docs: add Dify and update Kimi Code guides

apps/docs/content/guides/dify.mdx

@@ -0,0 +1,138 @@
+---
+title: Dify Integration
+description: Connect Dify's open-source LLM app development platform to LLM Gateway for AI-powered agents and workflows
+icon: Dify
+---
+
+import { Step, Steps } from "fumadocs-ui/components/steps";
+import { Callout } from "fumadocs-ui/components/callout";
+
+[Dify](https://dify.ai) is an open-source LLM app development platform that helps developers build and deploy production-grade AI agents, assistants, and workflow automations. By integrating Dify with LLM Gateway, you gain access to 210+ models (including GPT-5.5, Claude, Gemini, DeepSeek, and more) with built-in cost tracking, response caching, and automatic provider fallbacks.
+
+This guide walks you through connecting Dify to LLM Gateway using the custom OpenAI-compatible provider option.
+
+## Prerequisites
+
+- An LLM Gateway API key — [sign up free](https://llmgateway.io/signup) (no credit card required)
+- A Dify Cloud account or a self-hosted Dify instance
+
+## Setup
+
+<Steps>
+<Step>
+### Open Model Provider Settings
+
+Log in to your Dify dashboard. In the bottom-left corner of the sidebar, click on your profile picture or workspace name, and select **Settings**.
+
+Navigate to the **Model Provider** page to view your active and available LLM configurations.
+
+<img
+	src="/guides/dify/0-add-provider.png"
+	alt="Opening Model Provider Settings in Dify"
+	style={{ borderRadius: "8px", margin: "1.5rem 0" }}
+/>
+
+</Step>
+
+<Step>
+### Add Custom OpenAI-compatible Provider
+
+Scroll down to the **Custom Providers** section. Locate the **OpenAI-API-compatible** card and click **Setup** (or click **Add Custom Provider** and select **OpenAI-API-compatible**).
+
+<img
+	src="/guides/dify/1-configure-provider.png"
+	alt="Selecting OpenAI-compatible provider in Dify"
+	style={{ borderRadius: "8px", margin: "1.5rem 0" }}
+/>
+
+</Step>
+
+<Step>
+### Configure Provider Connection
+
+In the setup modal, configure the connection settings for LLM Gateway:
+
+- **Provider Name**: Enter `LLM Gateway`.
+- **API Endpoint URL**: Enter `https://api.llmgateway.io/v1`.
+- **API Key**: Paste your LLM Gateway API key (starts with `llmgtwy_`).
+
+<img
+	src="/guides/dify/2-add-model.png"
+	alt="Configuring LLM Gateway connection in Dify"
+	style={{ borderRadius: "8px", margin: "1.5rem 0" }}
+/>
+
+</Step>
+
+<Step>
+### Add Models
+
+Inside the same provider configuration, register the models you wish to use from the LLM Gateway catalog:
+
+1. Click **Add Model**.
+2. Set **Model Name** to your desired model identifier (e.g., `openai/gpt-4o-mini`, `anthropic/claude-3-5-sonnet`, `deepseek/deepseek-r1`).
+3. Set **Model Type** to **LLM**.
+4. Configure model capabilities (such as whether it supports system prompts, function calling, vision, etc.).
+5. Click **Save** to add the model.
+
+<img
+	src="/guides/dify/3-provider-added.png"
+	alt="Registering custom models in Dify"
+	style={{ borderRadius: "8px", margin: "1.5rem 0" }}
+/>
+
+<Callout type="info">
+	You can add multiple models to the same LLM Gateway provider block by
+	repeating this step for other model IDs in the catalog.
+</Callout>
+
+</Step>
+
+<Step>
+### Save and Verify Provider
+
+Once you have added your models and finished configuring the credentials, click **Save** in the main modal. LLM Gateway will now appear as an active provider in your Dify workspace.
+
+<img
+	src="/guides/dify/4-select-model.png"
+	alt="LLM Gateway active provider status in Dify"
+	style={{ borderRadius: "8px", margin: "1.5rem 0" }}
+/>
+
+</Step>
+
+<Step>
+### Use LLM Gateway Models in Apps
+
+Create a new application (chatbot, agent, or workflow) in Dify or open an existing one. In the top-right corner of the orchestrator/studio view, click the **Model** dropdown.
+
+Select **LLM Gateway** as the provider, and choose one of the custom models you registered (e.g., `gpt-4o-mini`).
+
+<img
+	src="/guides/dify/5-test-chat.png"
+	alt="Selecting LLM Gateway models in Dify app builder"
+	style={{ borderRadius: "8px", margin: "1.5rem 0" }}
+/>
+
+</Step>
+
+<Step>
+### Run and Monitor
+
+Try sending a message in the debug console to test your connection. Dify will route the prompt through LLM Gateway, allowing you to monitor real-time token usage, latency, and cost details in your LLM Gateway dashboard.
+
+<img
+	src="/guides/dify/6-chat-details.png"
+	alt="Verifying chat outputs and latency in Dify"
+	style={{ borderRadius: "8px", margin: "1.5rem 0" }}
+/>
+
+</Step>
+</Steps>
+
+## Why Use LLM Gateway with Dify?
+
+- **Access 210+ models** — Switch between OpenAI, Anthropic, Google Vertex, and open-source models with a single provider endpoint.
+- **Cost optimization** — Save up to 90% on selected models using LLM Gateway's developer volume pricing.
+- **Enterprise fallbacks** — Prevent system downtime by letting LLM Gateway route requests to a backup provider automatically if the primary provider goes offline.
+- **Prompt caching** — Automatically cache repeated workflow prompts to reduce execution latencies and save API costs.

apps/docs/content/guides/kimi-code.mdx

@@ -9,7 +9,7 @@ import { Callout } from "fumadocs-ui/components/callout";
 
 [Kimi Code CLI](https://github.com/MoonshotAI/kimi-code) is an open-source, AI-powered coding agent developed by Moonshot AI designed to automate software development tasks directly within your terminal. It can read and edit code, execute shell commands, search files, and autonomously manage complex coding workflows.
 
-By configuring Kimi Code CLI to use LLM Gateway, you can point it at any model—GPT-5, Gemini, Llama, Claude, or 210+ others—while keeping the same API formats Kimi Code expects, with full cost tracking in your dashboard.
+Kimi Code features first-class support for the **models.dev** registry, a community-maintained model catalog. This allows Kimi Code to query and configure LLM Gateway dynamically — fetching all compatible models, capabilities (such as thinking or vision), and pricing without requiring manual TOML editing.
 
 ## Prerequisites
 
@@ -49,119 +49,143 @@ kimi --version
 </Step>
 
 <Step>
-### Configure config.toml
+### Launch Kimi Code and Open the Provider Manager
 
-Create or edit your Kimi Code configuration file at `~/.kimi-code/config.toml` (on Windows, this is typically under `C:\Users\<YourUsername>\.kimi-code\config.toml`).
+Start the interactive terminal in your project directory:
 
-Add the `llmgateway` provider and define the models you want to use. Here is an example configuration that sets up **GPT-5.5**, **Claude Opus 4.6**, **DeepSeek V4 Pro**, **MiniMax M3**, and **Qwen3.7 Max**:
+```bash
+kimi
+```
 
-```toml
-default_model = "llmgateway/gpt-5.5"
+Once loaded, type the `/provider` command and press Enter. Select **Known third-party provider** to fetch the catalog from the registry:
 
-[providers.llmgateway]
-type = "openai"
-api_key = "llmgtwy_your_api_key_here"
-base_url = "https://api.llmgateway.io/v1"
+<img
+	src="/guides/kimi-code/0-add-provider.png"
+	alt="Opening Provider Manager in Kimi Code"
+	style={{ borderRadius: "8px", margin: "1.5rem 0" }}
+/>
 
-[models."llmgateway/gpt-5.5"]
-provider = "llmgateway"
-model = "gpt-5.5"
-max_context_size = 1050000
-max_output_size = 128000
-capabilities = [ "image_in", "thinking", "tool_use" ]
-display_name = "GPT-5.5"
+</Step>
 
-[models."llmgateway/claude-opus-4-6"]
-provider = "llmgateway"
-model = "claude-opus-4-6"
-max_context_size = 1000000
-max_output_size = 128000
-capabilities = [ "image_in", "thinking", "tool_use" ]
-display_name = "Claude Opus 4.6"
+<Step>
+### Select LLM Gateway
 
-[models."llmgateway/deepseek-v4-pro"]
-provider = "llmgateway"
-model = "deepseek-v4-pro"
-max_context_size = 1050000
-max_output_size = 393216
-capabilities = [ "thinking", "tool_use" ]
-display_name = "DeepSeek V4 Pro"
+Type `llm` to filter the providers and select **LLM Gateway** from the list:
 
-[models."llmgateway/minimax-m3"]
-provider = "llmgateway"
-model = "minimax-m3"
-max_context_size = 1048576
-max_output_size = 131072
-capabilities = [ "image_in", "thinking", "tool_use" ]
-display_name = "MiniMax M3"
+<img
+	src="/guides/kimi-code/1-select-provider.png"
+	alt="Selecting LLM Gateway in Kimi Code"
+	style={{ borderRadius: "8px", margin: "1.5rem 0" }}
+/>
 
-[models."llmgateway/qwen3.7-max"]
-provider = "llmgateway"
-model = "qwen3.7-max"
-max_context_size = 1000000
-max_output_size = 65536
-capabilities = [ "thinking", "tool_use" ]
-display_name = "Qwen3.7 Max"
-```
+</Step>
+
+<Step>
+### Enter Your API Key
+
+When prompted, paste your LLM Gateway API key and press Enter. Kimi Code will save it securely to your local configuration:
 
 <img
-	src="/guides/kimi-code/0-config.png"
-	alt="Configuring config.toml"
+	src="/guides/kimi-code/2-enter-key.png"
+	alt="Entering LLM Gateway API Key"
 	style={{ borderRadius: "8px", margin: "1.5rem 0" }}
 />
 
 <Callout type="info">
-	Replace `llmgtwy_your_api_key_here` with your actual LLM Gateway API key from
-	the dashboard.
+	Your credentials are saved locally to `~/.kimi-code/config.toml`.
 </Callout>
 
 </Step>
 
 <Step>
-### Run Kimi Code CLI
+### Select a Model and Toggle Thinking
 
-Navigate to your project folder and launch the interactive terminal:
+The LLM Gateway catalog is now loaded. Use the arrow keys to browse or type to search for your desired model. Select the `llmgateway` tab to view only LLM Gateway models.
 
-```bash
-kimi
-```
+You can also toggle the **Thinking** option (On/Off) at the bottom depending on the model's capabilities:
 
-All requests will now be routed through LLM Gateway, allowing you to use advanced models for local autonomous coding while showing real-time usage and cost statistics on your LLM Gateway dashboard.
+<img
+	src="/guides/kimi-code/3-select-model.png"
+	alt="Browsing LLM Gateway Models"
+	style={{ borderRadius: "8px", margin: "1.5rem 0" }}
+/>
+
+For example, type `gpt-5.5` to find the latest reasoning model, select it, and press Enter:
 
 <img
-	src="/guides/kimi-code/1-chat.png"
-	alt="Running Kimi Code with LLM Gateway"
+	src="/guides/kimi-code/4-select-gpt-model.png"
+	alt="Selecting GPT-5.5 Model"
 	style={{ borderRadius: "8px", margin: "1.5rem 0" }}
 />
 
+</Step>
+
+<Step>
+### Start Coding
+
+All set! Kimi Code is now configured. Your requests will be securely routed through LLM Gateway, allowing you to use advanced models for local autonomous coding while showing real-time usage and cost statistics on your LLM Gateway dashboard.
+
+<img
+	src="/guides/kimi-code/5-chat.png"
+	alt="Running Kimi Code CLI session"
+	style={{ borderRadius: "8px", margin: "1.5rem 0" }}
+/>
+
+Use `/model` in the terminal session at any time to switch models.
+
 </Step>
 </Steps>
 
-## Configuration Details
+## Manual Configuration (Advanced)
 
-### The Providers Section
+If you prefer to configure your environment manually without using the interactive provider manager, you can write settings directly to your configuration file at `~/.kimi-code/config.toml` (or `C:\Users\<YourUsername>\.kimi-code\config.toml` on Windows).
 
-To connect to LLM Gateway, define a custom provider with `type = "openai"` and specify the base URL pointing to the LLM Gateway endpoint.
+Here is an example TOML configuration that registers **GPT-5.5**, **Claude 3.7 Sonnet**, **DeepSeek R1**, and **Qwen3.7 Max** manually:
 
 ```toml
+default_model = "llmgateway/gpt-5.5"
+
 [providers.llmgateway]
 type = "openai"
 api_key = "llmgtwy_your_api_key_here"
 base_url = "https://api.llmgateway.io/v1"
-```
 
-### Defining Custom Models
+[models."llmgateway/gpt-5.5"]
+provider = "llmgateway"
+model = "gpt-5.5"
+max_context_size = 1050000
+max_output_size = 128000
+capabilities = [ "thinking", "tool_use" ]
+display_name = "GPT-5.5"
 
-For each model you want to access, add a `[models."<provider_name>/<model_identifier>"]` block:
+[models."llmgateway/claude-3.7-sonnet"]
+provider = "llmgateway"
+model = "claude-3.7-sonnet"
+max_context_size = 200000
+max_output_size = 8192
+capabilities = [ "image_in", "thinking", "tool_use" ]
+display_name = "Claude 3.7 Sonnet"
 
-- **provider**: Must match the provider key under `[providers.<key>]` (e.g. `llmgateway`).
-- **model**: The exact model ID from the LLM Gateway catalog.
-- **capabilities**: An array containing capabilities the model supports, such as `"image_in"`, `"thinking"`, and `"tool_use"`.
-- **max_context_size**: The maximum context window of the model.
+[models."llmgateway/deepseek-r1"]
+provider = "llmgateway"
+model = "deepseek-r1"
+max_context_size = 131072
+max_output_size = 8192
+capabilities = [ "thinking", "tool_use" ]
+display_name = "DeepSeek R1"
+
+[models."llmgateway/qwen3.7-max"]
+provider = "llmgateway"
+model = "qwen3.7-max"
+max_context_size = 1000000
+max_output_size = 65536
+capabilities = [ "thinking", "tool_use" ]
+display_name = "Qwen3.7 Max"
+```
 
 ## Why Use LLM Gateway with Kimi Code CLI
 
-- **210+ models** — Access GPT-5, Gemini, Llama, DeepSeek, and more in a single CLI configuration.
+- **210+ models** — Access GPT-5.5, Gemini, Llama, DeepSeek, and more in a single CLI configuration.
 - **Unified cost tracking** — Get a detailed breakdown of costs per prompt and session in your dashboard.
 - **Response caching** — Automatically cache repeated requests (such as parsing or building commands) to save API costs.
 - **Automatic fallback** — Keep coding even if a provider encounters temporary downtime.

apps/docs/lib/custom-icons.tsx

@@ -341,4 +341,18 @@ export const customIcons: Record<string, IconComponent> = {
 			/>
 		</svg>
 	),
+	Dify: (props) => (
+		<svg
+			style={{ flex: "none", lineHeight: "1" }}
+			role="img"
+			viewBox="0 0 24 24"
+			xmlns="http://www.w3.org/2000/svg"
+			{...props}
+		>
+			<path
+				fill="currentColor"
+				d="m22.417 9.334-1.333 4.333-1.334-4.333h-1.583L20.1 14.94c.2.583-.14 1.06-.756 1.06h-.678v1.334h.996c.869 0 1.65-.55 1.945-1.367L24 9.334ZM2.833 6.667H0v8.666h2.833c3.5 0 4.5-2 4.5-4.333s-1-4.334-4.5-4.334zM2.866 14H1.6V8h1.266c2.013 0 2.867.988 2.867 3s-.854 3-2.867 3m11-5.267v.6h-1.532v1.334h1.533V14h-2.534V9.334H8v1.334h1.867V14h-2.2v1.334h10V14h-2.332v-3.333h2.333V9.334h-2.333V8h2.333V6.667h-1.733a2.07 2.07 0 0 0-2.067 2.067Zm-3.266-.2c.681 0 .933-.417.933-.933 0-.515-.252-.933-.933-.933-.68 0-.934.418-.934.933s.253.934.934.934"
+			/>
+		</svg>
+	),
 };