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@langchain/community

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require("../_virtual/_rolldown/runtime.cjs"); let node_llama_cpp = require("node-llama-cpp"); //#region src/utils/llama_cpp.ts async function createLlamaModel(inputs, llama) { const options = { gpuLayers: inputs?.gpuLayers, modelPath: inputs.modelPath, useMlock: inputs?.useMlock, useMmap: inputs?.useMmap, vocabOnly: inputs?.vocabOnly }; return llama.loadModel(options); } async function createLlamaContext(model, inputs) { const options = { batchSize: inputs?.batchSize, contextSize: inputs?.contextSize, threads: inputs?.threads }; return model.createContext(options); } async function createLlamaEmbeddingContext(model, inputs) { const options = { batchSize: inputs?.batchSize, contextSize: inputs?.contextSize, threads: inputs?.threads }; return model.createEmbeddingContext(options); } function createLlamaSession(context) { return new node_llama_cpp.LlamaChatSession({ contextSequence: context.getSequence() }); } async function createLlamaJsonSchemaGrammar(schemaString, llama) { if (schemaString === void 0) return; const schemaJSON = schemaString; return await llama.createGrammarForJsonSchema(schemaJSON); } async function createCustomGrammar(filePath, llama) { if (filePath === void 0) return; return llama.createGrammar({ grammar: filePath }); } //#endregion exports.createCustomGrammar = createCustomGrammar; exports.createLlamaContext = createLlamaContext; exports.createLlamaEmbeddingContext = createLlamaEmbeddingContext; exports.createLlamaJsonSchemaGrammar = createLlamaJsonSchemaGrammar; exports.createLlamaModel = createLlamaModel; exports.createLlamaSession = createLlamaSession; //# sourceMappingURL=llama_cpp.cjs.map