example(functions): Add OpenAI functions example (#767)

examples/functions/functions-openai.py

@@ -0,0 +1,76 @@
+import openai
+import json
+
+# Example dummy function hard coded to return the same weather
+# In production, this could be your backend API or an external API
+def get_current_weather(location, unit="fahrenheit"):
+    """Get the current weather in a given location"""
+    weather_info = {
+        "location": location,
+        "temperature": "72",
+        "unit": unit,
+        "forecast": ["sunny", "windy"],
+    }
+    return json.dumps(weather_info)
+
+
+def run_conversation():
+    # Step 1: send the conversation and available functions to GPT
+    messages = [{"role": "user", "content": "What's the weather like in Boston?"}]
+    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 = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages=messages,
+        functions=functions,
+        function_call="auto",  # auto is default, but we'll be explicit
+    )
+    response_message = response["choices"][0]["message"]
+
+    # Step 2: check if GPT wanted to call a function
+    if response_message.get("function_call"):
+        # Step 3: call the function
+        # Note: the JSON response may not always be valid; be sure to handle errors
+        available_functions = {
+            "get_current_weather": get_current_weather,
+        }  # only one function in this example, but you can have multiple
+        function_name = response_message["function_call"]["name"]
+        fuction_to_call = available_functions[function_name]
+        function_args = json.loads(response_message["function_call"]["arguments"])
+        function_response = fuction_to_call(
+            location=function_args.get("location"),
+            unit=function_args.get("unit"),
+        )
+
+        # Step 4: send the info on the function call and function response to GPT
+        messages.append(response_message)  # extend conversation with assistant's reply
+        messages.append(
+            {
+                "role": "function",
+                "name": function_name,
+                "content": function_response,
+            }
+        )  # extend conversation with function response
+        second_response = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo",
+            messages=messages,
+        )  # get a new response from GPT where it can see the function response
+        return second_response
+
+
+print(run_conversation())