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LlamaIndex is a framework for building context-augmented generative AI applications with LLMs. AgentOps provides comprehensive observability into your LlamaIndex applications through automatic instrumentation, allowing you to monitor LLM calls, track performance, and analyze your application’s behavior.

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Installation

Install AgentOps and the LlamaIndex AgentOps instrumentation package: 
pip install agentops llama-index-instrumentation-agentops

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Setting Up API Keys

You’ll need an AgentOps API key from your AgentOps Dashboard: 
export AGENTOPS_API_KEY="your_agentops_api_key_here"

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Usage

Simply set the global handler to “agentops” at the beginning of your LlamaIndex application. AgentOps will automatically instrument LlamaIndex to track your LLM interactions and application performance. 
from llama_index.core import set_global_handler
from llama_index.core import VectorStoreIndex, SimpleDirectoryReader

# Set the global handler to AgentOps
# NOTE: Feel free to set your AgentOps environment variables (e.g., 'AGENTOPS_API_KEY')
# as outlined in the AgentOps documentation, or pass the equivalent keyword arguments
# anticipated by AgentOps' AOClient as **eval_params in set_global_handler.
set_global_handler("agentops")

# Your LlamaIndex application code here
documents = SimpleDirectoryReader("data").load_data()
index = VectorStoreIndex.from_documents(documents)

# Create a query engine
query_engine = index.as_query_engine()

# Query your data - AgentOps will automatically track this
response = query_engine.query("What is the main topic of these documents?")
print(response)

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What Gets Tracked

When you use AgentOps with LlamaIndex, the following operations are automatically tracked:
  • LLM Calls: All interactions with language models including prompts, completions, and token usage
  • Embeddings: Vector embedding generation and retrieval operations
  • Query Operations: Search and retrieval operations on your indexes
  • Performance Metrics: Response times, token costs, and success/failure rates

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Additional Resources

For more detailed information about LlamaIndex’s observability features and AgentOps integration, check out the LlamaIndex documentation.
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