app.py

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

# Specify the model and tokenizer
model_name = "deepseek-ai/deepseek-math-7b-instruct"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

# Function to read text from a file
def read_input_text(file_path):
    with open(file_path, 'r', encoding='utf-8') as file:
        text = file.read()
    return text.strip()

# Example usage: Replace 'input.txt' with your file path
input_text = read_input_text('input.txt')

# Prepare input as a chat message
messages = [{"role": "user", "content": input_text}]
input_tensor = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt")

# Generate outputs from the model
outputs = model.generate(input_tensor.to(model.device), max_new_tokens=100)

# Decode the generated output
result = tokenizer.decode(outputs[0][input_tensor.shape[1]:], skip_special_tokens=True)
print(result)