import os

os.environ["OPENAI_API_KEY"] = os.getenv('open_ai')
os.environ["GOOGLE_API_KEY"] = os.getenv('gemini')
from langchain_google_genai import ChatGoogleGenerativeAI

gemini_model = ChatGoogleGenerativeAI(model = "gemini-pro")

os.environ["WOLFRAM_ALPHA_APPID"] = os.getenv('wolfram')


from langchain.utilities.wolfram_alpha import WolframAlphaAPIWrapper

wolfram = WolframAlphaAPIWrapper()

wolfram.run("What is 2x+5 = -3x + 7?")

"""## Standard Tool"""


import google.generativeai as genai

import gradio as gr

def get_completion(text):

  model = genai.GenerativeModel('gemini-pro')
  response = model.generate_content(text)
  return response.text

def extract_query(input_text):
  prompt_sum = f'''Given input {input_text} from the user, generate a input query that can be input to the WolframAlphaAPIWrapper() method. If
     the given input from the user is good as it is, then just output it as it is. If not, regenerate a query that WolframAlphaAPIWrapper() would
     understand. You just need output the final query.'''
  result = get_completion(prompt_sum)
  return result

# Define your davinci_output function
def davinci_output(input_text):
    # Add your code here to process the input and generate the output
    wolf_query = extract_query(input_text)
    output_text = wolfram.run(wolf_query)

    return output_text


examples = [
    ["what is (4.5*2.1)^2.2?"],
    ["Calculate 73*2-3*4"],
    ["What is square root of 89898998"]
]


# Create the Gradio interface
iface = gr.Interface(fn=davinci_output, inputs=gr.inputs.Textbox(placeholder="Enter the math problem"), outputs="text", title="Ask DaVinci",
                     description="Enter a math problem and see the genius of Leonardo DaVinci in action!",examples=examples)

# Run the Gradio app
iface.launch()