LlamaIndex integration - SynapsAI Cloud Docs

Use SynapsAI Cloud for both LLM and embedding calls in LlamaIndex by configuring OpenAI-compatible settings.

Environment setup

export OPENAI_API_KEY="$SYNAPSAI_API_KEY"
export OPENAI_API_BASE="https://api.synapsai.cloud/v1"

Chat + retrieval example

from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, Settings
from llama_index.llms.openai import OpenAI
from llama_index.embeddings.openai import OpenAIEmbedding

Settings.llm = OpenAI(model="<YOUR_MODEL_ID>", temperature=0.2)
Settings.embed_model = OpenAIEmbedding(model="<YOUR_EMBEDDING_MODEL_ID>")

documents = SimpleDirectoryReader("example_docs/").load_data()
index = VectorStoreIndex.from_documents(documents)

query_engine = index.as_query_engine()
response = query_engine.query("What are the core steps to deploy a model?")
print(response)

Install current LlamaIndex packages: pip install llama-index llama-index-llms-openai llama-index-embeddings-openai

Managed knowledge bases (OpenAI vector_stores) are a separate product — Knowledge bases. Lower-level local retrieval: Embeddings + FAISS. Hub: Integrations.