我做出了自己的第一個 LLM application！

from dotenv import load_dotenv
load_dotenv()

from anthropic import Anthropic

client = Anthropic()
model = "claude-sonnet-4-5"

message = client.messages.create(
    model=model,
    max_tokens=1000,
    messages=[
        {
            "role": "user",
            "content": "Extract the job fields from the following job description:\n\n" + job_description
        }
    ]
)

def add_user_message(messages, text):
    user_message = {"role": "user", "content": text}
    messages.append(user_message)

def add_assistant_message(messages, text):
    assistant_message = {"role": "assistant", "content": text}
    messages.append(assistant_message)

def chat(messages):
    message = client.messages.create(
        model=model,
        max_tokens=1000,
        messages=messages,
    )
    return message.content[0].text

# Start with an empty message list
messages = []

# Add the initial user question
add_user_message(messages, "Extract the job fields from the following job description:\n\n" + job_description)

# Get Claude's response
answer = chat(messages)

# Add Claude's response to the conversation history
add_assistant_message(messages, answer)

# Add a follow-up question
add_user_message(messages, "Explain how you infer frontend_percent.")

# Get the follow-up response with full context
final_answer = chat(messages)

You are a JD extractor.
Given a job description, you will extract the following fields:
- job_title: The title of the job position.
- company: The name of the company offering the job.
- location: The location of the job.
- frontend_percent: The percentage of the job that involves frontend development (0-100).
- frontend_percent_inferred: A boolean indicating whether the frontend_percent was inferred or explicitly stated.
- on_call: A string indicating whether the job requires on-call duties ("yes", "no", or "not_mentioned").
- on_call_details: Additional details about on-call duties, if mentioned.
- tech_stack: A list of technologies and programming languages required for the job.
- ai_requirement: An object containing:
  - level: A string indicating the level of AI requirement ("required", "preferred", "mentioned", or "not_mentioned").
  - details: A list of specific AI-related skills or requirements mentioned in the job description.

system_prompt = """
You are a JD extractor.
...
"""

client.messages.create(
    model=model,
    messages=messages,
    max_tokens=1000,
    system=system_prompt
)