docs(instructor.md): tutorial on using litellm with instructor

docs/my-website/docs/tutorials/instructor.md

@@ -0,0 +1,95 @@
+# Instructor - Function Calling
+
+Use LiteLLM Router with [jxnl's instructor library](https://github.com/jxnl/instructor) for function calling in prod. 
+
+## Usage
+
+```python
+import litellm
+from litellm import Router
+import instructor
+from pydantic import BaseModel
+
+litellm.set_verbose = True # 👈 print DEBUG LOGS
+
+client = instructor.patch(
+    Router(
+        model_list=[
+            {
+                "model_name": "gpt-3.5-turbo",  openai model name
+                "litellm_params": {  params for litellm completion/embedding call
+                    "model": "azure/chatgpt-v-2",
+                    "api_key": os.getenv("AZURE_API_KEY"),
+                    "api_version": os.getenv("AZURE_API_VERSION"),
+                    "api_base": os.getenv("AZURE_API_BASE"),
+                },
+            }
+        ]
+    )
+)
+
+
+class UserDetail(BaseModel):
+    name: str
+    age: int
+
+
+user = client.chat.completions.create(
+    model="gpt-3.5-turbo",
+    response_model=UserDetail,
+    messages=[
+        {"role": "user", "content": "Extract Jason is 25 years old"},
+    ],
+)
+
+assert isinstance(user, UserDetail)
+assert user.name == "Jason"
+assert user.age == 25
+
+print(f"user: {user}")
+```
+
+## Async Calls
+
+```python
+import litellm
+from litellm import Router
+import instructor, asyncio
+from pydantic import BaseModel
+
+aclient = instructor.apatch(
+    Router(
+        model_list=[
+            {
+                "model_name": "gpt-3.5-turbo",
+                "litellm_params": {
+                    "model": "azure/chatgpt-v-2",
+                    "api_key": os.getenv("AZURE_API_KEY"),
+                    "api_version": os.getenv("AZURE_API_VERSION"),
+                    "api_base": os.getenv("AZURE_API_BASE"),
+                },
+            }
+        ],
+        default_litellm_params={"acompletion": True}, # 👈 IMPORTANT - tells litellm to route to async completion function.
+    )
+)
+
+
+class UserExtract(BaseModel):
+    name: str
+    age: int
+
+
+async def main():
+    model = await aclient.chat.completions.create(
+        model="gpt-3.5-turbo",
+        response_model=UserExtract,
+        messages=[
+            {"role": "user", "content": "Extract jason is 25 years old"},
+        ],
+    )
+    print(f"model: {model}")
+
+
+asyncio.run(main())
+```

docs/my-website/sidebars.js

@@ -188,6 +188,7 @@ const sidebars = {
       label: 'Tutorials',
       items: [
         'tutorials/azure_openai',
+        'tutorials/instructor',
         'tutorials/oobabooga',
         "tutorials/gradio_integration",
         'tutorials/huggingface_codellama',