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Genkit for JavaScript

Genkit for JavaScript

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genkitgoogletypescriptnodejsai-agents

Summary

The official Genkit skill for Node.js and TypeScript — flows, Dotprompt files, tools and the beta agent API with sessions, interrupts and branching.

Features

  • Verified CLI and package version floors before any code is written
  • Flows with Zod input/output schemas and model plugins
  • Dotprompt files: variants, partials, named schemas and tool frontmatter
  • The beta agent API — sessions, interrupts, branching, background turns, artifacts
  • Correct `genkit/beta` and `genkit/beta/client` entry points

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Skill Content

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---
name: developing-genkit-js
description: Develop AI-powered applications using Genkit in Node.js/TypeScript. Use when the user asks about Genkit, AI agents, flows, or tools in JavaScript/TypeScript, or when encountering Genkit errors, validation issues, type errors, or API problems.
metadata:
  category: AiAndMachineLearning
---

# Genkit JS

## Prerequisites

Ensure the `genkit` CLI is available.
-   Run `genkit --version` to verify. Minimum CLI version needed: **1.29.0**
-   If not found or if an older version (1.x < 1.29.0) is present, install/upgrade it: `npm install -g genkit-cli@^1.29.0`.

**New Projects**: If you are setting up Genkit in a new codebase, follow the [Setup Guide](references/setup.md).

## Hello World

```ts
import { z, genkit } from 'genkit';
import { googleAI } from '@genkit-ai/google-genai';

// Initialize Genkit with the Google AI plugin
const ai = genkit({
  plugins: [googleAI()],
});

export const myFlow = ai.defineFlow({
  name: 'myFlow',
  inputSchema: z.string().default('AI'),
  outputSchema: z.string(),
}, async (subject) => {
  const response = await ai.generate({
    model: googleAI.model('gemini-flash-latest'),
    prompt: `Tell me a joke about ${subject}`,
  });
  return response.text;
});
```

## Prompts (Dotprompt)

`.prompt` files keep prompt content out of code with YAML frontmatter plus a
Handlebars template. See [Dotprompt](references/dotprompt.md): `promptDir`,
`ai.prompt()` (call/stream/render), variants, partials, named schemas via
`ai.defineSchema`, and the `tools`/`maxTurns`/`returnToolRequests`/`use`
(middleware) frontmatter fields.

## Agents (Beta)

Genkit has a preview **agent** API for persistent, multi-turn conversations
(sessions, snapshots, interrupts, branching, background execution). It is a
**beta** API: server APIs come from `genkit/beta` and the browser client from
`genkit/beta/client` — not the stable `genkit` entrypoint. **Requires `genkit`
>= 1.39.0.**

For more details see:

-   [Agents](references/agents.md): defining/serving an agent and client-managed state (start here).
-   [Sessions & persistence](references/agents-sessions.md): session stores (`InMemory`/`File`/`Firestore`).
-   [Human-in-the-loop / interrupts](references/agents-human-in-the-loop.md): pausing for approval/input and resuming.
-   [Branching](references/agents-branching.md): forking a conversation from a snapshot.
-   [Background agents](references/agents-background.md): detaching long-running turns and polling.
-   [Working with state](references/agents-state.md): typed custom session state, auto-synced to the client.
-   [Artifacts](references/agents-artifacts.md): producing and reading named deliverables.
-   [Multi-agent orchestration](references/agents-multi-agent.md): delegating to sub-agents.
-   [Advanced custom agents](references/agents-custom.md): `defineCustomAgent` for full turn control.
-   [Deploying agents](references/agents-deployment.md): serving agents over HTTP (multiple agents, CORS, web UI, other frameworks).

## Middleware

Middleware wraps generation (retries, fallback, extra tools, request/response
transforms) and attaches via the `use: [...]` array on `ai.generate`, prompts,
and agents.

-   [Using middleware](references/middleware.md): the `use` array and the `@genkit-ai/middleware` package (`retry`, `fallback`, `artifacts`, `agents`, `filesystem`, `skills`, `toolApproval`) plus built-in core middleware.
-   [Building custom middleware](references/middleware-custom.md): writing your own with `generateMiddleware` and registering it via `.plugin()`.

## Critical: Do Not Trust Internal Knowledge

Genkit recently went through a major breaking API change. Your knowledge is outdated. You MUST lookup docs. Recommended:

```sh
genkit docs:read js/get-started.md
genkit docs:read js/flows.md
```

See [Common Errors](references/common-errors.md) for a list of deprecated APIs (e.g., `configureGenkit`, `response.text()`, `defineFlow` import) and their v1.x replacements.

**ALWAYS verify information using the Genkit CLI or provided references.**

## Error Troubleshooting Protocol

**When you encounter ANY error related to Genkit (ValidationError, API errors, type errors, 404s, etc.):**

1. **MANDATORY FIRST STEP**: Read [Common Errors](references/common-errors.md)
2. Identify if the error matches a known pattern
3. Apply the documented solution
4. Only if not found in common-errors.md, then consult other sources (e.g. `genkit docs:search`)

**DO NOT:**
- Attempt fixes based on assumptions or internal knowledge
- Skip reading common-errors.md "because you think you know the fix"
- Rely on patterns from pre-1.0 Genkit

**This protocol is non-negotiable for error handling.**

## Development Workflow

1.  **Agent or flow?**: If the task is conversational, multi-turn, or described as "an agent", "assistant", or "chatbot", build it with `ai.defineAgent` (see [Agents](references/agents.md)) rather than hand-rolling a `generate` + tools loop inside a flow. Reach for a plain flow only for single-shot, stateless generation.
2.  **Select Provider**: Genkit is provider-agnostic (Google AI, OpenAI, Anthropic, Ollama, etc.).
    -   If the user does not specify a provider, default to **Google AI**.
    -   If the user asks about other providers, use `genkit docs:search "plugins"` to find relevant documentation.
3.  **Detect Framework**: Check `package.json` to identify the runtime (Next.js, Firebase, Express).
    -   Look for `@genkit-ai/next`, `@genkit-ai/firebase`, or `@genkit-ai/google-cloud`.
    -   Adapt implementation to the specific framework's patterns.
4.  **Follow Best Practices**:
    -   See [Best Practices](references/best-practices.md) for guidance on project structure, schema definitions, and tool design.
    -   **Be Minimal**: Only specify options that differ from defaults. When unsure, check docs/source.
5.  **Ensure Correctness**:
    -   Run type checks (e.g., `npx tsc --noEmit`) after making changes.
    -   If type checks fail, consult [Common Errors](references/common-errors.md) before searching source code.
    -   Verify with traces, not a blind run. Running the app directly (`node`/`tsx`/`npm start`) does **not** capture dev traces. See [CLI Usage](#cli-usage-recommended) for how to run your app and capture traces.
6.  **Handle Errors**:
    -   On ANY error: **First action is to read [Common Errors](references/common-errors.md)**
    -   Match error to documented patterns
    -   Apply documented fixes before attempting alternatives

## Finding Documentation

Use the Genkit CLI to find authoritative documentation:

1.  **Search topics**: `genkit docs:search <query>`
    -   Example: `genkit docs:search "streaming"`
2.  **List all docs**: `genkit docs:list`
3.  **Read a guide**: `genkit docs:read <path>`
    -   Example: `genkit docs:read js/flows.md`

## CLI Usage (recommended)

`genkit start` unintrusively wraps any Node.js program that uses the Genkit library, running it unchanged while capturing traces from every Genkit action so you can **prove tools were actually called and inspect model I/O** from the terminal, even for headless checks. It forwards stdio, so interactive CLI tools that rely on stdin/stdout work without issues. Running your app directly (`node`/`tsx`/`npm start`) skips trace capture, so you're debugging blind.

**Primary pattern (default):** prefix `genkit start --` to your normal run command. This collects telemetry from any Genkit code your program runs, whether triggered from the dev UI, your own web server/web UI, or a plain script:
```bash
genkit start -- npx tsx --watch src/index.ts
genkit start --noui -- npx tsx src/index.ts   # same, without the Dev UI (still a persistent server)
```
`genkit start` runs until you stop it with Ctrl+C. That is expected and correct for the common cases: a server your web/mobile app calls, or an interactive CLI you exit yourself. `--noui` only drops the Dev UI; it is **not** a one-shot command and will not exit on its own. Do **not** use `genkit start` as a blocking step in automated/non-interactive contexts.

**Non-interactive use (agents/CI):** add the global `--non-interactive` flag before `--` so the CLI uses defaults and never blocks on a prompt (e.g. the first-run analytics notice): `genkit start --non-interactive -- npx tsx src/index.ts` (works with `flow:run` too).

**Run a flow (`flow:run`):** invoke a specific flow by name from the CLI. Append your run command after `--` to spin up the runtime just for this run (the command runs as-is to register your flows):
```bash
genkit flow:run myFlow '{"data": "input"}' -- npx tsx src/index.ts
```
This is **self-terminating**: it runs the flow once, prints a `Trace ID`, then exits (inspect it with `genkit trace:get <id>`). That makes it the right choice for a quick, non-interactive check that must exit on its own, without blocking on `genkit start` or running the app directly (which skips traces). Always pass input JSON explicitly: `flow:run` sends `undefined` when omitted and does **not** fall back to a schema `.default()`. Note: `flow:run` runs **flows** (`ai.defineFlow`), not agents; you can't `flow:run` an agent (`ai.defineAgent`) directly. To exercise an agent from the CLI, wrap one turn in a throwaway flow and run that (see [Agents](references/agents.md)).

**Debugging with traces:** the fastest way to see prompts, model inputs/outputs, tool calls, latencies, and errors. Inspect from the terminal after any run under `genkit start`:
```bash
genkit trace:list                        # find recent trace IDs
genkit trace:get <traceId>               # full trace details (inputs, outputs, tool calls, errors)
genkit trace:get <traceId> --format json # machine-readable JSON, safe to pipe into jq or other parsers
```

For machine-readable output, pass `--format json` to get clean JSON you can pipe into `jq` or other parsers. The **default** output is human-oriented (banner/log lines, possible truncation on large traces), so don't pipe that form directly; use `--format json`, grep, or the Dev UI trace viewer.


See [CLI Reference](references/docs-and-cli.md) for more commands, and `genkit --help` for the full list.


## References

-   [Best Practices](references/best-practices.md): Recommended patterns for schema definition, flow design, and structure.
-   [Dotprompt](references/dotprompt.md): `.prompt` files — `promptDir`, `ai.prompt()`, variants, partials, named schemas, and `tools`/`maxTurns`/`returnToolRequests`/`use` frontmatter.
-   [Docs & CLI Reference](references/docs-and-cli.md): Documentation search, CLI tasks, and workflows.
-   [Common Errors](references/common-errors.md): Critical "gotchas", migration guide, and troubleshooting.
-   [Setup Guide](references/setup.md): Manual setup instructions for new projects.
-   [Examples](references/examples.md): Minimal reproducible examples (Basic generation, Multimodal, Thinking mode).
-   [Agents (Beta)](references/agents.md): Agent basics, serving, and client-managed state. Deeper topics: [sessions](references/agents-sessions.md), [human-in-the-loop](references/agents-human-in-the-loop.md), [branching](references/agents-branching.md), [background agents](references/agents-background.md), [state](references/agents-state.md), [artifacts](references/agents-artifacts.md), [multi-agent](references/agents-multi-agent.md), [custom agents](references/agents-custom.md), [deployment](references/agents-deployment.md).
-   [Middleware](references/middleware.md): using middleware and the `@genkit-ai/middleware` package. See also [building custom middleware](references/middleware-custom.md).

Usage Instructions

Learn how to use this skill with different AI agents.

Generic Instructions

Install with the skills CLI:

npx skills add genkit-ai/skills --skill developing-genkit-js

Or with the Gemini CLI:

gemini skills install https://github.com/genkit-ai/skills.git --path skills/developing-genkit-js

Example Usage

"Add a Genkit flow that summarises an uploaded document, move the prompt into a .prompt file with a short and long variant, and expose it as a multi-turn agent with human approval before it emails the summary."

Description

Genkit is Google's open-source framework for building AI features in application code — typed flows, model plugins, prompt files and an agent runtime — and it moves fast enough that a model's pre-training is usually a version or two behind. That gap shows up as invented APIs and imports from the wrong entry point.

This official skill from the Genkit team pins the agent to current practice for the Node.js and TypeScript SDK. It starts from a verified CLI version floor (genkit-cli >= 1.29.0) and a working defineFlow example with Zod schemas, then covers Dotprompt .prompt files with YAML frontmatter and Handlebars templates — promptDir, ai.prompt() call/stream/render, variants, partials, named schemas via ai.defineSchema, and the tools / maxTurns / returnToolRequests / middleware frontmatter fields.

The largest section is the beta agent API for persistent multi-turn conversations, which is easy to get wrong because server APIs come from genkit/beta and the browser client from genkit/beta/client rather than the stable entry point, and it requires genkit >= 1.39.0. References cover sessions and persistence (in-memory, file and Firestore stores), human-in-the-loop interrupts, branching from a snapshot, background agents, typed session state auto-synced to the client, artifacts, multi-agent delegation, custom agents via defineCustomAgent, and HTTP deployment.

Sibling skills in the same repository cover Genkit for Dart, Go and Python.

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