> ## Documentation Index
> Fetch the complete documentation index at: https://phidatainc-studio-tools-doc.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# LlamaIndex Async

## Code

```python cookbook/08_knowledge/vector_db/llamaindex_db/llamaindex_db.py theme={null}
import asyncio
from pathlib import Path
from shutil import rmtree

import httpx
from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.vectordb.llamaindex import LlamaIndexVectorDb
from llama_index.core import (
    SimpleDirectoryReader,
    StorageContext,
    VectorStoreIndex,
)
from llama_index.core.node_parser import SentenceSplitter
from llama_index.core.retrievers import VectorIndexRetriever

data_dir = Path(__file__).parent.parent.parent.joinpath("wip", "data", "paul_graham")
if data_dir.is_dir():
    rmtree(path=data_dir, ignore_errors=True)
data_dir.mkdir(parents=True, exist_ok=True)

url = "https://raw.githubusercontent.com/run-llama/llama_index/main/docs/docs/examples/data/paul_graham/paul_graham_essay.txt"
file_path = data_dir.joinpath("paul_graham_essay.txt")
response = httpx.get(url)
if response.status_code == 200:
    with open(file_path, "wb") as file:
        file.write(response.content)
    print(f"File downloaded and saved as {file_path}")
else:
    print("Failed to download the file")

documents = SimpleDirectoryReader(str(data_dir)).load_data()

splitter = SentenceSplitter(chunk_size=1024)

nodes = splitter.get_nodes_from_documents(documents)

storage_context = StorageContext.from_defaults()

index = VectorStoreIndex(nodes=nodes, storage_context=storage_context)

knowledge_retriever = VectorIndexRetriever(index)

knowledge = Knowledge(
    vector_db=LlamaIndexVectorDb(knowledge_retriever=knowledge_retriever)
)

# Create an agent with the knowledge instance
agent = Agent(
    knowledge=knowledge,
    search_knowledge=True,
    debug_mode=True,
)

if __name__ == "__main__":
    asyncio.run(
        agent.aprint_response(
            "Explain what this text means: low end eats the high end", markdown=True
        )
    )
```

## Usage

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U llama-index-core llama-index-readers-file llama-index-embeddings-openai pypdf openai agno
    ```
  </Step>

  <Step title="Run Agent">
    ```bash theme={null}
    python cookbook/08_knowledge/vector_db/llamaindex_db/llamaindex_db.py
    ```
  </Step>
</Steps>