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Basic Information

Genkit is an open-source framework from Firebase for building full-stack AI-powered applications. It provides unified SDKs and APIs that let developers integrate models from multiple providers and rapidly create chatbots, automations, recommendation systems, and other AI features. The project includes production-oriented capabilities such as structured output generation, multimodal inputs and outputs, tool calling, agentic workflows, prompt templating, persisted chat interfaces, and retrieval-augmented generation. Genkit offers language-specific SDKs with JavaScript/TypeScript marked stable, Go in beta, and Python in alpha. It is designed to work across server and client environments, with helpers for web and mobile frameworks and deployment options including Cloud Functions and Cloud Run. The README emphasizes developer tooling, sample apps, quickstarts for each language, and integration with Firebase Studio for trying Genkit without local setup.

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App URL
https://github.com/firebase/genkit
Github Repository
https://github.com/firebase/genkit/blob/main/README.md

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App Details

Features
Genkit’s core features include broad model provider support through a unified interface, enabling use of models from Google, OpenAI, Anthropic, Ollama, and others. It exposes streamlined APIs for text and image generation, type-safe structured data outputs, multimodal generation, and agentic tool calling. The framework supports prompt templating, persisted chat histories, AI workflows (flows), and RAG-style data retrieval. Developer productivity is boosted by a CLI and a local Developer UI for running, inspecting, and evaluating flows with execution traces and playgrounds. Cross-language SDKs provide consistent APIs across JavaScript/TypeScript, Go, and Python. Genkit also targets production use with deployment guidance, client helpers for web and mobile integration, and observability features for monitoring model performance, request volumes, latency, and errors.
Use Cases
Genkit helps developers by removing much of the complexity of integrating multiple AI models and building production-ready AI features. Its unified SDKs and provider plugins let teams switch or compare models without rewriting integration code. The CLI and Developer UI enable fast iteration, testing, and debugging of prompts, flows, and tool calls with visual traces and evaluation tools. Cross-language support lets teams choose the environment that best fits their stack while preserving consistent APIs. Genkit provides deployment guidance and client helpers for web and mobile, plus monitoring and observability to track model performance and operational metrics in production. Sample apps, quickstarts for each supported language, and integration with Firebase Studio lower the barrier to experimenting and shipping AI features.

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