Compatible (BYOK)

Use LangChain with GlideflowAI.

An application framework for composing model calls, tools, and retrieval workflows. Connect it through GlideflowAI's OpenAI-compatible API with a key you control.

Get a key

What this connection is for

LangChain is an application framework for composing model calls with prompts, retrieval, tools, and surrounding application logic. It is aimed at developers whose LLM feature is becoming a workflow rather than a single request. The framework can help keep provider configuration separate from chains and application orchestration when a product needs multiple steps or reusable components.

Choose LangChain when you need its abstractions for retrieval, tools, runnable composition, or tracing in an application you own. It can be unnecessary overhead for a one-request script, where the OpenAI SDK is often easier to reason about. Treat provider swaps carefully: test the concrete chain, tool behavior, and prompt output rather than assuming every compatible endpoint behaves identically.

LangChain documents custom base URLs for OpenAI Chat Completions-compatible providers. Initialize the OpenAI model integration with GlideflowAI's /v1 URL and server-side key, then pass an exact catalog ID into the chain you want to evaluate. Keep that model construction in one module so chains cannot accidentally drift to different provider settings. LangChain is an independent project; this is a user-managed connection, not an endorsement or partnership.

Why pair it with GlideflowAI

LangChain can keep its chain and retrieval composition intact while the ChatOpenAI-compatible model points at GlideflowAI.

That separation is useful when you want to test a model change on the same prompt pipeline instead of rebuilding the application's orchestration.

Setup

Use a new API key for the tool, select a model from the catalog, and begin with a small task. Do not put a key in a repository, screenshot, or shared configuration file.

1
Keep the key in the runtime environment
Set a private environment variable for the application process.
```
export GLIDEFLOW_API_KEY="sk-your-key"
```

Initialize an OpenAI-compatible chat model

Use LangChain's OpenAI model integration with the custom base_url parameter.

from langchain.chat_models import init_chat_model

model = init_chat_model(
    model="glm-5.2", model_provider="openai",
    base_url="https://api.glideflowai.com/v1",
    api_key=os.environ["GLIDEFLOW_API_KEY"],
)

Need the endpoint basics? Read authentication, browse the model catalog, or compare pricing.

Frequently asked questions

Which LangChain parameter sets the compatible endpoint?

Use base_url for the OpenAI chat model integration or init_chat_model setup, with https://api.glideflowai.com/v1 as the value.

Should I use a provider-specific LangChain package?

Use the standard OpenAI-compatible integration for GlideflowAI; select a dedicated package only when your chosen provider requires its own nonstandard request behavior.

How should I evaluate a model swap in a chain?

Run the same representative inputs through retrieval, tools, and final response steps, because a successful simple chat request does not validate the entire chain.

Is this an official integration?

No. The connection is configured by you using a compatible API and does not imply sponsorship, endorsement, or a partnership.

Ready to connect LangChain?

Create a key, use the setup above, and verify the connection on a small task before you scale it up.