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import os
from transformers import AutoTokenizer, AutoModelForCausalLM # Ensure correct model class
HUGGINGFACE_API_KEY = os.getenv("HUGGINGFACE_API_KEY")
if HUGGINGFACE_API_KEY is None:
raise ValueError("Hugging Face API key is not set. Please add it as a secret in your Hugging Face Space settings.")
print(f"Using Hugging Face API Key: {HUGGINGFACE_API_KEY}")
model = None
tokenizer = None
def load_model(model_name):
global tokenizer, model
if not tokenizer or not model:
print("Loading model and tokenizer...")
tokenizer = AutoTokenizer.from_pretrained(model_name)
tokenizer.pad_token = tokenizer.eos_token # Set pad_token to eos_token
model = AutoModelForCausalLM.from_pretrained(model_name) # Ensure correct model class
print("Model and tokenizer loaded successfully.")
return tokenizer, model
async def process_text_local(model_name, text):
print("Loading model and tokenizer...")
tokenizer, model = load_model(model_name)
print("Encoding text...")
inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=512) # Set max_length to 512
print("Text encoded successfully.")
print("Generating output...")
outputs = model.generate(**inputs, max_length=512)
print("Output generated successfully.")
result = tokenizer.decode(outputs[0], skip_special_tokens=True)
print("Output decoded successfully.")
return result
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