# Genkit

## Docs

- [AI Package](https://mintlify.wiki/firebase/genkit/api/go/ai.md): AI package API reference (Go)
- [Flows API](https://mintlify.wiki/firebase/genkit/api/go/flows.md): Flows API reference (Go)
- [Genkit Package](https://mintlify.wiki/firebase/genkit/api/go/genkit.md): Main Genkit package API reference (Go)
- [Prompts API](https://mintlify.wiki/firebase/genkit/api/go/prompts.md): Prompts API reference (Go)
- [Tools API](https://mintlify.wiki/firebase/genkit/api/go/tools.md): Tools API reference (Go)
- [Embedders API](https://mintlify.wiki/firebase/genkit/api/javascript/embedders.md): API reference for embedders in Genkit (JavaScript/TypeScript)
- [Evaluators API](https://mintlify.wiki/firebase/genkit/api/javascript/evaluators.md): API reference for evaluators in Genkit (JavaScript/TypeScript)
- [Flows API](https://mintlify.wiki/firebase/genkit/api/javascript/flows.md): Flow definition and execution APIs
- [Genkit](https://mintlify.wiki/firebase/genkit/api/javascript/genkit.md): Main Genkit class and initialization function
- [Models API](https://mintlify.wiki/firebase/genkit/api/javascript/models.md): Model generation and streaming APIs
- [Prompts API](https://mintlify.wiki/firebase/genkit/api/javascript/prompts.md): Prompt definition and execution APIs
- [Retrievers API](https://mintlify.wiki/firebase/genkit/api/javascript/retrievers.md): API reference for retrievers and indexers in Genkit (JavaScript/TypeScript)
- [Tools API](https://mintlify.wiki/firebase/genkit/api/javascript/tools.md): API reference for defining and using tools in Genkit (JavaScript/TypeScript)
- [Flows API](https://mintlify.wiki/firebase/genkit/api/python/flows.md): Flows API reference (Python)
- [Genkit Class](https://mintlify.wiki/firebase/genkit/api/python/genkit.md): Main Genkit class API reference (Python)
- [Models API](https://mintlify.wiki/firebase/genkit/api/python/models.md): Models API reference (Python)
- [Plugin API](https://mintlify.wiki/firebase/genkit/api/python/plugins.md): Plugin API reference (Python)
- [Prompts API](https://mintlify.wiki/firebase/genkit/api/python/prompts.md): Prompts API reference (Python)
- [Tools API](https://mintlify.wiki/firebase/genkit/api/python/tools.md): Tools API reference (Python)
- [Architecture](https://mintlify.wiki/firebase/genkit/concepts/architecture.md): Understanding Genkit's architecture and how components work together
- [Flows](https://mintlify.wiki/firebase/genkit/concepts/flows.md): Observable, type-safe functions for building AI workflows
- [Models](https://mintlify.wiki/firebase/genkit/concepts/models.md): Unified API for working with AI models from any provider
- [Observability](https://mintlify.wiki/firebase/genkit/concepts/observability.md): Tracing, monitoring, and debugging AI applications with Genkit
- [Plugins](https://mintlify.wiki/firebase/genkit/concepts/plugins.md): Extend Genkit with model providers, telemetry, and custom capabilities
- [Prompts](https://mintlify.wiki/firebase/genkit/concepts/prompts.md): Reusable, testable prompt templates with dotprompt files
- [Tools](https://mintlify.wiki/firebase/genkit/concepts/tools.md): Extend AI models with custom functions and agentic workflows
- [Cloud Run Deployment](https://mintlify.wiki/firebase/genkit/deployment/cloud-run.md): Deploy containerized Genkit applications to Google Cloud Run
- [Firebase Deployment](https://mintlify.wiki/firebase/genkit/deployment/firebase.md): Deploy Genkit flows to Cloud Functions for Firebase
- [Go Deployment](https://mintlify.wiki/firebase/genkit/deployment/go.md): Deploy Genkit Go applications with HTTP servers
- [Node.js Deployment](https://mintlify.wiki/firebase/genkit/deployment/nodejs.md): Deploy Genkit flows with Express to any Node.js platform
- [Deployment Overview](https://mintlify.wiki/firebase/genkit/deployment/overview.md): Learn how to deploy Genkit AI applications to production
- [Python Deployment](https://mintlify.wiki/firebase/genkit/deployment/python.md): Deploy Genkit Python applications with Flask, FastAPI, and ASGI servers
- [Genkit CLI](https://mintlify.wiki/firebase/genkit/devtools/cli.md): Command-line interface for Genkit development
- [Debugging](https://mintlify.wiki/firebase/genkit/devtools/debugging.md): Techniques for debugging Genkit AI applications
- [Developer UI](https://mintlify.wiki/firebase/genkit/devtools/developer-ui.md): Interactive interface for testing and debugging Genkit applications
- [Testing](https://mintlify.wiki/firebase/genkit/devtools/testing.md): Strategies for testing AI applications built with Genkit
- [Go Quickstart](https://mintlify.wiki/firebase/genkit/getting-started/go-quickstart.md): Build your first AI application with Genkit in Go
- [Installation](https://mintlify.wiki/firebase/genkit/getting-started/installation.md): Install Genkit for JavaScript, Go, or Python to start building AI-powered applications
- [JavaScript/TypeScript Quickstart](https://mintlify.wiki/firebase/genkit/getting-started/javascript-quickstart.md): Build your first AI application with Genkit in JavaScript or TypeScript
- [Python Quickstart](https://mintlify.wiki/firebase/genkit/getting-started/python-quickstart.md): Build your first AI application with Genkit in Python (Alpha)
- [Chat Interfaces](https://mintlify.wiki/firebase/genkit/guides/chat-interfaces.md): Build conversational AI applications with message history and session management
- [Evaluation](https://mintlify.wiki/firebase/genkit/guides/evaluation.md): Test and measure the quality of your AI outputs
- [Multimodal](https://mintlify.wiki/firebase/genkit/guides/multimodal.md): Work with images, video, and audio in your AI applications
- [Retrieval-Augmented Generation (RAG)](https://mintlify.wiki/firebase/genkit/guides/rag.md): Build AI systems that retrieve and use relevant information from your data
- [Streaming](https://mintlify.wiki/firebase/genkit/guides/streaming.md): Stream AI responses in real-time for responsive user experiences
- [Structured Output](https://mintlify.wiki/firebase/genkit/guides/structured-output.md): Generate type-safe JSON data with AI models
- [Text Generation](https://mintlify.wiki/firebase/genkit/guides/text-generation.md): Generate text with AI models using Genkit's unified interface
- [Tool Calling](https://mintlify.wiki/firebase/genkit/guides/tool-calling.md): Give AI models the ability to take actions and access external data
- [Introduction to Genkit](https://mintlify.wiki/firebase/genkit/introduction.md): An open-source framework for building production-ready AI-powered applications across JavaScript, Go, and Python
- [Anthropic Plugin](https://mintlify.wiki/firebase/genkit/plugins/anthropic.md): Use Claude models from Anthropic with Genkit
- [Chroma Plugin](https://mintlify.wiki/firebase/genkit/plugins/chroma.md): Use ChromaDB vector store for RAG with Genkit
- [Creating Plugins](https://mintlify.wiki/firebase/genkit/plugins/creating-plugins.md): Learn how to create custom Genkit plugins to extend the framework
- [Express Plugin](https://mintlify.wiki/firebase/genkit/plugins/express.md): Expose Genkit flows as HTTP endpoints with Express.js
- [Firebase Plugin](https://mintlify.wiki/firebase/genkit/plugins/firebase.md): Deploy Genkit applications to Firebase and enable telemetry
- [Google GenAI Plugin](https://mintlify.wiki/firebase/genkit/plugins/google-genai.md): Use Google AI (Gemini) and Vertex AI models with Genkit
- [Ollama Plugin](https://mintlify.wiki/firebase/genkit/plugins/ollama.md): Run local AI models with Ollama and Genkit
- [Plugins Overview](https://mintlify.wiki/firebase/genkit/plugins/overview.md): Learn about Genkit plugins and how to extend the framework with custom capabilities
- [Pinecone Plugin](https://mintlify.wiki/firebase/genkit/plugins/pinecone.md): Use Pinecone vector database for RAG with Genkit
- [Plugin API Reference](https://mintlify.wiki/firebase/genkit/plugins/plugin-api.md): Complete API reference for creating Genkit plugins
- [Publishing Plugins](https://mintlify.wiki/firebase/genkit/plugins/publishing.md): How to publish Genkit plugins to npm and share with the community
- [Vertex AI Plugin](https://mintlify.wiki/firebase/genkit/plugins/vertex-ai.md): Use Google Cloud Vertex AI models with Genkit
- [Anthropic Provider (Claude)](https://mintlify.wiki/firebase/genkit/providers/anthropic.md): Access Claude models with advanced reasoning capabilities
- [Creating Custom Providers](https://mintlify.wiki/firebase/genkit/providers/custom-providers.md): Build custom model provider plugins for any AI service
- [Google AI Provider (Gemini Developer API)](https://mintlify.wiki/firebase/genkit/providers/google-genai.md): Access Gemini models with the Google AI provider for quick prototyping
- [Ollama Provider](https://mintlify.wiki/firebase/genkit/providers/ollama.md): Run open-source AI models locally with Ollama
- [OpenAI-Compatible APIs](https://mintlify.wiki/firebase/genkit/providers/openai-compatible.md): Connect to OpenAI, xAI, DeepSeek, and any OpenAI-compatible service
- [Model Providers Overview](https://mintlify.wiki/firebase/genkit/providers/overview.md): Choose the right AI model provider for your Genkit application
- [Vertex AI Provider](https://mintlify.wiki/firebase/genkit/providers/vertex-ai.md): Enterprise-grade Google Cloud AI platform with advanced features
- [Quick Start](https://mintlify.wiki/firebase/genkit/quickstart.md): Get started with Genkit in under a minute across JavaScript, Go, or Python
- [Changelog](https://mintlify.wiki/firebase/genkit/resources/changelog.md): Latest updates and version history for Genkit
- [Community Resources](https://mintlify.wiki/firebase/genkit/resources/community.md): Connect with the Genkit community, get help, and contribute to the project
- [Contributing to Genkit](https://mintlify.wiki/firebase/genkit/resources/contributing.md): Learn how to contribute to the Genkit open-source project
- [Examples and Samples](https://mintlify.wiki/firebase/genkit/resources/examples.md): Explore Genkit examples and sample applications across JavaScript, Go, and Python
- [Why Choose Genkit?](https://mintlify.wiki/firebase/genkit/why-genkit.md): Discover what makes Genkit the ideal framework for building production-ready AI applications