docs: add Kenari provider page

docs/providers/kenari.md

@@ -0,0 +1,124 @@
+# Kenari
+
+## Overview
+
+| Property | Details |
+|-------|-------|
+| Description | Kenari is an OpenAI-compatible LLM gateway with Indonesian Rupiah (IDR) billing, serving models from DeepSeek, GLM, Kimi, Qwen, Claude, GPT and others through one endpoint. |
+| Provider Route on LiteLLM | `kenari/` |
+| Link to Provider Doc | [Kenari Docs ↗](https://kenari.id/docs) |
+| Base URL | `https://kenari.id/v1` |
+| Supported Operations | [`/chat/completions`](#sample-usage) |
+
+<br />
+
+## What is Kenari?
+
+Kenari is an LLM gateway that offers:
+- **One API for many models**: DeepSeek, GLM, Kimi, Qwen, Claude, GPT and more behind a single OpenAI-compatible endpoint
+- **IDR wallet billing**: prepaid Indonesian Rupiah balance, QRIS top-up
+- **OpenAI-compatible API**: works with existing OpenAI SDK code
+- **Streaming support**: real-time response streaming
+- **Tool calling**: function calling on supported models
+
+## Required Variables
+
+```python showLineNumbers title="Environment Variables"
+os.environ["KENARI_API_KEY"] = ""  # your Kenari API key (kn-...)
+```
+
+Get your Kenari API key from the [kenari.id dashboard](https://kenari.id).
+
+## Usage - LiteLLM Python SDK
+
+### Non-streaming
+
+```python showLineNumbers title="Kenari Non-streaming Completion"
+import os
+import litellm
+from litellm import completion
+
+os.environ["KENARI_API_KEY"] = ""  # your Kenari API key
+
+messages = [{"content": "What is the capital of Indonesia?", "role": "user"}]
+
+# Kenari call
+response = completion(
+    model="kenari/deepseek-v4-flash",
+    messages=messages
+)
+
+print(response)
+```
+
+### Streaming
+
+```python showLineNumbers title="Kenari Streaming Completion"
+import os
+import litellm
+from litellm import completion
+
+os.environ["KENARI_API_KEY"] = ""  # your Kenari API key
+
+messages = [{"content": "Write a short poem about the sea.", "role": "user"}]
+
+# Kenari call with streaming
+response = completion(
+    model="kenari/deepseek-v4-flash",
+    messages=messages,
+    stream=True
+)
+
+for chunk in response:
+    print(chunk.choices[0].delta.content or "", end="")
+```
+
+## Usage - LiteLLM Proxy
+
+Add the following to your LiteLLM Proxy configuration file:
+
+```yaml showLineNumbers title="config.yaml"
+model_list:
+  - model_name: deepseek-v4-flash
+    litellm_params:
+      model: kenari/deepseek-v4-flash
+      api_key: os.environ/KENARI_API_KEY
+```
+
+Start your LiteLLM Proxy server:
+
+```bash showLineNumbers title="Start LiteLLM Proxy"
+litellm --config config.yaml
+
+# RUNNING on http://0.0.0.0:4000
+```
+
+```python showLineNumbers title="Kenari via Proxy"
+import openai
+
+client = openai.OpenAI(
+    api_key="your-litellm-proxy-api-key",
+    base_url="http://localhost:4000"
+)
+
+response = client.chat.completions.create(
+    model="deepseek-v4-flash",
+    messages=[{"role": "user", "content": "Hello!"}]
+)
+
+print(response.choices[0].message.content)
+```
+
+## Overriding the API Base
+
+Point LiteLLM at a different Kenari-compatible deployment with `KENARI_API_BASE`:
+
+```python showLineNumbers title="Custom API Base"
+import os
+
+os.environ["KENARI_API_BASE"] = "https://your-deployment.example.com/v1"
+```
+
+## Available Models
+
+The live model list is served at [`https://kenari.id/v1/models`](https://kenari.id/v1/models). Use any listed model id with the `kenari/` prefix, for example `kenari/deepseek-v4-pro` or `kenari/glm-5-2`.

sidebars.js

@@ -1021,6 +1021,7 @@ const sidebars = {
         "providers/inception",
         "providers/infinity",
         "providers/jina_ai",
+        "providers/kenari",
         "providers/lambda_ai",
         "providers/langgraph",
         "providers/lemonade",