Metadata-Version: 2.3
Name: shraga-common
Version: 0.8.6
Summary: Common infrastructure for Shraga AI
License: Apache-2.0
Author: Itamar Syn-Hershko
Author-email: itamar@bigdataboutique.com
Requires-Python: >=3.11,<4.0
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
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Description-Content-Type: text/markdown

# Shraga

Shraga is a modern AI application with a backend based on FastAPI and a frontend built with React.

## Installation and Setup

### Requirements

1. Python 3.11 or higher
2. Pip
3. Poetry (for dependency management)
4. Node.js and pnpm (for frontend)

### Backend Setup

First, install Poetry if you don't have it already:

```bash
pipx install poetry
```

Clone the repository and install dependencies:

```bash
git clone <repository-url>
cd shraga
poetry install --no-root
poetry run pre-commit install
```

To activate the virtual environment:

```bash
poetry shell
which python  # Verify the correct Python interpreter is being used
```

## Running the Application

### Backend

To run the backend server with hot-reloading enabled:

```bash
SHRAGA_FLOWS_PATH=flows CONFIG_PATH=config.demo.yaml uvicorn main:app --reload
```

### Frontend

To run the frontend development server:

```bash
cd frontend
pnpm install  # Only needed first time or when dependencies change
pnpm run dev
```

By default, the frontend will be available at http://localhost:5000 and will connect to the backend API running on http://localhost:8000.

## Configuration

Shraga uses YAML configuration files to manage its settings. The repository includes:

- `config.example.yaml`: A template configuration file with documentation

You can specify which configuration file to use with the `CONFIG_PATH` environment variable.

## Demo Flow

To run the demo flow without requiring an LLM, Elasticsearch, or Opensearch:

1. Use the demo configuration file:
   ```bash
   export CONFIG_PATH=config.demo.yaml
   ```

2. Run the backend with the demo flows:
   ```bash
   export SHRAGA_FLOWS_PATH=flows
   uvicorn main:app --reload
   ```

## Development Tools

Several command-line tools are included with this package to help with development and management tasks:

### User Management

```bash
# Create a user with basic authentication (interactive mode)
poetry run create-basic-auth-user

# Create a user with command-line arguments
poetry run create-basic-auth-user <email> <password> <config_file>

# Example
poetry run create-basic-auth-user user@example.com mypassword123 config.demo.yaml
```

This tool will:
- Prompt you to enter a user email address (with validation)
- Securely collect and validate a password
- Ask for the configuration file to update
- Generate a bcrypt hash of the password
- Save the credentials to a text file for reference
- Update the specified configuration file with the new user

### Code Style

This project uses pre-commit hooks to enforce code style. They're installed with:

```bash
poetry run pre-commit install
```

## API Documentation

### Authentication

Shraga supports two authentication methods: Basic Authentication and JWT Authentication.

#### Basic Authentication

To authenticate with the API using basic authentication, you need to encode your credentials using base64.

##### Getting a Basic Auth Token

To get `YOUR_TOKEN_HERE`, encode your credentials using base64:

```bash
# Replace user@domain.com and your_password with actual credentials
echo -n "user@domain.com:your_password" | base64
# This outputs the token to use in the Authorization header
```

#### JWT Authentication

JWT (JSON Web Token) authentication allows for more secure and scalable authentication, especially useful when integrating Shraga with your own applications.

##### 1. Configure JWT Secret in config.yaml

First, add a JWT secret to your configuration file:

```yaml
auth:
  jwt:
    secret: "your-super-secret-jwt-key-here"  # Use a strong, randomly generated secret
```

**Important**: Use a strong, randomly generated secret in production. Never commit secrets to version control.

##### 2. Getting a JWT Token

To obtain a JWT token, you'll need to implement a login endpoint in your application that verifies user credentials and returns a signed JWT. Here's an example using PyJWT:

```python
import jwt
import time
from typing import Dict, Any

def create_jwt_token(user_email: str, user_id: int, user_name: str, secret: str) -> str:
    now = int(time.time())
    payload: Dict[str, Any] = {
        "sub": user_email,        # Subject (user identifier)
        "uid": user_id,           # User ID
        "name": user_name,        # User name
        "iat": now,               # Issued at
        "exp": now + 86400,       # Expires in 24 hours
    }
    return jwt.encode(payload, secret, algorithm="HS256")
```

### Flow Run API

To generate a response programmatically, use the flow run endpoint. You can authenticate using either Basic or JWT authentication:

#### Using Basic Authentication

```bash
curl -X POST "http://myhost/api/flows/run" \
  -H "Content-Type: application/json" \
  -H "Authorization: Basic YOUR_BASIC_TOKEN_HERE" \
  -d '{
    "flow_id": "flow name",
    "question": "this is my question?"
  }'
```

#### Using JWT Authentication

```bash
curl -X POST "http://myhost/api/flows/run" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN_HERE" \
  -d '{
    "flow_id": "flow name",
    "question": "this is my question?"
  }'
```

### Report API

The Report API allows any user with analytics privileges to retrieve chat conversations from all organizations.

For generating chat reports, use the `/api/report/export` endpoint:

```bash
curl -X POST "http://localhost:5000/api/report/export" \
  -H "Content-Type: application/json" \
  -H "Authorization: Basic YOUR_TOKEN_HERE" \
  -d '{
    "report_type": "history",
    "start": "2025-04-01 00:00:00",
    "end": "2025-06-01 00:00:00",
    "filters": { 
        "company_id": "1111",
        "email": "test@test.com"
    }
  }'
```

#### Parameters

- `report_type`: "history" (required)
- `start`: "YYYY-MM-DD HH:MM:SS" (optional)
- `end`: "YYYY-MM-DD HH:MM:SS" (optional)
- `user_id`: string (optional)
- `user_org`: string (optional)

#### Prerequisites

The endpoint is available for users with `analytics` permission and `history` must be enabled in config.yaml.

Analytics permission can be configured in config.yaml:

**Option 1: Domain-based access**
```yaml
history:
   enabled: true
   analytics: 
     domains:
       - domain.ltd
```

**Option 2: User-based access**
```yaml
history:
   enabled: true
   analytics: 
      users:
         - username_from_auth.users
```

## Project Structure

- `/shraga_common`: Core library with reusable components
- `/scripts`: Command-line utilities and helper scripts
- `/frontend`: React-based web interface
- `/flows`: Flow definitions for different use cases
- `/terraform`: Infrastructure as code for deployment

## License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.


