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200 | import ollama
from openpyxl import Workbook, load_workbook
import json
import os
# === Function Calling Schema ===
functions = [
{
"type":"function",
"function": {
"name":"suggest_pass_adjustment",
"description": "對於 59 分學生，詢問是否補到 60 分",
"parameters": {
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "學生姓名(name)"
}
},
"required": ["name"]
}
}
},
{
"type": "function",
"function": {
"name":"suggest_remedial_adjustment",
"description": "對於低於 59 分學生，詢問是否補分，以及新分數",
"parameters": {
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "學生姓名(name)"
},
"current_score": {"type": "integer"}
},
"required": ["name", "current_score"]
}
}
},
{
"type": "function",
"function": {
"name":"suggest_edit_for_passed",
"description": "詢問是否要修改分數大於60分，及格學生的分數",
"parameters": {
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "學生姓名(name)"
},
"current_score": {"type": "integer"}
},
"required": ["name", "current_score"]
}
}
},
{
"type": "function",
"function": {
"name":"suggest_apply_adjustment",
"description": "將學生分數更新為指定的新分數",
"parameters": {
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "學生姓名(name)"
},
"new_score": {"type": "integer"}
},
"required": ["name", "new_score"]
}
}
},
]
# === 初始化成績表（如不存在）===
filename = "grades.xlsx"
if not os.path.exists(filename):
wb = Workbook()
ws = wb.active
ws.title = "成績表"
ws.append(["姓名", "分數"])
ws.append(["王小明", 59])
ws.append(["林小美", 73])
ws.append(["張大文", 45])
wb.save(filename)
print(f"✅ 已建立初始成績檔：{filename}")
else:
print(f"📥 已載入成績檔：{filename}")
# === GPT 對應的處理函式 ===
# 以下四個函式為 GPT 根據不同情況呼叫的處理邏輯
# 建議學生逐步閱讀與理解：輸入、邏輯、Excel 修改方式
def handle_pass_adjustment(row, name):
ans = input(f"{name} 的分數是 59，是否補及格至 60？（Y/n）：")
if ans.lower() in ["y", "yes", ""]:
row[1].value = 60
print(f"✅ {name} 已補及格（60 分）")
return f"{name} 補及格至 60 分 建議多加強"
else:
print("🟡 未調整")
return f"{name} 未補及格"
def handle_remedial_adjustment(row, name, score):
ans = input(f"{name} 的分數是 {score}，是否補分？（Y/n）：")
if ans.lower() in ["y", "yes", ""]:
try:
new_score = int(input("👉 請輸入補分後的新分數："))
row[1].value = new_score
print(f"✅ 已將 {name} 改為 {new_score} 分")
return f"{name} 補分為 {new_score} 分 建議多加強"
except:
print("⚠️ 格式錯誤，略過")
return f"{name} 補分輸入錯誤，未調整"
else:
print("🟡 未調整")
return f"{name} 未補分"
def handle_edit_for_passed(row, name, score):
ans = input(f"{name} 成績為 {score} 分，是否要修改？（輸入新分數或按 Enter 跳過）：")
if ans.strip():
try:
new_score = int(ans)
row[1].value = new_score
print(f"✅ 已將 {name} 改為 {new_score} 分")
return f"{name} 改為 {new_score} 分"
except:
print("⚠️ 格式錯誤，略過")
return f"{name} 修改輸入錯誤，未調整"
else:
print("✅ 保留原分數")
return f"{name} 保留原分數 {score} 分"
def handle_apply_adjustment(row, name, new_score):
row[1].value = new_score
print(f"✅ GPT 決定將 {name} 的分數改為 {new_score}")
return f"{name} 的分數改為 {new_score}"
# === 以下請同學補寫 main loop ===
# - 使用 for row in ws.iter_rows(min_row=2): 遍歷每位學生
# - 呼叫 GPT 的 chat.completions.create 傳入使用者輸入與 function schema
# - 根據 GPT 回傳的 function_call.name 判斷要呼叫哪一個處理函式
# - 最後將分數儲存為 grades_final.xlsx
# 提示：請將回傳的 arguments 用 json.loads(...) 解析後取出參數
wb = load_workbook(filename)
ws = wb.active
for row in ws.iter_rows(min_row=2):
name = row[0].value
score = row[1].value
user_input = f"{name} 的分數是 {score}"
response = ollama.chat(
model="llama3.2",
messages=[{"role": "user", "content": user_input}],
tools=functions,
)
if hasattr(response, "message") and hasattr(response.message, "tool_calls") and response.message.tool_calls:
tool_call = response.message.tool_calls[0]
func_name = tool_call['function']['name']
args = tool_call['function']['arguments']
if func_name == "suggest_pass_adjustment":
result = handle_pass_adjustment(row, name)
elif func_name == "suggest_remedial_adjustment":
result = handle_remedial_adjustment(row, name, args['current_score'])
elif func_name == "suggest_edit_for_passed":
result = handle_edit_for_passed(row, name, args['current_score'])
elif func_name == "suggest_apply_adjustment":
result = handle_apply_adjustment(row, name, args['new_score'])
else:
result = "❌ 無對應函式"
# 後續回應
follow_up = ollama.chat(
model="llama3.2",
messages=[
{"role": "user", "content": user_input},
response.message,
{"role": "tool", "name": func_name, "content": result}
]
)
print(f"💬 GPT 回覆：{follow_up.message['content']}")
else:
print("🤖 GPT 沒有呼叫任何函式")
# === 儲存檔案 ===
final_name = "grades_final.xlsx"
wb.save(final_name)
print(f"\n🎉 所有成績處理完成，已儲存為 {final_name}")
|
