Integration

Integration guide for connecting MariaDB AI RAG to external applications, with Python REST API examples for authentication, document upload, chunking, and middleware setup.

External Systems

MariaDB AI RAG can be integrated with external systems through its REST API. Common integration patterns include:

• Document Management Systems: Automatically ingest documents from DMS platforms using the document ingestion endpoints

• Knowledge Bases: Enhance existing knowledge bases with AI-powered search via the retrieval endpoints

• Customer Support Systems: Integrate with ticketing systems for AI-assisted responses using the orchestration pipeline

• Business Intelligence Tools: Connect BI tools for natural language querying of data through the API

Example integration with a document management system:

import requests
import json

# Authenticate
auth_response = requests.post(
    "http://localhost:8000/token",
    data={"username": "[e-mail]", "password": "secure_password"}
)
token = auth_response.json()["access_token"]

# Upload document
with open("document.pdf", "rb") as f:
    files = {"file": ("document.pdf", f, "application/pdf")}
    headers = {"Authorization": f"Bearer {token}"}
    response = requests.post(
        "http://localhost:8000/documents/ingest",
        files=files,
        headers=headers
    )

document_id = response.json()["id"]

# Process document
chunking_response = requests.post(
    "http://localhost:8000/chunks/document",
    json={"document_id": document_id},
    headers={"Authorization": f"Bearer {token}"}
)

Authentication Integration

MariaDB AI RAG uses JWT-based authentication. The system can be integrated with existing authentication systems by implementing custom authentication middleware.

# JWT Authentication settings
SECRET_KEY=your_secure_random_string
ACCESS_TOKEN_EXPIRE_MINUTES=60

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