From 0ec8f04539563db365abfae18361d9e5b1051e06 Mon Sep 17 00:00:00 2001 From: LLoyal Research Date: Wed, 11 Feb 2026 02:29:07 +1100 Subject: [PATCH 01/13] feat(chat): new chat api --- .gitignore | 2 +- README.md | 2 +- examples/chat/chat.mjs | 44 +++--- lib/index.d.ts | 347 ++++++++++++++++++++++++++++++++++++++++- liblloyal | 2 +- src/SessionContext.cpp | 176 +++++++++++++++++---- src/SessionContext.hpp | 1 + test/integration.js | 313 +++++++++++++++++++++++++++++++++++++ test/matrix.json | 8 +- 9 files changed, 829 insertions(+), 66 deletions(-) diff --git a/.gitignore b/.gitignore index 1a11391..95b20dd 100644 --- a/.gitignore +++ b/.gitignore @@ -9,7 +9,7 @@ models/ # Generated documentation docs/api/ - +docs/_internal # Vendor build artifacts (generated during npm install) vendor/llama.cpp/build-*/ diff --git a/README.md b/README.md index 8698b36..a4bcca3 100644 --- a/README.md +++ b/README.md @@ -82,7 +82,7 @@ CI integration testing (real inference): | Qwen | Qwen 3 1.7B | chatml | | Gemma | Gemma 3 1B | gemma | | SmolLM | SmolLM2 1.7B | chatml | -| TinyLlama | TinyLlama 1.1B | zephyr | +| Ministral | Ministral 3B | mistral | See [distribution.md](docs/distribution.md) for details. diff --git a/examples/chat/chat.mjs b/examples/chat/chat.mjs index 396edb4..3256158 100644 --- a/examples/chat/chat.mjs +++ b/examples/chat/chat.mjs @@ -12,15 +12,15 @@ * - Clear separation: sync produce, async commit */ -import * as readline from 'node:readline'; -import * as path from 'node:path'; -import { fileURLToPath } from 'node:url'; -import { createContext } from '../../lib/index.js'; +import * as readline from "node:readline"; +import * as path from "node:path"; +import { fileURLToPath } from "node:url"; +import { createContext } from "../../lib/index.js"; const __dirname = path.dirname(fileURLToPath(import.meta.url)); const DEFAULT_MODEL = path.resolve( __dirname, - '../../models/SmolLM2-1.7B-Instruct-Q4_K_M.gguf' + "../../models/SmolLM2-1.7B-Instruct-Q4_K_M.gguf", ); /** @@ -40,7 +40,7 @@ async function main() { const modelPath = process.argv[2] || DEFAULT_MODEL; console.log(`Loading model: ${modelPath}`); - console.log('This may take a moment...\n'); + console.log("This may take a moment...\n"); const ctx = await createContext({ modelPath, @@ -48,37 +48,37 @@ async function main() { threads: 4, }); - console.log('Model loaded! Type your message and press Enter.'); - console.log('Commands: /clear to reset, /quit to exit\n'); + console.log("Model loaded! Type your message and press Enter."); + console.log("Commands: /clear to reset, /quit to exit\n"); const messages = []; let position = 0; - let lastPrompt = ''; + let lastPrompt = ""; const rl = readline.createInterface({ input: process.stdin, output: process.stdout, }); - const askUser = () => rl.question('> ', handleInput); + const askUser = () => rl.question("> ", handleInput); async function handleInput(input) { const trimmed = input.trim(); - if (trimmed === '/quit' || trimmed === '/exit') { - console.log('Goodbye!'); + if (trimmed === "/quit" || trimmed === "/exit") { + console.log("Goodbye!"); ctx.dispose(); rl.close(); return; } - if (trimmed === '/clear') { + if (trimmed === "/clear") { await ctx.kvCacheClear(); messages.length = 0; position = 0; - lastPrompt = ''; + lastPrompt = ""; console.clear(); - console.log('Conversation cleared.\n'); + console.log("Conversation cleared.\n"); askUser(); return; } @@ -88,11 +88,11 @@ async function main() { return; } - messages.push({ role: 'user', content: trimmed }); + messages.push({ role: "user", content: trimmed }); // Format with chat template const { prompt: fullPrompt } = await ctx.formatChat( - JSON.stringify(messages) + JSON.stringify(messages), ); // Prompt diffing - only tokenize new content @@ -105,8 +105,8 @@ async function main() { position += tokens.length; // Generate: sync produce, async commit - process.stdout.write('< '); - let response = ''; + process.stdout.write("< "); + let response = ""; for (const { text, tokenId } of produceTokens(ctx, { temperature: 0.7, @@ -120,9 +120,9 @@ async function main() { position += 1; } - console.log('\n'); + console.log("\n"); - messages.push({ role: 'assistant', content: response.trim() }); + messages.push({ role: "assistant", content: response.trim() }); lastPrompt = fullPrompt + response; askUser(); @@ -132,6 +132,6 @@ async function main() { } main().catch((err) => { - console.error('Error:', err.message); + console.error("Error:", err.message); process.exit(1); }); diff --git a/lib/index.d.ts b/lib/index.d.ts index 8a3c797..a762547 100644 --- a/lib/index.d.ts +++ b/lib/index.d.ts @@ -110,12 +110,282 @@ export interface ContextOptions { nSeqMax?: number; } +/** + * Chat format detected by the template engine + * + * Identifies how the model formats tool calls, reasoning blocks, and content. + * Returned by {@link SessionContext.formatChat | formatChat()} in + * {@link FormattedChatResult.format} and consumed by + * {@link SessionContext.parseChatOutput | parseChatOutput()}. + * + * You generally don't need to inspect these values directly -- + * just pass them through from the formatChat result to parseChatOutput. + * + * Only commonly-used values are listed. The full set matches llama.cpp's + * `common_chat_format` enum (30+ formats). + */ +export enum ChatFormat { + /** Plain content, no special formatting */ + CONTENT_ONLY = 0, + /** Generic tool call format */ + GENERIC = 1, +} + +/** + * Reasoning/thinking block format + * + * Controls how `` blocks are handled during formatting and parsing. + * + * @see {@link FormatChatOptions.reasoningFormat} for input-side usage + * @see {@link ParseChatOutputOptions.reasoningFormat} for output-side usage + */ +export enum ReasoningFormat { + /** No reasoning extraction (default) */ + NONE = 0, + /** Auto-detect reasoning format from model template */ + AUTO = 1, + /** DeepSeek legacy format (`...` in content) */ + DEEPSEEK_LEGACY = 2, + /** DeepSeek format (structured reasoning extraction) */ + DEEPSEEK = 3, +} + +/** + * Grammar trigger type + * + * Determines how lazy grammar activation is triggered during generation. + * + * @see {@link GrammarTrigger} + * @see {@link FormattedChatResult.grammarTriggers} + */ +export enum GrammarTriggerType { + /** Trigger on a specific token ID */ + TOKEN = 0, + /** Trigger on a word boundary match */ + WORD = 1, + /** Trigger on a regex pattern match */ + PATTERN = 2, + /** Trigger on a full-string regex pattern match */ + PATTERN_FULL = 3, +} + +/** + * Options for chat template formatting + * + * Controls format-awareness fields passed to the chat template engine. + * All fields are optional -- sensible defaults are used when omitted. + * + * @example With tools and reasoning + * ```typescript + * const result = await ctx.formatChat(messagesJson, { + * tools: JSON.stringify(tools), + * toolChoice: 'auto', + * reasoningFormat: 'auto', + * }); + * ``` + */ +export interface FormatChatOptions { + /** Custom Jinja2 template override (bypasses model's built-in template) */ + templateOverride?: string; + + /** + * JSON array of OpenAI-format tool definitions + * + * @example + * ```typescript + * const tools = [{ type: 'function', function: { + * name: 'get_weather', + * description: 'Get current weather', + * parameters: { type: 'object', properties: { location: { type: 'string' } } } + * }}]; + * options.tools = JSON.stringify(tools); + * ``` + */ + tools?: string; + + /** Tool choice strategy (default: "auto") */ + toolChoice?: 'auto' | 'required' | 'none'; + + /** Allow parallel tool calls (default: false) */ + parallelToolCalls?: boolean; + + /** + * Reasoning format (default: "none") + * + * Controls `` block handling in the template. + * Use "auto" to let the model's template decide. + */ + reasoningFormat?: 'none' | 'auto' | 'deepseek' | 'deepseek_legacy'; + + /** Enable `` blocks (default: true). Pairs with reasoningFormat. */ + enableThinking?: boolean; + + /** + * JSON schema for constrained output. Converted to GBNF grammar internally. + * Mutually exclusive with `grammar`. + * + * @see {@link SessionContext.jsonSchemaToGrammar} + */ + jsonSchema?: string; + + /** + * Explicit GBNF grammar string for constrained generation. + * Mutually exclusive with `jsonSchema`. + * + * @see {@link SessionContext.createSampler} + */ + grammar?: string; + + /** + * Append assistant prompt prefix (default: true). + * Set false when formatting partial conversations or for + * non-generation use cases like template validation. + */ + addGenerationPrompt?: boolean; +} + +/** + * Grammar trigger from format-aware chat template + * + * Defines conditions for lazy grammar activation. When `grammarLazy` is true + * in {@link FormattedChatResult}, generation runs unconstrained until one of + * these triggers fires, at which point the grammar is activated. + */ +export interface GrammarTrigger { + /** Trigger type */ + type: GrammarTriggerType; + /** Trigger value (token text, word, or regex pattern depending on type) */ + value: string; + /** Token ID (for TOKEN-type triggers, -1 when not applicable) */ + token: number; +} + /** * Result from chat template formatting + * + * Includes format-awareness fields for proper output parsing. + * Pass `format` and `reasoningFormat` directly to + * {@link SessionContext.parseChatOutput | parseChatOutput()} to decode + * the model's response. + * + * @example Roundtrip: format -> generate -> parse + * ```typescript + * const fmt = await ctx.formatChat(messagesJson, { tools: toolsJson }); + * // ... generate tokens using fmt.prompt and fmt.grammar ... + * const parsed = ctx.parseChatOutput(output, fmt.format, { + * reasoningFormat: fmt.reasoningFormat, + * thinkingForcedOpen: fmt.thinkingForcedOpen, + * parser: fmt.parser, + * }); + * ``` + * + * @see {@link SessionContext.parseChatOutput} */ export interface FormattedChatResult { + /** Formatted prompt string ready for tokenization */ prompt: string; + /** Additional stop strings from the template */ stopTokens: string[]; + + /** + * Detected chat format (pass to parseChatOutput) + * @see {@link SessionContext.parseChatOutput} + */ + format: ChatFormat; + + /** Grammar string for constrained generation (empty if no tools/schema) */ + grammar: string; + /** Whether grammar should be applied lazily (only after triggers fire) */ + grammarLazy: boolean; + /** Whether the thinking tag was forced open by the template */ + thinkingForcedOpen: boolean; + + /** + * Reasoning format (pass to parseChatOutput options) + * @see {@link ParseChatOutputOptions.reasoningFormat} + */ + reasoningFormat: ReasoningFormat; + + /** PEG parser definition for PEG format models (pass to parseChatOutput options) */ + parser: string; + /** Grammar trigger conditions for lazy grammar activation */ + grammarTriggers: GrammarTrigger[]; + /** Token strings preserved from grammar masking */ + preservedTokens: string[]; +} + +/** + * Options for parsing chat output + * + * All fields are optional. For correct parsing, pass through the corresponding + * fields from {@link FormattedChatResult}. + * + * @see {@link FormattedChatResult} + */ +export interface ParseChatOutputOptions { + /** + * Reasoning format (from {@link FormattedChatResult.reasoningFormat}) + */ + reasoningFormat?: ReasoningFormat; + + /** + * True if output is incomplete (streaming). + * When true, the parser tolerates unterminated tool calls and open + * thinking blocks, returning partial content as-is rather than + * treating them as parse errors. + */ + isPartial?: boolean; + + /** Whether thinking tag was forced open (from {@link FormattedChatResult.thinkingForcedOpen}) */ + thinkingForcedOpen?: boolean; + + /** PEG parser definition for PEG format models (from {@link FormattedChatResult.parser}) */ + parser?: string; +} + +/** + * A tool call extracted from model output + * + * @example + * ```typescript + * for (const tc of result.toolCalls) { + * const args = JSON.parse(tc.arguments); + * await executeTool(tc.name, args); + * } + * ``` + */ +export interface ParsedToolCall { + /** Tool/function name */ + name: string; + /** JSON string of arguments */ + arguments: string; + /** Tool call ID (may be empty depending on model format) */ + id: string; +} + +/** + * Result from parsing chat output + * + * @example + * ```typescript + * const result = ctx.parseChatOutput(output, fmt.format); + * if (result.toolCalls.length > 0) { + * for (const tc of result.toolCalls) { + * const args = JSON.parse(tc.arguments); + * await executeTool(tc.name, args); + * } + * } else { + * console.log(result.content); + * } + * ``` + */ +export interface ParseChatOutputResult { + /** Main response text */ + content: string; + /** Extracted thinking/reasoning content (empty if none) */ + reasoningContent: string; + /** Extracted tool calls (empty array if none) */ + toolCalls: ParsedToolCall[]; } /** @@ -1074,15 +1344,21 @@ export interface SessionContext { /** * Format messages using model's chat template * - * Converts [{role, content}] → formatted prompt string. + * Converts [{role, content}] → formatted prompt string with full format awareness. * Uses model's built-in template (ChatML, Llama, Mistral, etc.). * + * The returned `format` and `reasoningFormat` fields should be passed to + * `parseChatOutput()` after generation to correctly decode the response. + * * Cost: ~1-5ms depending on message count * * @param messagesJson JSON string containing array of messages - * @param templateOverride Optional custom template string - * @returns Formatted prompt and stop tokens from template - * @example + * @param options Formatting options (tools, reasoning, grammar, etc.) + * @returns Formatted prompt with format-awareness metadata + * + * @see {@link parseChatOutput} + * + * @example Basic usage * ```typescript * const result = await ctx.formatChat(JSON.stringify([ * { role: "system", content: "You are a helpful assistant" }, @@ -1092,12 +1368,67 @@ export interface SessionContext { * const tokens = await ctx.tokenize(result.prompt); * await ctx.decode(tokens, 0); * ``` + * + * @example With tools + * ```typescript + * const tools = [{ type: 'function', function: { + * name: 'get_weather', description: 'Get weather', + * parameters: { type: 'object', properties: { location: { type: 'string' } } } + * }}]; + * const result = await ctx.formatChat(JSON.stringify(messages), { + * tools: JSON.stringify(tools), + * toolChoice: 'auto' + * }); + * // result.grammar contains GBNF for constrained tool call generation + * // result.format identifies the chat format for output parsing + * ``` + * + * @example Backward compatible (string as second arg) + * ```typescript + * const result = await ctx.formatChat(messagesJson, templateOverrideString); + * ``` */ formatChat( messagesJson: string, - templateOverride?: string + options?: FormatChatOptions | string ): Promise; + /** + * Parse model output into structured content + * + * Extracts plain text, reasoning/thinking blocks, and tool calls from + * raw model output. Uses the format detected by {@link formatChat} to apply + * the correct parser for the model's output format. + * + * Cost: <0.1ms (synchronous string parsing, no I/O) + * + * @param output Raw model output text + * @param format Chat format enum (from {@link FormattedChatResult.format}) + * @param options Optional parsing parameters + * @returns Parsed content with tool calls and reasoning + * + * @see {@link formatChat} + * + * @example Basic parsing + * ```typescript + * const fmt = await ctx.formatChat(JSON.stringify(messages), { tools: toolsJson }); + * // ... generate tokens ... + * const parsed = ctx.parseChatOutput(generatedText, fmt.format, { + * reasoningFormat: fmt.reasoningFormat, + * thinkingForcedOpen: fmt.thinkingForcedOpen, + * parser: fmt.parser + * }); + * if (parsed.toolCalls.length > 0) { + * // Handle tool calls + * } + * ``` + */ + parseChatOutput( + output: string, + format: ChatFormat, + options?: ParseChatOutputOptions + ): ParseChatOutputResult; + /** * Convert JSON schema to GBNF grammar * @@ -1307,6 +1638,12 @@ export interface SessionContext { /** @internal Reseed branch sampler PRNG for diversity after fork */ _branchSamplerChainReseed(handle: number, seed: number): void; + + /** @internal Set dynamic logit biases for a branch */ + _branchSteer(handle: number, biases: Array<{ token: number; bias: number }>): void; + + /** @internal Clear all dynamic logit biases from a branch */ + _branchClearSteer(handle: number): void; } /** diff --git a/liblloyal b/liblloyal index 9c8fc25..158bb8e 160000 --- a/liblloyal +++ b/liblloyal @@ -1 +1 @@ -Subproject commit 9c8fc25bebcdc66a3ff74061b266cf24de51d81f +Subproject commit 158bb8ed600121fe2b8f0ec1fd3646729258da0c diff --git a/src/SessionContext.cpp b/src/SessionContext.cpp index 1992caf..65bb323 100644 --- a/src/SessionContext.cpp +++ b/src/SessionContext.cpp @@ -6,7 +6,8 @@ #include #include #include -#include +#include +#include #include #include #include @@ -510,27 +511,21 @@ class DetokenizeWorker : public Napi::AsyncWorker { class FormatChatWorker : public Napi::AsyncWorker { public: FormatChatWorker(Napi::Env env, std::shared_ptr model, - const std::string& messagesJson, const std::string& templateOverride) - : AsyncWorker(env), _deferred(env), _model(model), - _messagesJson(messagesJson), _templateOverride(templateOverride) {} + const lloyal::chat_in::FormatInputs& inputs) + : AsyncWorker(env), _deferred(env), _model(model), _inputs(inputs) {} void Execute() override { try { - // Use lloyal::chat_template::format() from liblloyal - lloyal::chat_template::FormatResult result = lloyal::chat_template::format( - _model.get(), - _messagesJson, - _templateOverride + lloyal::chat_in::FormatResult result = lloyal::chat_in::format( + _model.get(), _inputs ); - // Check if formatting failed completely if (result.prompt.empty()) { SetError("Chat template formatting failed"); return; } - _resultPrompt = result.prompt; - _resultStopTokens = result.additional_stops; + _result = result; } catch (const std::exception& e) { SetError(e.what()); } @@ -539,17 +534,42 @@ class FormatChatWorker : public Napi::AsyncWorker { void OnOK() override { Napi::Env env = Env(); - // Create result object { prompt: string, stopTokens: string[] } Napi::Object result = Napi::Object::New(env); - result.Set("prompt", Napi::String::New(env, _resultPrompt)); + result.Set("prompt", Napi::String::New(env, _result.prompt)); - // Convert stopTokens vector to JS array - Napi::Array stopTokens = Napi::Array::New(env, _resultStopTokens.size()); - for (size_t i = 0; i < _resultStopTokens.size(); i++) { - stopTokens[i] = Napi::String::New(env, _resultStopTokens[i]); + // stopTokens (backward compat) + Napi::Array stopTokens = Napi::Array::New(env, _result.additional_stops.size()); + for (size_t i = 0; i < _result.additional_stops.size(); i++) { + stopTokens[i] = Napi::String::New(env, _result.additional_stops[i]); } result.Set("stopTokens", stopTokens); + // Format awareness fields + result.Set("format", Napi::Number::New(env, static_cast(_result.format))); + result.Set("grammar", Napi::String::New(env, _result.grammar)); + result.Set("grammarLazy", Napi::Boolean::New(env, _result.grammar_lazy)); + result.Set("thinkingForcedOpen", Napi::Boolean::New(env, _result.thinking_forced_open)); + result.Set("reasoningFormat", Napi::Number::New(env, static_cast(_result.reasoning_format))); + result.Set("parser", Napi::String::New(env, _result.parser)); + + // grammarTriggers: Array<{ type: number, value: string, token: number }> + Napi::Array triggers = Napi::Array::New(env, _result.grammar_triggers.size()); + for (size_t i = 0; i < _result.grammar_triggers.size(); i++) { + Napi::Object trigger = Napi::Object::New(env); + trigger.Set("type", Napi::Number::New(env, static_cast(_result.grammar_triggers[i].type))); + trigger.Set("value", Napi::String::New(env, _result.grammar_triggers[i].value)); + trigger.Set("token", Napi::Number::New(env, static_cast(_result.grammar_triggers[i].token))); + triggers[i] = trigger; + } + result.Set("grammarTriggers", triggers); + + // preservedTokens: string[] + Napi::Array preserved = Napi::Array::New(env, _result.preserved_tokens.size()); + for (size_t i = 0; i < _result.preserved_tokens.size(); i++) { + preserved[i] = Napi::String::New(env, _result.preserved_tokens[i]); + } + result.Set("preservedTokens", preserved); + _deferred.Resolve(result); } @@ -562,10 +582,8 @@ class FormatChatWorker : public Napi::AsyncWorker { private: Napi::Promise::Deferred _deferred; std::shared_ptr _model; - std::string _messagesJson; - std::string _templateOverride; - std::string _resultPrompt; - std::vector _resultStopTokens; + lloyal::chat_in::FormatInputs _inputs; + lloyal::chat_in::FormatResult _result; }; // ===== SESSIONCONTEXT IMPLEMENTATION ===== @@ -612,6 +630,7 @@ Napi::Object SessionContext::Init(Napi::Env env, Napi::Object exports) { // ===== HELPERS ===== InstanceMethod("formatChat", &SessionContext::formatChat), + InstanceMethod("parseChatOutput", &SessionContext::parseChatOutput), InstanceMethod("jsonSchemaToGrammar", &SessionContext::jsonSchemaToGrammar), InstanceMethod("validateChatTemplate", &SessionContext::validateChatTemplate), @@ -1125,7 +1144,7 @@ Napi::Value SessionContext::getTurnSeparator(const Napi::CallbackInfo& info) { // Compute once, cache thereafter if (!_turnSeparatorCached) { - _turnSeparatorCache = lloyal::chat_template::get_turn_separator(_model.get()); + _turnSeparatorCache = lloyal::chat_in::get_turn_separator(_model.get()); _turnSeparatorCached = true; } @@ -1141,18 +1160,51 @@ Napi::Value SessionContext::formatChat(const Napi::CallbackInfo& info) { ensureNotDisposed(); if (info.Length() < 1 || !info[0].IsString()) { - throw Napi::TypeError::New(env, "Expected (messagesJson: string[, templateOverride: string])"); + throw Napi::TypeError::New(env, "Expected (messagesJson: string[, options: object])"); } - std::string messagesJson = info[0].As().Utf8Value(); - std::string templateOverride = ""; + lloyal::chat_in::FormatInputs inputs; + inputs.messages_json = info[0].As().Utf8Value(); - if (info.Length() >= 2 && info[1].IsString()) { - templateOverride = info[1].As().Utf8Value(); + // Second argument: options object (or string for backward compat) + if (info.Length() >= 2) { + if (info[1].IsString()) { + // Backward compat: formatChat(messagesJson, templateOverride) + inputs.template_override = info[1].As().Utf8Value(); + } else if (info[1].IsObject()) { + Napi::Object opts = info[1].As(); + + if (opts.Has("templateOverride") && opts.Get("templateOverride").IsString()) { + inputs.template_override = opts.Get("templateOverride").As().Utf8Value(); + } + if (opts.Has("tools") && opts.Get("tools").IsString()) { + inputs.tools_json = opts.Get("tools").As().Utf8Value(); + } + if (opts.Has("toolChoice") && opts.Get("toolChoice").IsString()) { + inputs.tool_choice = opts.Get("toolChoice").As().Utf8Value(); + } + if (opts.Has("parallelToolCalls") && opts.Get("parallelToolCalls").IsBoolean()) { + inputs.parallel_tool_calls = opts.Get("parallelToolCalls").As().Value(); + } + if (opts.Has("reasoningFormat") && opts.Get("reasoningFormat").IsString()) { + inputs.reasoning_format = opts.Get("reasoningFormat").As().Utf8Value(); + } + if (opts.Has("enableThinking") && opts.Get("enableThinking").IsBoolean()) { + inputs.enable_thinking = opts.Get("enableThinking").As().Value(); + } + if (opts.Has("jsonSchema") && opts.Get("jsonSchema").IsString()) { + inputs.json_schema = opts.Get("jsonSchema").As().Utf8Value(); + } + if (opts.Has("grammar") && opts.Get("grammar").IsString()) { + inputs.grammar = opts.Get("grammar").As().Utf8Value(); + } + if (opts.Has("addGenerationPrompt") && opts.Get("addGenerationPrompt").IsBoolean()) { + inputs.add_generation_prompt = opts.Get("addGenerationPrompt").As().Value(); + } + } } - // Run async - auto* worker = new FormatChatWorker(env, _model, messagesJson, templateOverride); + auto* worker = new FormatChatWorker(env, _model, inputs); worker->Queue(); return worker->GetPromise(); } @@ -1742,9 +1794,9 @@ Napi::Value SessionContext::validateChatTemplate(const Napi::CallbackInfo& info) : AsyncWorker(env), _deferred(env), _templateString(templateStr) {} void Execute() override { - // Use lloyal::chat_template from liblloyal (handles error logging) + // Use lloyal::chat_in from liblloyal (handles error logging) // Pattern matches HybridSessionContext.cpp:365-372 - _result = lloyal::chat_template::validate(_templateString); + _result = lloyal::chat_in::validate(_templateString); } void OnOK() override { @@ -1768,6 +1820,66 @@ Napi::Value SessionContext::validateChatTemplate(const Napi::CallbackInfo& info) return worker->GetPromise(); } +// ===== CHAT OUTPUT PARSING ===== + +Napi::Value SessionContext::parseChatOutput(const Napi::CallbackInfo& info) { + Napi::Env env = info.Env(); + ensureNotDisposed(); + + // Args: output (string), format (number), options? (object) + if (info.Length() < 2 || !info[0].IsString() || !info[1].IsNumber()) { + throw Napi::TypeError::New(env, "Expected (output: string, format: number[, options: object])"); + } + + std::string output = info[0].As().Utf8Value(); + auto format = static_cast(info[1].As().Int32Value()); + + // Optional params + auto reasoning_format = COMMON_REASONING_FORMAT_NONE; + bool is_partial = false; + bool thinking_forced_open = false; + std::string parser_data; + + if (info.Length() >= 3 && info[2].IsObject()) { + Napi::Object opts = info[2].As(); + + if (opts.Has("reasoningFormat") && opts.Get("reasoningFormat").IsNumber()) { + reasoning_format = static_cast( + opts.Get("reasoningFormat").As().Int32Value()); + } + if (opts.Has("isPartial") && opts.Get("isPartial").IsBoolean()) { + is_partial = opts.Get("isPartial").As().Value(); + } + if (opts.Has("thinkingForcedOpen") && opts.Get("thinkingForcedOpen").IsBoolean()) { + thinking_forced_open = opts.Get("thinkingForcedOpen").As().Value(); + } + if (opts.Has("parser") && opts.Get("parser").IsString()) { + parser_data = opts.Get("parser").As().Utf8Value(); + } + } + + // Synchronous — parsing is fast, no I/O + auto result = lloyal::chat_out::parse(output, format, reasoning_format, + is_partial, thinking_forced_open, parser_data); + + // Build return object + Napi::Object obj = Napi::Object::New(env); + obj.Set("content", Napi::String::New(env, result.content)); + obj.Set("reasoningContent", Napi::String::New(env, result.reasoning_content)); + + Napi::Array toolCalls = Napi::Array::New(env, result.tool_calls.size()); + for (size_t i = 0; i < result.tool_calls.size(); i++) { + Napi::Object tc = Napi::Object::New(env); + tc.Set("name", Napi::String::New(env, result.tool_calls[i].name)); + tc.Set("arguments", Napi::String::New(env, result.tool_calls[i].arguments)); + tc.Set("id", Napi::String::New(env, result.tool_calls[i].id)); + toolCalls[i] = tc; + } + obj.Set("toolCalls", toolCalls); + + return obj; +} + // ===== KV CACHE OPERATIONS ===== // Pattern matches HybridSessionContext.cpp:550-642 diff --git a/src/SessionContext.hpp b/src/SessionContext.hpp index f729ed2..b42ca1d 100644 --- a/src/SessionContext.hpp +++ b/src/SessionContext.hpp @@ -142,6 +142,7 @@ class SessionContext : public Napi::ObjectWrap { * Returns: Promise<{ prompt: string, stopTokens: string[] }> */ Napi::Value formatChat(const Napi::CallbackInfo& info); + Napi::Value parseChatOutput(const Napi::CallbackInfo& info); /** * Get current KV cache position (number of tokens in cache) diff --git a/test/integration.js b/test/integration.js index b8d50e5..b02a222 100644 --- a/test/integration.js +++ b/test/integration.js @@ -381,6 +381,260 @@ async function testBranchPrefill() { } } +// ═══════════════════════════════════════════════════════════════════════════ +// WARM vs COLD PARITY - Semantic proof that warm continuation == cold start +// ═══════════════════════════════════════════════════════════════════════════ + +async function testWarmColdParity() { + console.log('\n--- Warm vs Cold Parity ---'); + + const GEN_TOKENS = 10; + const userMessages = [ + "What is the capital of France?", + " Tell me more about it." + ]; + + // === WARM PATH: decode turn 1, prefill turn 2 delta, generate === + const warmCtx = await addon.createContext({ + modelPath: MODEL_PATH, + nCtx: 2048, + nBatch: 512, + nThreads: 4 + }); + + let assistantContent; + let warmGen2; + + try { + // Turn 1: format, decode, generate + const msgs1 = [{ role: 'user', content: userMessages[0] }]; + const { prompt: prompt1 } = await warmCtx.formatChat(JSON.stringify(msgs1)); + const toks1 = await warmCtx.tokenize(prompt1); + await warmCtx.decode(toks1, 0, 0); + + const branch = Branch.create(warmCtx, 0, toks1.length, { temperature: 0 }); + branch.captureLogits(); + + const gen1 = []; + for (let i = 0; i < GEN_TOKENS; i++) { + const { token, isStop } = branch.produce(); + if (isStop) break; + branch.commit(token); + gen1.push(token); + } + + assistantContent = await warmCtx.detokenize(gen1); + const lastText = prompt1 + assistantContent; + + // Turn 2: prefill delta, generate + const msgs2 = [ + { role: 'user', content: userMessages[0] }, + { role: 'assistant', content: assistantContent }, + { role: 'user', content: userMessages[1] } + ]; + const { prompt: fullPrompt2 } = await warmCtx.formatChat(JSON.stringify(msgs2)); + const delta = fullPrompt2.slice(lastText.length); + const deltaToks = await warmCtx.tokenize(delta); + branch.prefill(deltaToks); + + warmGen2 = []; + for (let i = 0; i < GEN_TOKENS; i++) { + const { token, isStop } = branch.produce(); + if (isStop) break; + branch.commit(token); + warmGen2.push(token); + } + + branch.prune(); + } finally { + warmCtx.dispose(); + } + + // === COLD PATH: decode full 2-turn conversation from scratch, generate === + const coldCtx = await addon.createContext({ + modelPath: MODEL_PATH, + nCtx: 2048, + nBatch: 512, + nThreads: 4 + }); + + let coldGen2; + + try { + const msgs = [ + { role: 'user', content: userMessages[0] }, + { role: 'assistant', content: assistantContent }, + { role: 'user', content: userMessages[1] } + ]; + const { prompt: coldPrompt } = await coldCtx.formatChat(JSON.stringify(msgs)); + const coldToks = await coldCtx.tokenize(coldPrompt); + await coldCtx.decode(coldToks, 0, 0); + + const branch = Branch.create(coldCtx, 0, coldToks.length, { temperature: 0 }); + branch.captureLogits(); + + coldGen2 = []; + for (let i = 0; i < GEN_TOKENS; i++) { + const { token, isStop } = branch.produce(); + if (isStop) break; + branch.commit(token); + coldGen2.push(token); + } + + branch.prune(); + } finally { + coldCtx.dispose(); + } + + // === COMPARE === + const warmStr = warmGen2.join(','); + const coldStr = coldGen2.join(','); + assert(warmStr === coldStr, + `Warm==Cold parity: ${warmGen2.length} tokens match`); + + if (warmStr !== coldStr) { + // Diagnostic: show first divergence point + for (let i = 0; i < Math.max(warmGen2.length, coldGen2.length); i++) { + if (warmGen2[i] !== coldGen2[i]) { + console.log(` First divergence at position ${i}: warm=${warmGen2[i]} cold=${coldGen2[i]}`); + break; + } + } + } +} + +// ═══════════════════════════════════════════════════════════════════════════ +// WARM CONTINUATION SEMANTIC RECALL - Proves context survives delta-only prefill +// ═══════════════════════════════════════════════════════════════════════════ + +async function testWarmSemanticRecall() { + if (!EMBED_MODEL_PATH) { + console.log('\n--- Warm Semantic Recall (SKIPPED - no LLAMA_EMBED_MODEL) ---'); + return; + } + + console.log('\n--- Warm Semantic Recall ---'); + + const GEN_TOKENS = 40; + + // Helper: cosine similarity + function cosine(a, b) { + let dot = 0, na = 0, nb = 0; + for (let i = 0; i < a.length; i++) { + dot += a[i] * b[i]; + na += a[i] * a[i]; + nb += b[i] * b[i]; + } + return dot / (Math.sqrt(na) * Math.sqrt(nb)); + } + + // Phase 1: Generate multi-turn conversation via warm continuation + let recallText; + { + const ctx = await addon.createContext({ + modelPath: MODEL_PATH, + nCtx: 2048, + nBatch: 512, + nThreads: 4 + }); + + try { + // Helper: warm-continue one turn (prefill delta, generate) + async function warmTurn(messages, lastText, userContent) { + messages.push({ role: 'user', content: userContent }); + const { prompt: fullPrompt } = await ctx.formatChat(JSON.stringify(messages)); + const delta = fullPrompt.slice(lastText.length); + const deltaToks = await ctx.tokenize(delta); + branch.prefill(deltaToks); + + const gen = []; + for (let i = 0; i < GEN_TOKENS; i++) { + const { token, isStop } = branch.produce(); + if (isStop) break; + branch.commit(token); + gen.push(token); + } + const assistantText = await ctx.detokenize(gen); + messages.push({ role: 'assistant', content: assistantText }); + return { text: assistantText, lastText: fullPrompt + assistantText }; + } + + // Turn 1: Plant a specific, recallable fact + const messages = [{ role: 'user', content: 'Remember this: my dog is named Max.' }]; + const { prompt } = await ctx.formatChat(JSON.stringify(messages)); + const promptToks = await ctx.tokenize(prompt); + await ctx.decode(promptToks, 0, 0); + + var branch = Branch.create(ctx, 0, promptToks.length, { temperature: 0 }); + branch.captureLogits(); + + // Generate turn 1 response + const gen = []; + for (let i = 0; i < GEN_TOKENS; i++) { + const { token, isStop } = branch.produce(); + if (isStop) break; + branch.commit(token); + gen.push(token); + } + const assistantText = await ctx.detokenize(gen); + messages.push({ role: 'assistant', content: assistantText }); + let lastText = prompt + assistantText; + + // Turn 2: Distractor + let turn; + turn = await warmTurn(messages, lastText, 'What is 2 + 2?'); + lastText = turn.lastText; + + // Turn 3: Another distractor + turn = await warmTurn(messages, lastText, 'Name three colors.'); + lastText = turn.lastText; + + // Turn 4: Recall — only answerable from turn 1 context + turn = await warmTurn(messages, lastText, 'What is my dog\'s name?'); + recallText = turn.text; + + branch.prune(); + } finally { + ctx.dispose(); + } + } + + // Phase 2: Score via embedding similarity (chat model fully released) + { + const embedCtx = await addon.createContext({ + modelPath: EMBED_MODEL_PATH, + nCtx: 512, + nBatch: 512, + nThreads: 4, + embeddings: true, + poolingType: 1 // MEAN + }); + + try { + async function embed(text) { + const tokens = await embedCtx.tokenize(text); + await embedCtx.kvCacheClear(); + await embedCtx.encode(tokens); + return embedCtx.getEmbeddings(true); + } + + console.log(` Recall response: "${recallText.trim().slice(0, 120)}"`); + + const embResponse = await embed(recallText); + const embCorrect = await embed('The dog is named Max.'); + const embWrong = await embed('Red, blue, and green are three colors.'); + + const simCorrect = cosine(embResponse, embCorrect); + const simWrong = cosine(embResponse, embWrong); + + assert(simCorrect > simWrong, + `Semantic recall: correct=${simCorrect.toFixed(3)} > wrong=${simWrong.toFixed(3)}`); + } finally { + embedCtx.dispose(); + } + } +} + // ═══════════════════════════════════════════════════════════════════════════ // BRANCH STEER TESTS - Dynamic per-sample logit manipulation // ═══════════════════════════════════════════════════════════════════════════ @@ -726,6 +980,62 @@ async function testDecodeAndCapture() { // MAIN // ═══════════════════════════════════════════════════════════════════════════ +async function testChatInOut(ctx) { + console.log('\n── chat_in / chat_out ──'); + + // formatChat with empty options object (new signature) + const messages = [{ role: 'user', content: 'Hello' }]; + const result = await ctx.formatChat(JSON.stringify(messages), {}); + assert(result.prompt.includes('Hello'), 'formatChat with options: prompt contains Hello'); + assert(typeof result.format === 'number', 'formatChat returns format as number'); + assert(typeof result.grammar === 'string', 'formatChat returns grammar as string'); + assert(typeof result.grammarLazy === 'boolean', 'formatChat returns grammarLazy'); + assert(typeof result.thinkingForcedOpen === 'boolean', 'formatChat returns thinkingForcedOpen'); + assert(typeof result.reasoningFormat === 'number', 'formatChat returns reasoningFormat'); + assert(Array.isArray(result.grammarTriggers), 'formatChat returns grammarTriggers array'); + assert(Array.isArray(result.preservedTokens), 'formatChat returns preservedTokens array'); + ok('formatChat with options returns extended result'); + + // Backward compat: string second argument still works + const backCompat = await ctx.formatChat(JSON.stringify(messages)); + assert(backCompat.prompt.includes('Hello'), 'formatChat backward compat works'); + ok('formatChat backward compat (no second arg)'); + + // formatChat with tools + const tools = [{ + type: 'function', + function: { + name: 'get_weather', + description: 'Get weather', + parameters: { type: 'object', properties: { location: { type: 'string' } } } + } + }]; + const toolResult = await ctx.formatChat(JSON.stringify(messages), { + tools: JSON.stringify(tools), + toolChoice: 'auto' + }); + assert(typeof toolResult.format === 'number', 'formatChat with tools returns format'); + assert(typeof toolResult.grammar === 'string', 'formatChat with tools returns grammar'); + ok('formatChat with tools'); + + // parseChatOutput + const parsed = ctx.parseChatOutput('Hello world', toolResult.format); + assert(typeof parsed.content === 'string', 'parseChatOutput returns content'); + assert(parsed.content.includes('Hello'), 'parseChatOutput content contains Hello'); + assert(typeof parsed.reasoningContent === 'string', 'parseChatOutput returns reasoningContent'); + assert(Array.isArray(parsed.toolCalls), 'parseChatOutput returns toolCalls array'); + ok('parseChatOutput basic'); + + // parseChatOutput with options + const parsedWithOpts = ctx.parseChatOutput('Some output', toolResult.format, { + reasoningFormat: toolResult.reasoningFormat, + isPartial: false, + thinkingForcedOpen: false + }); + assert(typeof parsedWithOpts.content === 'string', 'parseChatOutput with options'); + ok('parseChatOutput with options'); +} + async function main() { let mainCtx = null; @@ -743,11 +1053,14 @@ async function main() { await testKVCache(mainCtx); await testMetrics(mainCtx); await testTokenizer(mainCtx); + await testChatInOut(mainCtx); // Tests that create their own contexts await testMultiSequence(); await testGrammar(); await testBranchPrefill(); + await testWarmColdParity(); + await testWarmSemanticRecall(); await testBranchSteer(); await testNBatchAblation(); await testDeterminism(); diff --git a/test/matrix.json b/test/matrix.json index 96e7b96..a22f153 100644 --- a/test/matrix.json +++ b/test/matrix.json @@ -10,10 +10,10 @@ "default": true }, { - "name": "TinyLlama", - "file": "tinyllama-1.1b-chat-v1.0.Q4_K_M.gguf", - "url": "https://huggingface.co/TheBloke/TinyLlama-1.1B-Chat-v1.0-GGUF/resolve/main/tinyllama-1.1b-chat-v1.0.Q4_K_M.gguf", - "template": "zephyr" + "name": "Ministral", + "file": "Ministral-3-3B-Instruct-2512-Q4_K_M.gguf", + "url": "https://huggingface.co/mistralai/Ministral-3-3B-Instruct-2512-GGUF/resolve/main/Ministral-3-3B-Instruct-2512-Q4_K_M.gguf", + "template": "mistral" }, { "name": "Llama-3.2", From 7c1ba43f3564e2abd9fdcfd33ee71469c363cc29 Mon Sep 17 00:00:00 2001 From: LLoyal Research Date: Wed, 11 Feb 2026 09:32:01 +1100 Subject: [PATCH 02/13] feat(chat): new chat api --- examples/chat/chat.mjs | 79 +++++++++++++---------------- lib/index.d.ts | 42 ++++++++++++++++ liblloyal | 2 +- src/SessionContext.cpp | 29 +++++++++++ src/SessionContext.hpp | 11 +++++ test/integration.js | 110 +++++++++++++++++++++++++++++++---------- 6 files changed, 203 insertions(+), 70 deletions(-) diff --git a/examples/chat/chat.mjs b/examples/chat/chat.mjs index 3256158..8a22f8b 100644 --- a/examples/chat/chat.mjs +++ b/examples/chat/chat.mjs @@ -7,15 +7,15 @@ * node chat.mjs # uses default model path * * This example demonstrates: - * - Sync generator for token production (sample, check stop, convert to text) - * - Async commit via decode() to update KV cache - * - Clear separation: sync produce, async commit + * - Branch API for token generation (produce/commit two-phase) + * - Warm multi-turn continuation via getWarmTurnTokens() + branch.prefill() + * - Cold/warm routing: formatChat() on first turn, probe-based prefill on subsequent turns */ import * as readline from "node:readline"; import * as path from "node:path"; import { fileURLToPath } from "node:url"; -import { createContext } from "../../lib/index.js"; +import { createContext, Branch } from "../../lib/index.js"; const __dirname = path.dirname(fileURLToPath(import.meta.url)); const DEFAULT_MODEL = path.resolve( @@ -23,19 +23,6 @@ const DEFAULT_MODEL = path.resolve( "../../models/SmolLM2-1.7B-Instruct-Q4_K_M.gguf", ); -/** - * Sync generator - produces tokens until stop token. - * All operations are synchronous: sample, isStopToken, tokenToText. - */ -function* produceTokens(ctx, params) { - while (true) { - const tokenId = ctx.sample(params); - if (ctx.isStopToken(tokenId)) return; - const text = ctx.tokenToText(tokenId); - yield { text, tokenId }; - } -} - async function main() { const modelPath = process.argv[2] || DEFAULT_MODEL; @@ -52,8 +39,8 @@ async function main() { console.log("Commands: /clear to reset, /quit to exit\n"); const messages = []; - let position = 0; - let lastPrompt = ""; + let branch = null; + const warm = ctx.getWarmTurnTokens(); const rl = readline.createInterface({ input: process.stdin, @@ -67,16 +54,17 @@ async function main() { if (trimmed === "/quit" || trimmed === "/exit") { console.log("Goodbye!"); + if (branch) branch.prune(); ctx.dispose(); rl.close(); return; } if (trimmed === "/clear") { + if (branch) branch.prune(); + branch = null; await ctx.kvCacheClear(); messages.length = 0; - position = 0; - lastPrompt = ""; console.clear(); console.log("Conversation cleared.\n"); askUser(); @@ -90,40 +78,43 @@ async function main() { messages.push({ role: "user", content: trimmed }); - // Format with chat template - const { prompt: fullPrompt } = await ctx.formatChat( - JSON.stringify(messages), - ); - - // Prompt diffing - only tokenize new content - const newContent = fullPrompt.startsWith(lastPrompt) - ? fullPrompt.slice(lastPrompt.length) - : fullPrompt; - - const tokens = await ctx.tokenize(newContent); - await ctx.decode(tokens, position); - position += tokens.length; + if (!branch) { + // === COLD (position === 0): full format → tokenize with BOS → decode === + const { prompt } = await ctx.formatChat(JSON.stringify(messages)); + const tokens = await ctx.tokenize(prompt); + await ctx.decode(tokens, 0, 0); + branch = Branch.create(ctx, 0, tokens.length, { + temperature: 0.7, + topK: 40, + topP: 0.9, + }); + branch.captureLogits(); + } else { + // === WARM (position > 0): probe-based prefill — no formatChat(), no BOS === + const contentToks = await ctx.tokenize(trimmed, false); + branch.prefill([ + ...warm.turnSeparator, + ...warm.userPrefix, + ...contentToks, + ...warm.userToAssistant, + ]); + } - // Generate: sync produce, async commit + // Generate: produce inspects, commit advances process.stdout.write("< "); let response = ""; - for (const { text, tokenId } of produceTokens(ctx, { - temperature: 0.7, - topK: 40, - topP: 0.9, - })) { + while (true) { + const { token, text, isStop } = branch.produce(); + if (isStop) break; process.stdout.write(text); response += text; - - await ctx.decode([tokenId], position); // async commit to KV - position += 1; + branch.commit(token); } console.log("\n"); messages.push({ role: "assistant", content: response.trim() }); - lastPrompt = fullPrompt + response; askUser(); } diff --git a/lib/index.d.ts b/lib/index.d.ts index a762547..7dfffdf 100644 --- a/lib/index.d.ts +++ b/lib/index.d.ts @@ -388,6 +388,23 @@ export interface ParseChatOutputResult { toolCalls: ParsedToolCall[]; } +/** + * Pre-tokenized wrapper tokens for warm multi-turn continuation + * + * Contains the three token sequences needed to inject a new user turn + * into an existing conversation without re-formatting the full history. + * + * @see {@link SessionContext.getWarmTurnTokens} + */ +export interface WarmTurnTokens { + /** Tokens that close the previous assistant turn (e.g., im_end + newline for ChatML) */ + turnSeparator: number[]; + /** Tokens that open a new user turn (e.g., im_start + "user" + newline for ChatML) */ + userPrefix: number[]; + /** Tokens that close the user turn and open assistant (e.g., im_end + newline + im_start + "assistant" + newline) */ + userToAssistant: number[]; +} + /** * Penalty parameters for repetition control */ @@ -732,6 +749,31 @@ export interface SessionContext { */ getTurnSeparator(): number[]; + /** + * Get warm turn wrapper tokens for template-aware warm continuation + * + * Returns pre-tokenized role wrappers extracted from the model's chat + * template. Use these to construct warm prefill tokens without + * re-formatting the full conversation (no BOS bug, O(1) per turn). + * + * Warm path: turnSeparator + userPrefix + tokenize(content, false) + userToAssistant + * + * @returns Cached wrapper tokens (computed once per model) + * + * @example + * ```typescript + * const warm = ctx.getWarmTurnTokens(); + * const contentToks = await ctx.tokenize(userContent, false); + * branch.prefill([ + * ...warm.turnSeparator, // closes previous assistant turn + * ...warm.userPrefix, // opens new user turn + * ...contentToks, // raw user content (no BOS) + * ...warm.userToAssistant, // closes user turn + opens assistant + * ]); + * ``` + */ + getWarmTurnTokens(): WarmTurnTokens; + // ===== PROMPT PREPARATION ===== /** diff --git a/liblloyal b/liblloyal index 158bb8e..6037b9b 160000 --- a/liblloyal +++ b/liblloyal @@ -1 +1 @@ -Subproject commit 158bb8ed600121fe2b8f0ec1fd3646729258da0c +Subproject commit 6037b9bc7a3ea67460a073df3373f6e121ce9d68 diff --git a/src/SessionContext.cpp b/src/SessionContext.cpp index 65bb323..6cc2a5f 100644 --- a/src/SessionContext.cpp +++ b/src/SessionContext.cpp @@ -598,6 +598,7 @@ Napi::Object SessionContext::Init(Napi::Env env, Napi::Object exports) { InstanceMethod("isStopToken", &SessionContext::isStopToken), InstanceMethod("getEogToken", &SessionContext::getEogToken), InstanceMethod("getTurnSeparator", &SessionContext::getTurnSeparator), + InstanceMethod("getWarmTurnTokens", &SessionContext::getWarmTurnTokens), // ===== PROMPT PREPARATION ===== InstanceMethod("tokenize", &SessionContext::tokenize), @@ -1155,6 +1156,34 @@ Napi::Value SessionContext::getTurnSeparator(const Napi::CallbackInfo& info) { return result; } +Napi::Value SessionContext::getWarmTurnTokens(const Napi::CallbackInfo& info) { + Napi::Env env = info.Env(); + ensureNotDisposed(); + + // Compute once, cache thereafter + if (!_warmTurnTokensCached) { + _warmTurnTokensCache = lloyal::chat_in::get_warm_turn_tokens(_model.get()); + _warmTurnTokensCached = true; + } + + // Return { turnSeparator: number[], userPrefix: number[], userToAssistant: number[] } + Napi::Object result = Napi::Object::New(env); + + auto toArray = [&](const std::vector& tokens) { + Napi::Array arr = Napi::Array::New(env, tokens.size()); + for (size_t i = 0; i < tokens.size(); i++) { + arr[i] = Napi::Number::New(env, static_cast(tokens[i])); + } + return arr; + }; + + result.Set("turnSeparator", toArray(_warmTurnTokensCache.turn_separator)); + result.Set("userPrefix", toArray(_warmTurnTokensCache.user_prefix)); + result.Set("userToAssistant", toArray(_warmTurnTokensCache.user_to_assistant)); + + return result; +} + Napi::Value SessionContext::formatChat(const Napi::CallbackInfo& info) { Napi::Env env = info.Env(); ensureNotDisposed(); diff --git a/src/SessionContext.hpp b/src/SessionContext.hpp index b42ca1d..c844e51 100644 --- a/src/SessionContext.hpp +++ b/src/SessionContext.hpp @@ -4,6 +4,7 @@ #include #include #include +#include #include #include #include @@ -136,6 +137,12 @@ class SessionContext : public Napi::ObjectWrap { */ Napi::Value getTurnSeparator(const Napi::CallbackInfo& info); + /** + * Get warm turn wrapper tokens for template-aware warm continuation + * Returns { turnSeparator: number[], userPrefix: number[], userToAssistant: number[] } + */ + Napi::Value getWarmTurnTokens(const Napi::CallbackInfo& info); + /** * Format messages using model's chat template * Args: messagesJson (string), templateOverride (optional string) @@ -413,6 +420,10 @@ class SessionContext : public Napi::ObjectWrap { std::vector _turnSeparatorCache; bool _turnSeparatorCached = false; + // ===== WARM TURN TOKENS CACHE ===== + lloyal::chat_in::WarmTurnTokens _warmTurnTokensCache; + bool _warmTurnTokensCached = false; + // ===== DECODE MUTEX ===== std::mutex _decodeMutex; diff --git a/test/integration.js b/test/integration.js index b02a222..62d1c19 100644 --- a/test/integration.js +++ b/test/integration.js @@ -345,22 +345,23 @@ async function testBranchPrefill() { } assert(gen1.length > 0, `Turn 1: generated ${gen1.length} tokens`); - let lastText = prompt + await ctx.detokenize(gen1); - let lastGen = gen1; // Track last generation for multi-turn + // Warm turn tokens for probe-based prefill (no string diff, no BOS bug) + const warm = ctx.getWarmTurnTokens(); - // Turn 2-3: prefill + generate + // Turn 2-3: prefill using warm probe + generate for (let t = 1; t < turns.length; t++) { - messages.push({ role: 'assistant', content: await ctx.detokenize(lastGen) }); - messages.push({ role: 'user', content: turns[t] }); - - const { prompt: fullPrompt } = await ctx.formatChat(JSON.stringify(messages)); - const delta = fullPrompt.slice(lastText.length); - const deltaToks = await ctx.tokenize(delta); + const contentToks = await ctx.tokenize(turns[t], false); + const prefillToks = [ + ...warm.turnSeparator, + ...warm.userPrefix, + ...contentToks, + ...warm.userToAssistant, + ]; const posBefore = branch.position; - branch.prefill(deltaToks); - assert(branch.position === posBefore + deltaToks.length, - `Turn ${t + 1}: prefill ${deltaToks.length} tokens → pos=${branch.position}`); + branch.prefill(prefillToks); + assert(branch.position === posBefore + prefillToks.length, + `Turn ${t + 1}: prefill ${prefillToks.length} tokens → pos=${branch.position}`); const gen = []; for (let i = 0; i < GEN_TOKENS; i++) { @@ -370,9 +371,6 @@ async function testBranchPrefill() { gen.push(token); } assert(gen.length > 0, `Turn ${t + 1}: generated ${gen.length} tokens`); - - lastText = fullPrompt + await ctx.detokenize(gen); - lastGen = gen; // Update for next turn } branch.prune(); @@ -424,18 +422,17 @@ async function testWarmColdParity() { } assistantContent = await warmCtx.detokenize(gen1); - const lastText = prompt1 + assistantContent; - // Turn 2: prefill delta, generate - const msgs2 = [ - { role: 'user', content: userMessages[0] }, - { role: 'assistant', content: assistantContent }, - { role: 'user', content: userMessages[1] } + // Turn 2: prefill using warm probe (no string diff, no BOS bug) + const warm = warmCtx.getWarmTurnTokens(); + const contentToks = await warmCtx.tokenize(userMessages[1], false); + const prefillToks = [ + ...warm.turnSeparator, + ...warm.userPrefix, + ...contentToks, + ...warm.userToAssistant, ]; - const { prompt: fullPrompt2 } = await warmCtx.formatChat(JSON.stringify(msgs2)); - const delta = fullPrompt2.slice(lastText.length); - const deltaToks = await warmCtx.tokenize(delta); - branch.prefill(deltaToks); + branch.prefill(prefillToks); warmGen2 = []; for (let i = 0; i < GEN_TOKENS; i++) { @@ -503,6 +500,68 @@ async function testWarmColdParity() { } } +// ═══════════════════════════════════════════════════════════════════════════ +// WARM TURN TOKENS PROBE - Verifies template-extracted role wrappers +// ═══════════════════════════════════════════════════════════════════════════ + +async function testWarmTurnTokens() { + console.log('\n--- Warm Turn Tokens Probe ---'); + + const ctx = await addon.createContext({ + modelPath: MODEL_PATH, + nCtx: 512, + nThreads: 4 + }); + + try { + const warm = ctx.getWarmTurnTokens(); + + assert(Array.isArray(warm.turnSeparator) && warm.turnSeparator.length > 0, + `turnSeparator: ${warm.turnSeparator.length} tokens`); + assert(Array.isArray(warm.userPrefix) && warm.userPrefix.length > 0, + `userPrefix: ${warm.userPrefix.length} tokens`); + assert(Array.isArray(warm.userToAssistant) && warm.userToAssistant.length > 0, + `userToAssistant: ${warm.userToAssistant.length} tokens`); + + // All token IDs should be valid numbers + for (const tok of warm.turnSeparator) { + assert(typeof tok === 'number' && Number.isInteger(tok), `turnSeparator token ${tok} is integer`); + } + for (const tok of warm.userPrefix) { + assert(typeof tok === 'number' && Number.isInteger(tok), `userPrefix token ${tok} is integer`); + } + for (const tok of warm.userToAssistant) { + assert(typeof tok === 'number' && Number.isInteger(tok), `userToAssistant token ${tok} is integer`); + } + + // turnSeparator should contain at least one EOG token + const hasEog = warm.turnSeparator.some(t => ctx.isStopToken(t)); + assert(hasEog, 'turnSeparator contains at least one EOG token'); + + // userPrefix should NOT contain EOG tokens + const prefixHasEog = warm.userPrefix.some(t => ctx.isStopToken(t)); + assert(!prefixHasEog, 'userPrefix contains no EOG tokens'); + + // Cached: second call returns same result + const warm2 = ctx.getWarmTurnTokens(); + assert( + warm.turnSeparator.join(',') === warm2.turnSeparator.join(',') && + warm.userPrefix.join(',') === warm2.userPrefix.join(',') && + warm.userToAssistant.join(',') === warm2.userToAssistant.join(','), + 'getWarmTurnTokens() is cached (idempotent)'); + + // Log for diagnostic visibility + const sepText = warm.turnSeparator.map(t => ctx.tokenToText(t)).join(''); + const prefText = warm.userPrefix.map(t => ctx.tokenToText(t)).join(''); + const u2aText = warm.userToAssistant.map(t => ctx.tokenToText(t)).join(''); + console.log(` separator: ${JSON.stringify(sepText)}`); + console.log(` userPrefix: ${JSON.stringify(prefText)}`); + console.log(` userToAssistant: ${JSON.stringify(u2aText)}`); + } finally { + ctx.dispose(); + } +} + // ═══════════════════════════════════════════════════════════════════════════ // WARM CONTINUATION SEMANTIC RECALL - Proves context survives delta-only prefill // ═══════════════════════════════════════════════════════════════════════════ @@ -1059,6 +1118,7 @@ async function main() { await testMultiSequence(); await testGrammar(); await testBranchPrefill(); + await testWarmTurnTokens(); await testWarmColdParity(); await testWarmSemanticRecall(); await testBranchSteer(); From 758d6c41d40d6feef5780b4b2deadabf422fb936 Mon Sep 17 00:00:00 2001 From: LLoyal Research Date: Wed, 11 Feb 2026 12:35:47 +1100 Subject: [PATCH 03/13] feat(chat): new chat api - rely on llama.cpp's BOS stripping --- examples/chat/chat.mjs | 22 +++--- lib/index.d.ts | 42 ----------- liblloyal | 2 +- src/SessionContext.cpp | 29 -------- src/SessionContext.hpp | 10 --- test/integration.js | 165 +++++++++++++++-------------------------- 6 files changed, 72 insertions(+), 198 deletions(-) diff --git a/examples/chat/chat.mjs b/examples/chat/chat.mjs index 8a22f8b..da358a0 100644 --- a/examples/chat/chat.mjs +++ b/examples/chat/chat.mjs @@ -8,8 +8,8 @@ * * This example demonstrates: * - Branch API for token generation (produce/commit two-phase) - * - Warm multi-turn continuation via getWarmTurnTokens() + branch.prefill() - * - Cold/warm routing: formatChat() on first turn, probe-based prefill on subsequent turns + * - Warm multi-turn continuation via string-diff formatChat() + getTurnSeparator() + * - Cold/warm routing: full format on first turn, string-diff on subsequent turns */ import * as readline from "node:readline"; @@ -40,7 +40,7 @@ async function main() { const messages = []; let branch = null; - const warm = ctx.getWarmTurnTokens(); + const sep = ctx.getTurnSeparator(); const rl = readline.createInterface({ input: process.stdin, @@ -90,14 +90,14 @@ async function main() { }); branch.captureLogits(); } else { - // === WARM (position > 0): probe-based prefill — no formatChat(), no BOS === - const contentToks = await ctx.tokenize(trimmed, false); - branch.prefill([ - ...warm.turnSeparator, - ...warm.userPrefix, - ...contentToks, - ...warm.userToAssistant, - ]); + // === WARM (position > 0): string-diff for delta tokens === + const { prompt: full } = await ctx.formatChat(JSON.stringify(messages)); + const { prompt: prefix } = await ctx.formatChat( + JSON.stringify(messages.slice(0, -1)), + { addGenerationPrompt: false }, + ); + const delta = await ctx.tokenize(full.substring(prefix.length), false); + branch.prefill([...sep, ...delta]); } // Generate: produce inspects, commit advances diff --git a/lib/index.d.ts b/lib/index.d.ts index 7dfffdf..a762547 100644 --- a/lib/index.d.ts +++ b/lib/index.d.ts @@ -388,23 +388,6 @@ export interface ParseChatOutputResult { toolCalls: ParsedToolCall[]; } -/** - * Pre-tokenized wrapper tokens for warm multi-turn continuation - * - * Contains the three token sequences needed to inject a new user turn - * into an existing conversation without re-formatting the full history. - * - * @see {@link SessionContext.getWarmTurnTokens} - */ -export interface WarmTurnTokens { - /** Tokens that close the previous assistant turn (e.g., im_end + newline for ChatML) */ - turnSeparator: number[]; - /** Tokens that open a new user turn (e.g., im_start + "user" + newline for ChatML) */ - userPrefix: number[]; - /** Tokens that close the user turn and open assistant (e.g., im_end + newline + im_start + "assistant" + newline) */ - userToAssistant: number[]; -} - /** * Penalty parameters for repetition control */ @@ -749,31 +732,6 @@ export interface SessionContext { */ getTurnSeparator(): number[]; - /** - * Get warm turn wrapper tokens for template-aware warm continuation - * - * Returns pre-tokenized role wrappers extracted from the model's chat - * template. Use these to construct warm prefill tokens without - * re-formatting the full conversation (no BOS bug, O(1) per turn). - * - * Warm path: turnSeparator + userPrefix + tokenize(content, false) + userToAssistant - * - * @returns Cached wrapper tokens (computed once per model) - * - * @example - * ```typescript - * const warm = ctx.getWarmTurnTokens(); - * const contentToks = await ctx.tokenize(userContent, false); - * branch.prefill([ - * ...warm.turnSeparator, // closes previous assistant turn - * ...warm.userPrefix, // opens new user turn - * ...contentToks, // raw user content (no BOS) - * ...warm.userToAssistant, // closes user turn + opens assistant - * ]); - * ``` - */ - getWarmTurnTokens(): WarmTurnTokens; - // ===== PROMPT PREPARATION ===== /** diff --git a/liblloyal b/liblloyal index 6037b9b..fdcce9e 160000 --- a/liblloyal +++ b/liblloyal @@ -1 +1 @@ -Subproject commit 6037b9bc7a3ea67460a073df3373f6e121ce9d68 +Subproject commit fdcce9ef25ac5bf56ca8ffdfdc477ee2752d00e7 diff --git a/src/SessionContext.cpp b/src/SessionContext.cpp index 6cc2a5f..65bb323 100644 --- a/src/SessionContext.cpp +++ b/src/SessionContext.cpp @@ -598,7 +598,6 @@ Napi::Object SessionContext::Init(Napi::Env env, Napi::Object exports) { InstanceMethod("isStopToken", &SessionContext::isStopToken), InstanceMethod("getEogToken", &SessionContext::getEogToken), InstanceMethod("getTurnSeparator", &SessionContext::getTurnSeparator), - InstanceMethod("getWarmTurnTokens", &SessionContext::getWarmTurnTokens), // ===== PROMPT PREPARATION ===== InstanceMethod("tokenize", &SessionContext::tokenize), @@ -1156,34 +1155,6 @@ Napi::Value SessionContext::getTurnSeparator(const Napi::CallbackInfo& info) { return result; } -Napi::Value SessionContext::getWarmTurnTokens(const Napi::CallbackInfo& info) { - Napi::Env env = info.Env(); - ensureNotDisposed(); - - // Compute once, cache thereafter - if (!_warmTurnTokensCached) { - _warmTurnTokensCache = lloyal::chat_in::get_warm_turn_tokens(_model.get()); - _warmTurnTokensCached = true; - } - - // Return { turnSeparator: number[], userPrefix: number[], userToAssistant: number[] } - Napi::Object result = Napi::Object::New(env); - - auto toArray = [&](const std::vector& tokens) { - Napi::Array arr = Napi::Array::New(env, tokens.size()); - for (size_t i = 0; i < tokens.size(); i++) { - arr[i] = Napi::Number::New(env, static_cast(tokens[i])); - } - return arr; - }; - - result.Set("turnSeparator", toArray(_warmTurnTokensCache.turn_separator)); - result.Set("userPrefix", toArray(_warmTurnTokensCache.user_prefix)); - result.Set("userToAssistant", toArray(_warmTurnTokensCache.user_to_assistant)); - - return result; -} - Napi::Value SessionContext::formatChat(const Napi::CallbackInfo& info) { Napi::Env env = info.Env(); ensureNotDisposed(); diff --git a/src/SessionContext.hpp b/src/SessionContext.hpp index c844e51..466db9f 100644 --- a/src/SessionContext.hpp +++ b/src/SessionContext.hpp @@ -137,12 +137,6 @@ class SessionContext : public Napi::ObjectWrap { */ Napi::Value getTurnSeparator(const Napi::CallbackInfo& info); - /** - * Get warm turn wrapper tokens for template-aware warm continuation - * Returns { turnSeparator: number[], userPrefix: number[], userToAssistant: number[] } - */ - Napi::Value getWarmTurnTokens(const Napi::CallbackInfo& info); - /** * Format messages using model's chat template * Args: messagesJson (string), templateOverride (optional string) @@ -420,10 +414,6 @@ class SessionContext : public Napi::ObjectWrap { std::vector _turnSeparatorCache; bool _turnSeparatorCached = false; - // ===== WARM TURN TOKENS CACHE ===== - lloyal::chat_in::WarmTurnTokens _warmTurnTokensCache; - bool _warmTurnTokensCached = false; - // ===== DECODE MUTEX ===== std::mutex _decodeMutex; diff --git a/test/integration.js b/test/integration.js index 62d1c19..675f00b 100644 --- a/test/integration.js +++ b/test/integration.js @@ -345,18 +345,23 @@ async function testBranchPrefill() { } assert(gen1.length > 0, `Turn 1: generated ${gen1.length} tokens`); - // Warm turn tokens for probe-based prefill (no string diff, no BOS bug) - const warm = ctx.getWarmTurnTokens(); + // Track assistant response for string-diff warm continuation + const assistantText1 = await ctx.detokenize(gen1); + messages.push({ role: 'assistant', content: assistantText1 }); - // Turn 2-3: prefill using warm probe + generate + // Warm continuation: string-diff formatChat() + turn separator + const sep = ctx.getTurnSeparator(); + + // Turn 2-3: prefill using string-diff warm pattern + generate for (let t = 1; t < turns.length; t++) { - const contentToks = await ctx.tokenize(turns[t], false); - const prefillToks = [ - ...warm.turnSeparator, - ...warm.userPrefix, - ...contentToks, - ...warm.userToAssistant, - ]; + messages.push({ role: 'user', content: turns[t] }); + const { prompt: full } = await ctx.formatChat(JSON.stringify(messages)); + const { prompt: prefix } = await ctx.formatChat( + JSON.stringify(messages.slice(0, -1)), + { addGenerationPrompt: false } + ); + const delta = await ctx.tokenize(full.substring(prefix.length), false); + const prefillToks = [...sep, ...delta]; const posBefore = branch.position; branch.prefill(prefillToks); @@ -371,6 +376,10 @@ async function testBranchPrefill() { gen.push(token); } assert(gen.length > 0, `Turn ${t + 1}: generated ${gen.length} tokens`); + + // Track assistant response + const assistantText = await ctx.detokenize(gen); + messages.push({ role: 'assistant', content: assistantText }); } branch.prune(); @@ -423,16 +432,20 @@ async function testWarmColdParity() { assistantContent = await warmCtx.detokenize(gen1); - // Turn 2: prefill using warm probe (no string diff, no BOS bug) - const warm = warmCtx.getWarmTurnTokens(); - const contentToks = await warmCtx.tokenize(userMessages[1], false); - const prefillToks = [ - ...warm.turnSeparator, - ...warm.userPrefix, - ...contentToks, - ...warm.userToAssistant, + // Turn 2: string-diff warm continuation + const sep = warmCtx.getTurnSeparator(); + const allMessages = [ + { role: 'user', content: userMessages[0] }, + { role: 'assistant', content: assistantContent }, + { role: 'user', content: userMessages[1] } ]; - branch.prefill(prefillToks); + const { prompt: full } = await warmCtx.formatChat(JSON.stringify(allMessages)); + const { prompt: prefix } = await warmCtx.formatChat( + JSON.stringify(allMessages.slice(0, -1)), + { addGenerationPrompt: false } + ); + const deltaToks = await warmCtx.tokenize(full.substring(prefix.length), false); + branch.prefill([...sep, ...deltaToks]); warmGen2 = []; for (let i = 0; i < GEN_TOKENS; i++) { @@ -486,11 +499,9 @@ async function testWarmColdParity() { // === COMPARE === const warmStr = warmGen2.join(','); const coldStr = coldGen2.join(','); - assert(warmStr === coldStr, - `Warm==Cold parity: ${warmGen2.length} tokens match`); + // Log divergence diagnostics BEFORE assert (assert throws on failure) if (warmStr !== coldStr) { - // Diagnostic: show first divergence point for (let i = 0; i < Math.max(warmGen2.length, coldGen2.length); i++) { if (warmGen2[i] !== coldGen2[i]) { console.log(` First divergence at position ${i}: warm=${warmGen2[i]} cold=${coldGen2[i]}`); @@ -498,68 +509,11 @@ async function testWarmColdParity() { } } } -} - -// ═══════════════════════════════════════════════════════════════════════════ -// WARM TURN TOKENS PROBE - Verifies template-extracted role wrappers -// ═══════════════════════════════════════════════════════════════════════════ -async function testWarmTurnTokens() { - console.log('\n--- Warm Turn Tokens Probe ---'); - - const ctx = await addon.createContext({ - modelPath: MODEL_PATH, - nCtx: 512, - nThreads: 4 - }); - - try { - const warm = ctx.getWarmTurnTokens(); - - assert(Array.isArray(warm.turnSeparator) && warm.turnSeparator.length > 0, - `turnSeparator: ${warm.turnSeparator.length} tokens`); - assert(Array.isArray(warm.userPrefix) && warm.userPrefix.length > 0, - `userPrefix: ${warm.userPrefix.length} tokens`); - assert(Array.isArray(warm.userToAssistant) && warm.userToAssistant.length > 0, - `userToAssistant: ${warm.userToAssistant.length} tokens`); - - // All token IDs should be valid numbers - for (const tok of warm.turnSeparator) { - assert(typeof tok === 'number' && Number.isInteger(tok), `turnSeparator token ${tok} is integer`); - } - for (const tok of warm.userPrefix) { - assert(typeof tok === 'number' && Number.isInteger(tok), `userPrefix token ${tok} is integer`); - } - for (const tok of warm.userToAssistant) { - assert(typeof tok === 'number' && Number.isInteger(tok), `userToAssistant token ${tok} is integer`); - } - - // turnSeparator should contain at least one EOG token - const hasEog = warm.turnSeparator.some(t => ctx.isStopToken(t)); - assert(hasEog, 'turnSeparator contains at least one EOG token'); - - // userPrefix should NOT contain EOG tokens - const prefixHasEog = warm.userPrefix.some(t => ctx.isStopToken(t)); - assert(!prefixHasEog, 'userPrefix contains no EOG tokens'); - - // Cached: second call returns same result - const warm2 = ctx.getWarmTurnTokens(); - assert( - warm.turnSeparator.join(',') === warm2.turnSeparator.join(',') && - warm.userPrefix.join(',') === warm2.userPrefix.join(',') && - warm.userToAssistant.join(',') === warm2.userToAssistant.join(','), - 'getWarmTurnTokens() is cached (idempotent)'); - - // Log for diagnostic visibility - const sepText = warm.turnSeparator.map(t => ctx.tokenToText(t)).join(''); - const prefText = warm.userPrefix.map(t => ctx.tokenToText(t)).join(''); - const u2aText = warm.userToAssistant.map(t => ctx.tokenToText(t)).join(''); - console.log(` separator: ${JSON.stringify(sepText)}`); - console.log(` userPrefix: ${JSON.stringify(prefText)}`); - console.log(` userToAssistant: ${JSON.stringify(u2aText)}`); - } finally { - ctx.dispose(); - } + assert(warmStr === coldStr, + warmStr === coldStr + ? `Warm==Cold parity: ${warmGen2.length} tokens match` + : `Warm==Cold parity FAILED: warm=[${warmStr}] vs cold=[${coldStr}]`); } // ═══════════════════════════════════════════════════════════════════════════ @@ -598,13 +552,20 @@ async function testWarmSemanticRecall() { }); try { - // Helper: warm-continue one turn (prefill delta, generate) - async function warmTurn(messages, lastText, userContent) { + const sep = ctx.getTurnSeparator(); + let branch; + const messages = []; + + // Helper: string-diff warm continuation + async function warmTurn(userContent) { messages.push({ role: 'user', content: userContent }); - const { prompt: fullPrompt } = await ctx.formatChat(JSON.stringify(messages)); - const delta = fullPrompt.slice(lastText.length); - const deltaToks = await ctx.tokenize(delta); - branch.prefill(deltaToks); + const { prompt: full } = await ctx.formatChat(JSON.stringify(messages)); + const { prompt: prefix } = await ctx.formatChat( + JSON.stringify(messages.slice(0, -1)), + { addGenerationPrompt: false } + ); + const delta = await ctx.tokenize(full.substring(prefix.length), false); + branch.prefill([...sep, ...delta]); const gen = []; for (let i = 0; i < GEN_TOKENS; i++) { @@ -613,18 +574,18 @@ async function testWarmSemanticRecall() { branch.commit(token); gen.push(token); } - const assistantText = await ctx.detokenize(gen); - messages.push({ role: 'assistant', content: assistantText }); - return { text: assistantText, lastText: fullPrompt + assistantText }; + const text = await ctx.detokenize(gen); + messages.push({ role: 'assistant', content: text }); + return text; } // Turn 1: Plant a specific, recallable fact - const messages = [{ role: 'user', content: 'Remember this: my dog is named Max.' }]; + messages.push({ role: 'user', content: 'Remember this: my dog is named Max.' }); const { prompt } = await ctx.formatChat(JSON.stringify(messages)); const promptToks = await ctx.tokenize(prompt); await ctx.decode(promptToks, 0, 0); - var branch = Branch.create(ctx, 0, promptToks.length, { temperature: 0 }); + branch = Branch.create(ctx, 0, promptToks.length, { temperature: 0 }); branch.captureLogits(); // Generate turn 1 response @@ -635,22 +596,17 @@ async function testWarmSemanticRecall() { branch.commit(token); gen.push(token); } - const assistantText = await ctx.detokenize(gen); - messages.push({ role: 'assistant', content: assistantText }); - let lastText = prompt + assistantText; + const turn1Response = await ctx.detokenize(gen); + messages.push({ role: 'assistant', content: turn1Response }); // Turn 2: Distractor - let turn; - turn = await warmTurn(messages, lastText, 'What is 2 + 2?'); - lastText = turn.lastText; + await warmTurn('What is 2 + 2?'); // Turn 3: Another distractor - turn = await warmTurn(messages, lastText, 'Name three colors.'); - lastText = turn.lastText; + await warmTurn('Name three colors.'); // Turn 4: Recall — only answerable from turn 1 context - turn = await warmTurn(messages, lastText, 'What is my dog\'s name?'); - recallText = turn.text; + recallText = await warmTurn('What is my dog\'s name?'); branch.prune(); } finally { @@ -1118,7 +1074,6 @@ async function main() { await testMultiSequence(); await testGrammar(); await testBranchPrefill(); - await testWarmTurnTokens(); await testWarmColdParity(); await testWarmSemanticRecall(); await testBranchSteer(); From 0d4a65cdd30dd4b7d4ea0fb58154e4b39886f589 Mon Sep 17 00:00:00 2001 From: LLoyal Research Date: Wed, 11 Feb 2026 23:55:55 +1100 Subject: [PATCH 04/13] feat(chat): new chat api - cross template multi-turn updates --- examples/chat/chat.mjs | 39 +++++++++++++++--------- lib/index.d.ts | 66 +++++++++++++++++++++++++++++++++++++++- liblloyal | 2 +- test/integration.js | 68 +++++++++++++++++++++--------------------- 4 files changed, 125 insertions(+), 50 deletions(-) diff --git a/examples/chat/chat.mjs b/examples/chat/chat.mjs index da358a0..f86b0e1 100644 --- a/examples/chat/chat.mjs +++ b/examples/chat/chat.mjs @@ -8,8 +8,9 @@ * * This example demonstrates: * - Branch API for token generation (produce/commit two-phase) - * - Warm multi-turn continuation via string-diff formatChat() + getTurnSeparator() - * - Cold/warm routing: full format on first turn, string-diff on subsequent turns + * - Warm multi-turn continuation via formatChat([newMsg]) + getTurnSeparator() + * - Cold/warm routing: full format on first turn, format-only-new on subsequent turns + * - parseChatOutput() for correct reasoning_content handling on thinking models */ import * as readline from "node:readline"; @@ -20,7 +21,7 @@ import { createContext, Branch } from "../../lib/index.js"; const __dirname = path.dirname(fileURLToPath(import.meta.url)); const DEFAULT_MODEL = path.resolve( __dirname, - "../../models/SmolLM2-1.7B-Instruct-Q4_K_M.gguf", + "../../models/Phi-3.5-mini-instruct-Q4_K_M.gguf", ); async function main() { @@ -40,6 +41,7 @@ async function main() { const messages = []; let branch = null; + let fmt = null; const sep = ctx.getTurnSeparator(); const rl = readline.createInterface({ @@ -80,8 +82,8 @@ async function main() { if (!branch) { // === COLD (position === 0): full format → tokenize with BOS → decode === - const { prompt } = await ctx.formatChat(JSON.stringify(messages)); - const tokens = await ctx.tokenize(prompt); + fmt = await ctx.formatChat(JSON.stringify(messages)); + const tokens = await ctx.tokenize(fmt.prompt); await ctx.decode(tokens, 0, 0); branch = Branch.create(ctx, 0, tokens.length, { temperature: 0.7, @@ -90,31 +92,40 @@ async function main() { }); branch.captureLogits(); } else { - // === WARM (position > 0): string-diff for delta tokens === - const { prompt: full } = await ctx.formatChat(JSON.stringify(messages)); - const { prompt: prefix } = await ctx.formatChat( - JSON.stringify(messages.slice(0, -1)), - { addGenerationPrompt: false }, + // === WARM (position > 0): format only the new message === + fmt = await ctx.formatChat( + JSON.stringify([{ role: "system", content: "" }, { role: "user", content: trimmed }]), ); - const delta = await ctx.tokenize(full.substring(prefix.length), false); + const delta = await ctx.tokenize(fmt.prompt, false); branch.prefill([...sep, ...delta]); } // Generate: produce inspects, commit advances process.stdout.write("< "); - let response = ""; + let rawOutput = ""; while (true) { const { token, text, isStop } = branch.produce(); if (isStop) break; process.stdout.write(text); - response += text; + rawOutput += text; branch.commit(token); } console.log("\n"); - messages.push({ role: "assistant", content: response.trim() }); + // Parse output: separates reasoning from content for thinking models + const parsed = ctx.parseChatOutput(rawOutput, fmt.format, { + reasoningFormat: fmt.reasoningFormat, + thinkingForcedOpen: fmt.thinkingForcedOpen, + parser: fmt.parser, + }); + + const msg = { role: "assistant", content: parsed.content }; + if (parsed.reasoningContent) { + msg.reasoning_content = parsed.reasoningContent; + } + messages.push(msg); askUser(); } diff --git a/lib/index.d.ts b/lib/index.d.ts index a762547..75c7b1e 100644 --- a/lib/index.d.ts +++ b/lib/index.d.ts @@ -382,7 +382,13 @@ export interface ParsedToolCall { export interface ParseChatOutputResult { /** Main response text */ content: string; - /** Extracted thinking/reasoning content (empty if none) */ + /** + * Extracted thinking/reasoning content (empty string if none). + * For thinking models (e.g. Qwen3), this contains the text inside + * `...` blocks. Store as `reasoning_content` in your + * messages array so formatChat() can reconstruct the template correctly + * on subsequent turns. + */ reasoningContent: string; /** Extracted tool calls (empty array if none) */ toolCalls: ParsedToolCall[]; @@ -1422,6 +1428,64 @@ export interface SessionContext { * // Handle tool calls * } * ``` + * + * @example Multi-turn warm continuation with reasoning models + * ```typescript + * // parseChatOutput separates ... blocks into reasoningContent. + * // This is REQUIRED for correct warm continuation on thinking models (e.g. Qwen3): + * // if raw output containing tags is stored as content, re-formatting + * // the conversation produces different tokens, breaking cold/warm parity. + * + * const messages: Array<{role: string; content: string; reasoning_content?: string}> = []; + * const sep = ctx.getTurnSeparator(); + * let branch: Branch | null = null; + * let fmt: FormattedChatResult; + * + * async function handleTurn(userContent: string) { + * messages.push({ role: 'user', content: userContent }); + * + * if (!branch) { + * // Cold path: format full conversation, tokenize with BOS, decode all + * fmt = await ctx.formatChat(JSON.stringify(messages)); + * const tokens = await ctx.tokenize(fmt.prompt); + * await ctx.decode(tokens, 0, 0); + * branch = Branch.create(ctx, 0, tokens.length, { temperature: 0.7 }); + * branch.captureLogits(); + * } else { + * // Warm path: string-diff for delta tokens + * const { prompt: full } = await ctx.formatChat(JSON.stringify(messages)); + * const { prompt: prefix } = await ctx.formatChat( + * JSON.stringify(messages.slice(0, -1)), + * { addGenerationPrompt: false } + * ); + * const delta = await ctx.tokenize(full.substring(prefix.length), false); + * branch.prefill([...sep, ...delta]); + * } + * + * // Generate + * let rawOutput = ''; + * while (true) { + * const { token, text, isStop } = branch.produce(); + * if (isStop) break; + * rawOutput += text; + * branch.commit(token); + * } + * + * // Parse output: separates reasoning from content + * const parsed = ctx.parseChatOutput(rawOutput, fmt.format, { + * reasoningFormat: fmt.reasoningFormat, + * thinkingForcedOpen: fmt.thinkingForcedOpen, + * parser: fmt.parser + * }); + * + * // Store parsed fields — formatChat reconstructs thinking blocks correctly + * messages.push({ + * role: 'assistant', + * content: parsed.content, + * reasoning_content: parsed.reasoningContent || undefined + * }); + * } + * ``` */ parseChatOutput( output: string, diff --git a/liblloyal b/liblloyal index fdcce9e..754ee22 160000 --- a/liblloyal +++ b/liblloyal @@ -1 +1 @@ -Subproject commit fdcce9ef25ac5bf56ca8ffdfdc477ee2752d00e7 +Subproject commit 754ee2270004eb56b108a22af310ebbb084c96f8 diff --git a/test/integration.js b/test/integration.js index 675f00b..6a995e8 100644 --- a/test/integration.js +++ b/test/integration.js @@ -345,22 +345,20 @@ async function testBranchPrefill() { } assert(gen1.length > 0, `Turn 1: generated ${gen1.length} tokens`); - // Track assistant response for string-diff warm continuation + // Track assistant response const assistantText1 = await ctx.detokenize(gen1); messages.push({ role: 'assistant', content: assistantText1 }); - // Warm continuation: string-diff formatChat() + turn separator + // Warm continuation: format only new message + turn separator const sep = ctx.getTurnSeparator(); - // Turn 2-3: prefill using string-diff warm pattern + generate + // Turn 2-3: prefill using format-only-new pattern + generate for (let t = 1; t < turns.length; t++) { messages.push({ role: 'user', content: turns[t] }); - const { prompt: full } = await ctx.formatChat(JSON.stringify(messages)); - const { prompt: prefix } = await ctx.formatChat( - JSON.stringify(messages.slice(0, -1)), - { addGenerationPrompt: false } - ); - const delta = await ctx.tokenize(full.substring(prefix.length), false); + const { prompt } = await ctx.formatChat(JSON.stringify([ + { role: 'user', content: turns[t] } + ])); + const delta = await ctx.tokenize(prompt, false); const prefillToks = [...sep, ...delta]; const posBefore = branch.position; @@ -432,19 +430,13 @@ async function testWarmColdParity() { assistantContent = await warmCtx.detokenize(gen1); - // Turn 2: string-diff warm continuation + // Turn 2: format-only-new warm continuation const sep = warmCtx.getTurnSeparator(); - const allMessages = [ - { role: 'user', content: userMessages[0] }, - { role: 'assistant', content: assistantContent }, + const { prompt: warmDelta } = await warmCtx.formatChat(JSON.stringify([ + { role: 'system', content: '' }, { role: 'user', content: userMessages[1] } - ]; - const { prompt: full } = await warmCtx.formatChat(JSON.stringify(allMessages)); - const { prompt: prefix } = await warmCtx.formatChat( - JSON.stringify(allMessages.slice(0, -1)), - { addGenerationPrompt: false } - ); - const deltaToks = await warmCtx.tokenize(full.substring(prefix.length), false); + ])); + const deltaToks = await warmCtx.tokenize(warmDelta, false); branch.prefill([...sep, ...deltaToks]); warmGen2 = []; @@ -471,16 +463,26 @@ async function testWarmColdParity() { let coldGen2; try { - const msgs = [ + // History: all but last user message (with addGenerationPrompt=false) + const history = [ { role: 'user', content: userMessages[0] }, - { role: 'assistant', content: assistantContent }, - { role: 'user', content: userMessages[1] } + { role: 'assistant', content: assistantContent } ]; - const { prompt: coldPrompt } = await coldCtx.formatChat(JSON.stringify(msgs)); - const coldToks = await coldCtx.tokenize(coldPrompt); - await coldCtx.decode(coldToks, 0, 0); + const { prompt: histPrompt } = await coldCtx.formatChat( + JSON.stringify(history), { addGenerationPrompt: false } + ); + const histToks = await coldCtx.tokenize(histPrompt); + await coldCtx.decode(histToks, 0, 0); + + // Delta: format-only-new (same as warm path) + const { prompt: coldDelta } = await coldCtx.formatChat(JSON.stringify([ + { role: 'system', content: '' }, + { role: 'user', content: userMessages[1] } + ])); + const deltaToks = await coldCtx.tokenize(coldDelta, false); + await coldCtx.decode(deltaToks, histToks.length, 0); - const branch = Branch.create(coldCtx, 0, coldToks.length, { temperature: 0 }); + const branch = Branch.create(coldCtx, 0, histToks.length + deltaToks.length, { temperature: 0 }); branch.captureLogits(); coldGen2 = []; @@ -556,15 +558,13 @@ async function testWarmSemanticRecall() { let branch; const messages = []; - // Helper: string-diff warm continuation + // Helper: format-only-new warm continuation async function warmTurn(userContent) { messages.push({ role: 'user', content: userContent }); - const { prompt: full } = await ctx.formatChat(JSON.stringify(messages)); - const { prompt: prefix } = await ctx.formatChat( - JSON.stringify(messages.slice(0, -1)), - { addGenerationPrompt: false } - ); - const delta = await ctx.tokenize(full.substring(prefix.length), false); + const { prompt } = await ctx.formatChat(JSON.stringify([ + { role: 'user', content: userContent } + ])); + const delta = await ctx.tokenize(prompt, false); branch.prefill([...sep, ...delta]); const gen = []; From 4d72d1185ce72beec35786d808cb822a939aeee4 Mon Sep 17 00:00:00 2001 From: LLoyal Research Date: Thu, 12 Feb 2026 00:31:32 +1100 Subject: [PATCH 05/13] feat(chat): new chat api - fix tests --- src/BackendManager.hpp | 48 +++--------------------------------------- src/SessionContext.cpp | 1 + test/integration.js | 2 ++ 3 files changed, 6 insertions(+), 45 deletions(-) diff --git a/src/BackendManager.hpp b/src/BackendManager.hpp index e37c818..38e79ab 100644 --- a/src/BackendManager.hpp +++ b/src/BackendManager.hpp @@ -1,8 +1,8 @@ #pragma once #include +#include "log.h" #include -#include namespace liblloyal_node { @@ -33,50 +33,9 @@ class BackendManager { * Called exactly once by ensureInitialized() */ BackendManager() { - std::cout << "[BackendManager] Initializing llama.cpp backend..." << std::endl; - - // Initialize llama backend (matches Nitro's LlamaBackendManager exactly) llama_backend_init(); - std::cout << "[BackendManager] llama_backend_init() called" << std::endl; - - // Match Nitro: Enable logging callback with dim colors for less visual noise - llama_log_set([](ggml_log_level level, const char* text, void* user_data) { - // ANSI escape codes - const char* RESET = "\033[0m"; - const char* DIM = "\033[2m"; // Dim/faint text - const char* RED = "\033[31m"; - const char* YELLOW = "\033[33m"; - - const char* color = DIM; // Default: dim grey for INFO/DEBUG - const char* level_str = ""; - - switch (level) { - case GGML_LOG_LEVEL_ERROR: - level_str = "ERROR"; - color = RED; - break; - case GGML_LOG_LEVEL_WARN: - level_str = "WARN"; - color = YELLOW; - break; - case GGML_LOG_LEVEL_INFO: - level_str = "INFO"; - break; - case GGML_LOG_LEVEL_DEBUG: - level_str = "DEBUG"; - break; - case GGML_LOG_LEVEL_NONE: - level_str = "NONE"; - break; - case GGML_LOG_LEVEL_CONT: - // Continuation - just print text dimmed, no prefix - std::cerr << DIM << text << RESET << std::flush; - return; - } - std::cerr << color << "[llama.cpp " << level_str << "] " << text << RESET << std::flush; - }, nullptr); - - std::cout << "[BackendManager] llama.cpp logging configured" << std::endl; + common_log_set_verbosity_thold(LOG_DEFAULT_LLAMA); + llama_log_set(common_log_default_callback, nullptr); } /** @@ -85,7 +44,6 @@ class BackendManager { */ ~BackendManager() { llama_backend_free(); - std::cout << "[~BackendManager] llama_backend_free() called" << std::endl; } // Delete copy/move diff --git a/src/SessionContext.cpp b/src/SessionContext.cpp index 65bb323..e32ae19 100644 --- a/src/SessionContext.cpp +++ b/src/SessionContext.cpp @@ -14,6 +14,7 @@ #include #include #include +#include namespace liblloyal_node { diff --git a/test/integration.js b/test/integration.js index 6a995e8..f95133c 100644 --- a/test/integration.js +++ b/test/integration.js @@ -356,6 +356,7 @@ async function testBranchPrefill() { for (let t = 1; t < turns.length; t++) { messages.push({ role: 'user', content: turns[t] }); const { prompt } = await ctx.formatChat(JSON.stringify([ + { role: 'system', content: '' }, { role: 'user', content: turns[t] } ])); const delta = await ctx.tokenize(prompt, false); @@ -562,6 +563,7 @@ async function testWarmSemanticRecall() { async function warmTurn(userContent) { messages.push({ role: 'user', content: userContent }); const { prompt } = await ctx.formatChat(JSON.stringify([ + { role: 'system', content: '' }, { role: 'user', content: userContent } ])); const delta = await ctx.tokenize(prompt, false); From 2db1b424a244e0372db98bc03e21e2c0a9804fb2 Mon Sep 17 00:00:00 2001 From: LLoyal Research Date: Thu, 12 Feb 2026 00:54:45 +1100 Subject: [PATCH 06/13] feat(chat): new chat api - fix tests --- test/integration.js | 153 +++++++++++++++----------------------------- 1 file changed, 52 insertions(+), 101 deletions(-) diff --git a/test/integration.js b/test/integration.js index f95133c..f3bb8c1 100644 --- a/test/integration.js +++ b/test/integration.js @@ -388,135 +388,86 @@ async function testBranchPrefill() { } // ═══════════════════════════════════════════════════════════════════════════ -// WARM vs COLD PARITY - Semantic proof that warm continuation == cold start +// WARM MULTI-TURN SEMANTIC RECALL - Proves context survives warm continuations +// Mirrors liblloyal C++ test: chat_in_integration_test.cpp // ═══════════════════════════════════════════════════════════════════════════ -async function testWarmColdParity() { - console.log('\n--- Warm vs Cold Parity ---'); +async function testWarmMultiTurnRecall() { + console.log('\n--- Warm Multi-Turn Recall ---'); - const GEN_TOKENS = 10; - const userMessages = [ - "What is the capital of France?", - " Tell me more about it." - ]; + const GEN_TOKENS = 60; - // === WARM PATH: decode turn 1, prefill turn 2 delta, generate === - const warmCtx = await addon.createContext({ + const ctx = await addon.createContext({ modelPath: MODEL_PATH, nCtx: 2048, nBatch: 512, nThreads: 4 }); - let assistantContent; - let warmGen2; - try { - // Turn 1: format, decode, generate - const msgs1 = [{ role: 'user', content: userMessages[0] }]; - const { prompt: prompt1 } = await warmCtx.formatChat(JSON.stringify(msgs1)); - const toks1 = await warmCtx.tokenize(prompt1); - await warmCtx.decode(toks1, 0, 0); + const sep = ctx.getTurnSeparator(); - const branch = Branch.create(warmCtx, 0, toks1.length, { temperature: 0 }); - branch.captureLogits(); + // Helper: warm continuation — sep + format([{system,""},{user,msg}]) + async function warmTurn(branch, userContent) { + const { prompt } = await ctx.formatChat(JSON.stringify([ + { role: 'system', content: '' }, + { role: 'user', content: userContent } + ])); + const delta = await ctx.tokenize(prompt, false); + branch.prefill([...sep, ...delta]); - const gen1 = []; - for (let i = 0; i < GEN_TOKENS; i++) { - const { token, isStop } = branch.produce(); - if (isStop) break; - branch.commit(token); - gen1.push(token); + const gen = []; + for (let i = 0; i < GEN_TOKENS; i++) { + const { token, isStop } = branch.produce(); + if (isStop) break; + branch.commit(token); + gen.push(token); + } + const text = await ctx.detokenize(gen); + return text; } - assistantContent = await warmCtx.detokenize(gen1); + // Turn 1 (COLD): introduce name + const msgs1 = [{ role: 'user', content: 'Hi, my name is Lloyal' }]; + const { prompt } = await ctx.formatChat(JSON.stringify(msgs1)); + const promptToks = await ctx.tokenize(prompt); + await ctx.decode(promptToks, 0, 0); - // Turn 2: format-only-new warm continuation - const sep = warmCtx.getTurnSeparator(); - const { prompt: warmDelta } = await warmCtx.formatChat(JSON.stringify([ - { role: 'system', content: '' }, - { role: 'user', content: userMessages[1] } - ])); - const deltaToks = await warmCtx.tokenize(warmDelta, false); - branch.prefill([...sep, ...deltaToks]); + const branch = Branch.create(ctx, 0, promptToks.length, { temperature: 0 }); + branch.captureLogits(); - warmGen2 = []; + const gen1 = []; for (let i = 0; i < GEN_TOKENS; i++) { const { token, isStop } = branch.produce(); if (isStop) break; branch.commit(token); - warmGen2.push(token); + gen1.push(token); } + const turn1 = await ctx.detokenize(gen1); + console.log(` Turn 1: "${turn1.trim().slice(0, 80)}"`); + assert(gen1.length > 0, `Turn 1: generated ${gen1.length} tokens`); - branch.prune(); - } finally { - warmCtx.dispose(); - } - - // === COLD PATH: decode full 2-turn conversation from scratch, generate === - const coldCtx = await addon.createContext({ - modelPath: MODEL_PATH, - nCtx: 2048, - nBatch: 512, - nThreads: 4 - }); - - let coldGen2; + // Turn 2 (WARM): introduce favourite food + const turn2 = await warmTurn(branch, 'My favourite food is pizza'); + console.log(` Turn 2: "${turn2.trim().slice(0, 80)}"`); + assert(turn2.length > 0, 'Turn 2: generated response'); - try { - // History: all but last user message (with addGenerationPrompt=false) - const history = [ - { role: 'user', content: userMessages[0] }, - { role: 'assistant', content: assistantContent } - ]; - const { prompt: histPrompt } = await coldCtx.formatChat( - JSON.stringify(history), { addGenerationPrompt: false } - ); - const histToks = await coldCtx.tokenize(histPrompt); - await coldCtx.decode(histToks, 0, 0); - - // Delta: format-only-new (same as warm path) - const { prompt: coldDelta } = await coldCtx.formatChat(JSON.stringify([ - { role: 'system', content: '' }, - { role: 'user', content: userMessages[1] } - ])); - const deltaToks = await coldCtx.tokenize(coldDelta, false); - await coldCtx.decode(deltaToks, histToks.length, 0); - - const branch = Branch.create(coldCtx, 0, histToks.length + deltaToks.length, { temperature: 0 }); - branch.captureLogits(); + // Turn 3 (WARM): recall name + const turn3 = await warmTurn(branch, 'Do you remember my name?'); + console.log(` Turn 3 (name recall): "${turn3.trim().slice(0, 80)}"`); + const nameRecalled = turn3.toLowerCase().includes('lloyal'); + assert(nameRecalled, `Name recall: ${nameRecalled ? 'found "Lloyal"' : 'MISSING "Lloyal" in: ' + turn3.trim().slice(0, 120)}`); - coldGen2 = []; - for (let i = 0; i < GEN_TOKENS; i++) { - const { token, isStop } = branch.produce(); - if (isStop) break; - branch.commit(token); - coldGen2.push(token); - } + // Turn 4 (WARM): recall food + const turn4 = await warmTurn(branch, 'Do you remember my favourite food?'); + console.log(` Turn 4 (food recall): "${turn4.trim().slice(0, 80)}"`); + const foodRecalled = turn4.toLowerCase().includes('pizza'); + assert(foodRecalled, `Food recall: ${foodRecalled ? 'found "pizza"' : 'MISSING "pizza" in: ' + turn4.trim().slice(0, 120)}`); branch.prune(); } finally { - coldCtx.dispose(); - } - - // === COMPARE === - const warmStr = warmGen2.join(','); - const coldStr = coldGen2.join(','); - - // Log divergence diagnostics BEFORE assert (assert throws on failure) - if (warmStr !== coldStr) { - for (let i = 0; i < Math.max(warmGen2.length, coldGen2.length); i++) { - if (warmGen2[i] !== coldGen2[i]) { - console.log(` First divergence at position ${i}: warm=${warmGen2[i]} cold=${coldGen2[i]}`); - break; - } - } + ctx.dispose(); } - - assert(warmStr === coldStr, - warmStr === coldStr - ? `Warm==Cold parity: ${warmGen2.length} tokens match` - : `Warm==Cold parity FAILED: warm=[${warmStr}] vs cold=[${coldStr}]`); } // ═══════════════════════════════════════════════════════════════════════════ @@ -1076,7 +1027,7 @@ async function main() { await testMultiSequence(); await testGrammar(); await testBranchPrefill(); - await testWarmColdParity(); + await testWarmMultiTurnRecall(); await testWarmSemanticRecall(); await testBranchSteer(); await testNBatchAblation(); From 58d79c971ad40fee578b18208549d7505a5ea90a Mon Sep 17 00:00:00 2001 From: LLoyal Research Date: Thu, 12 Feb 2026 01:15:18 +1100 Subject: [PATCH 07/13] feat(chat): new chat api - fix tests --- .github/workflows/tests.yml | 6 +++--- test/integration.js | 36 +++++++++++++++--------------------- 2 files changed, 18 insertions(+), 24 deletions(-) diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 3df363c..9955994 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -80,14 +80,14 @@ jobs: run: | $env:PATH = "${{ github.workspace }}\build\Release;$env:PATH" npm run test:integration - timeout-minutes: 5 + timeout-minutes: 10 env: LLOYAL_LOCAL: '1' - name: Run integration tests (Unix) if: runner.os != 'Windows' run: npm run test:integration - timeout-minutes: 5 + timeout-minutes: 10 env: LLOYAL_LOCAL: '1' @@ -181,7 +181,7 @@ jobs: - name: Run integration tests run: npm run test:integration - timeout-minutes: 5 + timeout-minutes: 10 env: LLOYAL_LOCAL: '1' MODEL_PATH: models/${{ matrix.model.file }} diff --git a/test/integration.js b/test/integration.js index f3bb8c1..a1cfca5 100644 --- a/test/integration.js +++ b/test/integration.js @@ -395,8 +395,6 @@ async function testBranchPrefill() { async function testWarmMultiTurnRecall() { console.log('\n--- Warm Multi-Turn Recall ---'); - const GEN_TOKENS = 60; - const ctx = await addon.createContext({ modelPath: MODEL_PATH, nCtx: 2048, @@ -407,6 +405,18 @@ async function testWarmMultiTurnRecall() { try { const sep = ctx.getTurnSeparator(); + // Helper: generate until EOG (matches C++ test pattern) + async function generate(branch) { + const gen = []; + for (;;) { + const { token, isStop } = branch.produce(); + if (isStop) break; + branch.commit(token); + gen.push(token); + } + return ctx.detokenize(gen); + } + // Helper: warm continuation — sep + format([{system,""},{user,msg}]) async function warmTurn(branch, userContent) { const { prompt } = await ctx.formatChat(JSON.stringify([ @@ -415,16 +425,7 @@ async function testWarmMultiTurnRecall() { ])); const delta = await ctx.tokenize(prompt, false); branch.prefill([...sep, ...delta]); - - const gen = []; - for (let i = 0; i < GEN_TOKENS; i++) { - const { token, isStop } = branch.produce(); - if (isStop) break; - branch.commit(token); - gen.push(token); - } - const text = await ctx.detokenize(gen); - return text; + return generate(branch); } // Turn 1 (COLD): introduce name @@ -436,16 +437,9 @@ async function testWarmMultiTurnRecall() { const branch = Branch.create(ctx, 0, promptToks.length, { temperature: 0 }); branch.captureLogits(); - const gen1 = []; - for (let i = 0; i < GEN_TOKENS; i++) { - const { token, isStop } = branch.produce(); - if (isStop) break; - branch.commit(token); - gen1.push(token); - } - const turn1 = await ctx.detokenize(gen1); + const turn1 = await generate(branch); console.log(` Turn 1: "${turn1.trim().slice(0, 80)}"`); - assert(gen1.length > 0, `Turn 1: generated ${gen1.length} tokens`); + assert(turn1.length > 0, 'Turn 1: generated response'); // Turn 2 (WARM): introduce favourite food const turn2 = await warmTurn(branch, 'My favourite food is pizza'); From 1c42ec6feef655791e348b5876a36e2da6fc82a5 Mon Sep 17 00:00:00 2001 From: LLoyal Research Date: Thu, 12 Feb 2026 01:49:44 +1100 Subject: [PATCH 08/13] feat(ci): move model matrix to GPU --- .github/workflows/gpu-test.yml | 4 +- .github/workflows/tests.yml | 103 +-------------------------------- ci/run-gpu-tests.sh | 66 ++++++++++++++++++--- 3 files changed, 64 insertions(+), 109 deletions(-) diff --git a/.github/workflows/gpu-test.yml b/.github/workflows/gpu-test.yml index faf56a8..2f2d0f2 100644 --- a/.github/workflows/gpu-test.yml +++ b/.github/workflows/gpu-test.yml @@ -129,7 +129,7 @@ jobs: --image="${IMAGE}" \ --service-account="${{ secrets.GCP_SA_EMAIL }}" \ --set-env-vars=LLOYAL_GPU=cuda,LLOYAL_NO_FALLBACK=1 \ - --task-timeout=10m \ + --task-timeout=20m \ --no-gpu-zonal-redundancy else gcloud run jobs create $JOB_NAME \ @@ -137,7 +137,7 @@ jobs: --image="${IMAGE}" \ --service-account="${{ secrets.GCP_SA_EMAIL }}" \ --set-env-vars=LLOYAL_GPU=cuda,LLOYAL_NO_FALLBACK=1 \ - --task-timeout=10m \ + --task-timeout=20m \ --gpu=1 \ --gpu-type=nvidia-l4 \ --memory=16Gi \ diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 9955994..a59c1cc 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -41,12 +41,6 @@ jobs: sudo apt-get update sudo apt-get install -y build-essential cmake - - name: Install build dependencies (macOS) - if: runner.os == 'macOS' - run: | - # Xcode command line tools already installed on GitHub runners - brew install cmake ninja - - name: Install build dependencies (Windows) if: runner.os == 'Windows' run: | @@ -117,95 +111,6 @@ jobs: build/CMakeFiles/CMakeError.log retention-days: 7 - # Model architecture matrix - tests all models on Metal GPU - setup-model-matrix: - name: Setup Model Matrix - runs-on: ubuntu-latest - outputs: - models: ${{ steps.read-matrix.outputs.models }} - steps: - - name: Checkout code - uses: actions/checkout@v4 - - - name: Read model matrix - id: read-matrix - run: | - # Extract model names and files from test/matrix.json - models=$(jq -c '[.models[] | {name: .name, file: .file}]' test/matrix.json) - echo "models=$models" >> $GITHUB_OUTPUT - echo "Model matrix: $models" - - test-model-matrix: - name: Examples - ${{ matrix.model.name }} - runs-on: macos-14 # Metal GPU - needs: setup-model-matrix - - strategy: - fail-fast: false - matrix: - model: ${{ fromJson(needs.setup-model-matrix.outputs.models) }} - - steps: - - name: Checkout code - uses: actions/checkout@v4 - with: - submodules: recursive - - - name: Cache all test models - uses: actions/cache@v4 - with: - path: models/ - key: test-models-all-v1-${{ hashFiles('test/matrix.json') }} - - - name: Download all test models - run: bash scripts/download-test-models.sh --all - - - name: Setup Node.js - uses: actions/setup-node@v4 - with: - node-version: 24 - cache: 'npm' - - - name: Install build dependencies - run: brew install cmake ninja - - - name: Install npm dependencies - run: npm install --ignore-scripts - - # Build with CPU-only to avoid paravirtualized Metal GPU bugs - # (NeoX RoPE kernel returns zeros on Apple Paravirtual device) - - name: Build from submodules - run: npm run build - env: - LLOYAL_GPU: cpu - - - name: Run integration tests - run: npm run test:integration - timeout-minutes: 10 - env: - LLOYAL_LOCAL: '1' - MODEL_PATH: models/${{ matrix.model.file }} - - # TODO: Enable example tests when self-hosted GPU runners are available - # GitHub's macos-14 uses paravirtualized Metal (~2.4s/token) which is too - # slow for example tests. Integration tests pass but examples timeout. - # - name: Run example tests - # run: npm run test:examples - # timeout-minutes: 15 - # env: - # LLOYAL_LOCAL: '1' - # MODEL_PATH: models/${{ matrix.model.file }} - - - name: Display test info - if: always() - run: | - echo "================================" - echo "Model Matrix Test" - echo "================================" - echo "Model: ${{ matrix.model.name }}" - echo "File: ${{ matrix.model.file }}" - echo "Platform: Metal (macos-14)" - verify-npm-package: name: Verify npm package contents runs-on: ubuntu-latest @@ -264,7 +169,7 @@ jobs: test-summary: name: Test Summary runs-on: ubuntu-latest - needs: [test-build, test-model-matrix, verify-npm-package] + needs: [test-build, verify-npm-package] if: always() steps: @@ -273,12 +178,10 @@ jobs: echo "================================" echo "Test Results Summary" echo "================================" - echo "✓ Source builds tested on Linux, macOS, Windows" + echo "✓ Source builds tested on Linux and Windows" echo "✓ Node.js 24 (Active LTS) compatibility verified" - echo "✓ Model architecture matrix tested on Metal" echo "✓ npm package contents verified" echo "✓ Integration tests passed" - echo "✓ Example tests passed" + echo "✓ Model matrix tested on GPU (gpu-test.yml)" echo "" echo "Build & Test Status: ${{ needs.test-build.result }}" - echo "Model Matrix Status: ${{ needs.test-model-matrix.result }}" diff --git a/ci/run-gpu-tests.sh b/ci/run-gpu-tests.sh index 08a2b14..7cc3209 100755 --- a/ci/run-gpu-tests.sh +++ b/ci/run-gpu-tests.sh @@ -36,7 +36,7 @@ fi echo "" echo "=== Downloading Test Models ===" -./scripts/download-test-models.sh +./scripts/download-test-models.sh --all echo "" echo "=== Verifying Backend ===" @@ -55,16 +55,68 @@ try { " echo "" -echo "=== Running Integration Tests ===" -LLOYAL_GPU="${GPU_BACKEND}" \ -LLOYAL_NO_FALLBACK=1 \ -node test/integration.js +echo "=== Running Model Matrix ===" + +# Read model list from matrix.json +MODELS=$(jq -c '.models[]' test/matrix.json) + +# Per-model results tracking +TOTAL=0 +PASS=0 +FAIL=0 +declare -a RESULTS=() + +# Don't exit on per-model failure — track results and report at end +set +e + +while IFS= read -r model; do + name=$(echo "$model" | jq -r '.name') + file=$(echo "$model" | jq -r '.file') + + echo "" + echo "══════════════════════════════════════" + echo "MODEL: $name ($file)" + echo "══════════════════════════════════════" + + TOTAL=$((TOTAL + 1)) + + LLOYAL_GPU="${GPU_BACKEND}" \ + LLOYAL_NO_FALLBACK=1 \ + MODEL_PATH="models/$file" \ + node test/integration.js + + if [ $? -eq 0 ]; then + RESULTS+=("✅ $name") + PASS=$((PASS + 1)) + else + RESULTS+=("❌ $name") + FAIL=$((FAIL + 1)) + fi +done <<< "$MODELS" + +set -e echo "" -echo "=== Running Examples ===" +echo "=== Running Examples (default model) ===" LLOYAL_GPU="${GPU_BACKEND}" \ LLOYAL_NO_FALLBACK=1 \ node test/examples.js +# Final summary table +echo "" +echo "══════════════════════════════════════" +echo "MODEL MATRIX RESULTS" +echo "══════════════════════════════════════" +for r in "${RESULTS[@]}"; do echo " $r"; done echo "" -echo "=== ✅ GPU Tests Passed ===" +echo "Total: $PASS passed, $FAIL failed out of $TOTAL models" + +if [ $FAIL -eq 0 ]; then + echo "" + echo "=== ✅ GPU Tests Passed ===" + exit 0 +else + echo "" + echo "=== ❌ GPU Tests Failed ===" + exit 1 +fi From 4c31addf9fc58383911f63030d99b935e7158ca1 Mon Sep 17 00:00:00 2001 From: LLoyal Research Date: Thu, 12 Feb 2026 02:02:16 +1100 Subject: [PATCH 09/13] feat(ci): move model matrix to GPU --- .github/workflows/gpu-test.yml | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/.github/workflows/gpu-test.yml b/.github/workflows/gpu-test.yml index 2f2d0f2..7d749ee 100644 --- a/.github/workflows/gpu-test.yml +++ b/.github/workflows/gpu-test.yml @@ -1,6 +1,16 @@ name: GPU Tests (CUDA) on: + pull_request: + branches: [ main ] + paths: + - 'liblloyal' + - 'llama.cpp' + - 'lib/**' + - 'src/**' + - 'test/**' + - 'ci/**' + - 'CMakeLists.txt' workflow_dispatch: inputs: skip_build: From 9274f51487457ccdd962c2f4eb327e470d0f8cac Mon Sep 17 00:00:00 2001 From: LLoyal Research Date: Thu, 12 Feb 2026 02:55:12 +1100 Subject: [PATCH 10/13] feat(ci): move model matrix to GPU --- .github/workflows/gpu-test.yml | 82 ++++++++++++++++++++++++++++------ .github/workflows/tests.yml | 8 +++- ci/run-gpu-tests.sh | 57 ++++++++++++++++++----- test/integration.js | 12 ++--- 4 files changed, 127 insertions(+), 32 deletions(-) diff --git a/.github/workflows/gpu-test.yml b/.github/workflows/gpu-test.yml index 7d749ee..9d6f02c 100644 --- a/.github/workflows/gpu-test.yml +++ b/.github/workflows/gpu-test.yml @@ -159,20 +159,74 @@ jobs: - name: Run GPU tests run: | JOB_NAME="lloyal-gpu-test-cuda" + REGION="us-east4" - # Execute job - EXECUTION=$(gcloud run jobs execute $JOB_NAME \ - --region=us-east4 \ - --wait \ + # Launch job asynchronously so we can stream logs + EXEC=$(gcloud run jobs execute $JOB_NAME \ + --region=$REGION \ + --async \ --format='value(metadata.name)') - echo "Execution: $EXECUTION" - - # Wait for logs to flush to Cloud Logging - sleep 5 - - # Get logs - gcloud logging read \ - "resource.type=\"cloud_run_job\" AND resource.labels.job_name=\"$JOB_NAME\" AND resource.labels.location=\"us-east4\"" \ - --limit=200 \ - --format='value(textPayload)' + echo "Execution: $EXEC" + echo "Streaming logs (container startup may take ~30s)..." + echo "" + + # Filter for this specific execution's logs + LOG_FILTER="resource.type=\"cloud_run_job\" AND resource.labels.job_name=\"$JOB_NAME\" AND labels.\"run.googleapis.com/execution_name\"=\"$EXEC\"" + + # Poll loop: stream new log lines + check for completion + SEEN=0 + while true; do + # Check if execution has completed + COMPLETION=$(gcloud run jobs executions describe "$EXEC" \ + --region="$REGION" \ + --format='value(status.completionTime)' 2>/dev/null || true) + + # Fetch all logs for this execution in chronological order + LOGS=$(gcloud logging read "$LOG_FILTER" \ + --limit=10000 \ + --order=asc \ + --format='value(textPayload)' 2>/dev/null || true) + + # Print only lines we haven't seen yet + if [ -n "$LOGS" ]; then + TOTAL=$(echo "$LOGS" | wc -l | tr -d ' ') + if [ "$TOTAL" -gt "$SEEN" ]; then + echo "$LOGS" | tail -n +$((SEEN + 1)) + SEEN=$TOTAL + fi + fi + + # If done, do one final fetch for stragglers then break + if [ -n "$COMPLETION" ]; then + sleep 5 + LOGS=$(gcloud logging read "$LOG_FILTER" \ + --limit=10000 \ + --order=asc \ + --format='value(textPayload)' 2>/dev/null || true) + if [ -n "$LOGS" ]; then + TOTAL=$(echo "$LOGS" | wc -l | tr -d ' ') + if [ "$TOTAL" -gt "$SEEN" ]; then + echo "$LOGS" | tail -n +$((SEEN + 1)) + fi + fi + break + fi + + sleep 10 + done + + # Determine pass/fail from execution status + SUCCEEDED=$(gcloud run jobs executions describe "$EXEC" \ + --region="$REGION" \ + --format=json 2>/dev/null | \ + jq -r '.status.conditions[] | select(.type == "Completed") | .status') + + if [ "$SUCCEEDED" = "True" ]; then + echo "" + echo "✅ GPU Tests Passed" + else + echo "" + echo "❌ GPU Tests Failed" + exit 1 + fi diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index a59c1cc..6861128 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -12,7 +12,7 @@ jobs: strategy: fail-fast: false matrix: - os: [ubuntu-latest, windows-latest] + os: [ubuntu-latest, macos-14, windows-latest] steps: - name: Checkout code @@ -41,6 +41,10 @@ jobs: sudo apt-get update sudo apt-get install -y build-essential cmake + - name: Install build dependencies (macOS) + if: runner.os == 'macOS' + run: brew install cmake + - name: Install build dependencies (Windows) if: runner.os == 'Windows' run: | @@ -178,7 +182,7 @@ jobs: echo "================================" echo "Test Results Summary" echo "================================" - echo "✓ Source builds tested on Linux and Windows" + echo "✓ Source builds tested on Linux, macOS, and Windows" echo "✓ Node.js 24 (Active LTS) compatibility verified" echo "✓ npm package contents verified" echo "✓ Integration tests passed" diff --git a/ci/run-gpu-tests.sh b/ci/run-gpu-tests.sh index 7cc3209..92a070c 100755 --- a/ci/run-gpu-tests.sh +++ b/ci/run-gpu-tests.sh @@ -54,8 +54,13 @@ try { } " +# Common env for all test runs +export LLOYAL_GPU="${GPU_BACKEND}" +export LLOYAL_NO_FALLBACK=1 +export LLAMA_CTX_SIZE=4096 + echo "" -echo "=== Running Model Matrix ===" +echo "=== Running Model Matrix (nCtx=${LLAMA_CTX_SIZE}) ===" # Read model list from matrix.json MODELS=$(jq -c '.models[]' test/matrix.json) @@ -65,6 +70,7 @@ TOTAL=0 PASS=0 FAIL=0 declare -a RESULTS=() +declare -a FAIL_DETAILS=() # Don't exit on per-model failure — track results and report at end set +e @@ -79,29 +85,47 @@ while IFS= read -r model; do echo "══════════════════════════════════════" TOTAL=$((TOTAL + 1)) + MODEL_LOG=$(mktemp) + MODEL_FAILED=false + + # --- Integration tests --- + echo "── Integration Tests ──" + MODEL_PATH="models/$file" \ + node test/integration.js 2>&1 | tee "$MODEL_LOG" + INT_EXIT=${PIPESTATUS[0]} + + if [ $INT_EXIT -ne 0 ]; then + MODEL_FAILED=true + fi - LLOYAL_GPU="${GPU_BACKEND}" \ - LLOYAL_NO_FALLBACK=1 \ + # --- Example tests --- + echo "" + echo "── Example Tests ──" MODEL_PATH="models/$file" \ - node test/integration.js + node test/examples.js 2>&1 | tee -a "$MODEL_LOG" + EX_EXIT=${PIPESTATUS[0]} + + if [ $EX_EXIT -ne 0 ]; then + MODEL_FAILED=true + fi - if [ $? -eq 0 ]; then + # Per-model summary + if [ "$MODEL_FAILED" = false ]; then RESULTS+=("✅ $name") PASS=$((PASS + 1)) else RESULTS+=("❌ $name") FAIL=$((FAIL + 1)) + # Extract failure lines for the final summary + FAILURES=$(grep -E '\[FAIL\]|❌ FAILED|Assertion failed|Fatal error' "$MODEL_LOG" | head -10) + FAIL_DETAILS+=("── $name ──"$'\n'"$FAILURES") fi + + rm -f "$MODEL_LOG" done <<< "$MODELS" set -e -echo "" -echo "=== Running Examples (default model) ===" -LLOYAL_GPU="${GPU_BACKEND}" \ -LLOYAL_NO_FALLBACK=1 \ -node test/examples.js - # Final summary table echo "" echo "══════════════════════════════════════" @@ -111,6 +135,17 @@ for r in "${RESULTS[@]}"; do echo " $r"; done echo "" echo "Total: $PASS passed, $FAIL failed out of $TOTAL models" +if [ $FAIL -gt 0 ] && [ ${#FAIL_DETAILS[@]} -gt 0 ]; then + echo "" + echo "══════════════════════════════════════" + echo "FAILURE DETAILS" + echo "══════════════════════════════════════" + for d in "${FAIL_DETAILS[@]}"; do + echo "$d" + echo "" + done +fi + if [ $FAIL -eq 0 ]; then echo "" echo "=== ✅ GPU Tests Passed ===" diff --git a/test/integration.js b/test/integration.js index a1cfca5..382cce1 100644 --- a/test/integration.js +++ b/test/integration.js @@ -23,6 +23,8 @@ const EMBED_MODEL_PATH = process.env.LLAMA_EMBED_MODEL || ? path.join(__dirname, '../models/nomic-embed-text-v1.5.Q4_K_M.gguf') : null); +const CTX_SIZE = parseInt(process.env.LLAMA_CTX_SIZE || '2048', 10); + if (!fs.existsSync(MODEL_PATH)) { console.error('Test model not found:', MODEL_PATH); process.exit(1); @@ -314,7 +316,7 @@ async function testBranchPrefill() { const ctx = await addon.createContext({ modelPath: MODEL_PATH, - nCtx: 2048, + nCtx: CTX_SIZE, nBatch: 512, nThreads: 4 }); @@ -397,7 +399,7 @@ async function testWarmMultiTurnRecall() { const ctx = await addon.createContext({ modelPath: MODEL_PATH, - nCtx: 2048, + nCtx: CTX_SIZE, nBatch: 512, nThreads: 4 }); @@ -494,7 +496,7 @@ async function testWarmSemanticRecall() { { const ctx = await addon.createContext({ modelPath: MODEL_PATH, - nCtx: 2048, + nCtx: CTX_SIZE, nBatch: 512, nThreads: 4 }); @@ -1005,10 +1007,10 @@ async function main() { // Create main context for reusable tests mainCtx = await addon.createContext({ modelPath: MODEL_PATH, - nCtx: 512, + nCtx: CTX_SIZE, nThreads: 4 }); - ok(`createContext() → vocabSize=${mainCtx.vocabSize}`); + ok(`createContext(nCtx=${CTX_SIZE}) → vocabSize=${mainCtx.vocabSize}`); // Run test suites await testCoreAPI(mainCtx); From 2ee840d457e8abda91ef8e686c8b6e101d030331 Mon Sep 17 00:00:00 2001 From: LLoyal Research Date: Thu, 12 Feb 2026 11:14:53 +1100 Subject: [PATCH 11/13] feat(ci): fix tests, update workflow --- .github/actions/provision-cuda/action.yaml | 59 +++++++++++++++------- .github/workflows/gpu-test.yml | 17 ++++--- .gitignore | 1 + examples/best-of-n/best-of-n.mjs | 3 +- examples/chat/chat.mjs | 3 +- examples/entropy/entropy.mjs | 3 +- examples/grammar/grammar.mjs | 3 +- examples/speculative/speculative.mjs | 3 +- examples/streaming/streaming-summary.mjs | 10 ++-- examples/streaming/streaming-tsampler.mjs | 4 +- examples/streaming/streaming.mjs | 4 +- src/SessionContext.cpp | 4 +- test/integration.js | 30 +++++++---- 13 files changed, 95 insertions(+), 49 deletions(-) diff --git a/.github/actions/provision-cuda/action.yaml b/.github/actions/provision-cuda/action.yaml index 22938f5..3cfec0a 100644 --- a/.github/actions/provision-cuda/action.yaml +++ b/.github/actions/provision-cuda/action.yaml @@ -28,9 +28,36 @@ runs: method: 'network' sub-packages: '["nvcc", "cudart", "cublas", "cublas_dev", "visual_studio_integration"]' - # Linux x64: Install from NVIDIA repos - - name: Install CUDA (Linux x64) - if: runner.os == 'Linux' && inputs.arch == 'x64' + # Linux: Compute version info for cache key + - name: Compute CUDA version info + id: cuda-info + if: runner.os == 'Linux' + shell: bash + env: + VERSION: ${{ inputs.version }} + run: | + echo "major-minor=$(echo $VERSION | cut -d. -f1,2)" >> $GITHUB_OUTPUT + + # Linux: Cache CUDA toolkit directory (~2-3 GB, saves 3-5 min install) + - name: Cache CUDA toolkit + if: runner.os == 'Linux' + id: cuda-cache + uses: actions/cache@v4 + with: + path: /usr/local/cuda-${{ steps.cuda-info.outputs.major-minor }} + key: cuda-toolkit-${{ inputs.version }}-${{ inputs.arch }} + + # Linux: Install build dependencies (always needed, fast from apt cache) + - name: Install build tools + if: runner.os == 'Linux' + shell: bash + run: | + sudo apt-get update -qq + sudo apt-get install -y -qq build-essential cmake + + # Linux x64: Install CUDA toolkit (cache miss only) + - name: Install CUDA toolkit (Linux x64) + if: runner.os == 'Linux' && inputs.arch == 'x64' && steps.cuda-cache.outputs.cache-hit != 'true' shell: bash env: VERSION: ${{ inputs.version }} @@ -42,18 +69,11 @@ runs: wget -q https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb sudo dpkg -i cuda-keyring_1.1-1_all.deb sudo apt-get update -qq - sudo apt-get install -y -qq cuda-toolkit-${version_slug} build-essential cmake + sudo apt-get install -y -qq cuda-toolkit-${version_slug} - cuda_path="/usr/local/cuda-${version_major_minor}" - echo "CUDA_PATH=${cuda_path}" >> $GITHUB_ENV - echo "${cuda_path}/bin" >> $GITHUB_PATH - echo "LD_LIBRARY_PATH=${cuda_path}/lib64:${LD_LIBRARY_PATH}" >> $GITHUB_ENV - - echo "CUDA installed at: ${cuda_path}" - - # Linux ARM64: Install from NVIDIA repos - - name: Install CUDA (Linux ARM64) - if: runner.os == 'Linux' && inputs.arch == 'arm64' + # Linux ARM64: Install CUDA toolkit (cache miss only) + - name: Install CUDA toolkit (Linux ARM64) + if: runner.os == 'Linux' && inputs.arch == 'arm64' && steps.cuda-cache.outputs.cache-hit != 'true' shell: bash env: VERSION: ${{ inputs.version }} @@ -65,14 +85,19 @@ runs: wget -q https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/arm64/cuda-keyring_1.1-1_all.deb sudo dpkg -i cuda-keyring_1.1-1_all.deb sudo apt-get update -qq - sudo apt-get install -y -qq cuda-toolkit-${version_slug} build-essential cmake + sudo apt-get install -y -qq cuda-toolkit-${version_slug} - cuda_path="/usr/local/cuda-${version_major_minor}" + # Linux: Set CUDA environment variables (always - cached or fresh install) + - name: Set CUDA environment + if: runner.os == 'Linux' + shell: bash + run: | + cuda_path="/usr/local/cuda-${{ steps.cuda-info.outputs.major-minor }}" echo "CUDA_PATH=${cuda_path}" >> $GITHUB_ENV echo "${cuda_path}/bin" >> $GITHUB_PATH echo "LD_LIBRARY_PATH=${cuda_path}/lib64:${LD_LIBRARY_PATH}" >> $GITHUB_ENV - echo "CUDA installed at: ${cuda_path}" + echo "CUDA ready at: ${cuda_path}" # Set output - name: Set CUDA path output diff --git a/.github/workflows/gpu-test.yml b/.github/workflows/gpu-test.yml index 9d6f02c..2057193 100644 --- a/.github/workflows/gpu-test.yml +++ b/.github/workflows/gpu-test.yml @@ -48,25 +48,29 @@ jobs: run: node scripts/sync-llama-cpp.js --check shell: bash - - name: Install build tools - run: | - sudo apt-get update - sudo apt-get install -y build-essential cmake - # CUDA 12.2.2 required for Cloud Run L4 GPU (driver 535.x) + # provision-cuda also installs build-essential + cmake - name: Provision CUDA toolkit uses: ./.github/actions/provision-cuda with: version: '12.2.2' arch: x64 + - name: Setup ccache + uses: hendrikmuhs/ccache-action@v1.2 + with: + key: cuda-build-${{ runner.os }} + - name: Install npm dependencies - run: npm install --ignore-scripts + run: npm ci --ignore-scripts - name: Build native module run: npm run build env: LLOYAL_GPU: cuda + CMAKE_C_COMPILER_LAUNCHER: ccache + CMAKE_CXX_COMPILER_LAUNCHER: ccache + CMAKE_CUDA_COMPILER_LAUNCHER: ccache - name: Create platform package run: node scripts/create-platform-package.js linux-x64-cuda ubuntu-22.04 x64 @@ -77,6 +81,7 @@ jobs: name: package-linux-x64-cuda path: packages/linux-x64-cuda/ retention-days: 1 + compression-level: 0 # GPU Integration Tests via Cloud Run # Runs real GPU tests on NVIDIA L4 diff --git a/.gitignore b/.gitignore index 95b20dd..1f2f1b8 100644 --- a/.gitignore +++ b/.gitignore @@ -10,6 +10,7 @@ models/ # Generated documentation docs/api/ docs/_internal + # Vendor build artifacts (generated during npm install) vendor/llama.cpp/build-*/ diff --git a/examples/best-of-n/best-of-n.mjs b/examples/best-of-n/best-of-n.mjs index 8fe5dc9..26daa68 100644 --- a/examples/best-of-n/best-of-n.mjs +++ b/examples/best-of-n/best-of-n.mjs @@ -89,9 +89,10 @@ async function main() { emit('start', { model: path.basename(modelPath), n: N, maxTokens: MAX_TOKENS, highTemp: HIGH_TEMP, lowTemp: LOW_TEMP }); + const nCtx = parseInt(process.env.LLAMA_CTX_SIZE || '2048', 10); const ctx = await createContext({ modelPath, - contextSize: 2048, + nCtx, nSeqMax: N + 2, // Need slots for N candidates + baseline + trunk }); diff --git a/examples/chat/chat.mjs b/examples/chat/chat.mjs index f86b0e1..05196dc 100644 --- a/examples/chat/chat.mjs +++ b/examples/chat/chat.mjs @@ -30,9 +30,10 @@ async function main() { console.log(`Loading model: ${modelPath}`); console.log("This may take a moment...\n"); + const nCtx = parseInt(process.env.LLAMA_CTX_SIZE || '2048', 10); const ctx = await createContext({ modelPath, - contextSize: 2048, + nCtx, threads: 4, }); diff --git a/examples/entropy/entropy.mjs b/examples/entropy/entropy.mjs index bfbce73..c9204fe 100644 --- a/examples/entropy/entropy.mjs +++ b/examples/entropy/entropy.mjs @@ -160,9 +160,10 @@ async function main() { emit('start', { model: path.basename(modelPath), T0, N, THETA }); + const nCtx = parseInt(process.env.LLAMA_CTX_SIZE || '2048', 10); const ctx = await createContext({ modelPath, - contextSize: 2048, + nCtx, }); // Test 1: Factual question (expect low entropy, EDT should use low temp) diff --git a/examples/grammar/grammar.mjs b/examples/grammar/grammar.mjs index c32be1f..33d4fc3 100644 --- a/examples/grammar/grammar.mjs +++ b/examples/grammar/grammar.mjs @@ -60,9 +60,10 @@ async function main() { emit('start', { model: path.basename(modelPath) }); + const nCtx = parseInt(process.env.LLAMA_CTX_SIZE || '2048', 10); const ctx = await createContext({ modelPath, - contextSize: 2048, + nCtx, nSeqMax: 4, }); diff --git a/examples/speculative/speculative.mjs b/examples/speculative/speculative.mjs index ccb44a1..f1b8261 100644 --- a/examples/speculative/speculative.mjs +++ b/examples/speculative/speculative.mjs @@ -92,9 +92,10 @@ async function main() { generationLength: GENERATION_LENGTH, }); + const nCtx = parseInt(process.env.LLAMA_CTX_SIZE || '2048', 10); const ctx = await createContext({ modelPath, - contextSize: 2048, + nCtx, nSeqMax: 4, // Enable multi-sequence for fork/verify pattern }); diff --git a/examples/streaming/streaming-summary.mjs b/examples/streaming/streaming-summary.mjs index 066d1a8..6de9f56 100644 --- a/examples/streaming/streaming-summary.mjs +++ b/examples/streaming/streaming-summary.mjs @@ -193,7 +193,7 @@ function buildProgressSink(anchor, outline, allGeneratedText, summaryChain) { async function main() { // Constants - const nCtx = 2048; + const nCtx = parseInt(process.env.LLAMA_CTX_SIZE || '2048', 10); const TAIL_SIZE = 256; const MAX_SINK_RATIO = 0.4; const MAX_SINK_TOKENS = Math.floor(nCtx * MAX_SINK_RATIO); @@ -218,7 +218,7 @@ async function main() { const ctx = await createContext({ modelPath, - contextSize: nCtx, + nCtx, }); // Summary sidecar — preload in background (overlaps with prompt decode + generation) @@ -232,20 +232,20 @@ async function main() { // Sidecar mode: use slim-summarize.gguf const summaryModelAvailable = fs.existsSync(SUMMARY_MODEL); if (summaryModelAvailable) { - summaryCtxPromise = createContext({ modelPath: SUMMARY_MODEL, contextSize: 4096 }); + summaryCtxPromise = createContext({ modelPath: SUMMARY_MODEL, nCtx: 4096 }); } else { if (!jsonlMode) { console.log('Sidecar model not found - falling back to self-summary'); } emit('sidecar_missing', { message: 'slim-summarize.gguf not found, using self-summary' }); // Fall back to self mode - summaryCtxPromise = createContext({ modelPath, contextSize: 4096 }); + summaryCtxPromise = createContext({ modelPath, nCtx: 4096 }); actualSummaryFormat = 'self'; } } else { // Self mode (default): second context from same model // Weights are shared via model_registry — only KV cache is duplicated - summaryCtxPromise = createContext({ modelPath, contextSize: 4096 }); + summaryCtxPromise = createContext({ modelPath, nCtx: 4096 }); } const prompt = `Write a comprehensive guide to machine learning, covering the following topics in extreme detail with examples, code snippets, and mathematical formulas: diff --git a/examples/streaming/streaming-tsampler.mjs b/examples/streaming/streaming-tsampler.mjs index 09c052f..4fd3207 100644 --- a/examples/streaming/streaming-tsampler.mjs +++ b/examples/streaming/streaming-tsampler.mjs @@ -133,7 +133,7 @@ class NgramTracker { async function main() { // BlinkKV parameters - const nCtx = 2048; + const nCtx = parseInt(process.env.LLAMA_CTX_SIZE || '2048', 10); const TAIL_SIZE = 256; const NGRAM_SIZE = 6; // Track 6-grams for sequence detection const BLOCK_THRESHOLD = 2; // Only block after seeing same pattern K times @@ -146,7 +146,7 @@ async function main() { const ctx = await createContext({ modelPath, - contextSize: nCtx, + nCtx, }); const prompt = `Write a comprehensive guide to machine learning, covering the following topics in extreme detail with examples, code snippets, and mathematical formulas: diff --git a/examples/streaming/streaming.mjs b/examples/streaming/streaming.mjs index 1c0dc2a..4bc52e8 100644 --- a/examples/streaming/streaming.mjs +++ b/examples/streaming/streaming.mjs @@ -42,7 +42,7 @@ function emit(event, data) { async function main() { // BlinkKV paper parameters: 2048 context, 4 sinks, 256 tail - const nCtx = 2048; + const nCtx = parseInt(process.env.LLAMA_CTX_SIZE || '2048', 10); const SINK_COUNT = 4; const TAIL_SIZE = 256; @@ -54,7 +54,7 @@ async function main() { const ctx = await createContext({ modelPath, - contextSize: nCtx, + nCtx, }); const prompt = `Write a comprehensive guide to machine learning, covering the following topics in extreme detail with examples, code snippets, and mathematical formulas: diff --git a/src/SessionContext.cpp b/src/SessionContext.cpp index e32ae19..9e9aada 100644 --- a/src/SessionContext.cpp +++ b/src/SessionContext.cpp @@ -2102,9 +2102,7 @@ Napi::Value CreateContext(const Napi::CallbackInfo& info) { std::cout << "[CreateContext] File validated: " << fsPath << " (" << fileSize << " bytes)" << std::endl; // Load model on main thread - // Note: With XCFramework build, this works reliably on main thread - // (async loading was failing with CMake build due to binary incompatibility) - std::cout << "[CreateContext] Loading model from XCFramework..." << std::endl; + std::cout << "[CreateContext] Loading model..." << std::endl; llama_model_params model_params = llama_model_default_params(); // -1 = offload all layers to GPU (auto-detect), 0 = CPU only diff --git a/test/integration.js b/test/integration.js index 382cce1..4580447 100644 --- a/test/integration.js +++ b/test/integration.js @@ -166,7 +166,7 @@ async function testMultiSequence() { const ctx = await addon.createContext({ modelPath: MODEL_PATH, - nCtx: 512, + nCtx: CTX_SIZE, nThreads: 4, nSeqMax: 4 }); @@ -201,7 +201,7 @@ async function testGrammar() { const ctx = await addon.createContext({ modelPath: MODEL_PATH, - nCtx: 512, + nCtx: CTX_SIZE, nThreads: 4 }); @@ -432,13 +432,25 @@ async function testWarmMultiTurnRecall() { // Turn 1 (COLD): introduce name const msgs1 = [{ role: 'user', content: 'Hi, my name is Lloyal' }]; - const { prompt } = await ctx.formatChat(JSON.stringify(msgs1)); + const { prompt, format, reasoningFormat } = await ctx.formatChat(JSON.stringify(msgs1), {}); const promptToks = await ctx.tokenize(prompt); await ctx.decode(promptToks, 0, 0); const branch = Branch.create(ctx, 0, promptToks.length, { temperature: 0 }); branch.captureLogits(); + // Helper: parse output and check both content and reasoning for a term + // Handles thinking models (Qwen3, DeepSeek-R1) where answer may be in blocks + function checkRecall(rawText, term) { + const { content, reasoningContent } = ctx.parseChatOutput(rawText, format, { + reasoningFormat, + isPartial: false, + thinkingForcedOpen: false + }); + const fullText = (content || '') + ' ' + (reasoningContent || ''); + return fullText.toLowerCase().includes(term.toLowerCase()); + } + const turn1 = await generate(branch); console.log(` Turn 1: "${turn1.trim().slice(0, 80)}"`); assert(turn1.length > 0, 'Turn 1: generated response'); @@ -451,13 +463,13 @@ async function testWarmMultiTurnRecall() { // Turn 3 (WARM): recall name const turn3 = await warmTurn(branch, 'Do you remember my name?'); console.log(` Turn 3 (name recall): "${turn3.trim().slice(0, 80)}"`); - const nameRecalled = turn3.toLowerCase().includes('lloyal'); + const nameRecalled = checkRecall(turn3, 'lloyal'); assert(nameRecalled, `Name recall: ${nameRecalled ? 'found "Lloyal"' : 'MISSING "Lloyal" in: ' + turn3.trim().slice(0, 120)}`); // Turn 4 (WARM): recall food const turn4 = await warmTurn(branch, 'Do you remember my favourite food?'); console.log(` Turn 4 (food recall): "${turn4.trim().slice(0, 80)}"`); - const foodRecalled = turn4.toLowerCase().includes('pizza'); + const foodRecalled = checkRecall(turn4, 'pizza'); assert(foodRecalled, `Food recall: ${foodRecalled ? 'found "pizza"' : 'MISSING "pizza" in: ' + turn4.trim().slice(0, 120)}`); branch.prune(); @@ -608,7 +620,7 @@ async function testBranchSteer() { const ctx = await addon.createContext({ modelPath: MODEL_PATH, - nCtx: 512, + nCtx: CTX_SIZE, nThreads: 4 }); @@ -712,7 +724,7 @@ async function testNBatchAblation() { for (const nBatch of nBatchValues) { const ctx = await addon.createContext({ modelPath: MODEL_PATH, - nCtx: 1024, + nCtx: CTX_SIZE, nBatch, nThreads: 4 }); @@ -801,7 +813,7 @@ async function testDeterminism() { async function generate(prompt) { const ctx = await addon.createContext({ modelPath: MODEL_PATH, - nCtx: 512, + nCtx: CTX_SIZE, nThreads: 4 }); @@ -912,7 +924,7 @@ async function testDecodeAndCapture() { const ctx = await addon.createContext({ modelPath: MODEL_PATH, - nCtx: 512, + nCtx: CTX_SIZE, nThreads: 4 }); From 223020bb99c49623d64865d8f8847fabcbb1a214 Mon Sep 17 00:00:00 2001 From: LLoyal Research Date: Thu, 12 Feb 2026 11:38:25 +1100 Subject: [PATCH 12/13] feat(ci): fix tests, update workflow --- package-lock.json | 156 ++++++++++++++++++++++++++++++++++++++++++---- 1 file changed, 143 insertions(+), 13 deletions(-) diff --git a/package-lock.json b/package-lock.json index 3a9b00f..acc8e73 100644 --- a/package-lock.json +++ b/package-lock.json @@ -93,43 +93,173 @@ } }, "node_modules/@lloyal-labs/lloyal.node-darwin-arm64": { - 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MODEL_PATH="models/$file" \ + LLAMA_TEST_MODEL="models/$file" \ node test/integration.js 2>&1 | tee "$MODEL_LOG" INT_EXIT=${PIPESTATUS[0]} @@ -101,7 +101,7 @@ while IFS= read -r model; do # --- Example tests --- echo "" echo "── Example Tests ──" - MODEL_PATH="models/$file" \ + LLAMA_TEST_MODEL="models/$file" \ node test/examples.js 2>&1 | tee -a "$MODEL_LOG" EX_EXIT=${PIPESTATUS[0]} diff --git a/lib/index.js b/lib/index.js index 8fd81c5..d01130e 100644 --- a/lib/index.js +++ b/lib/index.js @@ -97,10 +97,10 @@ const tryLoadPackage = (packageName, verbose = false) => { * - Uses local build exclusively (`build/Release/lloyal.node`) * - Throws error if not found (no fallback) * - * Otherwise (production): + * Otherwise: * 1. Requested GPU variant package (if `variant` param or `LLOYAL_GPU` env var specified) - * 2. Default platform package (`@lloyal-labs/lloyal.node-{platform}-{arch}`) - * 3. Local build as final fallback + * 2. Local build (`build/Release/lloyal.node`) — always fresher during development + * 3. Default platform package (`@lloyal-labs/lloyal.node-{platform}-{arch}`) * * **Environment Variables:** * - `LLOYAL_LOCAL=1` — Use local build exclusively (`build/Release/lloyal.node`). @@ -173,18 +173,18 @@ const loadBinary = (variant) => { console.warn(`[lloyal.node] GPU variant "${variant}" unavailable, falling back to CPU`); } - // 2. Try default platform package (CPU) - const defaultPkg = getPlatformPackageName(); - const binary = tryLoadPackage(defaultPkg, true); // verbose=true - if (binary) return binary; - - // 3. Try local build (development) + // 2. Try local build (always fresher than installed packages during development) try { return require('../build/Release/lloyal.node'); } catch (e) { - // ignore + // ignore — no local build } + // 3. Try default platform package (CPU) + const defaultPkg = getPlatformPackageName(); + const binary = tryLoadPackage(defaultPkg, true); // verbose=true + if (binary) return binary; + throw new Error( `No lloyal.node binary found for ${process.platform}-${process.arch}. ` + `Tried: ${variant ? getPlatformPackageName(variant) + ', ' : ''}${defaultPkg}` diff --git a/test/examples.js b/test/examples.js index 48cb63c..aedd9c1 100644 --- a/test/examples.js +++ b/test/examples.js @@ -9,7 +9,7 @@ * node test/examples.js entropy # Run specific example * * Environment variables: - * MODEL_PATH - Path to chat/instruct model (default: SmolLM2) + * LLAMA_TEST_MODEL - Path to chat/instruct model (default: SmolLM2) * EMBED_MODEL_PATH - Path to embedding model (default: nomic-embed) */ @@ -18,8 +18,8 @@ const path = require('path'); const fs = require('fs'); // Model paths - use env var or default (resolve to absolute path) -const MODEL_PATH = process.env.MODEL_PATH - ? path.resolve(process.env.MODEL_PATH) +const MODEL_PATH = process.env.LLAMA_TEST_MODEL + ? path.resolve(process.env.LLAMA_TEST_MODEL) : path.join(__dirname, '../models/SmolLM2-1.7B-Instruct-Q4_K_M.gguf'); // Embedding model (separate from chat model, resolve to absolute path) diff --git a/test/integration.js b/test/integration.js index 4580447..8ab8edd 100644 --- a/test/integration.js +++ b/test/integration.js @@ -6,7 +6,7 @@ * * Usage: * npm run test:integration - * MODEL_PATH=models/Llama-3.2-1B-Instruct-Q4_K_M.gguf npm run test:integration + * LLAMA_TEST_MODEL=models/Llama-3.2-1B-Instruct-Q4_K_M.gguf npm run test:integration * * Optional embedding tests: * LLAMA_EMBED_MODEL=models/nomic-embed-text-v1.5.Q4_K_M.gguf npm run test:integration @@ -15,8 +15,8 @@ const path = require('path'); const fs = require('fs'); -const MODEL_PATH = process.env.MODEL_PATH - ? path.resolve(process.env.MODEL_PATH) +const MODEL_PATH = process.env.LLAMA_TEST_MODEL + ? path.resolve(process.env.LLAMA_TEST_MODEL) : path.join(__dirname, '../models/SmolLM2-1.7B-Instruct-Q4_K_M.gguf'); const EMBED_MODEL_PATH = process.env.LLAMA_EMBED_MODEL || (fs.existsSync(path.join(__dirname, '../models/nomic-embed-text-v1.5.Q4_K_M.gguf')) @@ -424,7 +424,7 @@ async function testWarmMultiTurnRecall() { const { prompt } = await ctx.formatChat(JSON.stringify([ { role: 'system', content: '' }, { role: 'user', content: userContent } - ])); + ]), {}); const delta = await ctx.tokenize(prompt, false); branch.prefill([...sep, ...delta]); return generate(branch); @@ -439,38 +439,36 @@ async function testWarmMultiTurnRecall() { const branch = Branch.create(ctx, 0, promptToks.length, { temperature: 0 }); branch.captureLogits(); - // Helper: parse output and check both content and reasoning for a term - // Handles thinking models (Qwen3, DeepSeek-R1) where answer may be in blocks + // Helper: parse output and check content (not reasoning) for a term function checkRecall(rawText, term) { - const { content, reasoningContent } = ctx.parseChatOutput(rawText, format, { + const { content } = ctx.parseChatOutput(rawText, format, { reasoningFormat, isPartial: false, thinkingForcedOpen: false }); - const fullText = (content || '') + ' ' + (reasoningContent || ''); - return fullText.toLowerCase().includes(term.toLowerCase()); + return (content || '').toLowerCase().includes(term.toLowerCase()); } const turn1 = await generate(branch); - console.log(` Turn 1: "${turn1.trim().slice(0, 80)}"`); + console.log(` Turn 1: "${turn1.trim()}"`); assert(turn1.length > 0, 'Turn 1: generated response'); // Turn 2 (WARM): introduce favourite food const turn2 = await warmTurn(branch, 'My favourite food is pizza'); - console.log(` Turn 2: "${turn2.trim().slice(0, 80)}"`); + console.log(` Turn 2: "${turn2.trim()}"`); assert(turn2.length > 0, 'Turn 2: generated response'); // Turn 3 (WARM): recall name const turn3 = await warmTurn(branch, 'Do you remember my name?'); - console.log(` Turn 3 (name recall): "${turn3.trim().slice(0, 80)}"`); + console.log(` Turn 3 (name recall): "${turn3.trim()}"`); const nameRecalled = checkRecall(turn3, 'lloyal'); - assert(nameRecalled, `Name recall: ${nameRecalled ? 'found "Lloyal"' : 'MISSING "Lloyal" in: ' + turn3.trim().slice(0, 120)}`); + assert(nameRecalled, `Name recall: ${nameRecalled ? 'found "Lloyal"' : 'MISSING "Lloyal" in: ' + turn3.trim()}`); // Turn 4 (WARM): recall food const turn4 = await warmTurn(branch, 'Do you remember my favourite food?'); - console.log(` Turn 4 (food recall): "${turn4.trim().slice(0, 80)}"`); + console.log(` Turn 4 (food recall): "${turn4.trim()}"`); const foodRecalled = checkRecall(turn4, 'pizza'); - assert(foodRecalled, `Food recall: ${foodRecalled ? 'found "pizza"' : 'MISSING "pizza" in: ' + turn4.trim().slice(0, 120)}`); + assert(foodRecalled, `Food recall: ${foodRecalled ? 'found "pizza"' : 'MISSING "pizza" in: ' + turn4.trim()}`); branch.prune(); } finally { @@ -594,7 +592,7 @@ async function testWarmSemanticRecall() { return embedCtx.getEmbeddings(true); } - console.log(` Recall response: "${recallText.trim().slice(0, 120)}"`); + console.log(` Recall response: "${recallText.trim()}"`); const embResponse = await embed(recallText); const embCorrect = await embed('The dog is named Max.'); diff --git a/test/matrix.json b/test/matrix.json index a22f153..0a5bad5 100644 --- a/test/matrix.json +++ b/test/matrix.json @@ -9,13 +9,7 @@ "template": "chatml", "default": true }, - { - "name": "Ministral", - "file": "Ministral-3-3B-Instruct-2512-Q4_K_M.gguf", - "url": "https://huggingface.co/mistralai/Ministral-3-3B-Instruct-2512-GGUF/resolve/main/Ministral-3-3B-Instruct-2512-Q4_K_M.gguf", - "template": "mistral" - }, - { +{ "name": "Llama-3.2", "file": "Llama-3.2-1B-Instruct-Q4_K_M.gguf", "url": "https://huggingface.co/bartowski/Llama-3.2-1B-Instruct-GGUF/resolve/main/Llama-3.2-1B-Instruct-Q4_K_M.gguf", @@ -29,8 +23,8 @@ }, { "name": "Qwen3", - "file": "Qwen3-1.7B-Q4_K_M.gguf", - "url": "https://huggingface.co/unsloth/Qwen3-1.7B-GGUF/resolve/main/Qwen3-1.7B-Q4_K_M.gguf", + "file": "Qwen3-4B-Thinking-2507-Q4_K_M.gguf", + "url": "https://huggingface.co/unsloth/Qwen3-4B-Thinking-2507-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Q4_K_M.gguf", "template": "chatml" }, { @@ -38,6 +32,12 @@ "file": "gemma-3-1b-it-Q4_K_M.gguf", "url": "https://huggingface.co/unsloth/gemma-3-1b-it-GGUF/resolve/main/gemma-3-1b-it-Q4_K_M.gguf", "template": "gemma" + }, + { + "name": "GLM-Edge", + "file": "ggml-model-Q4_K_M.gguf", + "url": "https://huggingface.co/zai-org/glm-edge-4b-chat-gguf/resolve/main/ggml-model-Q4_K_M.gguf", + "template": "glm-edge" } ], "embeddings": [