LlamaIndex

pip install agentx-python llama-index llama-index-llms-openai

from agentx import AgentX
from llama_index.core import VectorStoreIndex, SimpleDirectoryReader
from llama_index.llms.openai import OpenAI

client = AgentX.from_env()

documents = SimpleDirectoryReader("./docs").load_data()
index = VectorStoreIndex.from_documents(documents)
query_engine = index.as_query_engine(llm=OpenAI(model="gpt-4o-mini"))

def llamaindex_agent(case):
    response = query_engine.query(case.query)
    return {"output": str(response), "metadata": {"model": "gpt-4o-mini"}}

run_context = (
    client.evaluations
    .run(dataset_id="...", subject={"kind": "custom_agent", "displayName": "Docs RAG Agent", "framework": "llamaindex"})
    .execute(llamaindex_agent)
    .finalize()
)
print("Average rating:", run_context.average_rating)

def llamaindex_agent(case):
    response = query_engine.query(case.query)
    return {
        "output": str(response),
        "metadata": {"model": "gpt-4o-mini"},
        "retrieval_context": [node.get_content() for node in response.source_nodes],
    }