# Takk

> Takk is a PaaS/SaaS service that simplifies Python deployment. Define your entire application stack in pure Python - web services, background workers, databases, and infrastructure - then deploy with a single command.

## Overview

Takk eliminates the need for Docker Compose, Terraform, and CI/CD configuration files. Instead, you define everything in a single, type-safe Python `Project` class. Takk handles containerization, networking, secrets management, database provisioning, and TLS certificates automatically. The required resources are derived from a pydantic `BaseModel` or `BaseSettings` class, which is added to the `Project` definition. Resources will not be provisioned if they exist in a `.env` or as env vars.

## Assumptions
Takk assumes that Docker is installed and running.

## Key Features

- **Single Command Deployment**: Run `takk up` locally, `takk deploy` for cloud
- **Automatic Infrastructure**: Databases, queues, and storage provisioned from code analysis
- **Type-Safe Configuration**: Python Project class with full IDE support
- **Secret Management**: Secure injection of credentials per-component
- **Multiple App Types**: FastAPI, Streamlit, MLflow, background workers, scheduled jobs

## Documentation Sections

### Core Concepts
- [Getting Started Guide](https://docs.takk.cloud/llms/get_started.md) - Installation and first project
- [Project Definition](https://docs.takk.cloud/llms/project_definition.md) - The central configuration object
- [Secrets Management](https://docs.takk.cloud/llms/secrets.md) - Secure credential handling
- [Configure Resources](https://docs.takk.cloud/llms/resources.md) - Configure resources like Psql, Redis, MongoDB, etc.

### Application Types
- [Network Applications](https://docs.takk.cloud/llms/network_apps.md) - Define Network applications like, FastAPI, Streamlit, MLflow servers
- [Background Jobs](https://docs.takk.cloud/llms/jobs.md) - Scheduled, cron and one-time tasks
- [Queues and Workers](https://docs.takk.cloud/llms/queues.md) - Message-driven processing
- [Pub/Sub](https://docs.takk.cloud/llms/pubsub.md) - Event-driven messaging

### Development & Deployment
- [Local Development](https://docs.takk.cloud/llms/local.md) - Running locally with Docker
- [Deployment Guide](https://docs.takk.cloud/llms/deploy.md) - Deploying to cloud environments

### Examples
- [Support Ticket Classification](https://docs.takk.cloud/llms/support_ticket.md) - AI-powered ticket routing example

### Troubleshooting
- [FAQs](https://docs.takk.cloud/llms/troubleshooting.md) - Common questions and solutions

## Quick Start Example

Install through `uv`
```bash
uv add takk
```

```python
from pydantic import PostgresDsn, SecretStr
from pydantic_settings import BaseSettings
from takk import Project, NetworkApp, Job, value_for
from takk.secrets import AiToken, AiBaseAPI, AiBaseUrl
from takk.resources import ServerlessPostgresInstance

from app.jobs import materialize_job, MaterializeArgs

class AppSettings(BaseSettings):

    # Declaring PostgresDsn automatically provisions a serverless PostgreSQL cluster
    # if no value is provided in .env or environment variables
    psql_uri: PostgresDsn

    # A single connection serves all AI model types: Chat, Vision, Embedding, AudioTranscriber.
    # AiBaseAPI is for OpenAI-compatible endpoints (base URL includes /v1).
    # AiBaseUrl is for Anthropic-compatible endpoints (base URL only, no /v1).
    # AiToken is the API key for either provider.
    ai_api: AiBaseAPI 
    ai_token: AiToken


project = Project(
    name="my-api",
    shared_secrets=[AppSettings],

    # A uvicorn app named `my_app` exposing port 8000
    my_app=NetworkApp(
        command=["/bin/bash", "-c", "uvicorn src.app:app --host 0.0.0.0 --port 8000"],
        port=8000,
        docker_image=None  # None means using the managed Python image
    ),

    # A scheduled job named `background_job`
    background_job=Job(
        materialize_job,
        cron_schedule=value_for(prod="0 3 * * *", default=None),  # Runs daily at 3 AM in prod
        arguments=MaterializeArgs(),
    ),

    # Override the default serverless PostgreSQL to enable extensions.
    # Without this, Takk provisions a ServerlessPostgresInstance with default settings.
    default=ServerlessPostgresInstance(extensions=["pgvector"]),
)
```

Then run:
```bash
uv run takk up               # Local development with automatic hot reloading for uvicorn
uv run takk deploy --env qa  # Cloud deployment
```

## Contact

- Documentation: https://docs.takk.cloud
- Takk Cloud: https://takk.dev/