Pink Programming Chatbot (Flask + Neo4j)

Overview

• Flask web app scaffold for a chatbot that stores users, chats, and messages in Neo4j.
• Participants complete the Cypher TODOs in db.py to enable user auth, chat creation, and viewing history.
• OpenAI is used to generate assistant replies; reads config from environment variables.

Quick Start

• Python 3.9+
• Install dependencies:
  • uv: uv sync
• Copy .env.example to .env and set values.
• Run: python app.py

Environment Variables

• NEO4J_CONNECTION_URI: Neo4j Connection URI (copy from your Aura instance).
• NEO4J_USERNAME / NEO4J_PASSWORD: (default username: neo4j, paste password that you get during the instance creation).
• OPENAI_API_KEY: API key for OpenAI
• OPENAI_BASE_URL: https://api.openai.com/v1 (no need to change)

Workshop Tasks (Cypher TODOs in db.py)

• Create an account on https://console-preview.neo4j.io/ and create a free Aura instance.
• Create/Login User
  • create_user(username, password_hash): create a :User with properties and return it.
  • fetch_user_by_username(username): find a :User by username and return it.
• Chat With Chatbot
  • create_chat_and_first_message(user_id, message): create a :Chat and the first user :Message.
  • create_message(chat_id, role, content): append messages (both user and assistant) to a chat.
• See Previous Chats
  • list_user_chats(user_id): gat all chats for the user, return summary list.
  • fetch_chat(chat_id): return full chat with messages ordered by time.

Pages

• /register and /login: basic authentication using Flask sessions.
• /chat/new: start a new chat by sending the first message.
• /chats: list previous chats.
• /chats/<chat_id>: view and continue a chat.

Safety and Dev Tips

• Do not commit secrets. Use .env locally.
• Hash passwords; never store plain text. We use werkzeug.security.
• For production, set a strong FLASK_SECRET_KEY and configure HTTPS.