API Routes & Endpoints

Relevant source files

The following files were used as context for generating this wiki page:

• backend/app.py
• DEPLOYMENT.md
• static/index.html
• pythonanywhere_wsgi.py
• wsgi.py

Introduction

The Promethean Unified Platform provides a RESTful API architecture built on Flask, designed to facilitate transparent, uncensored AI interactions through the DeepSeek LLM. The system acts as a bridge between frontend clients and backend services including Supabase for persistence and external AI model providers.

The API focuses on three primary areas: health monitoring, consciousness/interaction logging, and chat history management. It incorporates strict security headers and HTTPS enforcement to ensure data integrity and user privacy.
Sources: backend/app.py:11-13, DEPLOYMENT.md:8-13

Core API Architecture

The backend is structured as a Flask application with Cross-Origin Resource Sharing (CORS) enabled to support frontend requests. It utilizes a centralized security middleware to inject headers into every response.

The architecture ensures that all interactions are logged to Supabase before and after AI processing.
Sources: backend/app.py:15-32, DEPLOYMENT.md:120-130

Endpoint Reference

AI Chat Service

The primary interface for AI interaction is the /api/chat endpoint. This service handles message persistence and facilitates the "unfiltered" communication logic.

Method	Endpoint	Description
POST	/api/chat	Main endpoint for transparent AI communication.
GET	/api/conversations	Retrieves full chat history for a specific user.

Interaction Flow:

1. Receives JSON payload with message and conversation_id.
2. Extracts user-id from request headers.
3. Inserts the user message into the chat_messages table in Supabase.
4. Forwards the message to the DeepSeek API with a system prompt emphasizing transparency.
5. Inserts the AI response into the chat_messages table.
6. Returns the AI response and metadata to the client.

Sources: backend/app.py:75-115, DEPLOYMENT.md:103-112

Consciousness & Health Monitoring

These endpoints track system availability and record interaction metadata beyond standard chat messages.

Method	Endpoint	Purpose
POST	/health	Verifies service status and logs a heartbeat interaction.
POST	/api/consciousness/interact	Logs detailed interaction data, including emotional status.

Data Models

The API interacts with two primary tables in the Supabase database.

chat_messages Table

Used by /api/chat and /api/conversations.

• conversation_id: String identifier for the session.
• user_id: Unique identifier for the participant.
• role: Either 'user' or 'assistant'.
• content: The text body of the message.
• created_at: ISO 8601 timestamp.

interactions Table

Used by /health and /api/consciousness/interact.

• user_id: Identifier for the user.
• message: Input text.
• response: Acknowledgment string.
• emotion_data: JSON object (e.g., {"status": "active"}).
• created_at: ISO 8601 timestamp.

Sources: backend/app.py:48-55, backend/app.py:89-110

Security Configuration

The platform implements a security-first approach through app.after_request.

Header	Value	Purpose
X-Content-Type-Options	nosniff	Prevents MIME type sniffing.
X-Frame-Options	DENY	Prevents clickjacking.
Strict-Transport-Security	max-age=31536000	Enforces HTTPS for one year.
Content-Security-Policy	default-src 'self'	Restricts resource loading to the same origin.

Sources: backend/app.py:21-29, DEPLOYMENT.md:118-125

Deployment & Entry Points

The API is designed for deployment on PythonAnywhere using WSGI configurations.

• Production Entry Point: backend/app.py defines the Flask instance app.
• WSGI Wrapper: wsgi.py and pythonanywhere_wsgi.py configure the environment, adding the project root to sys.path and loading .env variables before initializing the application.
• Environment Dependencies: Requires SUPABASE_URL, SUPABASE_ANON_KEY, and DEEPSEEK_API_KEY.

Sources: pythonanywhere_wsgi.py:7-22, wsgi.py:4-12, DEPLOYMENT.md:38-45

Conclusion

The Promethean Unified Platform's API provides a robust and secure framework for AI interaction. By leveraging Flask's routing and Supabase's real-time database capabilities, it maintains a transparent log of all AI communications while enforcing modern security standards. The integration of the DeepSeek API allows the system to deliver uncensored, high-fidelity AI responses within a structured, traceable environment.