Documentation

Vector Store API Documentation This document provides instructions on how to interact with the Vector Store API endpoints. All API endpoints are prefixed with `/v1`.

Retrieving Vectors from Vector Store Files Ragwalla now supports retrieving the actual vector embeddings for files in your vector stores. This feature gives you direct access to the processed...

# OpenAI Files API: Complete Guide to Upload, Manage & Delete Files The OpenAI Files API allows you to upload, manage, and delete files for use with Assistants, fine-tuning, and...

OpenAI is shutting down the Assistants API on August 26, 2026. Learn how to migrate to Responses API + Conversations API or use wire-compatible alternatives.

Custom Functions and Secrets Management Guide This guide covers how to create secure custom functions for Ragwalla agents and manage secrets safely. ## Table of Contents - [Overview](#overview) -...

Choosing the right text embedding model is crucial for building effective AI applications like chatbots and retrieval systems. This guide is aimed at developers familiar with OpenAI’s Assistant and highlights how Ragwalla gives you the freedom to select different embedding models – a flexibility not available in the standard OpenAI Assistant.

When using OpenAI Assistants, developers typically must manage their own mapping between file identifiers (file_id), URLs, and titles due to OpenAI's lack of metadata support on files. Ragwalla's Assistants API provides a simple solution by allowing developers to create and manage these mappings easily.

The Ragwalla Assistants API is designed to be fully wire-compatible with OpenAI's Assistants API, providing developers seamless integration through familiar SDKs and interfaces. This guide helps you quickly provision your own unique endpoint and start building intelligent applications.