import embedding

import lancedb

url    = "http://localhost:11434/api/embed"
model  = "nomic-embed-text"
text   = "Saya lupa password di HRIS AFMS2"

memories_db_path  = "./memories"
memories_table    = "knowledge_stories"

docs = [
    {
        "id": "wifi-001",
        "title": "Perubahan password WiFi menjadi login portal",
        "story": (
            "Password WiFi kantor telah berubah. "
            "Sekarang akses WiFi menggunakan login portal. "
            "Akun login akan diberikan melalui chat pribadi masing-masing user."
        ),
    },
    {
        "id": "m365-001",
        "title": "Cara cek spam pada Outlook Group",
        "story": (
            "Untuk mengecek spam pada Outlook Group, buka Outlook Web. "
            "Masuk ke menu Groups, pilih group terkait, lalu cek folder Junk Email atau Spam."
        ),
    },
    {
        "id": "printer-001",
        "title": "Printer tidak terdeteksi di komputer",
        "story": (
            "Jika printer tidak terdeteksi, cek koneksi kabel atau jaringan. "
            "Pastikan driver printer sudah terinstall, lalu coba restart service Print Spooler."
        ),
    },
]

rows = []
for doc in docs:
    row = {
        "id": doc["id"],
        "title": doc["title"],
        "story": doc["story"],
        "vector_title": embedding.embed_text(doc["title"]),
    }
    rows.append(row)

db     = lancedb.connect(memories_db_path)
table  = db.create_table(memories_table, data=rows, mode="overwrite")

print("Table berhasil dibuat.")
print("Nama table:", memories_table)
print("Jumlah row:", table.count_rows())