LangChain and LangGraph

ChatOpenAI can point to Internalize's compatible endpoint. Set use_responses_api=False so the integration uses Chat Completions.

pip install langchain-openai

import os
from langchain_openai import ChatOpenAI

model = ChatOpenAI(
    model="glm-5.3",
    base_url="https://convergingthought.com/v1",
    api_key=os.environ["INTERNALIZE_API_KEY"],
    use_responses_api=False,
    max_retries=0,
)
print(model.invoke("Hello!").content)

Use this model in your existing LangGraph agent or node. Internalize supplies inference and learning; your graph continues to own tools, conversation state, checkpoints, and application logic.

Route to a subjectCopy Anchor Link

For a model instance scoped to an authorized tenant, pass default_headers={"X-Internalize-Subject": subject_id} to ChatOpenAI. Resolve that ID from your application's authenticated identity, not a model-produced argument. Create a per-subject instance or use a request-scoped configuration; do not change headers on a shared instance during concurrent execution.

Without this header or a subject_id extra body field, inference explicitly uses base weights. A subject request resolves the active version when it is admitted. Running requests retain that immutable version.

Tool messagesCopy Anchor Link

Use ordinary bind_tools function tools. Keep AIMessage.tool_calls and matching ToolMessage IDs in the conversation, and return all tool results before the next model call. The gateway rejects missing, duplicate, and unknown tool results.

If you expose learning, bind the subject in a server-side handler. Persist the graph run's tool operation identity as the idempotency key. A graph checkpoint can restore the same job receipt rather than submit a replacement call after a process restart.

Bound the integrationCopy Anchor Link

Set retries to zero until your graph has explicit job recovery. Streams are buffered until final validation. Avoid strict structured-output helpers that request json_schema, unsupported multimodal content, or Responses-specific settings. An unknown field returns 422 rather than being ignored.

Learning is asynchronous and may exceed a web handler's lifetime. For long operations, store the job ID in graph state and resume observation from durable work. Check activated before assuming future calls can use the learned version.

See LangChain's official OpenAI integration and polling and recovery.