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import sys
import os
import torch
sys.path.append(os.path.dirname(os.path.dirname(__file__)))
from all_models import models
def query_(query, doc):
input_text = f"""
You are an AI assistant designed to extract relevant information from a document and generate a clear, concise answer.
Question: {query}
Provide a *single-paragraph response of 250 words* that summarizes key details, explains the answer logically, and avoids repetition. Ignore irrelevant details like page numbers, author names, and metadata.
Context:
"{doc}"
Answer:
"""
# Move inputs to the same device as the model
device = next(models.flan_model.parameters()).device
inputs = models.flan_tokenizer(input_text, return_tensors="pt").to(device)
input_length = inputs["input_ids"].shape[1]
max_tokens = input_length + 180
with torch.no_grad():
outputs = models.flan_model.generate(
**inputs,
do_sample=True,
max_length=max_tokens,
min_length=100,
early_stopping=True,
temperature=0.7,
top_k=50,
top_p=0.9,
repetition_penalty=1.2,
num_beams=3
)
answer = models.flan_tokenizer.decode(outputs[0], skip_special_tokens=True)
# print(answer)
# answer = extract_answer(answer)
return answer
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