import os
import urllib.request
import gradio as gr
from llama_cpp import Llama

def download_file(file_link, filename):
    # Checks if the file already exists before downloading
    if not os.path.isfile(filename):
        urllib.request.urlretrieve(file_link, filename)
        print("File downloaded successfully.")
    else:
        print("File already exists.")

# Dowloading GGML model from HuggingFace
ggml_model_path = "https://huggingface.co/CRD716/ggml-vicuna-1.1-quantized/resolve/main/ggml-vicuna-7b-1.1-q4_1.bin"
filename = "ggml-vicuna-7b-1.1-q4_1.bin"

download_file(ggml_model_path, filename)


llm = Llama(model_path=filename, n_ctx=512, n_batch=126)

def generate_text(prompt):
    output = llm(prompt, max_tokens=256, temperature=0.1, top_p=0.5, echo=False, stop=["#"])
    output_text = output['choices'][0]['text']
    return output_text

description = "Vicuna-7B"

examples = [
    ["What is the capital of France? ", "The capital of France is Paris."],
    ["Who wrote the novel 'Pride and Prejudice'?", "The novel 'Pride and Prejudice' was written by Jane Austen."],
    ["What is the square root of 64?", "The square root of 64 is 8."]
]

gradio_interface = gr.Interface(
  fn=generate_text,
  inputs="text",
  outputs="text",
  examples=examples
  title="Vicuna-7B",
)
gradio_interface.launch()