# Flama

> Flama is a production-ready, open-source Python framework for building Machine Learning APIs, LLM-serving endpoints, and MCP (Model Context Protocol) servers, with a Rust-powered core and automatic OpenAPI documentation.

## Introduction
- [Flama](https://flama.dev/docs/introduction/flama/)

## Getting Started
- [Installation](https://flama.dev/docs/getting-started/installation/)
- [Quickstart](https://flama.dev/docs/getting-started/quickstart/)
- [Upgrading](https://flama.dev/docs/getting-started/upgrading/)

## Fundamentals
- [Applications](https://flama.dev/docs/fundamentals/applications/)
- [Routes](https://flama.dev/docs/fundamentals/routes/)
- [Responses](https://flama.dev/docs/fundamentals/responses/)
- [Schemas](https://flama.dev/docs/fundamentals/schemas/)
- [Components](https://flama.dev/docs/fundamentals/components/)
- [Modules](https://flama.dev/docs/fundamentals/modules/)
- [Middlewares](https://flama.dev/docs/fundamentals/middlewares/)
- [Endpoints](https://flama.dev/docs/fundamentals/endpoints/)
- [Resources](https://flama.dev/docs/fundamentals/resources/)

## Flama CLI
- [Run](https://flama.dev/docs/flama-cli/run/)
- [Serve](https://flama.dev/docs/flama-cli/serve/)
- [Start](https://flama.dev/docs/flama-cli/start/)
- [Model](https://flama.dev/docs/flama-cli/model/)
- [Get](https://flama.dev/docs/flama-cli/get/)
- [Upgrade](https://flama.dev/docs/flama-cli/upgrade/)

## Advanced Topics
- [Configuration](https://flama.dev/docs/advanced-topics/configuration/)
- [Debugging](https://flama.dev/docs/advanced-topics/debug-mode/)
- [Flama Client](https://flama.dev/docs/advanced-topics/client/)
- [Pagination](https://flama.dev/docs/advanced-topics/pagination/)
- [Background Tasks](https://flama.dev/docs/advanced-topics/background-tasks/)
- [Lifespan](https://flama.dev/docs/advanced-topics/lifespan/)
- [Authentication](https://flama.dev/docs/advanced-topics/authentication/)
- [Testing](https://flama.dev/docs/advanced-topics/testing/)

## Predictive AI
- [Packaging models](https://flama.dev/docs/predictive-ai/packaging-models/)
- [Add models to your App](https://flama.dev/docs/predictive-ai/add-models/)
- [Model resources](https://flama.dev/docs/predictive-ai/model-resource/)
- [Model components](https://flama.dev/docs/predictive-ai/model-components/)

## Generative AI
- [Overview](https://flama.dev/docs/generative-ai/overview/)
- [Getting models](https://flama.dev/docs/generative-ai/getting-models/)
- [Serving LLMs](https://flama.dev/docs/generative-ai/serving-llms/)
- [Chatbot application](https://flama.dev/docs/generative-ai/chatbot-application/)
- [Model Context Protocol](https://flama.dev/docs/generative-ai/model-context-protocol/)

## Domain driven design
- [Introduction](https://flama.dev/docs/domain-driven-design/introduction/)
- [Data model](https://flama.dev/docs/domain-driven-design/data-model/)
- [Repository](https://flama.dev/docs/domain-driven-design/repository/)
- [Worker](https://flama.dev/docs/domain-driven-design/worker/)
- [Resources](https://flama.dev/docs/domain-driven-design/resources/)
- [Application assembly](https://flama.dev/docs/domain-driven-design/application-assembly/)

## Contributing
- [How to contribute](https://flama.dev/docs/contributing/how-to-contribute/)

## Blog
- [Building an MCP Server with Flama](https://flama.dev/blog/building_an_mcp_server_with_flama/): How to build and serve a Model Context Protocol server that exposes tools, resources, and prompts to AI agents
- [Serving LLMs with the Flama CLI](https://flama.dev/blog/serving_llms_with_flama_cli/): How to download, interact with, and serve large language models using the Flama command-line interface
- [Releasing Flama 2.0](https://flama.dev/blog/releasing_flama_2_0/): The main highlights of Flama 2.0 version
- [Releasing Flama 1.12](https://flama.dev/blog/releasing_flama_1_12/): The main highlights of Flama 1.12 version
- [Releasing Flama 1.11](https://flama.dev/blog/releasing_flama_1_11/): The main highlights of Flama 1.11 version
- [Releasing Flama 1.10](https://flama.dev/blog/releasing_flama_1_10/): The main highlights of Flama 1.10 version
- [Native Domain-Driven Design with Flama](https://flama.dev/blog/native_domain-driven_design_with_flama/): Using DDD for aligning business logic with the technical design of an application
- [Protected ML APIs with Flama JWT Authentication](https://flama.dev/blog/protected_ml_apis_with_flama_jwt_authentication/): How you can secure your API endpoints with token-based authentication
- [Releasing Flama 1.7](https://flama.dev/blog/releasing_flama_1_7/): The main highlights of Flama 1.7 version
- [Introducing Flama for Robust Machine Learning APIs](https://flama.dev/blog/introducing_flama_for_robust_machine_learning_apis/): Framework for Lightweight Applications and Machine-learning Automation
- [Quick start with Flama](https://flama.dev/blog/flama_quickstart/): Framework for Lightweight Applications and Machine-learning Automation
- [Flama is coming](https://flama.dev/blog/flama_is_coming/): Framework for Lightweight Applications and Machine-learning Automation

## Optional
- [Full framework reference](https://flama.dev/llms-full.txt): Complete Flama API surface in a single file