docs(providers): add DaoXE multi-model gateway guide

docs/providers/daoxe.md

@@ -0,0 +1,133 @@
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
+# DaoXE
+https://daoxe.com
+
+:::tip
+
+**LiteLLM supports DaoXE OpenAI-compatible models via `model=daoxe/<account-model-id>`.**
+
+DaoXE is a multi-model multi-protocol API gateway (OpenAI Chat Completions / Responses, Anthropic Messages for other clients). Model IDs are account-scoped — copy an exact ID from your DaoXE catalog or authenticated `GET /v1/models`. DaoXE is not available in mainland China.
+
+:::
+
+## API Key
+```python
+import os
+os.environ['DAOXE_API_KEY']
+# optional override:
+# os.environ['DAOXE_API_BASE']  # defaults to https://daoxe.com/v1
+```
+
+## Sample Usage
+```python
+from litellm import completion
+import os
+
+os.environ['DAOXE_API_KEY'] = ""
+response = completion(
+    model="daoxe/YOUR_ACCOUNT_MODEL_ID",
+    messages=[
+       {"role": "user", "content": "hello from litellm"}
+   ],
+    max_tokens=8,
+)
+print(response)
+```
+
+## Sample Usage - Streaming
+```python
+from litellm import completion
+import os
+
+os.environ['DAOXE_API_KEY'] = ""
+response = completion(
+    model="daoxe/YOUR_ACCOUNT_MODEL_ID",
+    messages=[
+       {"role": "user", "content": "hello from litellm"}
+   ],
+    stream=True,
+    max_tokens=8,
+)
+
+for chunk in response:
+    print(chunk)
+```
+
+## Sample Usage - Responses API
+```python
+from litellm import responses
+import os
+
+os.environ['DAOXE_API_KEY'] = ""
+response = responses(
+    model="daoxe/YOUR_ACCOUNT_MODEL_ID",
+    input="Reply with OK",
+)
+print(response)
+```
+
+## Usage with LiteLLM Proxy
+
+### 1. Set DaoXE on config.yaml
+
+```yaml
+model_list:
+  - model_name: daoxe
+    litellm_params:
+      model: daoxe/YOUR_ACCOUNT_MODEL_ID
+      api_key: "os.environ/DAOXE_API_KEY"
+```
+
+### 2. Start Proxy
+
+```
+litellm --config config.yaml
+```
+
+### 3. Test it
+
+<Tabs>
+<TabItem value="Curl" label="Curl Request">
+
+```shell
+curl --location 'http://0.0.0.0:4000/chat/completions' \
+--header 'Content-Type: application/json' \
+--data ' {
+      "model": "daoxe",
+      "messages": [
+        {
+          "role": "user",
+          "content": "what llm are you"
+        }
+      ],
+      "max_tokens": 8
+    }
+'
+```
+</TabItem>
+<TabItem value="openai" label="OpenAI v1.0.0+">
+
+```python
+import openai
+client = openai.OpenAI(
+    api_key="anything",
+    base_url="http://0.0.0.0:4000"
+)
+
+response = client.chat.completions.create(
+    model="daoxe",
+    messages=[{"role": "user", "content": "this is a test request"}],
+    max_tokens=8,
+)
+print(response)
+```
+</TabItem>
+</Tabs>
+
+## Notes
+
+- Prefer live model discovery over hardcoded lists
+- Disclosure: this page was contributed by someone affiliated with DaoXE
+- Public client examples: https://github.com/seven7763/DaoXE-AI

sidebars.js

@@ -1061,6 +1061,7 @@ const sidebars = {
         "providers/compactifai",
         "providers/crusoe",
         "providers/custom_llm_server",
+        "providers/daoxe",
         "providers/dashscope",
         "providers/databricks",
         "providers/datarobot",