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LLMProvider,
LLMCapabilities,
LLMPrompt,
LLMGenerateOptions,
LLMResponse,
LLMStreamChunk,
} from '@agentix-e/nl2spel';
import { MODEL_CONFIGS, type ModelConfig } from './model-configs.js';
export interface WebLLMConfig {
/** Model ID */
model: string;
/** Custom model config (optional override) */
customModelConfig?: Partial<ModelConfig>;
/** Load progress callback */
onProgress?: (progress: ModelLoadProgress) => void;
/** Whether to enable GBNF grammar constraints (default true) */
enableGrammar?: boolean;
/** Whether to output logs to console */
debug?: boolean;
}
export interface ModelLoadProgress {
progress: number; // 0-1
loaded: number; // bytes
total: number; // bytes
text: string; // Current phase description
}
/**
* WebLLMProvider — browser-side local LLM provider.
*
* Uses @mlc-ai/web-llm to run local models in the browser.
* WebLLM's CreateMLCEngine handles all GPU detection and error reporting internally.
* This provider simply delegates to WebLLM's native capabilities.
*/
export class WebLLMProvider implements LLMProvider {
public readonly name = 'webllm';
public readonly capabilities: LLMCapabilities;
private readonly config: WebLLMConfig;
private readonly modelConfig: ModelConfig;
private _engine: unknown = null;
private _initialized = false;
private _initPromise: Promise<void> | null = null;
constructor(config: WebLLMConfig) {
this.config = {
enableGrammar: true,
debug: false,
...config,
};
this.modelConfig = {
...(MODEL_CONFIGS[config.model] ?? MODEL_CONFIGS['gemma-2-2b-it']!),
...config.customModelConfig,
};
this.capabilities = {
maxContextTokens: this.modelConfig.maxContextTokens,
supportsGrammarConstraint: true,
supportsStreaming: true,
supportsStructuredOutput: false,
offlineAvailable: true,
};
}
/**
* Initialize — download and load the model via WebLLM.
* WebLLM's CreateMLCEngine handles GPU detection natively.
*/
async initialize(): Promise<void> {
if (this._initialized) return;
if (this._initPromise) return this._initPromise;
this._initPromise = this._doInitialize();
return this._initPromise;
}
private async _doInitialize(): Promise<void> {
try {
const { CreateMLCEngine } = await this.importWebLLM();
this._engine = await CreateMLCEngine(this.modelConfig.modelId, {
initProgressCallback: (report: { progress: number; timeElapsed: number; text: string }) => {
this.config.onProgress?.({
progress: report.progress,
loaded: 0,
total: 0,
text: report.text,
});
},
logLevel: this.config.debug ? 'INFO' : 'WARN',
});
this._initialized = true;
if (this.config.debug) {
console.log(`[WebLLM] Model ${this.modelConfig.displayName} loaded successfully`);
}
} catch (err) {
throw new Error(`WebLLM initialization failed: ${(err as Error).message}`);
}
}
/**
* Dynamic import of WebLLM (separated for test mocking)
*/
private async importWebLLM(): Promise<any> {
return import('@mlc-ai/web-llm');
}
/**
* Check if the provider is available.
* Simply returns true — actual GPU availability is determined by WebLLM at initialization.
*/
async isAvailable(): Promise<boolean> {
return true;
}
/**
* Generate a SpEL expression
*/
async generate(prompt: LLMPrompt, options?: LLMGenerateOptions): Promise<LLMResponse> {
await this.initialize();
const engine = this._engine as any;
const startTime = Date.now();
const messages = [
{ role: 'system' as const, content: prompt.system },
{ role: 'user' as const, content: prompt.user },
];
// GBNF grammar generation is available via GBNFGenerator for manual use.
// Auto-injection into WebLLM requests is not yet supported by @mlc-ai/web-llm.
// if (this.config.enableGrammar) {
// this.gbnfGenerator.generate(prompt.contextSchema);
// }
try {
const completion = await engine.chat.completions.create({
messages,
temperature: options?.temperature ?? 0.1,
max_tokens: options?.maxTokens ?? 512,
top_p: options?.topP ?? 0.9,
});
const text = completion.choices?.[0]?.message?.content?.trim() ?? '';
const usage = completion.usage;
return {
text,
model: this.modelConfig.displayName,
usage: {
promptTokens: usage?.prompt_tokens ?? 0,
completionTokens: usage?.completion_tokens ?? 0,
totalTokens: usage?.total_tokens ?? 0,
},
latencyMs: Date.now() - startTime,
finishReason: completion.choices?.[0]?.finish_reason ?? 'stop',
providerName: 'webllm',
};
} catch (err) {
throw new Error(`WebLLM generation failed: ${(err as Error).message}`);
}
}
/**
* Streaming generation — falls back to generate() since WebLLM stream API
* requires extra handling not yet implemented.
*/
async *generateStream(
prompt: LLMPrompt,
options?: LLMGenerateOptions,
): AsyncIterable<LLMStreamChunk> {
await this.initialize();
const result = await this.generate(prompt, options);
yield {
delta: result.text,
accumulated: result.text,
done: true,
finishReason: result.finishReason,
};
}
/**
* Release resources
*/
async dispose(): Promise<void> {
if (this._engine && typeof (this._engine as any).unload === 'function') {
try {
(this._engine as any).unload();
} catch {
// Ignore unload errors
}
}
this._engine = null;
this._initialized = false;
this._initPromise = null;
}
}
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