docs(lm_studio.md): add doc on lm studio support

docs/my-website/docs/providers/lm_studio.md

@@ -0,0 +1,130 @@
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
+# LM Studio
+
+https://lmstudio.ai/docs/basics/server
+
+:::tip
+
+**We support ALL LM Studio models, just set `model=lm_studio/<any-model-on-lmstudio>` as a prefix when sending litellm requests**
+
+:::
+
+## API Key
+```python
+# env variable
+os.environ['LM_STUDIO_API_BASE']
+os.environ['LM_STUDIO_API_KEY'] # optional, default is empty
+```
+
+## Sample Usage
+```python
+from litellm import completion
+import os
+
+os.environ['LM_STUDIO_API_BASE'] = ""
+
+response = completion(
+    model="lm_studio/llama-3-8b-instruct",
+    messages=[
+        {
+            "role": "user",
+            "content": "What's the weather like in Boston today in Fahrenheit?",
+        }
+    ]
+)
+print(response)
+```
+
+## Sample Usage - Streaming
+```python
+from litellm import completion
+import os
+
+os.environ['XAI_API_KEY'] = ""
+response = completion(
+    model="lm_studio/llama-3-8b-instruct",
+    messages=[
+        {
+            "role": "user",
+            "content": "What's the weather like in Boston today in Fahrenheit?",
+        }
+    ],
+    stream=True,
+)
+
+for chunk in response:
+    print(chunk)
+```
+
+
+## Usage with LiteLLM Proxy Server
+
+Here's how to call a XAI model with the LiteLLM Proxy Server
+
+1. Modify the config.yaml 
+
+  ```yaml
+  model_list:
+    - model_name: my-model
+      litellm_params:
+        model: lm_studio/<your-model-name>  # add lm_studio/ prefix to route as LM Studio provider
+        api_key: api-key                 # api key to send your model
+  ```
+
+
+2. Start the proxy 
+
+  ```bash
+  $ litellm --config /path/to/config.yaml
+  ```
+
+3. Send Request to LiteLLM Proxy Server
+
+  <Tabs>
+
+  <TabItem value="openai" label="OpenAI Python v1.0.0+">
+
+  ```python
+  import openai
+  client = openai.OpenAI(
+      api_key="sk-1234",             # pass litellm proxy key, if you're using virtual keys
+      base_url="http://0.0.0.0:4000" # litellm-proxy-base url
+  )
+
+  response = client.chat.completions.create(
+      model="my-model",
+      messages = [
+          {
+              "role": "user",
+              "content": "what llm are you"
+          }
+      ],
+  )
+
+  print(response)
+  ```
+  </TabItem>
+
+  <TabItem value="curl" label="curl">
+
+  ```shell
+  curl --location 'http://0.0.0.0:4000/chat/completions' \
+      --header 'Authorization: Bearer sk-1234' \
+      --header 'Content-Type: application/json' \
+      --data '{
+      "model": "my-model",
+      "messages": [
+          {
+          "role": "user",
+          "content": "what llm are you"
+          }
+      ],
+  }'
+  ```
+  </TabItem>
+
+  </Tabs>
+
+

docs/my-website/sidebars.js

@@ -156,6 +156,7 @@ const sidebars = {
         "providers/predibase",
         "providers/nvidia_nim", 
         "providers/xai",
+        "providers/lm_studio",
         "providers/cerebras", 
         "providers/volcano", 
         "providers/triton-inference-server",