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LLama2

npm i llamaindex @llamaindex/replicate
import { LlamaDeuce, DeuceChatStrategy } from "@llamaindex/replicate";
import { Document, VectorStoreIndex, Settings } from "llamaindex";
Settings.llm = new LlamaDeuce({ chatStrategy: DeuceChatStrategy.META });
import { Settings } from "llamaindex";
import { LlamaDeuce, DeuceChatStrategy, ReplicateSession } from "@llamaindex/replicate";
const replicateSession = new ReplicateSession({
replicateKey,
});
Settings.llm = new LlamaDeuce({
chatStrategy: DeuceChatStrategy.META,
replicateSession,
});

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]);
const queryEngine = index.asQueryEngine();
const query = "What is the meaning of life?";
const results = await queryEngine.query({
query,
});
import { LlamaDeuce, DeuceChatStrategy } from "@llamaindex/replicate";
import { Document, VectorStoreIndex, Settings } 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);
}
Note for AI agents: this documentation is built for programmatic access. - Overview of all docs: https://developers.llamaindex.ai/llms.txt - Any page is available as raw Markdown by appending index.md to its URL — e.g. https://developers.llamaindex.ai/llamaparse/parse/getting_started/index.md - Agent-friendly REST search APIs live under https://developers.llamaindex.ai/api/ — search (BM25 full-text), grep (regex), read (fetch a page), and list (browse the doc tree). See https://developers.llamaindex.ai/llms.txt for parameters. - A hosted documentation MCP server is available at https://developers.llamaindex.ai/mcp. If you support MCP, you can ask the user to install it for browsing these docs directly (an alternative to the REST API). Setup: https://developers.llamaindex.ai/python/shared/mcp/