qwen_model.py

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

# Replace with your target Qwen model on Hugging Face
MODEL_NAME = "Qwen/Qwen2.5-7B-Instruct"

# Initialize tokenizer and model
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
    MODEL_NAME,
    device_map="auto",        # or "cuda", etc. if you want to specify
    trust_remote_code=True
)

# Create pipeline
qwen_pipeline = pipeline(
    "text-generation",
    model=model,
    tokenizer=tokenizer
)

def generate_response(retrieved_texts, query, max_new_tokens=200):
    context = "\n".join(retrieved_texts)
    prompt = f"This is the detail about the image:\n{context}\n\nQuestion: {query}\nAnswer:"
    
    result = qwen_pipeline(prompt, max_new_tokens=max_new_tokens, ...)
    generated_text = result[0]["generated_text"]
    
    if "Answer:" in generated_text:
        final_answer = generated_text.split("Answer:")[-1].strip()
    else:
        final_answer = generated_text

    return final_answer