Create app.py

app.py

@@ -0,0 +1,105 @@
+# app.py
+import gradio as gr
+import requests
+from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
+
+# Load KoAlpaca model
+model_id = "beomi/KoAlpaca-Polyglot-5.8B"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")
+generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+NEIS_KEY = "a69e08342c8947b4a52cd72789a5ecaf"
+SCHOOL_INFO_URL = "https://open.neis.go.kr/hub/schoolInfo"
+SCHEDULE_URL = "https://open.neis.go.kr/hub/SchoolSchedule"
+
+REGIONS = {
+    "서울특별시교육청": "B10",
+    "경상북도교육청": "R10"
+}
+
+MONTH_NAMES = ["01", "02", "03", "04", "05", "06", "07", "08", "09", "10", "11", "12"]
+
+
+def get_school_code(region_code, school_name):
+    params = {
+        "KEY": NEIS_KEY,
+        "Type": "json",
+        "pIndex": 1,
+        "pSize": 1,
+        "SCHUL_NM": school_name,
+        "ATPT_OFCDC_SC_CODE": region_code
+    }
+    res = requests.get(SCHOOL_INFO_URL, params=params)
+    data = res.json()
+    try:
+        return data["schoolInfo"][1]["row"][0]["SD_SCHUL_CODE"], data["schoolInfo"][1]["row"][0]["ATPT_OFCDC_SC_CODE"]
+    except:
+        return None, None
+
+
+def get_schedule(region_code, school_code, year, month):
+    from_ymd = f"{year}{month}01"
+    to_ymd = f"{year}{month}31"
+    params = {
+        "KEY": NEIS_KEY,
+        "Type": "json",
+        "pIndex": 1,
+        "pSize": 100,
+        "ATPT_OFCDC_SC_CODE": region_code,
+        "SD_SCHUL_CODE": school_code,
+        "AA_FROM_YMD": from_ymd,
+        "AA_TO_YMD": to_ymd
+    }
+    res = requests.get(SCHEDULE_URL, params=params)
+    data = res.json()
+    try:
+        rows = data["SchoolSchedule"][1]["row"]
+        return rows
+    except:
+        return []
+
+
+def generate_answer(region, school_name, year, month, question):
+    region_code = REGIONS.get(region)
+    if not region_code:
+        return "잘못된 교육청입니다."
+
+    school_code, confirmed_region = get_school_code(region_code, school_name)
+    if not school_code:
+        return "학교 정보를 찾을 수 없습니다."
+
+    schedule_rows = get_schedule(confirmed_region, school_code, year, month)
+    if not schedule_rows:
+        schedule_text = "현재 일정 정보는 없습니다."
+    else:
+        schedule_text = "\n".join(f"{row['AA_YMD']}: {row['EVENT_NM']}" for row in schedule_rows)
+
+    prompt = f"""일정 정보:
+{schedule_text}
+
+사용자 질문: {question}
+
+자연스럽게 대답하세요."""
+
+    result = generator(prompt, max_new_tokens=200, temperature=0.7)[0]["generated_text"]
+    return result
+
+
+def interface_fn(region, school_name, year, month, question):
+    return generate_answer(region, school_name, year, month, question)
+
+
+with gr.Interface(
+    fn=interface_fn,
+    inputs=[
+        gr.Dropdown(choices=list(REGIONS.keys()), label="교육청 선택"),
+        gr.Textbox(label="학교명 입력"),
+        gr.Textbox(label="년도 입력", placeholder="예: 2025"),
+        gr.Dropdown(choices=MONTH_NAMES, label="월 선택 (예: 07)"),
+        gr.Textbox(label="GPT 질문 입력")
+    ],
+    outputs=gr.Textbox(label="GPT의 응답"),
+    title="학사일정 + GPT 챗봇 (KoAlpaca)"
+) as app:
+    app.launch()