LangChain integration - SynapsAI Cloud Docs

LangChain’s OpenAI wrappers work when you point OPENAI_API_BASE to SynapsAI and set the API key. See Migrate from OpenAI for environment variable setup.

Chat models (recommended)

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

from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    model="<YOUR_MODEL_ID>",
    temperature=0.1,
)

response = llm.invoke("Summarize the benefits of short prompt templates.")
print(response.content)

Legacy OpenAI LLM wrapper

Older LangChain versions use langchain_openai.OpenAI for completions-style models:

from langchain_openai import OpenAI

llm = OpenAI(model="<YOUR_MODEL_ID>", temperature=0.1)
print(llm.invoke("Summarize the benefits of short prompt templates."))

If LangChain throws errors about api_base, pass openai_api_base="https://api.synapsai.cloud/v1" directly to the model constructor, or ensure environment variables are set before import.

Embeddings

from langchain_openai import OpenAIEmbeddings

embeddings = OpenAIEmbeddings(model="<YOUR_EMBEDDING_MODEL_ID>")
vector = embeddings.embed_query("SynapsAI Cloud private inference")

See Embeddings + FAISS for a retrieval example. Other frameworks: Integrations. Keep keys on the server.