import gradio as gr
from mistralai.client import MistralClient
from mistralai.models.chat_completion import ChatMessage
import os
import pandas as pd
import numpy as np

def chat_with_mistral(source_cols, dest_col, prompt, tdoc_name, excel_file, url):

    df = pd.read_excel(excel_file)
    api_key = os.environ["MISTRAL_API_KEY"]
    model = "mistral-small"  # Use "Mistral-7B-v0.2" for "mistral-tiny"


    client = MistralClient(api_key=api_key)

    source_columns = source_cols#.split(", ")  # Split input into multiple variables
    df[dest_col] = ""
    try:
      file_name = url.split("/")[-2] + ".xlsx"
    except:
      file_name = excel_file

    if tdoc_name != '':
        filtered_df = df[df['File'] == tdoc_name]
        if not filtered_df.empty:
            concatenated_content = "\n\n".join(f"{column_name}: {filtered_df[column_name].iloc[0]}" for column_name in source_columns)
            messages = [ChatMessage(role="user", content=f"Using the following content: {concatenated_content}"), ChatMessage(role="user", content=prompt)]
            chat_response = client.chat(model=model, messages=messages)
            filtered_df.loc[filtered_df.index[0], dest_col] = chat_response.choices[0].message.content
            # Update the DataFrame with the modified row
            df.update(filtered_df)
            # Write the updated DataFrame to the Excel file
            df.to_excel(file_name, index=False)
            return file_name, df.head(5)
        else:
            return file_name, df.head(5)
    else:
        for index, row in df.iterrows():
            concatenated_content = "\n\n".join(f"{column_name}: {row[column_name]}" for column_name in source_columns)
            # Check if the concatenated content is not empty
            print('test')
            if not concatenated_content == "\n\n".join(f"{column_name}: nan" for column_name in source_columns):
                print('c bon')
                messages = [ChatMessage(role="user", content=f"Using the following content: {concatenated_content}"), ChatMessage(role="user", content=prompt)]
                chat_response = client.chat(model=model, messages=messages)
                df.at[index, dest_col] = chat_response.choices[0].message.content

        df.to_excel(file_name, index=False)
        return file_name, df.head(5)


def get_columns(file):
    if file is not None:
        df = pd.read_excel(file)
        return gr.update(choices=list(df.columns)), df.head(5)
    else:
        return gr.update(choices=[]), pd.DataFrame()