OpenAI Assistants Template

Implements real-time streaming of OpenAI Assistant responses to the frontend using Next.js API routes as middleware. The Chat component (app/components/chat.tsx) manages streaming state, processes incoming message chunks, and renders content progressively as it arrives from the OpenAI Assistants API. Uses React state management to accumulate streamed tokens and update the UI incrementally without blocking user interaction.

Coordinates three distinct OpenAI assistant tools (code interpreter, file search, and function calling) within a single assistant configuration. The /api/assistants POST endpoint creates an assistant with all tools enabled, and the Chat component processes tool-use responses by detecting tool calls, executing them, and submitting results back via the /api/assistants/threads/[threadId]/actions endpoint. Implements a request-response loop where the assistant can invoke tools, receive results, and continue reasoning.

Provides a File Viewer component (app/components/file-viewer.tsx) that manages the complete file lifecycle for file search: displaying a file upload interface, listing currently uploaded files with metadata, and enabling file deletion. The component calls the /api/assistants/files endpoint to perform CRUD operations on files associated with the assistant. It integrates with the file search capability, allowing users to upload documents that the assistant can then search semantically in response to queries.

Manages OpenAI conversation threads as persistent containers for multi-turn conversations. The /api/assistants/threads POST endpoint creates new threads, and subsequent messages are sent to specific thread IDs via /api/assistants/threads/[threadId]/messages. The Chat component maintains thread state and handles the full conversation lifecycle: thread creation, message appending, streaming responses, and function call handling within the same thread context. Thread IDs are preserved across page reloads, enabling conversation persistence.

Implements a request-response loop for function calling where the assistant generates function call requests with parameters, the Chat component detects these calls, executes them client-side, and submits results back to the assistant via /api/assistants/threads/[threadId]/actions. Functions are defined with JSON schemas that the assistant understands, and the component processes tool_calls from assistant messages, maps them to local function implementations, and handles both successful execution and error cases.

Enables file upload management and semantic search over uploaded documents using OpenAI's file search tool. The /api/assistants/files endpoint handles GET (list files), POST (upload new files), and DELETE (remove files) operations. Uploaded files are associated with the assistant and indexed for semantic search. The File Viewer component (app/components/file-viewer.tsx) provides UI for file management, and the assistant can search across uploaded files in response to user queries, returning results with file citations.

Provides a factory pattern for creating and configuring OpenAI assistants with specific tools, models, and system instructions. The /api/assistants POST endpoint creates an assistant with code interpreter and file search tools enabled, configurable system instructions, and a specified model (defaults to gpt-4-turbo). The openai.ts module initializes the OpenAI client, and the assistant configuration is reused across all example pages, demonstrating a single-assistant-multiple-examples pattern.

Handles progressive rendering of different message content types (text, code blocks, images, citations) as they stream in from the assistant. The Chat component uses React state to accumulate streamed content and renders it with appropriate formatting: text via React Markdown (v9.0.1), code blocks with syntax highlighting, images as embedded URLs, and file citations with links. The message rendering logic detects content type and applies the correct renderer, supporting mixed content within a single message.

Implements a middleware layer using Next.js API routes that abstracts OpenAI Assistants API complexity from the frontend. Each API route (/api/assistants/*, /api/files/*) handles a specific operation: assistant creation, thread management, message sending, function call submission, and file operations. Routes use the OpenAI Node.js SDK to communicate with OpenAI's API and return structured responses to the frontend, enabling the Chat component to work with high-level abstractions rather than raw API calls.

Provides isolated example pages (/examples/basic-chat, /examples/function-calling, /examples/file-search, /examples/all) that demonstrate each assistant capability independently while sharing the same underlying assistant configuration. Each example page is a self-contained Next.js page that imports the Chat component and shows how to use a specific feature. This pattern enables developers to understand each capability in isolation before combining them, and serves as reference implementations for common use cases.

Implements a reusable Chat component (app/components/chat.tsx) that encapsulates all conversation logic: message state management, streaming response handling, function call processing, and UI rendering. The component accepts configuration props (assistant ID, thread ID) and manages the full conversation lifecycle internally. It renders messages with appropriate formatting, displays loading states during streaming, handles user input, and processes assistant tool calls. The component is imported by all example pages, demonstrating composition and reusability.