LlamaIndex

from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, Settings
from llama_index.embeddings.openai import OpenAIEmbedding
from llama_index.llms.openai import OpenAI
 
Settings.llm = OpenAI(model="gpt-4o-mini")
Settings.embed_model = OpenAIEmbedding(model="text-embedding-3-small")
index = VectorStoreIndex.from_documents(documents)
query_engine = index.as_query_engine()
response = query_engine.query("What is pytest?")

"""llamaindex.py - construir índice y consultar."""
from llama_index.core import Document, VectorStoreIndex, Settings
from llama_index.embeddings.openai import OpenAIEmbedding
from llama_index.llms.openai import OpenAI as LlamaOpenAI
 
Settings.llm = LlamaOpenAI(model="gpt-4o-mini", temperature=0)
Settings.embed_model = OpenAIEmbedding(model="text-embedding-3-small")
 
documents = [
    Document(text="pytest uses fixtures to share test setup.", metadata={"source": "testing"}),
    Document(text="FastAPI validates request bodies with Pydantic.", metadata={"source": "web"}),
]
index = VectorStoreIndex.from_documents(documents)
engine = index.as_query_engine(similarity_top_k=2)
response = engine.query("How do pytest fixtures work?")
print(response)
print("sources:", [n.metadata for n in response.source_nodes])