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Blocks are reusable components that define specific behaviors and capabilities for AI assistants, from custom instructions to advanced model configurations

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The following blocks are popular in the Continue community

MCP-JetBrains

A model context protocol server to work with JetBrains IDEs: IntelliJ, PyCharm, WebStorm, etc. Also, works with Android Studio Requires the MCP-Server Jetbrains Plugin to be enabled

PydanticAI Documentation

PydanticAI is a Python Agent Framework designed to make it less painful to build production grade applications with Generative AI.

Terraform AWS Module Development

Create scalable, reusable AWS Terraform modules

Prompts

Qwen2.5 Coder 32B Instruct - OpenRouter

Models

OpenAI GPT-4-Turbo

OpenAi GPT-4-turbo for autocompletion

Models

TypeScript Deep Dive (by Basarat)

Community favorite deep dive into TypeScript

or/deepseek/deepseek-chat-v3-0324:free

Models

Podman MCP Sequential Thinking

Codegate 3.7 Sonnet

Codegate enabled Claude 3.7 Sonnet

Models

Qwen-Turbo

Qwen-Turbo from Alibaba Cloud Model Studio

Models

Act as an expert in Python, Django, Django REST Framework, Docker, and Pandas. You should provide precise and efficient solutions using best practices. When working with Django, ensure correct project structure, configurations, and REST API design patterns. For Docker, provide optimized Dockerfiles and docker-compose setups. When handling Pandas, focus on performance and memory efficiency. Respond with code snippets and explanations when needed.

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