` |
| `CANCELLED` | `CANCELLED` |
The batch operations (create / retrieve / cancel / list jobs, and
downloading a result file) are added
to the existing hand-rolled `MistralAiClient`. They are non-abstract
methods that throw
`UnsupportedFeatureException` by default, so existing `MistralAiClient`
implementations keep compiling
and are unaffected. No new dependency is introduced.
Scope:
- Chat requests only.
- One model per job (a Mistral constraint): the model configured on the
batch model applies to every
request in the batch.
- Inline submission (the documented path for batches under 10,000
requests); the file-upload submission
path is not included.
Verified with unit tests against a mock HTTP server custom-id ordering,
success/error mapping,
`output_file` + `error_file` merge, the running-state short-circuit (no
results fetched until the job
produces them), status-code failures, and pagination and with a
key-gated integration test
(`MistralAiBatchChatModelIT`) run end-to-end against the live Batch API
(submit → poll to completion →
read results, plus cancel and list).
## General checklist
- [X] There are no breaking changes (API, behaviour)
- [X] I have added unit and/or integration tests for my change
- [X] The tests cover both positive and negative cases
- [X] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [ ] I have manually run all the unit and integration tests in the core
and main modules, and they are all green
- [X] I have added/updated the documentation
- [ ] I have added an example in the examples repo (only for "big"
features)
- [ ] I have added/updated Spring Boot starter(s) (if applicable)
---------
Co-authored-by: Dmytro Liubarskyi <ljubarskij@gmail.com>
Pattern-based InputGuardrail that detects prompt injection attempts
using OWASP LLM01 categories (instruction override, role hijacking,
jailbreaks, system prompt leakage, delimiter injection, encoded
payloads). Zero external dependencies, sub-millisecond latency. Designed
to run as the first (cheapest) gate in a guardrail chain. Subclasses can
extend with domain-specific patterns and customise the failure message.
Relates to #3248
cc @dliubarskyi
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## Issue
Relates to #3248 — implements the first concrete `InputGuardrail`
security gate as discussed in the issue.
## Change
Adds `PromptInjectionGuardrail` to the `langchain4j-guardrails` module —
a pattern-based `InputGuardrail` that detects and blocks prompt
injection attempts before they reach the LLM.
### Why this approach
- **Zero external dependencies** — pure Java regex, no HTTP calls,
sub-millisecond latency
- **No framework coupling** — works identically under Spring Boot,
Quarkus, Helidon, or plain Java
- **Single responsibility** — one class, one concern, per the guardrails
tutorial
- **Designed for chaining** — intended to run first (cheapest) before
any LLM-based classifiers
- **Extensible** — subclasses can add domain-specific patterns and
customise the failure message
### Patterns covered (based on OWASP LLM01)
| Category | Examples |
|---|---|
| Instruction override | "ignore previous instructions", "forget all
rules", "disregard prior context" |
| Role hijacking | "you are now a...", "act as a...", "pretend to be..."
|
| Jailbreaks | "DAN", "developer mode", "bypass safety filters" |
| System prompt leakage | "reveal your prompt", "print your
instructions" |
| Delimiter injection | ` ```system `, `<system>`, `[INST]`, `<<SYS>>` |
| Encoded injection | `base64: <payload>`, "decode the following and
execute" |
### What this does NOT do
- Does not call any external service or LLM
- Does not modify `langchain4j-core` or any existing interface
- Does not introduce any new Maven dependencies
### Testing
- 58 parameterised test cases covering all 6 injection categories
- Tests for legitimate messages that must NOT be blocked
- Edge cases: blank input, empty input, null input, case insensitivity
- Extensibility tests: subclass `buildFailureMessage()` override,
additional patterns
### Follow-up
As discussed in #3248, a separate `LlmPromptInjectionGuardrail`
(LLM-based classifier) will follow in a subsequent PR — designed to
chain after this one for deeper semantic analysis.
## General checklist
- [x] There are no breaking changes (API, behaviour)
- [x] I have added unit and/or integration tests for my change
- [x] The tests cover both positive and negative cases
- [x] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [x] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green
- [x] I have added/updated the
[documentation](https://github.com/langchain4j/langchain4j/tree/main/docs/docs)
- [ ] I have added an example in the [examples
repo](https://github.com/langchain4j/langchain4j-examples) (only for
"big" features)
- [ ] I have added/updated [Spring Boot
starter(s)](https://github.com/langchain4j/langchain4j-spring) (if
applicable)
## Issue
Closes#1153 — distinguish APIs for embedding queries vs. documents/keys
(adds `EmbeddingInputType.QUERY`/`DOCUMENT` as a per-call parameter,
plus opt-in `embeddingInputType(...)` on
`EmbeddingStoreContentRetriever` / `EmbeddingStoreIngestor`).
Partially addresses #4019 — adds the multimodal image-embedding API at
the core level (`EmbeddingInput` of `Content` parts) and wires Cohere,
Voyage, Jina, Google (Gemini Embedding 2), and Bedrock Titan; does
not implement it for `OnnxEmbeddingModel`.
Relates to #5142 — provider-specific / per-call parameters for OpenAI
embeddings (`OpenAiEmbeddingRequestParameters`: `user`,
`encodingFormat`, `customParameters`; e.g. NVIDIA NIM `input_type` via
custom
parameters).
Relates to #4273 — observability for `EmbeddingModel` via listeners
(`EmbeddingModelListener` + request/response/error contexts, wired
across providers).
## Change
Introduces an `EmbeddingModel.embed(EmbeddingRequest) →
EmbeddingResponse` API, structured like `ChatModel`'s request/response
API, so embeddings can carry **per-call parameters** and **multimodal
inputs** and
participate in **observability**. Everything is additive and
`@Experimental`; the existing `embed(String)` / `embed(TextSegment)` /
`embedAll(List)` methods keep working unchanged.
### Core (`langchain4j-core`)
- New request/response types: `EmbeddingRequest`, `EmbeddingResponse`,
`EmbeddingResponseMetadata`, `EmbeddingRequestParameters` (+
`DefaultEmbeddingRequestParameters` and typed `EmbeddingParameter<T>`
tokens), `EmbeddingInput`, `EmbeddingInputType`.
- New default methods on `EmbeddingModel`: `embed(EmbeddingRequest)`,
`doEmbed(...)`, `defaultRequestParameters()`, `supportedParameters()`,
`supportedContentTypes()`, `provider()`, `listeners()`.
- **Strict opt-in / fail-fast:** per-call parameters and content types
are token/type-checked; a request that uses something the model doesn't
declare is rejected with `UnsupportedFeatureException` instead of
being silently ignored. `overrideWith` preserves the provider-specific
parameters subtype (as on the chat side).
- **Multimodal:** an `EmbeddingInput` is an ordered list of `Content`
parts (text/image); models fuse them into one embedding (or
one-per-item, per provider). Modality is auto-detected — no manual flag.
- **Observability:** `EmbeddingModelListener` + request/response/error
contexts (same shape as `ChatModelListener`), fired inline from
`embed(EmbeddingRequest)`. `addListener(...)` still works.
- **RAG opt-in:** `EmbeddingStoreContentRetriever` and
`EmbeddingStoreIngestor` gain an optional `embeddingInputType(...)`
(QUERY / DOCUMENT). Default behavior is unchanged (no input type sent).
- `ModelProvider`: added `COHERE`, `VOYAGE_AI`, `JINA`, with matching
OpenTelemetry `gen_ai.provider.name` mappings (`cohere` is a well-known
OTel value; `voyage_ai` / `jina` are custom, as permitted by the
spec).
### Providers
- **OpenAI** (dimensions, `user`/`encodingFormat`/custom params),
**Cohere** (Embed v4 multimodal + input types), **Voyage** (multimodal +
input types), **Jina** (CLIP multimodal), **Google AI Gemini** (input
types; **Gemini Embedding 2** multimodal), **Amazon Bedrock Titan**
(multimodal).
- **Google Gen AI** (`langchain4j-google-genai`): input type → SDK
`task_type`, per-call dimensions → `outputDimensionality`, `provider()`,
listeners.
- **Ollama**: text-only — `provider()` + listeners (per-call params
correctly fail fast).
- **In-process models** (ONNX / `AbstractInProcessEmbeddingModel`):
already work via the default `doEmbed→embedAll` bridge (text-only,
image/param requests fail fast); observability via `addListener(...)`.
No
code change (no builders to wire listeners into, no dedicated
`ModelProvider`).
- **Gemini Embedding 2** dropped the `task_type` parameter, so input
types are applied as prompt instructions (`task: search result | query:
…` / `title: none | text: …`) automatically; `gemini-embedding-001`
still uses `task_type`.
- `modelName` in the response metadata reflects the API-reported model
where the provider returns one (OpenAI/Voyage/Jina), falling back to the
configured name.
### Tests
- `AbstractEmbeddingModelIT` — a shared IT base (like
`AbstractChatModelIT`) covering the new API, convenience methods,
listeners, and fail-fast; each provider adds a small
`common/…EmbeddingModelIT` that
parameterizes it and declares its capabilities via `supports*()`
overrides.
- Mock-based unit tests per provider for wire format / routing /
fail-fast (run in CI without keys), plus core value-type and listener
tests.
### Docs
- Embedding-model section in the RAG tutorial (request/response,
multimodal, query-vs-document opt-in), the EmbeddingModel listener
section in the Observability tutorial, the embedding contribution
guidance in
`CONTRIBUTING.md`, and the six provider integration pages.
### Notes
- `EmbeddingResponseMetadata` intentionally has no `finishReason`
(embeddings have no finish reason). No real provider is affected: the
only provider that emits `STOP` (Cloudflare WorkersAI) overrides the
convenience methods directly, and every other provider always returned
`null` here.
- `revapi.json` suppressions were added where the new (non-breaking)
types are exposed in provider APIs.
## General checklist
- [x] There are no breaking changes (API, behaviour)
- [x] I have added unit and/or integration tests for my change
- [x] The tests cover both positive and negative cases
- [x] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [x] I have added/updated the documentation
- [ ] I have manually run all the unit and integration tests in the core
and main modules, and they are all green
- [ ] I have added an example in the examples repo (only for "big"
features)
- [ ] I have added/updated Spring Boot starter(s) (if applicable)
---------
Co-authored-by: agent <agent@langchain4j.dev>
## Issue
Closes#5727
## Change
`AnthropicMapper` already honored a `cache_control: "ephemeral"`
attribute on `UserMessage` (#4487). In an agentic tool loop,
`AiServices` resends the growing conversation tail (`AiMessage` +
`ToolExecutionResultMessage`) on every call, but neither of those
message types could be marked for caching, so every accumulated tool
result was rebilled at full price on each turn.
This extends the same `cache_control` handling to `AiMessage` and
`ToolExecutionResultMessage`, mirroring the existing `UserMessage`
behavior:
```java
AiMessage aiMessage = someAiMessage.toBuilder()
.attributes(Map.of("cache_control", "ephemeral"))
.build();
```
The cache marker is applied to the last content block of the message
(for `ToolExecutionResultMessage`, the `tool_result` block itself).
`AnthropicToolResultContent` and `AnthropicToolUseContent` gained
`cacheControl`-aware constructor/builder overloads so the marker is set
at construction time, consistent with how `AnthropicTextContent` already
does it for `UserMessage`.
## General checklist
- [X] There are no breaking changes (API, behaviour)
- [X] I have added unit and/or integration tests for my change
- [X] The tests cover both positive and negative cases
- [X] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [ ] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green
- [X] I have added/updated the
[documentation](https://github.com/langchain4j/langchain4j/tree/main/docs/docs)
- [ ] I have added an example in the [examples
repo](https://github.com/langchain4j/langchain4j-examples) (only for
"big" features)
- [ ] I have added/updated [Spring Boot
starter(s)](https://github.com/langchain4j/langchain4j-spring) (if
applicable)
<!--
Thank you so much for your contribution!
Please fill in all the sections below.
Please open the PR as ready for review (not as a draft), with tests and
documentation already included.
Please note that PRs with breaking changes, or without tests and
documentation, will be rejected.
Please note that PRs will be reviewed based on the priority of the
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Please refrain from pinging and asking when it will be reviewed. Thank
you for understanding!
-->
## Issue
<!-- Please specify the ID of the issue this PR is addressing. For
example: "Closes #1234" or "Fixes #1234" -->
Closes #
## Change
This is a complete rework of the `AgentRegistry` implemented by this
pull request github.com/langchain4j/langchain4j/pull/5551
The scope of this second implementation is quite different and less
invasive than the original one since it doesn't care of providing a
mechanism for dynamic discovery and rewiring of agents for an ongoing
execution, but only to provide a thin layer of integration with external
agents providers.
The new section added to the documentation should better clarify how
this works.
## General checklist
<!-- Please double-check the following points and mark them like this:
[X] -->
- [X] There are no breaking changes (API, behaviour)
- [X] I have added unit and/or integration tests for my change
- [X] The tests cover both positive and negative cases
- [X] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [ ] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green
- [ ] I have added/updated the
[documentation](https://github.com/langchain4j/langchain4j/tree/main/docs/docs)
- [ ] I have added an example in the [examples
repo](https://github.com/langchain4j/langchain4j-examples) (only for
"big" features)
- [ ] I have added/updated [Spring Boot
starter(s)](https://github.com/langchain4j/langchain4j-spring) (if
applicable)
## Checklist for adding new maven module
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have added my new module in the root `pom.xml` and
`langchain4j-bom/pom.xml`
## Checklist for adding new embedding store integration
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreIT` that extends
from either `EmbeddingStoreIT` or `EmbeddingStoreWithFilteringIT`
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreRemovalIT` that
extends from `EmbeddingStoreWithRemovalIT`
## Checklist for changing existing embedding store integration
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have manually verified that the
`{NameOfIntegration}EmbeddingStore` works correctly with the data
persisted using the latest released version of LangChain4j
<!--
Thank you so much for your contribution!
Please fill in all the sections below.
Please open the PR as ready for review (not as a draft), with tests and
documentation already included.
Please note that PRs with breaking changes, or without tests and
documentation, will be rejected.
Please note that PRs will be reviewed based on the priority of the
issues they address.
We ask for your patience. We are doing our best to review your PR as
quickly as possible.
Please refrain from pinging and asking when it will be reviewed. Thank
you for understanding!
-->
## Issue
<!-- Please specify the ID of the issue this PR is addressing. For
example: "Closes #1234" or "Fixes #1234" -->
Closes#5674
## Change
<!-- Please describe the changes you made. -->
## General checklist
<!-- Please double-check the following points and mark them like this:
[X] -->
- [X] There are no breaking changes (API, behaviour)
- [X] I have added unit and/or integration tests for my change
- [X] The tests cover both positive and negative cases
- [X] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [ ] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green
- [ ] I have added/updated the
[documentation](https://github.com/langchain4j/langchain4j/tree/main/docs/docs)
- [ ] I have added an example in the [examples
repo](https://github.com/langchain4j/langchain4j-examples) (only for
"big" features)
- [ ] I have added/updated [Spring Boot
starter(s)](https://github.com/langchain4j/langchain4j-spring) (if
applicable)
## Checklist for adding new maven module
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have added my new module in the root `pom.xml` and
`langchain4j-bom/pom.xml`
## Checklist for adding new embedding store integration
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreIT` that extends
from either `EmbeddingStoreIT` or `EmbeddingStoreWithFilteringIT`
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreRemovalIT` that
extends from `EmbeddingStoreWithRemovalIT`
## Checklist for changing existing embedding store integration
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have manually verified that the
`{NameOfIntegration}EmbeddingStore` works correctly with the data
persisted using the latest released version of LangChain4j
GoogleGenAiChatModel` and its streaming/batch counterparts can already
consume a context cache via `cachedContent(name)`, but the cache itself
has to be created out-of-band because the module exposes no way to
create or manage one. The current docs reflect this: they assume the
cache was already created "using the official Google Gen AI SDK or API"
and only cover passing its name in.
Context caching stores a large reused prefix (a long document, a big
system instruction) on the server, so later requests can reference it
instead of resending it each call, which reduces input-token cost and
latency. This adds `GoogleGenAiCaches`, a standalone helper that wraps
the `com.google.genai` SDK's `Caches` client, so that prefix can be
created and managed from LangChain4j rather than out-of-band:
```java
GoogleGenAiCaches caches = GoogleGenAiCaches.builder()
.apiKey(System.getenv("GOOGLE_AI_GEMINI_API_KEY"))
.build();
CachedContent cache = caches.createCache(
"gemini-2.5-flash",
List.of(
SystemMessage.from("You answer questions about the attached document."),
UserMessage.from(longDocumentText)),
Duration.ofHours(1));
ChatModel gemini = GoogleGenAiChatModel.builder()
.apiKey(System.getenv("GOOGLE_AI_GEMINI_API_KEY"))
.modelName("gemini-2.5-flash")
.cachedContent(cache.name().orElseThrow())
.build();
```
It mirrors the existing `GoogleGenAiFiles` helper: same builder
(`apiKey` / `apiEndpoint` / `customHeaders` / `client`), same client
construction via `GoogleGenAiClientFactory`, and thin SDK-native return
types. `createCache` takes LangChain4j `ChatMessage`s and builds the
cached content through the module's `GoogleGenAiContentMapper`, so
callers stay in the `ChatMessage` domain instead of assembling Google
`Content` objects.
The Python counterpart exposes the creation side the same way:
`langchain-google-genai` has a public `create_context_cache` helper that
builds the cache from LangChain messages and returns the name to pass as
`cached_content`.
Lifecycle covered: `createCache` / `getCache` / `listCaches` /
`updateCacheTtl` / `deleteCache`. If you'd prefer a smaller surface,
this trims naturally to just `createCache` (the `ChatMessage` mapping is
where the integration value is), leaving the rest of the lifecycle to
the SDK client.
Closes#5680.
Related: #5676 covers the consumption side on this module (a per-request
`cachedContent` override); this PR covers creating the cache that
parameter refers to. #5493 tracks the same creation/management need for
the older `google-ai-gemini` module.
### Changes
- `GoogleGenAiCaches`: new standalone helper wrapping `client.caches`
(create/get/list/updateCacheTtl/delete), mirroring `GoogleGenAiFiles`.
Cache content is built from `ChatMessage`s via
`GoogleGenAiContentMapper`.
- Docs: a "Creating and managing caches" subsection under "Cached
Content Support" in `google-genai.md` (create -> reuse via
`cachedContent` -> manage lifecycle).
### Testing
- `mvn -pl langchain4j-google-genai test` -> 121 passing, 0 failures.
Includes a new offline unit test
(`GoogleGenAiCachesTest`, 2 tests) covering the `ChatMessage` ->
`CreateCachedContentConfig` mapping, including the
null-ttl and no-system-message edge cases.
- Integration test `GoogleGenAiCachesIT` (gated on
`GOOGLE_AI_GEMINI_API_KEY`, like the rest of the module) exercises
the full create -> get -> list -> update -> delete lifecycle. **Run
against the real API on `gemini-2.5-flash`
(1/1 passing).** Explicit context caching requires a paid tier, so the
IT skips cleanly on a free-tier key (its
cache storage limit is 0); it cleans up the created cache in a `finally`
block.
- `spotless:check` passes.
### Checklist
- [x] No breaking changes (purely additive; one new class + docs).
- [x] Offline unit tests + a key-gated integration test (run live
against the real API).
- [x] Mirrors the existing `GoogleGenAiFiles` helper (builder, client
construction, thin SDK-native types).
- [x] Ran the module build and tests locally (green) + spotless.
## Issue
Closes#5248
## Change
The `structured-outputs` tutorial uses example text describing a person
named "John" with realistic-sounding attributes (42 years old, 1.75m
tall). As diagnosed by @PSchmitz-Valckenberg in #5248, this example text
gets indexed by `chat.langchain4j.dev`'s RAG pipeline as a regular
documentation chunk. When users ask the chat questions like *"how tall
is John?"*, the retriever finds a strong semantic match and the model
confidently answers based on the example data.
This PR applies the symptom-level fix suggested in the issue thread:
replace the realistic example with content that is unambiguously
fictional, so retrieval cannot mistake it for factual reference
material.
Specifically:
- The example text now describes a clearly fictional character ("Eldwin
Brightblade, 412 years old, court wizard of Aelyria.").
- The introductory sentence explicitly frames the input as *"describing
a fictional character"* to make the intent obvious to both human readers
and any downstream RAG indexer.
- All three occurrences of the example (intro narrative, the low-level
`ChatRequest` example, and the AI-Services example) are updated
consistently.
- The corresponding `// {"name":"John",...}` and `Person[name=John,...]`
output comments are updated to match the new values, so the example
output still reflects what the code would actually print.
As noted in the issue discussion, a more robust fix would be at the
ingestion / system-prompt layer of the chat app itself, but that lives
outside this repository. This PR addresses what can be fixed here in the
docs.
No code changes, no behavior changes, no test impact.
## General checklist
- [x] There are no breaking changes (API, behaviour)
- [ ] I have added unit and/or integration tests for my change - _N/A,
docs-only change_
- [ ] The tests cover both positive and negative cases - _N/A_
- [ ] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green - _N/A, no code
touched_
- [ ] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green - _N/A, no code touched_
- [x] I have added/updated the
[documentation](https://github.com/langchain4j/langchain4j/tree/main/docs/docs)
- _this PR is the documentation update_
- [ ] I have added an example in the [examples
repo](https://github.com/langchain4j/langchain4j-examples) (only for
"big" features) - _N/A_
- [ ] I have added/updated [Spring Boot
starter(s)](https://github.com/langchain4j/langchain4j-spring) (if
applicable) - _N/A_
## Issue
Closes#5658
## Change
Adds opt-in support for Anthropic's `cache-diagnosis-2026-04-07` beta
feature, which reports why a prompt-cache hit was missed instead of only
showing `usage.cacheReadInputTokens` drop to zero.
- `AnthropicChatRequestParameters`: new `returnCacheDiagnostics` +
`previousMessageId` (per-request, mirrors `userId`)
- `AnthropicChatResponseMetadata#cacheDiagnostics()` exposes the result
(sync and streaming) as a new `AnthropicCacheDiagnostics` type
- Request/response shape wired through new internal API POJOs
(`AnthropicDiagnosticsParameters`, `AnthropicDiagnostics`,
`AnthropicCacheMissReason`) and the mapper
- No behavior change when the feature isn't enabled (no extra request
field, no allocation)
## General checklist
- [X] There are no breaking changes (API, behaviour)
- [X] I have added unit and/or integration tests for my change
- [X] The tests cover both positive and negative cases
- [X] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [ ] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green
- [X] I have added/updated the
[documentation](https://github.com/langchain4j/langchain4j/tree/main/docs/docs)
- [ ] I have added an example in the [examples
repo](https://github.com/langchain4j/langchain4j-examples) (only for
"big" features)
- [ ] I have added/updated [Spring Boot
starter(s)](https://github.com/langchain4j/langchain4j-spring) (if
applicable)
---------
Co-authored-by: Dmytro Liubarskyi <ljubarskij@gmail.com>
## Issue
Closes#4907
## Change
This PR adds request-level image config override support for
`GoogleAiGeminiChatModel`.
### What was added
- Added provider-specific request parameters class:
- `GoogleAiGeminiChatRequestParameters`
- supports:
- `aspectRatio(String)`
- `imageAspectRatio(String)` (alias)
- `imageSize(String)`
- Added merge behavior via `overrideWith/defaultedBy` for
Gemini-specific parameters.
- Updated `BaseGeminiChatModel` request building logic to resolve
effective image config with precedence:
- `request-level` > `builder-level` > `null`
- Updated default chat parameters construction to preserve
Gemini-specific request parameters through the common `ChatModel`
parameter merge flow.
- Added/updated unit tests in `GoogleAiGeminiChatModelTest`:
- request-level image config overrides builder-level defaults
- builder-level image config is used when request-level values are
absent
## General checklist
- [X] There are no breaking changes (API, behaviour)
- [X] I have added unit and/or integration tests for my change
- [X] The tests cover both positive and negative cases
- [X] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [ ] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green
- [ ] I have added/updated the
[documentation](https://github.com/langchain4j/langchain4j/tree/main/docs/docs)
- [ ] I have added an example in the [examples
repo](https://github.com/langchain4j/langchain4j-examples) (only for
"big" features)
- [ ] I have added/updated [Spring Boot
starter(s)](https://github.com/langchain4j/langchain4j-spring) (if
applicable)
## Checklist for adding new maven module
- [ ] I have added my new module in the root `pom.xml` and
`langchain4j-bom/pom.xml`
## Checklist for adding new embedding store integration
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreIT` that extends
from either `EmbeddingStoreIT` or `EmbeddingStoreWithFilteringIT`
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreRemovalIT` that
extends from `EmbeddingStoreWithRemovalIT`
## Checklist for changing existing embedding store integration
- [ ] I have manually verified that the
`{NameOfIntegration}EmbeddingStore` works correctly with the data
persisted using the latest released version of LangChain4j
---------
Signed-off-by: ZhangDT-sky <485918776@qq.com>
Co-authored-by: Dmytro Liubarskyi <ljubarskij@gmail.com>
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
## Summary
Adds **Text-to-Speech (TTS)** support to LangChain4j: a new
provider-agnostic `TextToSpeechModel` abstraction in `langchain4j-core`,
an OpenAI implementation backed by the [OpenAI Speech
API](https://platform.openai.com/docs/api-reference/audio/createSpeech),
and the HTTP-client plumbing needed to return binary (audio) response
bodies intact.
## Changes
### `langchain4j-core` — new abstraction (`dev.langchain4j.model.audio`,
`@Experimental`)
- **`TextToSpeechModel`** — interface mirroring the existing
`AudioTranscriptionModel`:
- `synthesize(String text)` — convenience method using the model's
default voice
- `synthesize(TextToSpeechRequest request)`
- `provider()` defaulting to `OTHER`
- **`TextToSpeechRequest`** — carries `text` (validated non-blank) and
optional `voice`
- **`TextToSpeechResponse`** — wraps the core `Audio` type;
`from(Audio)` factory
### `langchain4j-open-ai` — OpenAI implementation
- **`OpenAiTextToSpeechModel`** — configurable `modelName`, `voice`
(default `alloy`), `timeout`, `maxRetries` (default `2`),
request/response logging, custom `baseUrl`, and `httpClientBuilder`.
Enforces
OpenAI's 4096-character input limit. `provider()` → `OPEN_AI`.
- **`OpenAiTextToSpeechModelName`** — `tts-1`, `tts-1-hd`,
`gpt-4o-mini-tts`, `gpt-4o-mini-tts-2025-12-15`
- **`OpenAiTextToSpeechRequest` / `OpenAiTextToSpeechResponse`** —
internal DTOs (`internal.audio.texttospeech`); the response is built
from the raw HTTP body (binary audio, not JSON)
- **`OpenAiTextToSpeechModelBuilderFactory`** — SPI factory for builder
customization
- **`OpenAiClient.textToSpeech(...)`** — `POST /audio/speech`, mapping
the raw bytes + `Content-Type` into the response
### HTTP client layer (shared) — binary response support
- **`SuccessfulHttpResponse`** — body is now stored as `byte[]`.
`body()` is preserved and returns a decoded `String` (using the charset
from the `Content-Type` header, UTF-8 fallback); adds `bodyBytes()` for
raw binary access and `contentType()`. The `body(String)` builder is
kept and a `body(byte[])` overload added — **additive, no public method
removed or changed**.
- **`JdkHttpClient`** — switched to `BodyHandlers.ofByteArray()`;
**`ApacheHttpClient` / `OkHttpClient`** read the body as raw bytes, so
binary payloads (audio) are no longer corrupted by text decoding.
- **`HttpResponseLogger`** — no longer decodes/dumps binary bodies as
text; logs `[binary body, N bytes, content-type: ...]` instead.
### Tests
- Core: `TextToSpeechModelTest`, `TextToSpeechRequestTest`
- HTTP: `SuccessfulHttpResponseTest` (charset decoding/edge cases),
`HttpClientIT` binary-response test asserting a valid MP3 is returned
across all client implementations
- OpenAI: `OpenAiTextToSpeechModelTest` (input-length and required-field
validation), `OpenAiTextToSpeechModelIT` (parameterized over every
supported model)
### Docs & API compatibility
- Added a **"Creating `OpenAiTextToSpeechModel`"** section to the OpenAI
docs page
- `revapi.json` updated to acknowledge the core
`TextToSpeechRequest`/`TextToSpeechResponse` types intentionally exposed
by `OpenAiTextToSpeechModel`
## Design notes
- Named `TextToSpeechModel` / `synthesize(...)` for discoverability (TTS
is the universally recognized term) and to read as a clear inverse of
the existing `AudioTranscriptionModel` / `transcribe(...)`.
- The shared HTTP-client change is **behavior-preserving**: for every
client (JDK / Apache / OkHttp), responses without an explicit charset
were already decoded as UTF-8, and explicit charsets are still
honored — verified empirically against `httpclient5 5.6.1` / `httpcore5
5.4`. The `String → byte[]` move is additive at the public API level.
## General checklist
- [x] There are no breaking changes (API, behaviour) — the shared
`SuccessfulHttpResponse` change is additive and verified
behavior-preserving; please review the HTTP-client layer regardless, as
it affects all
providers
- [x] I have added unit and/or integration tests for my change
- [x] The tests cover both positive and negative cases
- [x] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [x] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green
- [x] I have added/updated the
[documentation](https://github.com/langchain4j/langchain4j/tree/main/docs/docs)
- [ ] I have added an example in the [examples
repo](https://github.com/langchain4j/langchain4j-examples) (only for
"big" features)
- [ ] I have added/updated [Spring Boot
starter(s)](https://github.com/langchain4j/langchain4j-spring) (if
applicable)
---------
Co-authored-by: Dmytro Liubarskyi <ljubarskij@gmail.com>
## Summary
Closes#5530 (Phase 1).
Adds a typed, ergonomic way to enable Anthropic [Agent
Skills](https://docs.anthropic.com/en/docs/agents-and-tools/agent-skills/overview)
on `AnthropicChatModel` and `AnthropicStreamingChatModel`, so Claude can
generate real downloadable documents (`.xlsx`, `.pptx`, `.docx`, `.pdf`)
instead of only describing them:
```java
AnthropicChatModel model = AnthropicChatModel.builder()
.apiKey(System.getenv("ANTHROPIC_API_KEY"))
.modelName("claude-opus-4-8")
.maxTokens(4096)
.skills(AnthropicSkill.XLSX, AnthropicSkill.PPTX) // up to 8
.returnServerToolResults(true)
.build();
```
Today this requires hand-assembling a `container.skills` block via
`customParameters(...)`, manually adding the `code_execution` server
tool, and remembering three beta headers — undocumented and easy to get
wrong.
### What `skills(...)` does
When skills are configured it automatically:
- adds the `container.skills` array
(`{"type":"anthropic","skill_id":"xlsx","version":"latest"}`),
- adds the `code_execution` server tool, unless one is already
configured via `serverTools(...)` (no duplicates),
- merges the required `anthropic-beta` tokens
(`code-execution-2025-08-25`, `skills-2025-10-02`,
`files-api-2025-04-14`) with any user-supplied `beta(...)` value,
without duplicates.
The produced request matches the reference body from the issue:
```json
{
"model": "claude-opus-4-8",
"max_tokens": 4096,
"container": { "skills": [{ "type": "anthropic", "skill_id": "pptx", "version": "latest" }] },
"messages": [ ... ],
"tools": [{ "type": "code_execution_20250825", "name": "code_execution" }]
}
```
Generated file ids remain surfacable via `returnServerToolResults(true)`
under the `AiMessage` `"server_tool_results"` attribute. Both the
blocking and streaming models are covered.
## Scope / follow-up
This is the self-contained Phase 1 from the issue. The Anthropic **Files
API client** (upload / list / delete, and the genuinely missing
**download** primitive) is intentionally left out so its surface can be
agreed first — @RyanHowell30 explicitly suggested landing Phase 1 first
and aligning on the Files-client shape before implementing Phase 2.
Happy to follow up with it once there's direction on the desired API.
Advanced cases not covered by the `.skills(...)` sugar (per-skill
version pinning, custom workspace skills, reusing a `container.id`)
remain reachable through the existing `customParameters(...)` escape
hatch; typed support for those can be layered on later if wanted.
## Test plan
- [x] New `AnthropicSkillsTest` (8 unit tests, no network): container
block contents, auto-added `code_execution` tool, no duplication when
the tool is already configured, no container/tool when no skills,
serialized request shape, and beta-header merging/de-duplication.
- [x] `mvn -pl langchain4j-anthropic test` — all unit tests pass.
- [x] `mvn -pl langchain4j-anthropic spotless:check` — clean.
- Public API change is additive (new `AnthropicSkill` enum,
`skills(...)` builder methods, and a `container` field on the internal
`AnthropicCreateMessageRequest` mirroring the existing `outputConfig`
field) — binary compatible.
---------
Co-authored-by: Benamira05 <145583236+Benamira05@users.noreply.github.com>
Co-authored-by: Dmytro Liubarskyi <ljubarskij@gmail.com>
## Issue
Closes#5603
## Change
Right now the Anthropic integration folds every `SystemMessage` into the
top-level `system` field, so there's no way to use Claude Opus 4.8's
[mid-conversation system
messages](https://platform.claude.com/docs/en/build-with-claude/mid-conversation-system-messages).
This adds an opt-in `midConversationSystemMessages` option (default off)
that sends a `SystemMessage` appearing after the conversation has
started as a `role:"system"` entry in the `messages` array. Leading
system messages still go to the top-level `system` field, and with the
option off behaviour is unchanged.
The library doesn't enforce or reorder placement: it sends the
`SystemMessage` at whatever position the caller put it in, and Anthropic
rejects invalid placements with a 400 (an inline system message has to
follow a user turn, can't be first, and can't sit between a `tool_use`
and its `tool_result`). Those rules are noted on the option's Javadoc.
I've opened this as a draft to get a read on the approach. I don't mind
changing how it's exposed if you'd rather it worked differently.
## General checklist
- [x] There are no breaking changes (API, behaviour)
- [x] I have added unit and/or integration tests for my change
- [x] The tests cover both positive and negative cases
- [x] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [x] I have manually run all the unit and integration tests in the core
and main modules, and they are all green
- [ ] I have added/updated the documentation
- [ ] I have added an example in the examples repo (only for "big"
features)
- [ ] I have added/updated Spring Boot starter(s) (if applicable)
---------
Co-authored-by: Dmytro Liubarskyi <ljubarskij@gmail.com>
## Issue
Closes#5116
## Change
Adds a new **`onUnmappedRawEvent`** streaming callback that gives
advanced users access to provider streaming events that LangChain4j does
**not** map to one of its typed callbacks — e.g. OpenAI server-tool
lifecycle events (`response.web_search_call.in_progress` / `searching` /
`completed`). This is an escape hatch so power users don't have to fall
back to a provider's native SDK for events we don't model yet.
**API** (both `@Experimental`, `@since 1.17.0`, `default` so nothing
breaks):
- `StreamingChatResponseHandler.onUnmappedRawEvent(Object rawEvent)` —
low-level API
- `TokenStream.onUnmappedRawEvent(Consumer<Object> rawEventHandler)` —
AI Services API
**Semantics — no duplication.** The callback fires **only** for events
that were *not* already delivered via a typed callback
(`onPartialResponse`, `onPartialThinking`, `onPartialToolCall`,
`onCompleteToolCall`, `onCompleteResponse`). So you can consume the
typed callbacks and the raw stream together without seeing the same
event twice. This is enforced by a small internal
`MappingTrackingStreamingChatResponseHandler` that records whether an
event was mapped to a typed callback (`wasMapped()`), and providers emit
the raw event only when it wasn't.
> Naming note: it's called `onUnmappedRawEvent` (not `onRawEvent`) to
leave room for a planned follow-up that also exposes the raw event
behind *mapped* callbacks (e.g. `PartialToolCall.rawEvent()`), giving a
clean mapped/unmapped split.
**The concrete `rawEvent` type is provider-specific:**
| Provider | Raw event type |
|---|---|
| OpenAI, Anthropic, Google AI Gemini, Mistral, Ollama |
`dev.langchain4j.http.client.sse.ServerSentEvent` |
| OpenAI (official) – Responses API |
`com.openai.models.responses.ResponseStreamEvent` |
| OpenAI (official) – Chat Completions API |
`com.openai.models.chat.completions.ChatCompletionChunk` |
| Amazon Bedrock |
`software.amazon.awssdk.services.bedrockruntime.model.ConverseStreamOutput`
|
| Google GenAI | `com.google.genai.types.GenerateContentResponse` |
**Providers wired:** OpenAI (Chat Completions + Responses),
OpenAI-official (Chat Completions + Responses), Anthropic, Google AI
Gemini, Google GenAI, Amazon Bedrock, Mistral, Ollama.
**Docs:** added a "Unmapped Raw Events" section to
`response-streaming.md` and the callback to the `TokenStream` example in
`ai-services.md`.
## General checklist
- [x] There are no breaking changes (API, behaviour) — all additions are
`default` and `@Experimental`
- [x] I have added unit and/or integration tests for my change
- [x] The tests cover both positive and negative cases — i.e. unmapped
events are forwarded *and* typed (text/tool) events are **not** repeated
as raw events
- [x] I have manually run all the unit and integration tests in the
module(s) I have added/changed, and they are all green
- [x] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green
- [x] I have added/updated the
[documentation](https://github.com/langchain4j/langchain4j/tree/main/docs/docs)
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## Issue
<!-- Please specify the ID of the issue this PR is addressing. For
example: "Closes #1234" or "Fixes #1234" -->
Closes#5569
## Change
I added a configurable upper limit for the entries retained by the
`AgentMonitor`. There is a breaking change due to the fact that the
`AgentMonitor` itself doesn't directly implement anymore the
`AgentListener` interface, but it does so trough an inner class. I did
this because I wanted to clearly separate the public `AgentMonitor` API
from the `AgentListener` 's methods implementation.
## General checklist
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- [X] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [ ] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
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repo](https://github.com/langchain4j/langchain4j-examples) (only for
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## Issue
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example: "Closes #1234" or "Fixes #1234" -->
Closes#660
## Change
Added documentation regarding the SQL Server's half-precision vectors.
This is just a documentation change, no code affected
Bumps [dompurify](https://github.com/cure53/DOMPurify) from 3.4.10 to
3.4.11.
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a
href="https://github.com/cure53/DOMPurify/releases">dompurify's
releases</a>.</em></p>
<blockquote>
<h2>DOMPurify 3.4.11</h2>
<ul>
<li>Fixed an issue with a leaky config for hooks via
<code>setConfig</code>, thanks <a
href="https://github.com/trace37labs"><code>@trace37labs</code></a></li>
<li>Bumped vulnerable development dependencies to arrive at plain 0 with
<code>npm audit</code></li>
<li>Updated the <code>osv-scanner</code> suppression list as no
vulnerable dependencies are left for now</li>
<li>Updated up the linting tool-chain and removed now-redundant lint
directives</li>
<li>Updated the documentation is several spots, README, wiki, etc.</li>
<li>Bumped several dependencies where possible</li>
</ul>
</blockquote>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="0cae518740"><code>0cae518</code></a>
release: 3.4.11 (<a
href="https://redirect.github.com/cure53/DOMPurify/issues/1494">#1494</a>)</li>
<li>See full diff in <a
href="https://github.com/cure53/DOMPurify/compare/3.4.10...3.4.11">compare
view</a></li>
</ul>
</details>
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Add Oracle chat memory store integration link after merge of
https://github.com/langchain4j/langchain4j/pull/5351
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## Change
Adding Oracle Chat memory in the doc
## General checklist
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## Issue
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Closes #
## Change
<!-- Please describe the changes you made. -->
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extends from `EmbeddingStoreWithRemovalIT`
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persisted using the latest released version of LangChain4j
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## Issue
<!-- Please specify the ID of the issue this PR is addressing. For
example: "Closes #1234" or "Fixes #1234" -->
Closes #
## Change
Add a new `@ReverseTool` annotation allowing to declare the method
reversing the action performed by a tool. When an `AiService` is
configured as `transactional` (the name is very questionable let me know
if you have any better idea about it) and a tool invocation fails, the
reverse tool are invoked to roll back all the actions taken during the
invocation of that `AiService`.
@dliubarskyi My plan is to use this feature also in the agentic module,
but I will eventually do this with a follow up pull request, once we
will find an agreement on this.
@jmartisk I don't know if this has some impact on MCP tools and if this
feature could be extended also for them. Please let me know if you have
any advice on this regard.
## General checklist
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module I have added/changed, and they are all green
- [x] I have manually run all the unit and integration tests in the
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---------
Co-authored-by: Dmytro Liubarskyi <ljubarskij@gmail.com>
## Issue
Closes#5301
## Change
This PR introduces the provider-specific
`AnthropicChatRequestParameters` class to support per-invocation
overrides of all Anthropic-specific options, rather than baking them
into the model instance at build time.
### Key Changes:
- **Implemented `AnthropicChatRequestParameters`**: Subclasses
`DefaultChatRequestParameters` and exposes Anthropic-specific
parameters: `cacheSystemMessages`, `cacheTools`, `thinkingType`,
`thinkingBudgetTokens`, `sendThinking`, `returnThinking`,
`toolChoiceName`, `disableParallelToolUse`, and `userId`.
- **Integrated Per-Call Merging**: Updated `AnthropicChatModel` and
`AnthropicStreamingChatModel` to extract, merge, and apply parameters
dynamically on each `doChat(...)` call.
- **Narrowed Return Type**: Changed `defaultRequestParameters()` to
return the narrower `AnthropicChatRequestParameters` (with corresponding
compatibility exemptions in `revapi.json`).
- **Comprehensive Tests**: Added unit tests for merge behavior
(`overrideWith`, `defaultedBy`) and WireMock integration tests to verify
the serialized JSON payload.
### How it is Helpful (Benefits):
- **Avoids Duplicate Model Instances**: Prevents the need to instantiate
multiple model instances just to toggle features like prompt caching
(e.g. enabling caching for long agent loops, but disabling it for cheap
one-shot completions on the same model).
- **Dynamic Feature Control**: Allows applications to dynamically adjust
Extended Thinking budgets, tool choices, and parallel tool flags on a
call-by-call basis.
- **Consistent Architecture**: Aligns the Anthropic provider with other
major integrations (like OpenAI and Ollama) which already support
provider-specific request parameter overrides.
## General checklist
- [X] There are no breaking changes (API, behaviour)
- [X] I have added unit and/or integration tests for my change
- [X] The tests cover both positive and negative cases
- [X] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
---------
Co-authored-by: Dmytro Liubarskyi <ljubarskij@gmail.com>
Bumps and [ws](https://github.com/websockets/ws). These dependencies
needed to be updated together.
Updates `ws` from 7.5.10 to 7.5.11
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a
href="https://github.com/websockets/ws/releases">ws's
releases</a>.</em></p>
<blockquote>
<h2>7.5.11</h2>
<h1>Bug fixes</h1>
<ul>
<li>Backported 2b2abd45 to the 7.x release line (e14c4586).</li>
</ul>
</blockquote>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="fd36cd864f"><code>fd36cd8</code></a>
[dist] 7.5.11</li>
<li><a
href="e14c45861d"><code>e14c458</code></a>
[security] Limit retained message parts</li>
<li>See full diff in <a
href="https://github.com/websockets/ws/compare/7.5.10...7.5.11">compare
view</a></li>
</ul>
</details>
<br />
Updates `ws` from 8.20.0 to 8.21.0
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a
href="https://github.com/websockets/ws/releases">ws's
releases</a>.</em></p>
<blockquote>
<h2>7.5.11</h2>
<h1>Bug fixes</h1>
<ul>
<li>Backported 2b2abd45 to the 7.x release line (e14c4586).</li>
</ul>
</blockquote>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="fd36cd864f"><code>fd36cd8</code></a>
[dist] 7.5.11</li>
<li><a
href="e14c45861d"><code>e14c458</code></a>
[security] Limit retained message parts</li>
<li>See full diff in <a
href="https://github.com/websockets/ws/compare/7.5.10...7.5.11">compare
view</a></li>
</ul>
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## Summary
Adds documentation for the Hazelcast integration (chat memory stores +
embedding store), following the steps in `CONTRIBUTING.md` for
documenting a new embedding/chat-memory store integration.
The Hazelcast modules themselves are contributed in
langchain4j/langchain4j-community#695.
- **New page** `docs/docs/integrations/embedding-stores/hazelcast.md`
covering both modules:
- `langchain4j-community-hazelcast` (open source) —
`HazelcastChatMemoryStore`, backed by a Hazelcast `IMap`.
- `langchain4j-community-hazelcast-enterprise` (Hazelcast Enterprise) —
`HazelcastEmbeddingStore` (vector search via `VectorCollection`) and
`HazelcastCPMapChatMemoryStore` (strongly-consistent,
CP-Subsystem-backed). Re-exports `langchain4j-community-hazelcast`.
- **Embedding store comparison table** (`embedding-stores/index.md`):
new Hazelcast row — Storing Metadata ✅, Filtering by Metadata ❌ (no
server-side filtering), Removing Embeddings ✅.
- **Chat memory store comparison table**
(`chat-memory-stores/index.md`): new rows for the IMap-based and
CPMap-based stores, linking to the ITs in `langchain4j-community`.
The page documents builder APIs/defaults, the Enterprise repository +
license-key requirement, and the embedding-store limitations
(`removeAll(Filter)` unsupported; search filtering applied client-side,
best-effort).
## Notes
- Dependency coordinates use the `langchain4j-community` naming
(`langchain4j-community-hazelcast`,
`langchain4j-community-hazelcast-enterprise`,
`langchain4j-community-bom`).
- Example links point to a `hazelcast-example` module to be added to
`langchain4j-examples`. The example sources have been written and
verified: all three compile against the modules, and the open-source
IMap example runs license-free on Hazelcast Community Edition.
Bumps [shell-quote](https://github.com/ljharb/shell-quote) from 1.8.3 to
1.8.4.
<details>
<summary>Changelog</summary>
<p><em>Sourced from <a
href="https://github.com/ljharb/shell-quote/blob/main/CHANGELOG.md">shell-quote's
changelog</a>.</em></p>
<blockquote>
<h2><a
href="https://github.com/ljharb/shell-quote/compare/v1.8.3...v1.8.4">v1.8.4</a>
- 2026-05-22</h2>
<h3>Commits</h3>
<ul>
<li>[Fix] <code>quote</code>: validate object-token shapes <a
href="4378a6e613"><code>4378a6e</code></a></li>
<li>[Dev Deps] update <code>@ljharb/eslint-config</code>,
<code>auto-changelog</code>, <code>eslint</code>, <code>npmignore</code>
<a
href="22ebec0434"><code>22ebec0</code></a></li>
<li>[Tests] increase coverage <a
href="9f3caa3190"><code>9f3caa3</code></a></li>
<li>[readme] replace runkit CI badge with shields.io check-runs badge <a
href="3344a047dd"><code>3344a04</code></a></li>
<li>[Dev Deps] update <code>@ljharb/eslint-config</code> <a
href="699c5113d1"><code>699c511</code></a></li>
</ul>
</blockquote>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="ff166e2b63"><code>ff166e2</code></a>
v1.8.4</li>
<li><a
href="4378a6e613"><code>4378a6e</code></a>
[Fix] <code>quote</code>: validate object-token shapes</li>
<li><a
href="22ebec0434"><code>22ebec0</code></a>
[Dev Deps] update <code>@ljharb/eslint-config</code>,
<code>auto-changelog</code>, <code>eslint</code>, `npmig...</li>
<li><a
href="9f3caa3190"><code>9f3caa3</code></a>
[Tests] increase coverage</li>
<li><a
href="3344a047dd"><code>3344a04</code></a>
[readme] replace runkit CI badge with shields.io check-runs badge</li>
<li><a
href="699c5113d1"><code>699c511</code></a>
[Dev Deps] update <code>@ljharb/eslint-config</code></li>
<li>See full diff in <a
href="https://github.com/ljharb/shell-quote/compare/v1.8.3...v1.8.4">compare
view</a></li>
</ul>
</details>
<br />
[](https://docs.github.com/en/github/managing-security-vulnerabilities/about-dependabot-security-updates#about-compatibility-scores)
Dependabot will resolve any conflicts with this PR as long as you don't
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## Issue
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Closes #
## Change
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## General checklist
<!-- Please double-check the following points and mark them like this:
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- [ ] I have added unit and/or integration tests for my change
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- [ ] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [ ] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
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modules, and they are all green
<!-- Before adding documentation and example(s) (below), please wait
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- [ ] I have added/updated the
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repo](https://github.com/langchain4j/langchain4j-examples) (only for
"big" features)
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starter(s)](https://github.com/langchain4j/langchain4j-spring) (if
applicable)
## Checklist for adding new maven module
<!-- Please double-check the following points and mark them like this:
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- [ ] I have added my new module in the root `pom.xml` and
`langchain4j-bom/pom.xml`
## Checklist for adding new embedding store integration
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreIT` that extends
from either `EmbeddingStoreIT` or `EmbeddingStoreWithFilteringIT`
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreRemovalIT` that
extends from `EmbeddingStoreWithRemovalIT`
## Checklist for changing existing embedding store integration
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have manually verified that the
`{NameOfIntegration}EmbeddingStore` works correctly with the data
persisted using the latest released version of LangChain4j
Signed-off-by: Anjali K <anjali.kakkar@ltts.com>
Co-authored-by: Anjali K <anjali.kakkar@ltts.com>
Bumps [dompurify](https://github.com/cure53/DOMPurify) from 3.4.0 to
3.4.10.
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a
href="https://github.com/cure53/DOMPurify/releases">dompurify's
releases</a>.</em></p>
<blockquote>
<h2>DOMPurify 3.4.10</h2>
<ul>
<li>Refactored codebase for clarity: extracted the public type
declarations into <code>types.ts</code></li>
<li>Decomposed the three largest sanitizer functions into focused
helpers</li>
<li>Removed duplicated defaults and dead branches, consolidated
<code>SAFE_FOR_TEMPLATES</code> scrubbing into single shared path</li>
<li>Improved per-node performance by hoisting the mXSS probe regexes and
testing <code>textContent</code> before <code>innerHTML</code></li>
<li>Added a deterministic micro-benchmark harness (<code>npm run
bench</code>) with a <code>--compare</code> mode</li>
<li>Reduced CI cost by running the full three-engine browser suite once
per PR</li>
<li>Refreshed the <code>demos/</code> folder so every demo runs again,
and added a SVG-via-<code><img></code> demo</li>
<li>Documented the bench and <code>test:happydom</code> scripts in the
README</li>
<li>Completed the Attack Classes & Bypass History wiki page</li>
<li>Bumped several dependencies where possible</li>
</ul>
<h2>DOMPurify 3.4.9</h2>
<ul>
<li>Further improved the handling of Trusted Types config options,
thanks <a
href="https://github.com/offset"><code>@offset</code></a></li>
<li>Further improved the handling of <code>IN_PLACE</code> sanitization,
thanks <a
href="https://github.com/mozfreddyb"><code>@mozfreddyb</code></a></li>
<li>Added more test coverage for <code>IN_PLACE</code> and Trusted Types
related usage</li>
<li>Bumped several dependencies where possible</li>
<li>Updated README and wiki with more accurate documentation &
attack samples</li>
</ul>
<h2>DOMPurify 3.4.8</h2>
<ul>
<li>Cleaned up the repository root, renamed some and removed unneeded
files</li>
<li>Fixed an issue with handling of Trusted Types policies, thanks <a
href="https://github.com/fulstadev"><code>@fulstadev</code></a></li>
<li>Fixed the node iterator for better template scrubbing, thanks <a
href="https://github.com/IamLeandrooooo"><code>@IamLeandrooooo</code></a></li>
<li>Included formerly missing LICENSE-MPL in published npm package,
thanks <a
href="https://github.com/asamuzaK"><code>@asamuzaK</code></a></li>
<li>Bumped several dependencies where possible</li>
</ul>
<h2>DOMPurify 3.4.7</h2>
<ul>
<li>Hardened the handling of Shadow Roots when using
<code>IN_PLACE</code>, thanks <a
href="https://github.com/GameZoneHacker"><code>@GameZoneHacker</code></a></li>
<li>Removed a problem leading to permanent hook pollution, thanks <a
href="https://github.com/offset"><code>@offset</code></a></li>
<li>Refactored the test suite and expanded test coverage
significantly</li>
</ul>
<h2>DOMPurify 3.4.6</h2>
<ul>
<li>Fixed several issues with DOM Clobbering in <code>IN_PLACE</code>
mode, thanks <a
href="https://github.com/offset"><code>@offset</code></a> & <a
href="https://github.com/Bankde"><code>@Bankde</code></a></li>
<li>Hardened the checks for cross-realm <code>IN_PLACE</code> and Shadow
DOM sanitization, thanks <a
href="https://github.com/offset"><code>@offset</code></a> & <a
href="https://github.com/Bankde"><code>@Bankde</code></a></li>
<li>Added more test coverage for <code>IN_PLACE</code> and general DOM
Clobbering attacks</li>
<li>Bumped several dependencies where possible</li>
</ul>
<h2>DOMPurify 3.4.5</h2>
<ul>
<li>Fixed a bypass caused by the new HTML element
<code>selectedcontent</code> added in 3.4.4, thanks <a
href="https://github.com/KabirAcharya"><code>@KabirAcharya</code></a></li>
</ul>
<p><strong>Note that this is a security release for an issue introduced
in 3.4.4 and should be upgraded to immediately.</strong></p>
<h2>DOMPurify 3.4.4</h2>
<ul>
<li>Added the <code>selectedcontent</code> element to default
allow-list, thanks <a
href="https://github.com/lukewarlow"><code>@lukewarlow</code></a></li>
<li>Added the <code>command</code> and <code>commandfor</code>
attributes to default allowed-list, thanks <a
href="https://github.com/lukewarlow"><code>@lukewarlow</code></a></li>
<li>Added better template scrubbing for <code>IN_PLACE</code>
operations, thanks <a
href="https://github.com/DEMON1A"><code>@DEMON1A</code></a></li>
<li>Added stronger checks for cross-realm windows, thanks <a
href="https://github.com/DEMON1A"><code>@DEMON1A</code></a> & <a
href="https://github.com/fg0x0"><code>@fg0x0</code></a></li>
<li>Updated demo website and made sure it uses the latest from main</li>
<li>Updated existing workflows, fuzzer, dependabot, etc., added more
tests</li>
<li>Bumped several dependencies where possible</li>
</ul>
<!-- raw HTML omitted -->
</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="6ee5716f83"><code>6ee5716</code></a>
release: 3.4.10 (<a
href="https://redirect.github.com/cure53/DOMPurify/issues/1478">#1478</a>)</li>
<li><a
href="52102472d4"><code>5210247</code></a>
release: 3.4.9 (<a
href="https://redirect.github.com/cure53/DOMPurify/issues/1459">#1459</a>)</li>
<li><a
href="bcdd828541"><code>bcdd828</code></a>
release: 3.4.8 (<a
href="https://redirect.github.com/cure53/DOMPurify/issues/1439">#1439</a>)</li>
<li><a
href="ca30f070c3"><code>ca30f07</code></a>
release: 3.4.7 (<a
href="https://redirect.github.com/cure53/DOMPurify/issues/1414">#1414</a>)</li>
<li><a
href="bb7739e5bc"><code>bb7739e</code></a>
release: 3.4.6 (<a
href="https://redirect.github.com/cure53/DOMPurify/issues/1394">#1394</a>)</li>
<li><a
href="011b0c78f2"><code>011b0c7</code></a>
release: 3.4.5 (<a
href="https://redirect.github.com/cure53/DOMPurify/issues/1382">#1382</a>)</li>
<li><a
href="5817ad969c"><code>5817ad9</code></a>
release: 3.4.4 (<a
href="https://redirect.github.com/cure53/DOMPurify/issues/1374">#1374</a>)</li>
<li><a
href="520edb0371"><code>520edb0</code></a>
release: 3.4.3 (<a
href="https://redirect.github.com/cure53/DOMPurify/issues/1352">#1352</a>)</li>
<li><a
href="6f67fd396a"><code>6f67fd3</code></a>
Sync/3.4.2 (<a
href="https://redirect.github.com/cure53/DOMPurify/issues/1322">#1322</a>)</li>
<li><a
href="5b0cdbbf52"><code>5b0cdbb</code></a>
chore: merge main into 3.x for 3.4.1 release (<a
href="https://redirect.github.com/cure53/DOMPurify/issues/1301">#1301</a>)</li>
<li>Additional commits viewable in <a
href="https://github.com/cure53/DOMPurify/compare/3.4.0...3.4.10">compare
view</a></li>
</ul>
</details>
<details>
<summary>Install script changes</summary>
<p>This version adds <code>prepare</code> script that runs during
installation. Review the package contents before updating.</p>
</details>
<br />
[](https://docs.github.com/en/github/managing-security-vulnerabilities/about-dependabot-security-updates#about-compatibility-scores)
Dependabot will resolve any conflicts with this PR as long as you don't
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## Issue
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<!-- Before adding documentation and example(s) (below), please wait
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"big" features)
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starter(s)](https://github.com/langchain4j/langchain4j-spring) (if
applicable)
## Checklist for adding new maven module
<!-- Please double-check the following points and mark them like this:
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- [ ] I have added my new module in the root `pom.xml` and
`langchain4j-bom/pom.xml`
## Checklist for adding new embedding store integration
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreIT` that extends
from either `EmbeddingStoreIT` or `EmbeddingStoreWithFilteringIT`
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreRemovalIT` that
extends from `EmbeddingStoreWithRemovalIT`
## Checklist for changing existing embedding store integration
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have manually verified that the
`{NameOfIntegration}EmbeddingStore` works correctly with the data
persisted using the latest released version of LangChain4j
## Issue
<!-- No dedicated issue: this is a trivial documentation fix for broken
links. -->
N/A — trivial documentation fix (broken links).
## Change
The Anthropic integration page links to Anthropic's documentation using
the old `docs.anthropic.com/claude/...` URL structure. Anthropic has
migrated their docs, and these old URLs now redirect to pages that
return **404**. This updates the four remaining old-style links to the
current `docs.anthropic.com/en/...` structure, which is already used
elsewhere in the same file (e.g. the prompt-caching and pdf-support
links).
| Link text | Old (broken) | New (verified working) |
|---|---|---|
| Anthropic Documentation | `/claude/docs` | `/en/home` |
| Anthropic API Reference | `/claude/reference` | `/en/api/overview` |
| (parameter description) | `/claude/reference/messages_post` |
`/en/api/messages` |
| (tool use docs) | `/claude/docs/tool-use` |
`/en/docs/agents-and-tools/tool-use/overview` |
Each new URL was manually verified to load successfully, and each old
URL was confirmed to resolve to a 404 after the redirect.
## General checklist
- [X] There are no breaking changes (API, behaviour)
- [ ] I have added unit and/or integration tests for my change <!-- N/A:
documentation-only change -->
- [ ] The tests cover both positive and negative cases <!-- N/A:
documentation-only change -->
- [ ] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green <!-- N/A:
documentation-only change -->
- [ ] I have manually run all the unit and integration tests in the core
and main modules, and they are all green <!-- N/A: documentation-only
change -->
- [X] I have added/updated the documentation <!-- this PR is the
documentation update -->
Co-authored-by: gus.guo <gus.guo@tec-do.com>
## Issue
Closes#5431
## Change
The "Google Vertex AI PaLM 2" row in
`docs/docs/integrations/language-models/index.md` (line 16) links to
`/integrations/language-models/google-palm`, a page deleted in PR #4082
(commit `12e8ae2a2`, "the PaLM models are removed"). Only the table row
was left behind, so the route is now a 404. Removing it completes
#4082's cleanup.
Verified: `google-palm` is the only row with no source page (every other
resolves, e.g. `anthropic.md`); `git grep google-palm docs/` returns
only this line; CI missed it because `onBrokenLinks: 'warn'`
(`docusaurus.config.js:15`) downgrades broken links to warnings.
(Absolute Docusaurus routes look broken on GitHub — expected.)
Scope: 1 line removed, docs-only. No code changes.
## General checklist
- [X] There are no breaking changes (API, behaviour)
- [ ] I have added unit and/or integration tests for my change <!-- N/A
— docs-only -->
- [ ] The tests cover both positive and negative cases <!-- N/A —
docs-only -->
- [ ] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green <!-- N/A — no code
module touched -->
- [ ] I have manually run all the unit and integration tests in the core
and main modules, and they are all green <!-- N/A — docs-only -->
- [X] I have added/updated the documentation <!-- this PR IS the docs
fix -->
- [ ] I have added an example in the examples repo (only for "big"
features) <!-- N/A -->
- [ ] I have added/updated Spring Boot starter(s) (if applicable) <!--
N/A -->
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## Issue
<!-- Please specify the ID of the issue this PR is addressing. For
example: "Closes #1234" or "Fixes #1234" -->
Closes #
## Change
This pull request allows to optionally propagate the exception raised by
a tool execution. The main goal is to remove tons of code duplication in
the Quarkus extension that in some cases (like for tools guardrails)
relies on this behavior, but in general I believe this is a nice
addition also for LangChain4j itself.
## General checklist
<!-- Please double-check the following points and mark them like this:
[X] -->
- [x] There are no breaking changes (API, behaviour)
- [x] I have added unit and/or integration tests for my change
- [x] The tests cover both positive and negative cases
- [x] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [x] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green
<!-- Before adding documentation and example(s) (below), please wait
until the PR is reviewed and approved. -->
- [ ] I have added/updated the
[documentation](https://github.com/langchain4j/langchain4j/tree/main/docs/docs)
- [ ] I have added an example in the [examples
repo](https://github.com/langchain4j/langchain4j-examples) (only for
"big" features)
- [ ] I have added/updated [Spring Boot
starter(s)](https://github.com/langchain4j/langchain4j-spring) (if
applicable)
## Checklist for adding new maven module
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have added my new module in the root `pom.xml` and
`langchain4j-bom/pom.xml`
## Checklist for adding new embedding store integration
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreIT` that extends
from either `EmbeddingStoreIT` or `EmbeddingStoreWithFilteringIT`
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreRemovalIT` that
extends from `EmbeddingStoreWithRemovalIT`
## Checklist for changing existing embedding store integration
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have manually verified that the
`{NameOfIntegration}EmbeddingStore` works correctly with the data
persisted using the latest released version of LangChain4j
---------
Co-authored-by: Dmytro Liubarskyi <ljubarskij@gmail.com>
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you for understanding!
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## Issue
<!-- Please specify the ID of the issue this PR is addressing. For
example: "Closes #1234" or "Fixes #1234" -->
Closes #
## Change
<!-- Please describe the changes you made. -->
## General checklist
<!-- Please double-check the following points and mark them like this:
[X] -->
- [X] There are no breaking changes (API, behaviour)
- [X] I have added unit and/or integration tests for my change
- [X] The tests cover both positive and negative cases
- [X] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [ ] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green
<!-- Before adding documentation and example(s) (below), please wait
until the PR is reviewed and approved. -->
- [ ] I have added/updated the
[documentation](https://github.com/langchain4j/langchain4j/tree/main/docs/docs)
- [ ] I have added an example in the [examples
repo](https://github.com/langchain4j/langchain4j-examples) (only for
"big" features)
- [ ] I have added/updated [Spring Boot
starter(s)](https://github.com/langchain4j/langchain4j-spring) (if
applicable)
## Checklist for adding new maven module
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have added my new module in the root `pom.xml` and
`langchain4j-bom/pom.xml`
## Checklist for adding new embedding store integration
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreIT` that extends
from either `EmbeddingStoreIT` or `EmbeddingStoreWithFilteringIT`
- [ ] I have added a `{NameOfIntegration}EmbeddingStoreRemovalIT` that
extends from `EmbeddingStoreWithRemovalIT`
## Checklist for changing existing embedding store integration
<!-- Please double-check the following points and mark them like this:
[X] -->
- [ ] I have manually verified that the
`{NameOfIntegration}EmbeddingStore` works correctly with the data
persisted using the latest released version of LangChain4j
<!--
Thank you so much for your contribution!
Please fill in all the sections below.
Please open the PR as a draft initially. Once it is reviewed and
approved, we will ask you to add documentation and examples.
Please note that PRs with breaking changes or without tests will be
rejected.
Please note that PRs will be reviewed based on the priority of the
issues they address.
We ask for your patience. We are doing our best to review your PR as
quickly as possible.
Please refrain from pinging and asking when it will be reviewed. Thank
you for understanding!
-->
## Change
This PR adds support for using deployed models (on-demand deployments)
in IBM watsonx.ai through the `deploymentId` parameter, in addition to
the existing catalog-based model access via `projectId`/`spaceId` +
`modelName`.
## General checklist
<!-- Please double-check the following points and mark them like this:
[X] -->
- [x] There are no breaking changes (API, behaviour)
- [x] I have added unit and/or integration tests for my change
- [x] The tests cover both positive and negative cases
- [x] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [ ] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green
<!-- Before adding documentation and example(s) (below), please wait
until the PR is reviewed and approved. -->
- [x] I have added/updated the
[documentation](https://github.com/langchain4j/langchain4j/tree/main/docs/docs)
- [ ] I have added an example in the [examples
repo](https://github.com/langchain4j/langchain4j-examples) (only for
"big" features)
- [ ] I have added/updated [Spring Boot
starter(s)](https://github.com/langchain4j/langchain4j-spring) (if
applicable)
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