import google.generativeai as genai
import gradio as gr
import os

generation_config = {
  "temperature": 0,
  "top_p": 1,
  "top_k": 32,
  "max_output_token": 4096,
}

safety_settings = [
  {
    "category": "HARM_CATEGORY_HARASSMENT",
    "threshold": "BLOCK_MEDIUM_AND_ABOVE"
  },
  {
    "category": "HARM_CATEGORY_HATE_SPEECH",
    "threshold": "BLOCK_MEDIUM_AND_ABOVE"
  },
  {
    "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
    "threshold": "BLOCK_MEDIUM_AND_ABOVE"
  },
  {
    "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
    "threshold": "BLOCK_MEDIUM_AND_ABOVE"
  },
]

genai.configure(api_key="AIzaSyAEinSmbNfJHdThXN2nA3Oxf82Qb7zQsLo")

model = genai.GenerativeModel(model_name="gemini-pro-vision",
                              generation_config=generation_config,
                              safety_settings=safety_settings)

import_prompt = """ """

def upload_file(files, text_input):
  file_paths = [file.name for file in files]
  if file_paths:
    response = generate_gemini_response(input_prompt, text_input, file_paths[0])
  return file_paths[0], response

with gr.Blocks() as demo:
  header = gr.Label("Please let us know about your injury and Gen AI will try to help you")
  text_input = gr.Textbox(label="Explain a bit more about your injury")
  image_output = gr.Image()
  upload_button = gr.UploadButton("Upload an image",
                                  file_type=["image"],
                                  file_count="multiple")
  file_output = gr.Textbox(label="First-aid process")
  combined_output = [image_output, file_output]

  upload_button.upload(upload_file, [upload_button, text_input], combined_output)

demo.launch(debug=True)