weiqingy commented on code in PR #898:
URL: https://github.com/apache/flink-agents/pull/898#discussion_r3584893690
##########
docs/content/docs/development/chat_models.md:
##########
@@ -643,6 +643,98 @@ Some popular options include:
Model availability depends on your Azure region and subscription. Always check
the official Azure OpenAI documentation for regional availability before
implementing in production.
{{< /hint >}}
+### Gemini
+
+Google Gemini provides cloud-based chat models through the Gemini Developer
API and Vertex AI. The Flink Agents Gemini integration uses the official Google
Gen AI SDK and supports text conversations, system instructions, and tool
calling.
+
+{{< hint info >}}
+Gemini is only supported in Java currently. To use Gemini from Python agents,
see [Using Cross-Language Providers](#using-cross-language-providers).
+{{< /hint >}}
+
+#### Prerequisites
+
+1. For the Gemini Developer API, create an API key in [Google AI
Studio](https://aistudio.google.com/app/apikey)
+2. For Vertex AI, enable Vertex AI in your Google Cloud project and configure
Google Cloud credentials
+
+#### GeminiChatModelConnection Parameters
+
+{{< tabs "GeminiChatModelConnection Parameters" >}}
+
+{{< tab "Java" >}}
+
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `api_key` | String | Required unless `base_url` is set or `vertex_ai` is
`true` | Gemini Developer API key |
+| `base_url` | String | None | Custom endpoint, such as a proxy that injects
credentials |
+| `model` | String | None | Default model name, used when no model is supplied
per setup |
+| `timeout` | int | None | API request timeout in seconds |
+| `vertex_ai` | boolean | `false` | Use Vertex AI instead of the Gemini
Developer API |
+| `project` | String | None | Vertex AI project id |
+| `location` | String | None | Vertex AI location |
+
+{{< /tab >}}
+
+{{< /tabs >}}
+
+#### GeminiChatModelSetup Parameters
+
+{{< tabs "GeminiChatModelSetup Parameters" >}}
+
+{{< tab "Java" >}}
+
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `connection` | String | Required | Reference to connection method name |
+| `model` | String | `"gemini-3.1-pro-preview"` | Name of the chat model to
use |
+| `prompt` | Prompt \| String | None | Prompt template or reference to prompt
resource |
+| `tools` | List<String> | None | List of tool names available to the model |
+| `temperature` | double | `0.1` | Sampling temperature (0.0 to 2.0) |
+| `max_output_tokens` | long | `1024` | Maximum number of tokens to generate |
+| `additional_kwargs` | Map<String, Object> | `{}` | Additional Gemini
parameters (`top_k`, `top_p`, `stop_sequences`) |
+
+{{< /tab >}}
+
+{{< /tabs >}}
+
+#### Usage Example
+
+{{< tabs "Gemini Usage Example" >}}
+
+{{< tab "Java" >}}
+```java
+public class MyAgent extends Agent {
+ @ChatModelConnection
+ public static ResourceDescriptor geminiConnection() {
+ return
ResourceDescriptor.Builder.newBuilder(ResourceName.ChatModel.GEMINI_CONNECTION)
+ .addInitialArgument("api_key", System.getenv("GEMINI_API_KEY"))
+ .build();
+ }
+
+ @ChatModelSetup
+ public static ResourceDescriptor geminiChatModel() {
+ return
ResourceDescriptor.Builder.newBuilder(ResourceName.ChatModel.GEMINI_SETUP)
+ .addInitialArgument("connection", "geminiConnection")
+ .addInitialArgument("model", "gemini-3.1-pro-preview")
Review Comment:
The example and the table default (line 688) pin `gemini-3.1-pro-preview`,
matching the #718 code default. Since docs are the copy-paste surface, worth a
quick check it's generally callable? A verbatim paste would hit model-not-found
if it isn't GA yet. Not blocking — ignore if deliberate.
Otherwise, LGTM
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