오늘의어시 - 블로그 작성 어시

import gspread

client = gspread.authorize(creds)

# 구글 시트 열기
worksheet = client.open(SHEET_NAME).sheet1

# 첫 번째 행에서 열 이름을 찾아 해당 열 인덱스를 얻기
def get_column_index(column_name):
    first_row = worksheet.row_values(1)  # 첫 번째 행의 값 가져오기
    return first_row.index(column_name) + 1  # 열 번호는 1부터 시작하므로 1을 더해야 합니다.

def update_sheet_status(row_index, column_name, value):
    """시트의 상태를 업데이트하는 함수"""
    column_index = get_column_index(column_name)
    worksheet.update_cell(row_index + 2, column_index, value)

from langchain_openai import ChatOpenAI

chat_model = ChatOpenAI(model="gpt-4")

system_prompt = """Given the initial draft content provided by the user, generate a comprehensive and engaging blog post body that expands upon the draft with additional insights, explanations, and related content.
Make sure to structure the post in a way that is informative and engaging to the reader.
Incorporate the provided draft content seamlessly into the narrative, enhancing it with creative elements and factual information where appropriate.
The goal is to create a cohesive and compelling narrative that captures the reader's interest and provides valuable information on the topic.
All content must be written in Korean.
Please write the blog content in markdown format, tailored for a technical blog, including code snippets, bullet points, and headers to ensure clarity and enhance readability. Do not invent or create arbitrary source code or information; only expand upon and provide detailed and friendly explanations based on the information provided by the user.
"""

prompt_template = ChatPromptTemplate.from_messages(
    [("system", system_prompt),
    ("human", "{draft_content}")]
)

chain = (prompt_template
        | chat_model
        | StrOutputParser())

gen_content = chain.invoke({"draft_content" : draft_content})

PROCESS_FLOW = ["blog_content_generation", "github_upload"]
STATUS_FLOW = ["fetching", "running", "done"]

def proc_blog_content_generation():
    # 처리 로직
    pass

def proc_github_upload():
    # 처리 로직
    pass

tools = {
    "blog_content_generation" : proc_blog_content_generation,
    "github_upload" : proc_github_upload
}

for pf in PROCESS_FLOW:

    print(pf + "...")

    # pandas로 구글 시트 데이터 불러오기
    df = pd.DataFrame(worksheet.get_all_records())

    proc_invoke(pf, df)

    print("\nDone.")