skills/run-llama/vibe-llama/Retrieve relevant information through RAG

Retrieve relevant information through RAG

SKILL.md

Information Retrieval

Quick start

You can create an index on LlamaCloud using the following code. By default, new indexes use managed embeddings (OpenAI text-embedding-3-small, 1536 dimensions, 1 credit/page):

import os

from llama_index.core import SimpleDirectoryReader
from llama_cloud_services import LlamaCloudIndex

# create a new index (uses managed embeddings by default)
index = LlamaCloudIndex.from_documents(
    documents,
    "my_first_index",
    project_name="default",
    api_key="llx-...",
    verbose=True,
)

# connect to an existing index
index = LlamaCloudIndex("my_first_index", project_name="default")

You can also configure a retriever for managed retrieval:

# from the existing index
index.as_retriever()

# from scratch
from llama_cloud_services import LlamaCloudRetriever

retriever = LlamaCloudRetriever("my_first_index", project_name="default")

# perform retrieval
result = retriever.retrieve("What is the capital of France?")

And of course, you can use other index shortcuts to get use out of your new managed index:

query_engine = index.as_query_engine(llm=llm)

# perform retrieval and generation
result = query_engine.query("What is the capital of France?")

Retriever Settings

A full list of retriever settings/kwargs is below:

  • dense_similarity_top_k: Optional[int] -- If greater than 0, retrieve k nodes using dense retrieval
  • sparse_similarity_top_k: Optional[int] -- If greater than 0, retrieve k nodes using sparse retrieval
  • enable_reranking: Optional[bool] -- Whether to enable reranking or not. Sacrifices some speed for accuracy
  • rerank_top_n: Optional[int] -- The number of nodes to return after reranking initial retrieval results
  • alpha Optional[float] -- The weighting between dense and sparse retrieval. 1 = Full dense retrieval, 0 = Full sparse retrieval.

Requirements

The llama_cloud_services and llama-index-core packages must be installed in your environment:

pip install llama-index-core llama_cloud_services

And the LLAMA_CLOUD_API_KEY must be available as an environment variable:

export LLAMA_CLOUD_API_KEY="..."
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