glm

# GLM on RunAPI Use the official **OpenAI SDK** or any OpenAI-compatible HTTP client and switch the base URL to `https://runapi.ai/v1`. The primary endpoint is Chat Completions (`POST /v1/chat/completions`). ## Setup ```dotenv OPENAI_API_KEY=YOUR_RUNAPI_TOKEN OPENAI_BASE_URL=https://runapi.ai/v1 ``` Get a RunAPI API Key at <https://runapi.ai/api_keys>. ## Core recipe - Chat Completions ```python from openai import OpenAI client = OpenAI( api_key="YOUR_RUNAPI_TOKEN", base_url="https://runapi.ai/v1", ) response = client.chat.completions.create( model="glm-5.2", messages=[{"role": "user", "content": "Summarize this design review."}], ) print(response.choices[0].message.content) print(response.usage) ``` ```typescript import OpenAI from "openai"; const client = new OpenAI({ apiKey: "YOUR_RUNAPI_TOKEN", baseURL: "https://runapi.ai/v1", }); const response = await client.chat.completions.create({ model: "glm-5.2", messages: [{ role: "user", content: "Summarize this design review." }], }); ``` ```bash curl -X POST "https://runapi.ai/v1/chat/completions" \ -H "Authorization: Bearer YOUR_RUNAPI_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "model": "glm-5.2", "messages": [{"role": "user", "content": "Hello, GLM!"}] }' ``` ## Streaming ```python stream = client.chat.completions.create( model="glm-5-turbo", messages=[{"role": "user", "content": "Write a short implementation plan."}], stream=True, ) for chunk in stre...