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# backend/app/ai_processor.py
import torch
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
import os
import traceback # Untuk logging error
# --- MODEL_NAME tetap sama seperti yang sudah Anda pilih dan uji ---
MODEL_NAME = "google/flan-t5-small"
# MODEL_NAME = "facebook/bart-large-cnn"
# MODEL_NAME = "sshleifer/distilbart-cnn-6-6"
model = None
tokenizer = None
device = None
def initialize_model():
global model, tokenizer, device
if model is not None and tokenizer is not None:
# print("INFO: AI Processor - Model dan tokenizer sudah dimuat.") # Bisa di-uncomment jika perlu
return True
try:
print(f"INFO: AI Processor - Memulai proses pemuatan model: {MODEL_NAME}...")
if torch.cuda.is_available():
device = torch.device("cuda")
print("INFO: AI Processor - GPU (CUDA) terdeteksi.")
else:
device = torch.device("cpu")
print("INFO: AI Processor - GPU tidak terdeteksi, menggunakan CPU.")
print(f"INFO: AI Processor - Memuat tokenizer untuk {MODEL_NAME}...")
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
print("INFO: AI Processor - Tokenizer berhasil dimuat.")
print(f"INFO: AI Processor - Memuat model {MODEL_NAME} ke device {device}...")
model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME)
model.to(device)
model.eval()
print(f"INFO: AI Processor - Model {MODEL_NAME} berhasil dimuat ke {device}.")
return True
except Exception as e:
print(f"ERROR: AI Processor - Gagal memuat model {MODEL_NAME}: {str(e)}")
traceback.print_exc()
model = None
tokenizer = None
return False
def generate_cv_summary(input_text: str) -> str:
global model, tokenizer, device
if model is None or tokenizer is None:
error_msg = "ERROR: AI Processor - Model atau tokenizer belum berhasil diinisialisasi. Coba panggil initialize_model() lagi."
print(error_msg)
if not initialize_model(): # Coba inisialisasi ulang
return error_msg + " Inisialisasi ulang juga gagal."
if model is None or tokenizer is None: # Cek lagi setelah coba inisialisasi ulang
return "ERROR: AI Processor - Model tetap tidak tersedia setelah mencoba inisialisasi ulang."
# Log ini bisa dipertahankan untuk melihat apa yang diproses
# print(f"INFO: AI Processor - Menerima teks untuk diringkas (panjang: {len(input_text)} char).")
try:
# --- PROMPT ANDA YANG SUDAH DISESUAIKAN ---
prompt_prefix = "Summarize the following work experience for a professional, ATS-friendly CV. Focus on quantifiable achievements, key responsibilities, and relevant skills. Use concise bullet points if appropriate: "
# Atau prompt lain yang sudah Anda temukan bekerja dengan baik.
# -----------------------------------------
text_to_summarize = prompt_prefix + input_text
# print(f"DEBUG: AI Processor - Teks input ke tokenizer: '{text_to_summarize[:100]}...'") # Hapus jika terlalu verbose
inputs = tokenizer(text_to_summarize, return_tensors="pt", max_length=1024, truncation=True, padding="longest")
input_ids = inputs.input_ids.to(device)
attention_mask = inputs.attention_mask.to(device)
# print(f"DEBUG: AI Processor - Melakukan inferensi pada device {device}...") # Hapus jika terlalu verbose
with torch.no_grad():
summary_ids = model.generate(
input_ids,
attention_mask=attention_mask,
max_length=250,
min_length=50,
num_beams=4,
early_stopping=True,
no_repeat_ngram_size=3,
)
summary_text = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
# print(f"INFO: AI Processor - Ringkasan digenerate: '{summary_text[:100]}...'") # Bisa dipertahankan
return summary_text.strip()
except Exception as e:
print(f"ERROR: AI Processor - Error saat proses generasi ringkasan: {str(e)}")
traceback.print_exc()
return "Error: Terjadi masalah internal pada AI saat mencoba membuat ringkasan. Silakan coba lagi."
# initialize_model() akan dipanggil dari startup event di main.py |