Auto-Analyst Backend API Documentation

This document is a guide to the backend API endpoints utilized within the Auto-Analyst application. It encompasses a thorough breakdown of various aspects, including the handling of requests, the intricate processes of data transformations, and the structured responses that the API generates.

The Auto-Analyst application is designed to facilitate seamless interactions and efficient data management, making it essential for users to understand the available endpoints and their functionalities. Each section of this documentation is crafted to provide clarity and insight into how the API operates, ensuring that developers and users alike can effectively leverage its capabilities.

For more specific details regarding the various functionalities offered by the API, please refer to the following sections, which delve deeper into their respective areas:

📚 Core Documentation

Getting Started Guide: Quick start guide for new developers and LLMs to understand the system architecture and get up to speed quickly
System Architecture: Comprehensive overview of the backend system design, components, and data flow patterns
Troubleshooting Guide: Common issues, debugging tools, and solutions for development and deployment problems

🛠️ API Reference

Core Endpoints: Review the core endpoints that handle fundamental operations within the application, including data uploads, AI analysis, model settings, and session management.
Analytics Endpoints: Explore the endpoints dedicated to analytics, providing insights into usage statistics, performance metrics, cost analysis, and real-time monitoring.
Chat Endpoints: Discover the endpoints that manage chat interactions, enabling users to create, retrieve, and manage chat sessions effectively.
Code Endpoints: Learn about the endpoints for code execution, editing, fixing, and cleaning operations with advanced AI assistance.
Deep Analysis Endpoints: Comprehensive documentation for the multi-agent deep analysis system, including streaming progress, report management, template integration, and how user's active agents are leveraged for advanced analytical insights.
Feedback Endpoints: Understand the endpoints for managing user feedback on AI-generated messages, including rating systems and model performance tracking.
Templates Endpoints: Comprehensive guide to the template system, agent loading, user preferences, and how personalized AI agent configurations work for different users.