(docs) add function calling examples and function_to_dict

docs/my-website/docs/completion/function_call.md

@@ -0,0 +1,106 @@
+# Function Calling 
+LiteLLM only supports: OpenAI gpt-4-0613 and gpt-3.5-turbo-0613 for function calling 
+## Quick Start 
+```python
+import os, litellm
+from litellm import completion
+
+os.environ['OPENAI_API_KEY'] = ""
+
+messages = [
+    {"role": "user", "content": "What is the weather like in Boston?"}
+]
+
+def get_current_weather(location):
+  if location == "Boston, MA":
+    return "The weather is 12F"
+
+functions = [
+    {
+      "name": "get_current_weather",
+      "description": "Get the current weather in a given location",
+      "parameters": {
+        "type": "object",
+        "properties": {
+          "location": {
+            "type": "string",
+            "description": "The city and state, e.g. San Francisco, CA"
+          },
+          "unit": {
+            "type": "string",
+            "enum": ["celsius", "fahrenheit"]
+          }
+        },
+        "required": ["location"]
+      }
+    }
+  ]
+
+response = completion(model="gpt-3.5-turbo-0613", messages=messages, functions=functions)
+print(response)
+```
+
+## Using - litellm.utils.function_to_dict
+`function_to_dict` allows you to pass a function docstring and produce a dictionary usable for OpenAI function calling
+
+### Usage
+Define your function, use `litellm.utils.function_to_dict` to convert your function to a dictionary usable for OpenAI 
+
+```python
+def get_current_weather(location: str, unit: str):
+        """Get the current weather in a given location
+
+        Parameters
+        ----------
+        location : str
+            The city and state, e.g. San Francisco, CA
+        unit : {'celsius', 'fahrenheit'}
+            Temperature unit
+
+        Returns
+        -------
+        str
+            a sentence indicating the weather
+        """
+        if location == "Boston, MA":
+            return "The weather is 12F"
+    function_json = litellm.utils.function_to_dict(get_current_weather)
+    print(function_json)
+```
+
+#### Output
+```json
+{
+    'name': 'get_current_weather', 
+    'description': 'Get the current weather in a given location', 
+    'parameters': {
+        'type': 'object', 
+        'properties': {
+            'location': {'type': 'string', 'description': 'The city and state, e.g. San Francisco, CA'}, 
+            'unit': {'type': 'string', 'description': 'Temperature unit', 'enum': "['fahrenheit', 'celsius']"}
+        }, 
+        'required': ['location', 'unit']
+    }
+}
+```
+
+### Using function_to_dict with Function calling
+```python
+import os, litellm
+from litellm import completion
+
+os.environ['OPENAI_API_KEY'] = ""
+
+messages = [
+    {"role": "user", "content": "What is the weather like in Boston?"}
+]
+
+def get_current_weather(location):
+  if location == "Boston, MA":
+    return "The weather is 12F"
+
+functions = litellm.utils.function_to_dict(get_current_weather)
+
+response = completion(model="gpt-3.5-turbo-0613", messages=messages, functions=functions)
+print(response)
+```

docs/my-website/sidebars.js

@@ -31,14 +31,15 @@ const sidebars = {
         "completion/input", 
         "completion/prompt_formatting",
         "completion/output", 
+        "exception_mapping",
         "completion/stream", 
         "completion/message_trimming",
+        "completion/function_call",
         "completion/model_alias", 
         "completion/reliable_completions", 
         "completion/config",
         "completion/batching",
         "completion/mock_requests",
-        "exception_mapping",
       ],
     },
     {