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A SynapsAI deployment id is a drop-in model for OpenAI-shaped chat, completions, embeddings, images, audio, and vector stores. Use these guides to put that deployment in an app you already run.

Connection settings

model / deployment arguments must be the id from Models, not a public OpenAI or Hub name.

Choose a path

LangChain

ChatOpenAI and OpenAIEmbeddings against your deployment.

LlamaIndex

LLM + embeddings settings for indexes and query engines.

Embeddings + FAISS

Embed on SynapsAI, retrieve locally with FAISS.

Gradio / FastAPI

Keep the API key on the server; proxy from a UI or API.

Migrate from OpenAI

Environment variables, endpoint map, and differences (agents, custom containers, error types).

Minimal REST check

If this works, your OpenAI or LangChain client should too. More bodies: Examples. Agents and knowledge bases use SynapsAI routes (/v1/agent/..., /v1/vector_stores) — call those from your backend, not from browser bundles.

Production notes

  • Retry 429 with exponential backoff — Rate limits.
  • Scope keys per app — API keys.
  • Never ship keys in client-side code — Security.