{"id":4995,"library":"openai-chatkit","title":"OpenAI ChatKit (Python SDK)","description":"OpenAI ChatKit is a Python SDK designed for building custom backend servers for OpenAI's ChatKit, enabling developers to integrate advanced AI-powered chat experiences into their applications. It is a key component of the broader OpenAI AgentKit suite, facilitating the creation of conversational AI agents with features like response streaming, tool invocation, and thread management. The library is currently at version 1.6.3 and is actively maintained, with recent updates suggesting ongoing development and integration with OpenAI's evolving agent capabilities.","status":"active","version":"1.6.3","language":"en","source_language":"en","source_url":"https://github.com/openai/chatkit-python","tags":["AI","chatbot","OpenAI","SDK","backend","agent","chatkit"],"install":[{"cmd":"pip install openai-chatkit","lang":"bash","label":"Install `openai-chatkit`"}],"dependencies":[{"reason":"Required for interacting with OpenAI APIs to create ChatKit sessions and power AI agents.","package":"openai","optional":false},{"reason":"Commonly used web framework for building the backend endpoint that hosts the ChatKit server.","package":"fastapi","optional":true}],"imports":[{"symbol":"ChatKitServer","correct":"from openai_chatkit.server import ChatKitServer"},{"note":"While examples might implicitly refer to agents, the primary `Agent` class for defining AI logic is part of the main `openai` library's `lib.chatkit` subpackage.","wrong":"from openai_chatkit.agents import Agent","symbol":"Agent","correct":"from openai.lib.chatkit import Agent"},{"note":"Session creation is handled through the `beta.chatkit.sessions` client object of the main `openai` library, not directly from `openai-chatkit`.","wrong":"from openai_chatkit.sessions import create","symbol":"sessions.create","correct":"client.beta.chatkit.sessions.create(...)"}],"quickstart":{"code":"import os\nfrom fastapi import FastAPI, Request\nfrom openai import OpenAI\nfrom openai_chatkit.server import ChatKitServer, UserMessageItem\nfrom openai.lib.chatkit import Agent\n\napp = FastAPI()\nopenai_client = OpenAI(api_key=os.environ.get('OPENAI_API_KEY', ''))\n\n# Define your AI agent\nassistant_agent = Agent(\n    model=\"gpt-4o\",\n    name=\"Assistant\",\n    instructions=\"You are a helpful assistant.\"\n)\n\n# Implement your ChatKit server\nclass MyChatKitServer(ChatKitServer):\n    def __init__(self):\n        super().__init__()\n        self.agent = assistant_agent\n\n    async def respond(\n        self, thread_id: str, input: UserMessageItem, request: Request\n    ):\n        # Example: Process user input with your agent\n        # In a real application, you would manage state and agent context here\n        response_content = f\"Echoing: {input.text}\"\n        yield {\"type\": \"text\", \"text\": response_content}\n\nchatkit_server = MyChatKitServer()\n\n@app.post(\"/api/chatkit/session\")\nasync def create_chat_session(request: Request):\n    # In a real app, authenticate the user and provide a unique user_id\n    user_id = \"user_123\"\n    # Workflow ID would come from your OpenAI Agent Builder workflow\n    workflow_id = os.environ.get('CHATKIT_WORKFLOW_ID', 'wf-YOUR_WORKFLOW_ID')\n\n    # The client secret should be generated on the server-side only\n    session = openai_client.beta.chatkit.sessions.create(\n        workflow_id=workflow_id,\n        user_id=user_id\n    )\n    return {\"client_secret\": session.client_secret}\n\n@app.post(\"/api/chatkit/respond\")\nasync def chatkit_respond(request: Request):\n    return await chatkit_server.handle_request(request)","lang":"python","description":"This quickstart demonstrates setting up a basic FastAPI backend that uses `openai-chatkit` to handle chat interactions. It includes creating a ChatKit session (which provides a client secret for frontend authentication) and a response endpoint where your defined AI agent processes user messages. Remember to replace placeholder IDs and ensure your `OPENAI_API_KEY` and `CHATKIT_WORKFLOW_ID` are set as environment variables. A frontend (e.g., using `@openai/chatkit-react`) would then connect to these endpoints."},"warnings":[{"fix":"Stay updated with official OpenAI documentation and GitHub releases. Regularly test your integration when updating library versions. Consider pinning exact versions in production to avoid unexpected breakage.","message":"The `openai-chatkit` library is currently in beta, and the broader ChatKit and AgentKit ecosystem is evolving rapidly. This means there is a higher likelihood of breaking changes and API adjustments between versions, potentially leading to 'Dependency and Versioning Issues'.","severity":"breaking","affected_versions":"All versions (beta status)"},{"fix":"Implement a dedicated backend endpoint (e.g., with FastAPI) to handle the creation of ChatKit sessions and generation of `client_secret`s. Your frontend should only ever receive and use this short-lived `client_secret`.","message":"Never expose your raw OpenAI API key on the client-side. The `openai-chatkit` Python SDK is for backend use, where your server securely generates a short-lived `client_secret` using the main `openai` library's `beta.chatkit.sessions.create` method. This `client_secret` is then safely passed to your frontend ChatKit component for authentication.","severity":"gotcha","affected_versions":"All versions"},{"fix":"Ensure that all domains (including `localhost` for development and your production domains) where ChatKit is embedded are added to the 'Domain Allowlist' in your OpenAI organization settings. Session creation can succeed even if the domain is not allowed, leading to confusing debugging.","message":"A common 'blank screen' issue on the frontend occurs if the domain where ChatKit is embedded is not explicitly added to the allowlist in your OpenAI organization settings. This is a critical security feature to prevent unauthorized usage.","severity":"gotcha","affected_versions":"All versions"},{"fix":"Plan for both a backend implementation using `openai-chatkit` and a compatible frontend integration. The quickstart example above only covers the backend part.","message":"The `openai-chatkit` Python SDK is a *backend* library. It does not provide a user interface. You will need a separate frontend component (e.g., `@openai/chatkit-react` for React applications or the ChatKit JS web component) to display the chat interface and interact with your `openai-chatkit` backend.","severity":"gotcha","affected_versions":"All versions"},{"fix":"Monitor your OpenAI API usage and set budgets. Design agents to be efficient with token usage. Consider implementing rate limiting or usage caps if cost control is a primary concern.","message":"Costs for ChatKit solutions can be unpredictable, as they are directly tied to OpenAI API usage (token consumption) by your AI agents. This can fluctuate significantly based on user interaction complexity and volume.","severity":"gotcha","affected_versions":"All versions"},{"fix":"When starting a new project, refer directly to the latest official documentation and quickstart guides for the `openai-chatkit` Python SDK rather than relying on older starter app repositories which may not be actively maintained or compatible with current API versions. If using a starter app, verify its currency and compatibility.","message":"There have been reports (as of February 2026) that the official OpenAI ChatKit Starter App repositories experienced issues, specifically returning 404 errors, indicating potential changes or deprecations in how starter templates are meant to be used or deployed.","severity":"deprecated","affected_versions":"Likely recent versions, potentially from late 2025 onwards."}],"env_vars":null,"last_verified":"2026-04-12T00:00:00.000Z","next_check":"2026-07-11T00:00:00.000Z"}