<div style="text-align: left; margin-bottom: 20px;">
<img src="https://kiss-ai-stack.github.io/kissaistack.svg" alt="KISS AI Stack Banner" style="max-width: auto; height: 250px">
</div>
# KISS AI Stack - Server
The KISS AI Stack Server is an server stub designed to support RESTful and WebSocket APIs for handling AI-agent sessions with kiss-ai-stack-core tasks like agent lifecycle management, query execution, and document storage.
## Features
- REST API for authentication, session actions, queries, and document storage.
- WebSocket API for real-time, event-driven interactions.
- Built-in persistent and temporary session management.
- Flexible architecture to handle server events though AI agent's lifecycle events.
---
### Agent's session lifecycle Events
- `ON_AUTH`: Authenticate a session.
- `ON_INIT`: Initialize a session.
- `ON_CLOSE`: Close a session.
- `ON_QUERY`: Execute a query.
- `ON_STORE`: Store documents.
---
## Getting Started
### Requirements
- Python 3.12
### Installation
1. Install kiss-ai-stack-server package:
```bash
pip install kiss-ai-stack-server
```
2. Set environment variables file
```bash
# .env
ACCESS_TOKEN_SECRET_KEY = "your-secure-random-secret-key"
ACCESS_TOKEN_ALGORITHM = "HS256"
ACCESS_TOKEN_EXPIRE_MINUTES = 30
SESSION_DB_URL="sqlite://sessions.db"
```
3. Run the server:
```bash
from kiss_ai_stack_server import bootstrap_session_schema, agent_server
```
---
## REST API Endpoints
### 1. Authentication
**Endpoint:** `/auth`
**Method:** `POST`
**Request Body:**
```json
{
"client_id": "string",
"client_secret": "string"
}
```
**Response:**
```json
{
"session_id": "string",
"access_token": "string",
"expires_in": 3600
}
```
---
### 2. Session Actions
**Endpoint:** `/sessions?action={init|close}`
**Method:** `POST`
**Query Parameter:**
- `action` (required): Action to perform on the session (`init` or `close`).
**Request Body:**
```json
{
"session_id": "string"
}
```
**Response:** Session-related details or status.
---
### 3. Query Execution
**Endpoint:** `/queries`
**Method:** `POST`
**Request Body:**
```json
{
"query": "string",
"parameters": {
"key": "value"
}
}
```
**Response:** Query results.
---
### 4. Document Storage
**Endpoint:** `/documents`
**Method:** `POST`
**Request Body:**
```json
{
"documents": [
{
"id": "string",
"content": "string",
"metadata": {}
}
]
}
```
**Response:** Document storage confirmation.
---
## WebSocket API
**Endpoint:** `/ws`
### Workflow
1. Establish a WebSocket connection:
```bash
ws://localhost:8080/ws
```
2. Send a message:
```json
{
"event": "ON_QUERY",
"data": {
"query": "example query",
"parameters": {
"key": "value"
}
}
}
```
3. Receive a response:
```json
{
"event": "ON_QUERY",
"result": {
"response_key": "response_value"
}
}
```
## Contributing
Contributions are welcome! Feel free to fork the repository and submit a pull request.
---
## License
This project is licensed under the MIT License.
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