Plain
A modern web framework redesigned to adapt Django for AI agent collaboration environments.
Plain, developed by Dave Gaeddert of Dropseed, LLC, and released on April 15, 2026, is a full-stack Python web framework that reimagines the Django framework for a modern and explicit agent collaboration environment. Like a skilled human marksman and a smart AI intern exchanging code seamlessly on a single whiteboard, Plain aims for an agent-friendly development architecture designed to enable AI agents and human developers to collaborate in the most efficient and secure way. It boldly removes the legacy elements of the original Django, which were maintained for backward compatibility, and provides strict modularization and intuitive file structures, allowing agents to easily grasp the overall structure of the software and database relationships. Existing monolithic frameworks, with their excessive implicit configurations and complex metaprogramming, often lead to frequent malfunctions and unnecessary inference costs for AI coding agents. This has historically resulted in agents misinterpreting class inheritance relationships or configuration files when injecting code, leading to the automatic generation of incorrect code. To overcome this problem, Plain enforces that all configurations and definitions be declared in an explicit and typed manner. Just as having an accurate destination and route set in a navigation system prevents getting lost, Plain monitors the strict type specification and data model standards of the code through the `plain check` function, verifying the correctness of the code written by the agent in real-time and immediately correcting any errors. From the perspective of a biotechnology research lab or a bio venture company, Plain serves as a robust foundation for quickly building and deploying complex genomic data analysis pipelines or bio data portals with the help of AI agents. For example, if a researcher instructs an AI coding agent like Claude or GPT-4 to "create a web dashboard that can store and visualize genomic variation analysis data," the agent can define a Postgres data model under Plain's strict type rules and quickly implement a responsive data visualization web interface that operates without screen refreshes by combining Jinja2 templates and htmx. It incorporates uv as a package manager, resulting in very fast dependency management, and the code is perfectly formatted in advance based on Ruff and ty, ensuring that the code written by the agent immediately meets commercial-grade standards.
๐ป System Requirements
0 (CPU only, the AI agent tool does not require local VRAM as it uses a separate LLM API)
Less than 100MB for models and packages, less than 1GB for the entire development environment
โก Installation
### 4-1. Quick Start
```bash
uvx plain-start my-app
```
### 4-2. Detailed Installation
```bash
# 1. Install uv (if not already installed)
curl -LsSf https://astral.sh/uv/install.sh | sh
# 2. Create and navigate to the Plain app starter template project
uvx plain-start my-app
cd my-app
# 3. Start the development server (Postgres will be automatically configured using a local Docker container)
uv run plain dev
```๐งฌ Bio Use Cases
AI Agent-Based Bio Database Schema Design and Migration
Input the analytical data model settings to the agent, and through CLI commands, the agent performs non-stop schema design for Postgres 16+, applies migration, and performs a `plain check` validation, reducing DB setup time by more than 80%.
Real-Time Sequence Alignment Dashboard Development Using htmx and Jinja2
The agent combines Tailwind CSS and htmx to create a responsive web UI without screen refresh, and injects code reliably according to the Plain package structure, enabling the immediate construction of a research-use real-time sequence analysis tool in the form of a web portal.
Cloud Analytics Environment Deployment Based on uv Package Manager and Docker Containers
Using the `uv run plain dev` command and local Docker Postgres database configuration, the coding agent perfectly validates the deployment environment settings and quickly deploys and optimizes web services to the cloud server.
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