ChatGPTのFunciton Callingとは？その機能や使い方を徹底解説

pip install openai

pip install tiktoken

pip install requests
pip install beautifulsoup4

import os
import openai
import tiktoken
import requests
import beautifulsoup4 # 今回は使いませんでしたが必要ならばimport しておくと良いでしょう。

def get_ai_news(query: str = 'artificial intelligence', category: str = None, date_range: str = None):
    """Retrieve latest AI news articles from NewsAPI"""
    base_url = "https://newsapi.org/v2/everything"
    api_key = os.environ.get('NEWSAPI_KEY')
    if not api_key:
        raise ValueError("NEWSAPI_KEY environment variable not set")
        
    headers = {
        "X-Api-Key": api_key
    }
    params = {
        'q': query,
        'category': category,
        'qInTitle': 'AI',
        'sortBy': 'publishedAt'
    }

    params = {k: v for k, v in params.items() if v is not None}

    response = requests.get(base_url, headers=headers, params=params)
    data = response.json()

    if data['status'] == 'ok':
        total_results = data['totalResults']
        print(f"Processing {total_results} articles from NewsAPI")
        return data['articles']
    else:
        message = data.get('message', 'No message provided')
        print("Request failed with message:", message)
        return []

signature_get_ai_news = {
    "name": "get_ai_news",
    "description": "Get the latest AI news articles by keyword, category, or date range",
    "parameters": {
        "type": "object",
        "properties": {
            "query": {
                "type": "string",
                "description": "Freeform keywords or a phrase to search for AI-related news.",
            },
            "category": {
                "type": "string",
                "description": "The category of AI news you want to get articles for",
                "enum": ["machine-learning", "natural-language-processing", "computer-vision", "robotics", "general"]
            },
            "date_range": {
                "type": "string",
                "description": "The date range for the news articles (e.g., last_week, last_month, last_year)"
            }
        },
        "required": [],
    }
}

from openai import OpenAI

client = OpenAI(api_key=os.environ.get('OPEN_AI_API_KEY'))

def complete(messages, function_call: str = "auto"):
    """Fetch completion from OpenAI's GPT"""
    llm_model = "gpt-3.5-turbo-16k"
    llm_max_tokens = 15500
    llm_system_prompt = "You are an assistant that provides news and headlines to user requests. Always try to get the latest breaking AI news stories using the available function calls."
    encoding_model_messages = "gpt-3.5-turbo-0613"
    encoding_model_strings = "cl100k_base"
    function_call_limit = 3

    ... 以下省略

print("\nこんにちは、私は AI ニュース アシスタントです。 あなたの指示に基づいて、最新の AI ニュース記事を提供できます。")
print("プロンプトの例をいくつか示します:\n - 機械学習における最近の進歩について教えてください\n - 自然言語処理に関する最新ニュースは何ですか?\n - コンピュータ ビジョンに関連する最近の AI ニュースを見せてください")

messages = []
while True:
    prompt = input("\n何について知りたいですか? =>")
    messages.append({"role": "user", "content": prompt})
    complete(messages, function_call="get_ai_news")

    print("\n==AI ニュース記事==\n")

    articles = messages[-1]["content"].split("\n")[:-1]

    for article in articles:
        article_dict = eval(article)
        print(f"Title: {article_dict['title']}")
        print(f"Link: {article_dict['url']}")
        print(f"Published: {article_dict['publishedAt']}")
        print()

こんにちは、私は AI ニュース アシスタントです。 あなたの指示に基づいて、最新の AI ニュース記事を提供できます。
プロンプトの例をいくつか示します:
 - 機械学習における最近の進歩について教えてください
 - 自然言語処理に関する最新ニュースは何ですか?
 - コンピュータ ビジョンに関連する最近の AI ニュースを見せてください

何について知りたいですか? => recent breakthroughs in machine learning
Working...

==AI ニュース記事==

----------------------------------------------------------------------------------------------------
Title: Revolutionizing Healthcare: How AI is Transforming Medical Diagnosis and Treatment
Link: https://www.example.com/ai-healthcare-breakthrough
Published: 2023-06-15T10:30:00Z

Title: Google's Latest AI Model Achieves Groundbreaking Results in Image Recognition
Link: https://www.techblog.com/googles-new-ai-image-recognition
Published: 2023-06-12T08:15:00Z

Title: MIT Researchers Develop AI System for Predicting Stock Market Trends with Unprecedented Accuracy
Link: https://www.mitnews.edu/ai-stock-market-prediction
Published: 2023-06-10T14:20:00Z

import openai

def multiply(x, y):
    return x * y

multiply_function = {
    "name": "multiply",
    "description": "Multiply two numbers",
    "parameters": {
        "type": "object",
        "properties": {
            "x": {"type": "number", "description": "The first number"},
            "y": {"type": "number", "description": "The second number"}
        },
        "required": ["x", "y"]
    }
}

# Call the OpenAI API with the function
response = openai.ChatCompletion.create(
    model="gpt-4-0613",
    messages=messages,
    functions=[multiply_function],
    function_call="auto"
)

# Check if the assistant called the function
function_result = response.choices[0].message.get("function_result")
if function_result:
    result = function_result.multiply_result
    print(f"The result is: {result['x']} * {result['y']} = {result['result']}")
else:
    print(response.choices[0].message.content)

def get_item_info(name_item, items):
    item_info = items.get(name_item)
    if item_info is not None:
        ret = json.dumps(item_info, ensure_ascii=False)
    else:
        ret = None

    return ret