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- import openai
- import json
- openai.api_key = "EMPTY"
- openai.api_base = "http://luigi.millennium.berkeley.edu:8000/v1"
- # 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 the two cities of Boston and San Francisco?"}]
- 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"],
- },
- }
- ]
- completion = openai.ChatCompletion.create(
- model='gorilla-openfunctions-v2',
- messages=messages,
- functions=functions,
- function_call="auto", # auto is default, but we'll be explicit
- )
-
- print("--------------------")
- print(f"Function call strings(s): {completion.choices[0].message.content}")
- print("--------------------")
- print(f"OpenAI compatible `function_call`: {completion.choices[0].message.function_call}")
- run_conversation()
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