LlamaIndex

Installation

pip install agentlens-observe llama-index

Setup

import agentlens
from agentlens.integrations.llamaindex import AgentLensCallbackHandler
from llama_index.core import Settings
from llama_index.core.callbacks import CallbackManager

agentlens.configure(server_url="http://localhost:3000")

handler = AgentLensCallbackHandler()
Settings.callback_manager = CallbackManager([handler])

Set Settings.callback_manager once at startup — all LlamaIndex operations inherit it automatically.

Usage with Query Engine

from llama_index.core import VectorStoreIndex, SimpleDirectoryReader

documents = SimpleDirectoryReader("./data").load_data()
index = VectorStoreIndex.from_documents(documents)
query_engine = index.as_query_engine()

# Query is automatically traced
response = query_engine.query("What are the main topics in these documents?")

Usage with Agent

from llama_index.core.agent import ReActAgent
from llama_index.core.tools import FunctionTool

def search_web(query: str) -> str:
    """Search the web for information."""
    return f"Results for: {query}"

search_tool = FunctionTool.from_defaults(fn=search_web)
agent = ReActAgent.from_tools([search_tool], verbose=True)

# Agent runs are automatically traced
response = agent.chat("Find the latest news about AI")

What Gets Traced

• Query engine retrieval steps
• LLM calls with prompts and responses
• Tool invocations by agents
• Re-ranking and post-processing steps
• Embedding calls