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from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
# Load the model (TinyLlama)
model_name = "TinyLlama/TinyLlama-1.1B-Chat-v1.0"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
def get_llm_reply(user_input: str) -> str:
prompt = f"""
You are 'FreightBot', an AI freight agent that helps with truckload bookings, price estimates, and delivery updates.
Respond in a short, professional style like a real broker. Always sound confident.
User: {user_input}
FreightBot:
"""
inputs = tokenizer(prompt, return_tensors="pt")
output = model.generate(
**inputs,
max_new_tokens=100,
do_sample=True,
temperature=0.7
)
response = tokenizer.decode(output[0], skip_special_tokens=True)
return response.replace(prompt, "").strip()
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