docs(go): basic 0.9 updates

docs-go/cloud-run.md

@@ -1,8 +1,6 @@
 # Firebase Genkit with Cloud Run
 
-You can deploy Firebase Genkit flows as web services using Cloud Run. This page,
-as an example, walks you through the process of deploying the default sample
-flow.
+You can deploy Firebase Genkit flows as web services using Cloud Run.
 
 1.  Install the [Google Cloud CLI](https://cloud.google.com/sdk/docs/install) if
     you haven't already.
@@ -36,23 +34,26 @@ flow.
     go mod init example/cloudrun
     ```
 
-1.  Initialize Genkit in your project:
+1.  Install the Genkit package and the model plugin you want to use:
 
     ```posix-terminal
-    genkit init
+    go get "github.com/firebase/genkit/go"
     ```
 
-    Select the model provider you want to use.
+    One of the following:
 
-    Accept the defaults for the remaining prompts. The `genkit` tool will create
-    a sample source file to get you started developing your own AI flows.
-    For the rest of this tutorial, however, you'll just deploy the sample flow.
+    ```posix-terminal
+    go get "github.com/firebase/genkit/go/plugins/googleai"
+    ```
+
+    ```posix-terminal
+    go get "github.com/firebase/genkit/go/plugins/vertexai"
+    ```
 
-1.  Edit the sample file (`main.go` or `genkit.go`) to explicitly specify the
-    port the flow server should listen on:
+1.  Create a file (`main.go`) for your flows:
 
     ```golang
-    {% includecode github_path="firebase/genkit/go/internal/doc-snippets/flows.go" region_tag="init" adjust_indentation="auto" %}
+    {% includecode github_path="firebase/genkit/go/internal/doc-snippets/deploy/main.go" region_tag="main" adjust_indentation="auto" %}
     ```
 
 1.  Make API credentials available to your deployed function. Do one of the
@@ -118,7 +119,7 @@ flow.
     1.  Start the UI:
 
         ```posix-terminal
-        genkit start
+        genkit start -- go run .
         ```
 
     1.  In the developer UI (http://localhost:4000/), run the flow:
@@ -139,14 +140,14 @@ flow.
     - {Gemini (Google AI)}
 
       ```posix-terminal
-      gcloud run deploy --port 3400 \
+      gcloud run deploy \
         --update-secrets=GOOGLE_GENAI_API_KEY=<your-secret-name>:latest
       ```
 
     - {Gemini (Vertex AI)}
 
       ```posix-terminal
-      gcloud run deploy --port 3400 \
+      gcloud run deploy \
         --set-env-vars GCLOUD_PROJECT=<your-gcloud-project> \
         --set-env-vars GCLOUD_LOCATION=us-central1
       ```

docs-go/deploy.md

@@ -3,7 +3,7 @@
 You can deploy Firebase Genkit flows as web services using any service that can
 host a Go binary.
 This page, as an example, walks you through the general process of deploying the
-default sample flow, and points out where you must take provider-specific
+a sample flow, and points out where you must take provider-specific
 actions.
 
 1.  Create a directory for the Genkit sample project:
@@ -22,28 +22,28 @@ actions.
     go mod init example/cloudrun
     ```
 
-1.  Initialize Genkit in your project:
+1.  Install the Genkit package and the model plugin you want to use:
 
     ```posix-terminal
-    genkit init
+    go get "github.com/firebase/genkit/go"
     ```
 
-    Select the model provider you want to use.
+    One of the following:
 
-    Accept the defaults for the remaining prompts. The `genkit` tool will create
-    a sample source file to get you started developing your own AI flows.
-    For the rest of this tutorial, however, you'll just deploy the sample flow.
+    ```posix-terminal
+    go get "github.com/firebase/genkit/go/plugins/googleai"
+    ```
+
+    ```posix-terminal
+    go get "github.com/firebase/genkit/go/plugins/vertexai"
+    ```
 
-1.  Edit the sample file (`main.go` or `genkit.go`) to explicitly specify the
-    port the flow server should listen on:
+1.  Create a file (`main.go`) for your flows:
 
     ```golang
-    {% includecode github_path="firebase/genkit/go/internal/doc-snippets/flows.go" region_tag="init" adjust_indentation="auto" %}
+    {% includecode github_path="firebase/genkit/go/internal/doc-snippets/deploy/main.go" region_tag="main" adjust_indentation="auto" %}
     ```
 
-    If your provider requires you to listen on a specific port, be sure to
-    configure Genkit accordingly.
-
 1.  Implement some form of authentication and authorization to gate access to
     the flows you plan to deploy.
 
@@ -120,7 +120,7 @@ actions.
     1.  Start the UI:
 
         ```posix-terminal
-        genkit start
+        genkit start -- go run .
         ```
 
     1.  In the developer UI (http://localhost:4000/), run the flow:

docs-go/get-started-go.md

@@ -8,22 +8,71 @@ exploration.
 If you discover issues with the libraries or this documentation please report
 them in our [GitHub repository](https://github.com/firebase/genkit/).
 
-To get started with Genkit, install the Genkit CLI and run
-`genkit init` in a Go project. The rest of this page shows you how.
+This page shows you how to get started with Genkit in a Go project.
 
 ## Requirements
 
-- Go 1.22 or later. See [Download and install](https://go.dev/doc/install) in
-  the official Go docs.
+Go 1.22 or later. See [Download and install](https://go.dev/doc/install) in
+the official Go docs.
 
-- Node.js 20 or later (for the Genkit CLI and UI). See the next section for a
-  brief guide on installing Node.
+## Install Genkit dependencies {:#install}
 
-## Install Genkit {:#install}
+1.  If you don't already have a Go project that you want to add AI features to,
+    create a new module in an empty directory:
 
-1.  If you don't already have Node 20 or newer on your system, install it now.
+    ```posix-terminal
+    go mod init example/genkit-getting-started
+    ```
+
+1.  Install the Genkit package and the `googleai` model plugin:
+
+    ```posix-terminal
+    go get "github.com/firebase/genkit/go"
+
+    go get "github.com/firebase/genkit/go/plugins/googleai"
+    ```
+
+## Configure your model API key
+
+For this guide, we’ll show you how to use the Gemini API which provides a
+generous free tier and does not require a credit card to get started. To use the
+Gemini API, you'll need an API key. If you don't already have one, create a key
+in Google AI Studio.
+
+[Get an API key from Google AI Studio](https://makersuite.google.com/app/apikey)
+
+After you’ve created an API key, set the `GOOGLE_GENAI_API_KEY` environment
+variable to your key with the following command:
+
+```posix-terminal
+export GOOGLE_GENAI_API_KEY=<your API key>
+```
+
+Note: While this tutorial uses the Gemini API from AI Studio, Genkit supports a
+wide variety of model providers including
+[Gemini from Vertex AI](/docs/genkit/plugins/vertex-ai#generative_ai_models),
+Anthropic’s Claude 3 models and Llama 3.1 through the
+[Vertex AI Model Garden](/docs/genkit/plugins/vertex-ai#anthropic_claude_3_on_vertex_ai_model_garden),
+open source models through
+[Ollama](/docs/genkit/plugins/ollama), and several other
+[community-supported providers](/docs/genkit/models#models-supported) like
+OpenAI and Cohere.
+
+## Make your first request
+
+Get started with Genkit in just a few lines of simple code.
 
-    Recommendation: The [`nvm`](https://github.com/nvm-sh/nvm) and
+```go
+{% includecode github_path="firebase/genkit/go/internal/doc-snippets/init/main.go" region_tag="main" adjust_indentation="auto" %}
+```
+
+## Optional: Install the Genkit CLI
+
+Genkit has a CLI and developer UI that helps you locally test and debug your
+app. To install these tools:
+
+1.  If you don't already have Node 20 or newer on your system,
+    the [`nvm`](https://github.com/nvm-sh/nvm) and
     [`nvm-windows`](https://github.com/coreybutler/nvm-windows) tools are a
     convenient way to install specific versions of Node if it's not already
     installed on your system. These tools install Node on a per-user basis, so you
@@ -53,116 +102,24 @@ To get started with Genkit, install the Genkit CLI and run
 1.  Install the Genkit CLI by running the following command:
 
     ```posix-terminal
-    npm i -g genkit
+    npm i -g genkit-cli
     ```
 
     This command installs the Genkit CLI into your Node installation directory
     so that it can be used outside of a Node project.
 
-## Create and explore a sample project {:#explore}
-
-1.  Create a new project directory:
-
-    ```posix-terminal
-    mkdir genkit-intro && cd genkit-intro
-    ```
-
-1.  Initialize a Genkit project:
-
-    ```posix-terminal
-    genkit init
-    ```
-
-    1. Select `Go` as the runtime environment.
-
-    1. Select your model:
-
-       - {Gemini (Google AI)}
-
-         The simplest way to get started is with Google AI Gemini API. Make sure
-         it's
-         [available in your region](https://ai.google.dev/available_regions).
-
-         [Generate an API key](https://aistudio.google.com/app/apikey) for the
-         Gemini API using Google AI Studio. Then, set the `GOOGLE_GENAI_API_KEY`
-         environment variable to your key:
-
-         ```posix-terminal
-         export GOOGLE_GENAI_API_KEY=<your API key>
-         ```
-
-       - {Gemini (Vertex AI)}
-
-         If the Google AI Gemini API is not available in your region, consider
-         using the Vertex AI API which also offers Gemini and other models. You
-         will need to have a billing-enabled Google Cloud project, enable AI
-         Platform API, and set some additional environment variables:
-
-         ```posix-terminal
-         gcloud services enable aiplatform.googleapis.com
-
-         export GCLOUD_PROJECT=<your project ID>
-
-         export GCLOUD_LOCATION=us-central1
-         ```
-
-         See [Vertex AI pricing](https://cloud.google.com/vertex-ai/generative-ai/pricing).
-
-    1. Specify anything for the module name. For example: `example/genkit-intro`
-
-    1. Choose default answers to the rest of the questions, which will
-       initialize your project folder with some sample code.
-
-    The `genkit init` command creates a sample Go module and installs the
-    required dependencies. The file `main.go` contains a single flow,
-    `menuSuggestionFlow`, that prompts an LLM to suggest an item for a
-    restaurant with a given theme.
-
-    This file looks something like the following (the plugin configuration steps
-    might look different if you selected Vertex AI):
-
-    ```golang
-    {% includecode github_path="firebase/genkit/go/internal/doc-snippets/init/main.go" region_tag="main" adjust_indentation="auto" %}
-    ```
-
-    As you build out your app's AI features with Genkit, you will likely create
-    flows with multiple steps such as input preprocessing, more sophisticated
-    prompt construction, integrating external information sources for
-    retrieval-augmented generation (RAG), and more.
-
-1.  Now you can run and explore Genkit features and the sample project locally
-    on your machine. Download and start the Genkit Developer UI:
-
-    ```posix-terminal
-    genkit start
-    ```
-
-    <img src="resources/welcome_to_genkit_developer_ui.png" alt="Welcome to
-    Genkit Developer UI" class="screenshot attempt-right">
-
-    The Genkit Developer UI is now running on your machine. When you run models
-    or flows in the next step, your machine will perform the orchestration tasks
-    needed to get the steps of your flow working together; calls to external
-    services such as the Gemini API will continue to be made against live
-    servers.
-
-    Also, because you are in a dev environment, Genkit will store traces and
-    flow state in local files.
-
-1.  The Genkit Developer UI downloads and opens automatically when you run the
-    `genkit start` command.
-
-    The Developer UI lets you see which flows you have defined and models you
-    configured, run them, and examine traces of previous runs. Try out some of
-    these features:
-
-    - On the **Run** tab, you will see a list of all of the flows that you have
-      defined and any models that have been configured by plugins.
-
-      Click **menuSuggestionFlow** and try running it with some input text (for
-      example, `"cat"`). If all goes well, you'll be rewarded with a menu
-      suggestion for a cat themed restaurant.
-
-    - On the **Inspect** tab, you'll see a history of flow executions. For each
-      flow, you can see the parameters that were passed to the flow and a trace
-      of each step as they ran.
+## Next steps
+
+Now that you’re set up to make model requests with Genkit, learn how to use more
+Genkit capabilities to build your AI-powered apps and workflows. To get started
+with additional Genkit capabilities, see the following guides:
+
+*   [Generating content](/docs/genkit-go/models): Learn how to use Genkit’s unified
+    generation API to generate text and structured data from any supported
+    model.
+*   [Creating flows](/docs/genkit-go/flows): Learn how to use special Genkit
+    functions, called flows, that provide end-to-end observability for workflows
+    and rich debugging from Genkit tooling.
+*   [Prompting models](/docs/genkit-go/prompts): Learn how Genkit lets you treat
+    prompt templates as functions, encapsulating model configurations and
+    input/output schema.