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LLama2

Usage

import { Ollama, Settings, DeuceChatStrategy } from "llamaindex";

Settings.llm = new LlamaDeuce({ chatStrategy: DeuceChatStrategy.META });

Usage with Replication

import {
Ollama,
ReplicateSession,
Settings,
DeuceChatStrategy,
} from "llamaindex";

const replicateSession = new ReplicateSession({
replicateKey,
});

Settings.llm = new LlamaDeuce({
chatStrategy: DeuceChatStrategy.META,
replicateSession,
});

Load and index documents

For this example, we will use a single document. In a real-world scenario, you would have multiple documents to index.

const document = new Document({ text: essay, id_: "essay" });

const index = await VectorStoreIndex.fromDocuments([document]);

Query

const queryEngine = index.asQueryEngine();

const query = "What is the meaning of life?";

const results = await queryEngine.query({
query,
});

Full Example

import {
LlamaDeuce,
Document,
VectorStoreIndex,
Settings,
DeuceChatStrategy,
} from "llamaindex";

// Use the LlamaDeuce LLM
Settings.llm = new LlamaDeuce({ chatStrategy: DeuceChatStrategy.META });

async function main() {
const document = new Document({ text: essay, id_: "essay" });

// Load and index documents
const index = await VectorStoreIndex.fromDocuments([document]);

// get retriever
const retriever = index.asRetriever();

// Create a query engine
const queryEngine = index.asQueryEngine({
retriever,
});

const query = "What is the meaning of life?";

// Query
const response = await queryEngine.query({
query,
});

// Log the response
console.log(response.response);
}