LLM API 상호작용(OpenAI, Anthropic)

Why Use LLM APIs?

API Keys: Your Access Pass

OpenAI API: Initial Setup

import os
# It's best practice to load from an environment variable
# e.g., export OPENAI_API_KEY='sk-your-key-here'

# This line is usually enough if OPENAI_API_KEY is set
# The client automatically picks it up.
# If you need to set it manually in code (NOT recommended for production):
# from openai import OpenAI
# client = OpenAI(api_key="YOUR_ACTUAL_API_KEY")

print("OpenAI client library installed and ready!")
print("Ensure OPENAI_API_KEY is set as an environment variable.")

OpenAI API: First Chat Completion

from openai import OpenAI
import os

# Initialize the client. It will automatically pick up OPENAI_API_KEY
# from your environment variables if it's set.
client = OpenAI()

def get_completion(prompt_text):
    response = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[
            {"role": "user", "content": prompt_text}
        ],
        temperature=0.7,
        max_tokens=50
    )
    return response.choices[0].message.content

if __name__ == "__main__":
    # Make sure you have your OPENAI_API_KEY set as an environment variable
    # before running this code.
    if "OPENAI_API_KEY" not in os.environ:
        print("Error: OPENAI_API_KEY environment variable not set.")
        print("Please set it before running this script.")
    else:
        user_prompt = "What is the capital of France?"
        print(f"User: {user_prompt}")
        llm_response = get_completion(user_prompt)
        print(f"LLM: {llm_response}")

OpenAI: Key Parameters

OpenAI: Understanding Message Roles

from openai import OpenAI
import os

client = OpenAI()

def get_contextual_completion(messages_list):
    response = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=messages_list,
        temperature=0.7,
        max_tokens=70
    )
    return response.choices[0].message.content

if __name__ == "__main__":
    if "OPENAI_API_KEY" not in os.environ:
        print("Error: OPENAI_API_KEY environment variable not set.")
        print("Please set it before running this script.")
    else:
        conversation_history = [
            {"role": "system", "content": "You are a helpful assistant that provides short, factual answers."},
            {"role": "user", "content": "What is the capital of Japan?"},
            {"role": "assistant", "content": "The capital of Japan is Tokyo."},
            {"role": "user", "content": "And of Germany?"}
        ]
        print("Current conversation:")
        for msg in conversation_history:
            print(f"{msg['role'].capitalize()}: {msg['content']}")

        llm_response = get_contextual_completion(conversation_history)
        print(f"Assistant: {llm_response}")

Anthropic API: Initial Setup

import os
# It's best practice to load from an environment variable
# e.g., export ANTHROPIC_API_KEY='sk-ant-your-key-here'

# The client automatically picks it up if ANTHROPIC_API_KEY is set.
# If you need to set it manually in code (NOT recommended for production):
# from anthropic import Anthropic
# client = Anthropic(api_key="YOUR_ACTUAL_ANTHROPIC_API_KEY")

print("Anthropic client library installed and ready!")
print("Ensure ANTHROPIC_API_KEY is set as an environment variable.")

Anthropic API: First Messages Call

from anthropic import Anthropic
import os

# Initialize the client. It will automatically pick up ANTHROPIC_API_KEY
# from your environment variables if it's set.
client = Anthropic()

def get_claude_completion(prompt_text):
    response = client.messages.create(
        model="claude-3-haiku-20240307", # A fast, cheaper Claude model
        max_tokens=50,
        temperature=0.7,
        messages=[
            {"role": "user", "content": prompt_text}
        ]
    )
    return response.content[0].text

if __name__ == "__main__":
    # Make sure you have your ANTHROPIC_API_KEY set as an environment variable
    # before running this code.
    if "ANTHROPIC_API_KEY" not in os.environ:
        print("Error: ANTHROPIC_API_KEY environment variable not set.")
        print("Please set it before running this script.")
    else:
        user_prompt = "Tell me a very short fun fact about space."
        print(f"User: {user_prompt}")
        claude_response = get_claude_completion(user_prompt)
        print(f"Claude: {claude_response}")

Anthropic: Key Parameters & Roles

API Interaction Check

Recap: Connecting to LLMs