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import gradio as gr
import json
import os
import pandas as pd
from dotenv import load_dotenv
from services import GeminiService
from huggingface_hub import HfApi, hf_hub_download
# Load Env
load_dotenv()
SAVE_FILE = os.getenv("SAVE_FILE_NAME", "saved_professors.json")
HF_TOKEN = os.getenv("HF_TOKEN")
DATASET_REPO_ID = os.getenv("DATASET_REPO_ID")
# Init Service
try:
gemini_service = GeminiService()
except Exception as e:
print(f"Service Error: {e}")
gemini_service = None
# --- Helper Functions ---
def get_key(p):
return f"{p['name']}-{p['university']}"
def load_data():
data = []
# 1. 嘗試從雲端下載
if HF_TOKEN and DATASET_REPO_ID:
try:
print(f"正在同步雲端資料: {DATASET_REPO_ID}...")
hf_hub_download(
repo_id=DATASET_REPO_ID,
filename=SAVE_FILE,
repo_type="dataset",
token=HF_TOKEN,
local_dir="." # 覆蓋本地檔案
)
print("雲端同步完成。")
except Exception as e:
print(f"雲端同步略過 (初次啟動或無權限): {e}")
# 2. 讀取檔案
if os.path.exists(SAVE_FILE):
try:
with open(SAVE_FILE, 'r', encoding='utf-8') as f:
data = json.load(f)
except:
data = []
return data
def save_data(data):
# 1. 存本地
try:
with open(SAVE_FILE, 'w', encoding='utf-8') as f:
json.dump(data, f, ensure_ascii=False, indent=2)
except Exception as e:
print(f"Save Error: {e}")
return
# 2. 上傳雲端
if HF_TOKEN and DATASET_REPO_ID:
try:
api = HfApi(token=HF_TOKEN)
api.upload_file(
path_or_fileobj=SAVE_FILE,
path_in_repo=SAVE_FILE,
repo_id=DATASET_REPO_ID,
repo_type="dataset",
commit_message="Sync data from Space"
)
except Exception as e:
print(f"Upload Error: {e}")
def format_df(source_list, saved_list):
if not source_list:
return pd.DataFrame(columns=["狀態", "姓名", "大學", "系所", "標籤"])
if saved_list is None:
saved_list = []
saved_map = {get_key(p): p for p in saved_list}
data = []
for p in source_list:
display_p = saved_map.get(get_key(p), p)
status_map = {'match': '✅', 'mismatch': '❌', 'pending': '❓'}
status_icon = status_map.get(display_p.get('status'), '')
has_detail = "📄" if display_p.get('details') else ""
tags = ", ".join(display_p.get('tags', []))
data.append([
f"{status_icon} {has_detail}",
display_p['name'],
display_p['university'],
display_p['department'],
tags
])
return pd.DataFrame(data, columns=["狀態", "姓名", "大學", "系所", "標籤"])
def get_tags_text(prof):
if not prof or not prof.get('tags'):
return "目前標籤: (無)"
return "🏷️ " + ", ".join([f"`{t}`" for t in prof['tags']])
def get_tags_choices(prof):
if not prof: return []
return prof.get('tags', [])
# --- Event Handlers ---
def search_professors(query, current_saved):
if not query: return gr.update(), current_saved, gr.update()
try:
results = gemini_service.search_professors(query)
return format_df(results, current_saved), results, gr.update(visible=True)
except Exception as e:
raise gr.Error(f"搜尋失敗: {e}")
def load_more(query, current_search_results, current_saved):
if not query: return gr.update(), current_search_results
current_names = [p['name'] for p in current_search_results]
try:
new_results = gemini_service.search_professors(query, exclude_names=current_names)
existing_keys = set(get_key(p) for p in current_search_results)
for p in new_results:
if get_key(p) not in existing_keys:
current_search_results.append(p)
return format_df(current_search_results, current_saved), current_search_results
except Exception as e:
raise gr.Error(f"載入失敗: {e}")
def select_professor_from_df(evt: gr.SelectData, search_results, saved_data, view_mode):
if not evt: return [gr.update()] * 8
index = evt.index[0]
target_list = saved_data if view_mode == "追蹤清單" else search_results
if not target_list or index >= len(target_list):
return gr.update(), gr.update(), gr.update(), None, None, gr.update(), gr.update(), gr.update()
prof = target_list[index]
key = get_key(prof)
saved_prof = next((p for p in saved_data if get_key(p) == key), None)
current_prof = saved_prof if saved_prof else prof
details_md = ""
if current_prof.get('details') and len(current_prof.get('details')) > 10:
details_md = current_prof['details']
if not saved_prof:
saved_data.insert(0, current_prof)
save_data(saved_data)
else:
gr.Info(f"正在調查 {current_prof['name']}...")
try:
res = gemini_service.get_professor_details(current_prof)
current_prof['details'] = res['text']
current_prof['sources'] = res['sources']
details_md = res['text']
if saved_prof:
saved_prof.update(current_prof)
else:
saved_data.insert(0, current_prof)
save_data(saved_data)
except Exception as e:
raise gr.Error(f"調查失敗: {e}")
if current_prof.get('sources'):
details_md += "\n\n### 📚 參考來源\n"
for s in current_prof['sources']:
details_md += f"- [{s['title']}]({s['uri']})\n"
return (
gr.update(visible=True),
details_md,
[],
current_prof,
saved_data,
get_tags_text(current_prof),
gr.update(choices=get_tags_choices(current_prof), value=None),
gr.update(visible=True)
)
def add_tag(new_tag, selected_prof, saved_data, view_mode, search_results):
if not selected_prof or not new_tag:
return gr.update(), gr.update(), gr.update(), saved_data, gr.update()
if 'tags' not in selected_prof: selected_prof['tags'] = []
if new_tag not in selected_prof['tags']:
selected_prof['tags'].append(new_tag)
key = get_key(selected_prof)
found = False
for i, p in enumerate(saved_data):
if get_key(p) == key:
saved_data[i] = selected_prof
found = True
break
if not found:
saved_data.insert(0, selected_prof)
save_data(saved_data)
gr.Info(f"已新增標籤: {new_tag}")
target_list = saved_data if view_mode == "追蹤清單" else search_results
new_df = format_df(target_list, saved_data)
return (
gr.update(value=""),
get_tags_text(selected_prof),
gr.update(choices=selected_prof['tags']),
saved_data,
new_df
)
def remove_tag(tag_to_remove, selected_prof, saved_data, view_mode, search_results):
if not selected_prof or not tag_to_remove:
return gr.update(), gr.update(), saved_data, gr.update()
if 'tags' in selected_prof and tag_to_remove in selected_prof['tags']:
selected_prof['tags'].remove(tag_to_remove)
key = get_key(selected_prof)
for i, p in enumerate(saved_data):
if get_key(p) == key:
saved_data[i] = selected_prof
break
save_data(saved_data)
gr.Info(f"已移除標籤: {tag_to_remove}")
target_list = saved_data if view_mode == "追蹤清單" else search_results
new_df = format_df(target_list, saved_data)
return (
get_tags_text(selected_prof),
gr.update(choices=selected_prof['tags'], value=None),
saved_data,
new_df
)
def chat_response(history, message, selected_prof):
if not selected_prof: return history, ""
context = selected_prof.get('details', '')
if not context: return history, ""
service_history = []
for h in history:
service_history.append({"role": "user", "content": h[0]})
if h[1]: service_history.append({"role": "model", "content": h[1]})
try:
reply = gemini_service.chat_with_ai(service_history, message, context)
history.append((message, reply))
except Exception as e:
history.append((message, f"Error: {e}"))
return history, ""
def update_status(status, selected_prof, saved_data, view_mode, search_results):
if not selected_prof: return gr.update(), saved_data
selected_prof['status'] = status if selected_prof.get('status') != status else None
key = get_key(selected_prof)
for i, p in enumerate(saved_data):
if get_key(p) == key:
saved_data[i] = selected_prof
break
save_data(saved_data)
target_list = saved_data if view_mode == "追蹤清單" else search_results
return format_df(target_list, saved_data), saved_data
def remove_prof(selected_prof, saved_data, view_mode, search_results):
if not selected_prof: return gr.update(), gr.update(value=None), saved_data, gr.update(visible=False)
key = get_key(selected_prof)
new_saved = [p for p in saved_data if get_key(p) != key]
save_data(new_saved)
target_list = new_saved if view_mode == "追蹤清單" else search_results
return (
gr.Info("已移除"),
format_df(target_list, new_saved),
new_saved,
gr.update(visible=False)
)
def toggle_view(mode, search_res, saved_data):
if mode == "搜尋結果":
return format_df(search_res, saved_data), gr.update(visible=True)
else:
return format_df(saved_data, saved_data), gr.update(visible=False)
def init_on_load():
data = load_data()
return data, format_df(data, data)
# --- UI Layout ---
with gr.Blocks(title="Prof.404 開箱教授去哪兒?", theme=gr.themes.Soft()) as demo:
saved_state = gr.State([])
search_res_state = gr.State([])
selected_prof_state = gr.State(None)
# 🌟 這裡插入了您要求的徽章與文字,使用 HTML 置中
gr.Markdown("""
<div align="center">
# 🎓 Prof.404 - 開箱教授去哪兒? (API KEY RPD,建議自行 Fork)
[![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/DeepLearning101/Prof.404)
[![GitHub](https://img.shields.io/badge/GitHub-Repo-black)](https://github.com/Deep-Learning-101/prof-404)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Powered by](https://img.shields.io/badge/Powered%20by-Gemini%20Pro-4285F4?logo=google)](https://deepmind.google/technologies/gemini/)
👉 歡迎 Star ⭐ GitHub 👆 👆 HuggingFace ⭐ 覺得不錯 👈
**學術研究啟程的導航系統,拒絕當科研路上的無頭蒼蠅**
**(全新升級:支援雲端同步!Space 重啟資料不遺失 🔄)**
</div>
""")
with gr.Row():
search_input = gr.Textbox(label="搜尋研究領域", placeholder="例如: 大型語言模型, 後量子密碼遷移...", scale=4)
search_btn = gr.Button("🔍 搜尋", variant="primary", scale=1)
with gr.Row():
view_radio = gr.Radio(["搜尋結果", "追蹤清單"], label="顯示模式", value="追蹤清單")
with gr.Row():
# Left: List
with gr.Column(scale=1):
prof_df = gr.Dataframe(
headers=["狀態", "姓名", "大學", "系所", "標籤"],
datatype=["str", "str", "str", "str", "str"],
interactive=False,
label="教授列表 (點擊查看詳情)"
)
load_more_btn = gr.Button("載入更多", visible=False)
# Right: Details
with gr.Column(scale=2, visible=False) as details_col:
detail_md = gr.Markdown("詳細資料...")
# Status Buttons
with gr.Row():
btn_match = gr.Button("✅ 符合")
btn_mismatch = gr.Button("❌ 不符")
btn_pending = gr.Button("❓ 待觀察")
btn_remove = gr.Button("🗑️ 移除", variant="stop")
gr.Markdown("---")
# Tags Management
with gr.Column(visible=False) as tags_row:
tags_display = gr.Markdown("目前標籤: (無)")
with gr.Row():
tag_input = gr.Textbox(label="新增標籤", placeholder="輸入後按新增...", scale=3)
tag_add_btn = gr.Button("➕ 新增", scale=1)
with gr.Accordion("刪除標籤", open=False):
with gr.Row():
tag_dropdown = gr.Dropdown(label="選擇標籤", choices=[], scale=3)
tag_del_btn = gr.Button("🗑️ 刪除", scale=1, variant="secondary")
gr.Markdown("---")
gr.Markdown("### 💬 AI 助手")
chatbot = gr.Chatbot(height=300)
msg = gr.Textbox(label="提問")
send_btn = gr.Button("送出")
# --- Wiring ---
demo.load(init_on_load, inputs=None, outputs=[saved_state, prof_df])
search_btn.click(
search_professors,
inputs=[search_input, saved_state],
outputs=[prof_df, search_res_state, load_more_btn]
).then(
lambda: gr.update(value="搜尋結果"), outputs=[view_radio]
)
load_more_btn.click(
load_more,
inputs=[search_input, search_res_state, saved_state],
outputs=[prof_df, search_res_state]
)
view_radio.change(
toggle_view,
inputs=[view_radio, search_res_state, saved_state],
outputs=[prof_df, load_more_btn]
)
prof_df.select(
select_professor_from_df,
inputs=[search_res_state, saved_state, view_radio],
outputs=[
details_col, detail_md, chatbot, selected_prof_state, saved_state,
tags_display, tag_dropdown, tags_row
]
)
send_btn.click(chat_response, inputs=[chatbot, msg, selected_prof_state], outputs=[chatbot, msg])
msg.submit(chat_response, inputs=[chatbot, msg, selected_prof_state], outputs=[chatbot, msg])
tag_add_btn.click(
add_tag,
inputs=[tag_input, selected_prof_state, saved_state, view_radio, search_res_state],
outputs=[tag_input, tags_display, tag_dropdown, saved_state, prof_df]
)
tag_del_btn.click(
remove_tag,
inputs=[tag_dropdown, selected_prof_state, saved_state, view_radio, search_res_state],
outputs=[tags_display, tag_dropdown, saved_state, prof_df]
)
for btn, status in [(btn_match, 'match'), (btn_mismatch, 'mismatch'), (btn_pending, 'pending')]:
btn.click(
update_status,
inputs=[gr.State(status), selected_prof_state, saved_state, view_radio, search_res_state],
outputs=[prof_df, saved_state]
)
btn_remove.click(
remove_prof,
inputs=[selected_prof_state, saved_state, view_radio, search_res_state],
outputs=[gr.State(None), prof_df, saved_state, details_col]
)
if __name__ == "__main__":
demo.launch()