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(f"Average rating: {run_context.average_rating:.2f}")