🧠 AI-Powered Chat Summarizer API

An interactive FastAPI-based chat system where users can chat with an AI summarizer assistant that automatically generates summaries of their input — similar to ChatGPT, but focused on summarization.

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🚀 Features

• 👤 User Management (register, login, authentication ready)
• 💬 Chat Interface (each user can create multiple chat sessions)
• 🧾 Message System (user ↔ assistant chat flow)
• 🤖 AI Summarization (integrated Hugging Face transformer model)
• ⚡ Async & Fast (built with FastAPI and PostgreSQL)
• 🔐 JWT Authentication Ready
• 🧱 Modular Architecture (clean folder structure with routes, schemas, models)
• 🐳 Docker Support (for easy deployment)

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🏗️ Project Structure

.
├── .env
├── .gitignore
├── docker-compose.yml
├── Dockerfile
├── README.md
├── requirements.txt
└── src
    ├── init.py
    ├── api.py
    ├── auth
    │ ├── init.py
    │ ├── controller.py
    │ ├── models.py
    │ └── service.py
    ├── database
    │ ├── init.py
    │ └── core.py
    ├── entities
    │ ├── init.py
    │ ├── chats.py
    │ ├── message.py
    │ └── user.py
    ├── exceptions.py
    ├── logging.py
    ├── main.py
    ├── rate_limiter.py
    └── users
      ├── init.py
      ├── controller.py
      ├── models.py
      └── service.py

⚙️ Tech Stack

Layer	Technology
Framework	FastAPI
Database	PostgreSQL
ORM	SQLAlchemy
Model	Hugging Face Transformers (Need to Decide)
Auth (optional)	JWT with PyJWT / FastAPI Users
Deployment	Docker + Uvicorn

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🧩 Database Entities

🧍‍♂️ User Table

Field	Type	Description
id	UUID	Primary Key
email	String	Unique email
first_name	String
last_name	String
password_hash	String
created_at	DateTime

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💬 Chat Table

Field	Type	Description
id	UUID	Primary Key
user_id	UUID (FK → users.id)	User who owns this chat
title	String	Chat title
summary	String	Summary of chat content
created_at	DateTime	Timestamp

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📨 Message Table

Field	Type	Description
id	UUID	Primary Key
chat_id	UUID (FK → chat.id)	Chat reference
sender	Enum('user', 'assistant')	Who sent the message
content	String	Message text
created_at	DateTime	Timestamp

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🧠 How It Works

1. User registers or logs in.
2. User creates a new chat.
3. Each chat contains multiple messages between the user and the AI assistant.
4. When the user sends a message:
   • It’s saved in the database.
   • FastAPI sends the content to a Hugging Face summarization model.
   • The model generates a summary and returns it as the assistant’s reply.
   • Both the user’s message and assistant’s response are stored in the DB.

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🔥 API Endpoints

👤 User Routes

Method	Endpoint	Description	Status
POST	/users/register	Register a new user	Completed
POST	/users/login	Login user and return JWT token (optional)	Completed
GET	/users/me	Get user details	Completed

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💬 Chat Routes

Method	Endpoint	Description	Status
POST	/chats/	Create a new chat	Completed
GET	/chats/{user_id}	Get all chats for a user	Completed
GET	/chats/{chat_id}	Get a single chat with messages	Completed
DELETE	/chats/{chat_id}	Delete a chat (cascade deletes messages)	Completed

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📨 Message Routes

Method	Endpoint	Description
POST	/messages/	Send a message to a chat (user message + AI summarizer reply)
GET	/messages/{chat_id}	Get all messages in a chat

🧰 Setup Instructions

1️⃣ Clone the Repository

git clone https://github.com/dhruvrana8/fastapi-ai-chat-summarizer.git
cd fastapi-ai-chat-summarizer

2️⃣ Create a Virtual Environment

python -m venv venv
source venv/bin/activate  # macOS/Linux
venv\Scripts\activate     # Windows

3️⃣ Install Dependencies

pip install -r requirements.txt

4️⃣ Setup Database

DATABASE_URL=postgresql://user:password@localhost:5432/chat_db

Then create the tables:

python src/database/core.py

5️⃣ Run the App

uvicorn src.main:app --reload