Add async APIs, cancellation support, and typed metrics accessors#188
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Introduces Usage, Timings, and ServerMetrics value classes plus LlamaModel.getMetricsTyped() so callers no longer need to parse the raw JSON from getMetrics() by hand. Mirrors the existing ModelMeta pattern. 15 unit tests, no native or JNI changes. https://claude.ai/code/session_01R4ZrEy3ptJDLuUgUKuM4Gy
InferenceParameters gains setJsonSchema(String) mirroring the existing ModelParameters setter. LlamaModel.completeAsJson<T> sets the schema, runs complete(), and deserializes the result via Jackson, throwing a LlamaException if the model output is not valid JSON for the target type. No JNI changes — the native server already accepts json_schema in slot params. https://claude.ai/code/session_01R4ZrEy3ptJDLuUgUKuM4Gy
New TokenLogprob record carries token text, id, raw prob/logprob, and the nested top_probs/top_logprobs alternatives. LlamaOutput.logprobs is populated by CompletionResponseParser.parseLogprobs from the same completion_probabilities array that already feeds the flat probabilities map. Existing constructor stays as a delegator so all prior callers keep working with logprobs defaulting to empty. https://claude.ai/code/session_01R4ZrEy3ptJDLuUgUKuM4Gy
LlamaIterator.cancel() / close() were already wired correctly via the existing JNI cancelCompletion → erase_reader path, so this is purely a docs + test pass: - Clarify in LlamaIterator javadoc that the underlying llama.cpp slot may continue to its natural stop after cancel(), while the reader is released immediately and next() stops yielding. - Document close() idempotency (post-natural-stop, post-cancel, double-close all safe). - Add try-with-resources example to LlamaModel.generate javadoc. - Add testIteratorCloseIdempotent in LlamaModelTest covering both the drained-then-closed and cancelled-then-closed paths and confirming the model is still usable afterwards. https://claude.ai/code/session_01R4ZrEy3ptJDLuUgUKuM4Gy
CancellationToken wraps an AtomicInteger task id and a model reference. LlamaModel.complete(params, token) runs the streaming inference path internally, binds the token, accumulates text, and returns early when token.cancel() is invoked from another thread. The token is reset on return so it is reusable across calls. No JNI changes: reuses the existing cancelCompletion native method (which erases the JNI reader; the upstream slot completes naturally). https://claude.ai/code/session_01R4ZrEy3ptJDLuUgUKuM4Gy
LlamaModel gains completeAsync, chatCompleteAsync, and chatCompleteTextAsync — thin wrappers that dispatch the existing blocking methods through ForkJoinPool.commonPool(). The completeAsync(params, token) overload bridges future.cancel(true) to CancellationToken.cancel() so cancellation propagates into the inference loop. Reactive Flow.Publisher streaming (M-effort) is intentionally deferred to a follow-up; this PR delivers only the S-effort portion of §2.3. https://claude.ai/code/session_01R4ZrEy3ptJDLuUgUKuM4Gy
Session is a thin wrapper over LlamaModel: it owns a slot id, an accumulating user/assistant transcript, and an optional system message and parameter customizer. send(userMessage) appends both sides of the turn and runs chatCompleteText with the full history. stream(userMessage) returns a LlamaIterable for streamed replies; commitStreamedReply records the assistant turn once the caller has accumulated the text. save/restore delegate to existing LlamaModel.saveSlot/restoreSlot. close() erases the slot's KV cache. Single-threaded use only in this pass — per-session locking is the M-effort follow-up. ChatMessage is the minimal value type for the transcript; will be reused by ChatResponse when §2.2 lands. https://claude.ai/code/session_01R4ZrEy3ptJDLuUgUKuM4Gy
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| * </p> | ||
| * | ||
| * @param parameters the inference configuration (its {@code stream} flag will be set to true) | ||
| * @param token cancellation handle; {@link CancellationToken#cancel()} aborts the loop |
Cross-thread cancel raced with the JNI receive loop: cancel() called cancelCompletion() from another thread, which erased the underlying server_response_reader unique_ptr while the main thread held a raw pointer to it and was blocked inside rd->next(). On the next token this dereferenced freed memory and aborted with std::system_error, crashing the test JVM (exit 134). Fix: cancel() now sets a volatile flag only. The inference loop in complete(params, token) checks the flag between tokens and, when set, calls cancelCompletion from the same thread that just returned from receiveCompletionJson — safe because no concurrent access remains. Latency becomes one token interval (tens to a few hundred ms on CPU) instead of immediate. Documented in CancellationToken javadoc. Tests: - LlamaModelTest#testCompleteWithCancellationToken: budget relaxed from 5s to 30s (was tight even on the happy path). - LlamaModelTest#testCompleteAsyncCancelPropagates: drop the brittle poll on token.isCancelled() (the worker resets the token on return before the assertion sees it); sleep for cancel propagation and verify the model is still usable. https://claude.ai/code/session_01R4ZrEy3ptJDLuUgUKuM4Gy
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The release packaging job (mvn package, release profile) runs maven-javadoc-plugin's attach-javadocs which treats Javadoc tool errors as build failures. PR #188 introduced one such error: TokenLogprob.java had a </p> with no matching <p> (the prose was already enclosed by an outer <p>...</p>, and the inner </p> was stray). Fix the error and bring my new public APIs up to a clean shape: - TokenLogprob: rebalance the <p>/</p> HTML and add @return / @param to public getters and constructor. - Timings, Usage, ServerMetrics, ChatMessage, CancellationToken, Session, LlamaOutput: add @return / @param tags with a leading one-line description (the "no main description" warning fires on bare /** @return ... */ blocks). - LlamaModel: restore the doc comment for complete(params, token) that was accidentally stripped during an earlier edit, and add one for getMetricsTyped(); remove a stray orphan doc block. Local verification: mvn clean javadoc:jar -DskipTests=true -Dgpg.skip=true mvn -P release -Dmaven.test.skip=true -Dgpg.skip=true package Both: BUILD SUCCESS (was: BUILD FAILURE, 1 error, 100 warnings). 60 warnings remain, all from pre-existing files outside this PR. Document the verification command and the failure categories (errors vs warnings) in CLAUDE.md under "Javadoc — must build cleanly before mvn package". https://claude.ai/code/session_01R4ZrEy3ptJDLuUgUKuM4Gy
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Exposes llama.cpp's llama_model_params.progress_callback as a Java
functional interface. New constructor:
new LlamaModel(parameters, progress -> { ... return true; });
The callback receives a float in [0.0, 1.0] on the loader thread
(same thread that called the constructor) and may return false to
abort, in which case the constructor throws LlamaException.
JNI: extracts the existing loadModel body into load_model_impl,
adds a trampoline that forwards float progress to a Java
LoadProgressCallback.onProgress(float)Z via CallBooleanMethod.
Trampoline state lives on the loader stack — bounded lifetime is
the single load call.
Two native entry points share the implementation:
loadModel(String[]) — unchanged signature
loadModelWithProgress(String[], LoadProgressCallback)
Tests in LoadProgressCallbackTest (model-gated): non-decreasing
progress in [0,1] reaching ~1.0, returning false aborts with
LlamaException, null callback overload delegates to plain loadModel.
All 435 C++ unit tests still pass. mvn javadoc:jar BUILD SUCCESS.
https://claude.ai/code/session_01R4ZrEy3ptJDLuUgUKuM4Gy
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New typed chat API on top of the existing handleChatCompletions JNI
path — no native changes.
Value types:
- ChatChoice, ChatResponse — choices array, Usage, Timings, raw JSON
- ToolCall, ToolDefinition — OAI-shaped tool wire types
- ChatMessage (extended) — tool_call_id + tool_calls support, with
toolResult() and assistantToolCalls() factory methods (backwards-
compatible 2-arg constructor kept for Session and existing tests)
- ToolHandler — functional interface for tool callbacks
- ChatRequest — builder with messages, tools, tool_choice,
maxToolRounds, and an InferenceParameters customizer
InferenceParameters: new setMessagesJson(String), setToolsJson(String),
setToolChoice(String) for verbatim JSON injection from ChatRequest.
LlamaModel:
- chat(ChatRequest) → ChatResponse
Serializes the request (auto-enables use_jinja when tools present),
calls chatComplete, parses the OAI JSON into ChatResponse via the
extended ChatResponseParser.parseResponse.
- chatWithTools(ChatRequest, Map<String, ToolHandler>) → ChatResponse
Agent loop: per round, calls chat(); if the assistant returned
tool_calls, invokes each handler (capturing exceptions as
{"error":...} tool results so the loop continues), appends the
assistant turn and tool-result turns to the request, and loops up to
ChatRequest.maxToolRounds (default 8). Unknown tool names produce a
{"error":"unknown tool: <name>"} result.
ChatResponseParser: new parseResponse() and tool-call/choice parsers;
handles both string-shaped and object-shaped tool_calls.arguments
(some upstream variants emit each shape).
Tests:
- ChatResponseTest (7 new unit tests, model-free): plain reply, tool
calls with string arguments, object-shaped arguments, malformed
input, ChatRequest serialization round-trip.
- LlamaModelTest: testTypedChat and testChatWithToolsLoopShortCircuits
(model-gated).
mvn javadoc:jar BUILD SUCCESS (0 errors, 60 warnings — same as before,
none from new files).
https://claude.ai/code/session_01R4ZrEy3ptJDLuUgUKuM4Gy
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…pletion complete() returned only the generated text, while chat() already exposed Usage/Timings/TokenLogprob via ChatResponse. This commit parity-fills the plain completion path: - New CompletionResult value type (text + Usage + Timings + List<TokenLogprob> + StopReason + raw JSON). - New LlamaModel.completeWithStats(InferenceParameters) calling the existing non-streaming JNI path and parsing the response via a new CompletionResponseParser.parseCompletionResult. - Maps the non-OAI completion fields: content -> text, tokens_evaluated -> Usage.promptTokens, tokens_predicted -> Usage.completionTokens, timings sub-object -> Timings, completion_probabilities -> List<TokenLogprob>, stop_type -> StopReason. complete() (the String-returning overload) is unchanged for backwards compatibility. 5 unit tests in CompletionResultTest (model-free): full response, missing-fields defaults, stop reason mapping (eos / limit / word), malformed input. mvn javadoc:jar BUILD SUCCESS, no new warnings. https://claude.ai/code/session_01R4ZrEy3ptJDLuUgUKuM4Gy
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Three new methods on LlamaModel that hand a list of requests to the native scheduler at once and collect results in input order: - completeBatch(List<InferenceParameters>) -> List<String> - completeBatchWithStats(List<InferenceParameters>) -> List<CompletionResult> - chatBatch(List<ChatRequest>) -> List<ChatResponse> Implementation reuses the existing CompletableFuture wrappers (completeAsync, supplyAsync(() -> completeWithStats/chat)) and joins them all in input order. The native worker thread runs the upstream slot scheduler, which dispatches tasks across however many slots ModelParameters.setParallel(N) was configured with. With the default N=1 the batch still works correctly, just sequentially. No JNI changes — the upstream scheduler already supports parallel slot execution; this surfaces it as a typed Java API. Three model-gated tests in LlamaModelTest exercise the order-preserving contract and per-result Usage population. mvn javadoc:jar BUILD SUCCESS, no new warnings. https://claude.ai/code/session_01R4ZrEy3ptJDLuUgUKuM4Gy
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| * On return — whether by natural stop or cancellation — the token is unbound. | ||
| * </p> | ||
| * | ||
| * @param parameters the inference configuration (its {@code stream} flag will be set to true) |
Backpressure-aware Publisher<LlamaOutput> on top of the existing streaming iterator. Reactor / RxJava / Kotlin coroutines all bridge to the Reactive Streams interface natively, so consumers wrap with Flux.from(...) / Flowable.fromPublisher(...) / asFlow() in one line. LlamaPublisher: - Single-subscriber (second subscribe signals onError per RS spec). - Each subscribe starts a dedicated emitter daemon thread. - Demand honoured via AtomicLong + monitor: emitter blocks while demand == 0 and only calls iterator.next() when demand > 0. - request(n <= 0) signals onError with IllegalArgumentException per reactive-streams §3.9. - cancel() closes the underlying iterator (cooperative, same path as LlamaIterator.close); idempotent. - onComplete fires on stop token, onError on any throwable from the iterator path. LlamaModel: - streamPublisher(InferenceParameters) and streamChatPublisher(InferenceParameters) factories. Dependency: adds org.reactivestreams:reactive-streams 1.0.4 (~5 KB, Java 8 compatible) to pom.xml. Tests in LlamaPublisherTest: - nullSubscriberThrows (model-free). - backpressureAndCancel, singleSubscriberContract, invalidRequestSignalsError (model-gated). mvn javadoc:jar BUILD SUCCESS, no new warnings. https://claude.ai/code/session_01R4ZrEy3ptJDLuUgUKuM4Gy
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The kotlin-comparison doc and the open-issues doc were both stale after PR #188 shipped 11 features. Bring them up to date in place rather than introducing a separate changelog: docs/feature-investigation-llama-stack-client-kotlin.md - §1 capability matrix gets new rows for everything that landed (typed chat + tools, async wrappers, reactive Publisher, batch dispatch, Usage/Timings, Session, completeAsJson, TokenLogprob, CancellationToken, LoadProgressCallback). - New §1.1 status legend (SHIPPED / PARTIAL / OPEN). - Each §2.x section now starts with a Status: line summarising what shipped, with commit refs into this PR. §2.2/2.3/2.4/2.5/2.7/2.8/ 2.9/2.10 marked SHIPPED. §2.6 PARTIAL (locking deferred). §2.10 PARTIAL — cooperative cancel shipped; immediate cancel needs a new server-side JNI primitive (M-effort follow-up). §2.1 OPEN (multimodal image API). docs/history/49be664_open_issues.md - #113 updated STILL POSSIBLE -> FIXED in PR #188 commit 70df324, with a note that the richer payload (file name, bytes, weights flag) is intentionally not exposed because the upstream llama_model_params.progress_callback emits only a float. No code changes, no test impact. https://claude.ai/code/session_01R4ZrEy3ptJDLuUgUKuM4Gy
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PR #188 added loadModelWithProgress in Java (LlamaModel.java:380) and a matching JNIEXPORT definition in jllama.cpp (line 747), but forgot to add the forward declaration to the legacy hand-rolled jllama.h. The generated header net_ladenthin_llama_LlamaModel.h has it, but jllama.cpp only #includes jllama.h. Without the prior 'extern "C"' declaration in scope, the C++ compiler treats the function definition as a normal C++ function and produces a mangled symbol: _Z57Java_net_ladenthin_llama_LlamaModel_loadModelWithProgress... while the JVM looks up the unmangled name and throws UnsatisfiedLinkError: 'void net.ladenthin.llama.LlamaModel .loadModelWithProgress(java.lang.String[], net.ladenthin.llama.LoadProgressCallback)' at runtime. Adding the declaration to jllama.h restores C linkage. The plain loadModel symbol was unaffected because its declaration was already present. Verified locally with nm -D libjllama.so: before: _Z57Java_..._loadModelWithProgress... (mangled) after: Java_..._loadModelWithProgress (plain C) This unblocks LoadProgressCallbackTest on all platforms.
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The two queueCancel attempts (99d1c89 and the 705f980 'fix') both broke CI: 1. The first attempt erased the reader unique_ptr from jctx->readers on the cancelling thread, racing the inference thread's borrowed raw 'rd' pointer inside next(). Observed as std::system_error JVM aborts (exit 134) on Linux. 2. The second attempt left the reader alive and posted CANCEL through reader->queue_tasks.post(), expecting the slot's release to emit a natural stop result on queue_results. Inspection of upstream build/_deps/llama.cpp-src/tools/server/server-context.cpp:356-376 showed server_slot::release() only sets state = SLOT_STATE_IDLE and calls reset() — it does NOT post any result. The inference thread therefore blocked forever inside recv_with_timeout(id_tasks, 1 s) with should_stop hard-coded to false. CI hung on LlamaModelTest until the workflow was cancelled (the artifact from that run contains no LlamaModelTest.txt because surefire writes the per-class summary only when the class finishes). The cooperative path that shipped in PR #188 (ad66e3a + e3b9043) already achieves one-token-interval cancel latency (~150 ms), which matches the sub-token goal in practice. A genuine sub-token cancel would require an upstream change to SERVER_TASK_TYPE_CANCEL's slot handler so it emits a stop result on queue_results, or a should_stop predicate plumbed into receiveCompletionJson — the latter has worse latency than the cooperative path (>= 1 s polling interval). Revert - jllama.cpp: remove Java_net_ladenthin_llama_LlamaModel_queueCancel; cancelCompletion is the only cancel JNI entry point again. - jllama.h: remove the queueCancel forward declaration. - LlamaModel.java: remove the 'native void queueCancel(int)' declaration; restore complete(params, token) to the original cooperative loop that calls cancelCompletion(taskId) and breaks on isCancelled. - CancellationToken.java: restore to just the volatile cancelled flag (no registeredModel / registeredTaskId fields, no register / unregister methods). Class javadoc records the two failed follow-up attempts so the next person does not re-walk this path. Doc - §2.10 in docs/feature-investigation-llama-stack-client-kotlin.md flipped from SHIPPED back to 'SHIPPED — cooperative only', with a detailed postmortem of both failed attempts including the exact upstream source lines that demonstrate why the design cannot work without upstream changes. Verified - cmake --build build --target jllama: BUILD SUCCESS. nm -D shows only Java_..._cancelCompletion; queueCancel symbol is gone. - mvn test -Dtest='CancellationTokenTest,ContentPartTest, MultimodalMessagesTest,SessionConcurrencyTest': BUILD SUCCESS, 31 tests pass. - mvn javadoc:jar: BUILD SUCCESS.
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Three small gaps caught in a final audit of the §-doc and the issues doc: 1. feature-investigation §1 'What java-llama.cpp already covers': the Session row still read 'single-threaded'. PR #189 added per-Session locking; relabel to 'thread-safe per instance' so the §1 table matches the §2.6 status block. 2. feature-investigation §4 'Suggested rollout order': all ten entries listed there are SHIPPED now. The section is preserved as a historical artifact (useful for comparing original effort estimates against what actually shipped, especially §2.1 which came in much smaller than the L estimate and §2.10 which had to be reverted), but a header note now states up front that it is no longer a roadmap. 3. docs/history/49be664_open_issues.md #113 LoadProgressCallback: the entry said FIXED in PR #188 and stopped there, but the PR #188 implementation forgot the forward declaration in jllama.h, which made the JNI symbol C++-mangled and produced an UnsatisfiedLinkError on the first call to the feature. PR #189 commit 36d8862 added the missing declaration and the feature is now actually functional (LoadProgressCallbackTest passes on the current CI). Add a 'Subtle issue resolved by PR #189' paragraph so a future reader does not think 'PR #188 shipped this, why did it fail on the first run after merge'. No code changes; documentation only.
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Summary
completeAsync(),chatCompleteAsync(), andchatCompleteTextAsync()to run inference on the ForkJoinPool without blocking the callerCancellationTokenclass andcomplete(InferenceParameters, CancellationToken)to allow cross-thread cancellation of blocking inference callsServerMetrics,Usage, andTimingsclasses to provide structured access to server metrics JSON with derived fields (e.g., throughput rates)Sessionclass for multi-turn conversations with automatic message accumulation and KV-cache save/restoreLlamaOutputwithTokenLogproblist for per-token alternatives and token IDs (in addition to the existing token-to-probability map)setJsonSchema()parameter andcompleteForType()method for schema-constrained generation with automatic deserializationgenerate()andLlamaIteratorto clarify resource management and cancellation semanticsTest plan
CancellationTokenTest: State transitions and idempotencyUsageTest: Token counting and equalityChatMessageTest: Value class accessorsTimingsTest: JSON parsing with missing fieldsServerMetricsTest: Typed getters and derived throughput ratesTokenLogprobTest: Completion probability parsing (post- and pre-sampling modes)LlamaModelTest: New regression tests for iterator idempotency, cancellation token cross-thread behavior, async completion, and session multi-turnRelated issues / PRs
Checklist
CONTRIBUTING.mdandCODE_OF_CONDUCT.mdhttps://claude.ai/code/session_01R4ZrEy3ptJDLuUgUKuM4Gy