LLM.txt

What is LLM.txt?

llm.txt is a plain text file at the root of your server that describes:

• What the server does
• Available API endpoints
• How to authenticate
• Example requests

AI assistants and tools can read this file to understand how to interact with your IntelligenceBox.

Where to host it

By convention, an llm.txt file lives at the root of the server:

GET /llm.txt

IntelligenceBox does not generate or serve this file for you -- copy the summary below into a file your server hosts at that path (no authentication required), or paste it straight into your agent's context.

Example

If you host the file at the path above, agents can fetch it directly:

curl https://your-box-server/llm.txt

Recommended summary

Keep this in sync with the public API whenever endpoints change:

# IntelligenceBox API

Private AI server for chat and document search.

## Authentication
All requests require an API key header:
x-api-key: YOUR_API_KEY

## Endpoints

### Chat
POST /api/ai/chat
Send messages and receive streaming AI responses.

Request:
{
  "id": "unique-chat-id",
  "messages": [{"role": "user", "content": "Hello"}],
  "boxAddress": "https://your-server",
  "assistantId": "optional-assistant-id",
  "vector": ["optional-folder-ids"]
}

### List Folders
GET /api/public/vectors
Returns available document folders for RAG.

### Upload File
POST /api/public/vectors/:id/files
Upload a document (multipart/form-data, field "file") into a folder for RAG ingestion.
List/replace/delete via /api/public/vectors/:id/files[/:fileId]; download bytes via /api/public/vectors/:id/files/:fileId/content.

### List Assistants
GET /api/public/assistants
Returns available AI assistants.

## More Info
https://intelligencebox.it/docs

Why Use LLM.txt?

The llm.txt file bridges the gap between traditional API documentation and the way modern AI agents consume information. Unlike OpenAPI specs or HTML docs, it is designed to be lightweight and immediately parsable by language models without requiring a specialized client library.

• AI Tools: Tools like Claude, ChatGPT plugins, and autonomous agents can discover your API endpoints, authentication requirements, and request formats automatically.
• Documentation: The file doubles as a human-readable summary of your API, making it useful for developers who want a quick overview without navigating full documentation.
• Standardized: As adoption grows, llm.txt is becoming the de facto standard for AI-to-API discovery, similar to how robots.txt became the standard for search engine crawlers.
• Team-maintained: The IntelligenceBox team keeps this recommended summary in sync with the public API. Copy it into your own llm.txt or your agent's context, and re-check it when the API changes.

Integration Tips

If you are building an AI agent or tool that needs to interact with an IntelligenceBox instance, feed the summary above (or the llm.txt file, if the server hosts one) into your agent's system prompt or context window so the model understands which endpoints are available and how to authenticate. This approach lets your agent adapt to an IntelligenceBox server without hardcoded endpoint URLs.