56 lines
1.6 KiB
Python
56 lines
1.6 KiB
Python
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import embedding
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import lancedb
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url = "http://localhost:11434/api/embed"
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model = "nomic-embed-text"
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text = "Saya lupa password di HRIS AFMS2"
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memories_db_path = "./memories"
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memories_table = "knowledge_stories"
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docs = [
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{
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"id": "wifi-001",
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"title": "Perubahan password WiFi menjadi login portal",
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"story": (
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"Password WiFi kantor telah berubah. "
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"Sekarang akses WiFi menggunakan login portal. "
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"Akun login akan diberikan melalui chat pribadi masing-masing user."
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),
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},
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{
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"id": "m365-001",
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"title": "Cara cek spam pada Outlook Group",
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"story": (
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"Untuk mengecek spam pada Outlook Group, buka Outlook Web. "
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"Masuk ke menu Groups, pilih group terkait, lalu cek folder Junk Email atau Spam."
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),
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},
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{
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"id": "printer-001",
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"title": "Printer tidak terdeteksi di komputer",
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"story": (
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"Jika printer tidak terdeteksi, cek koneksi kabel atau jaringan. "
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"Pastikan driver printer sudah terinstall, lalu coba restart service Print Spooler."
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),
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},
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]
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rows = []
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for doc in docs:
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row = {
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"id": doc["id"],
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"title": doc["title"],
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"story": doc["story"],
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"vector_title": embedding.embed_text(doc["title"]),
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}
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rows.append(row)
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db = lancedb.connect(memories_db_path)
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table = db.create_table(memories_table, data=rows, mode="overwrite")
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print("Table berhasil dibuat.")
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print("Nama table:", memories_table)
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print("Jumlah row:", table.count_rows())
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