from lida import Manager, TextGenerationConfig , llm  
from dotenv import load_dotenv
import os
import openai
import base64
from PIL import Image
from io import BytesIO

print("Import Successful!")

load_dotenv()

def base64_to_image(base64_string):
    # Decode the base64 string
    byte_data = base64.b64decode(base64_string)
    
    # Use BytesIO to convert the byte data to image
    return Image.open(BytesIO(byte_data))

def save_image(base64_str, save_path):
    img = base64_to_image(base64_str)
    img.save(save_path)
    print(f"Image saved at {save_path}")

openai.api_key = os.getenv('OPENAI_API_KEY')

#text_gen = llm("openai")
#text_gen = llm(provider="hf", model="togethercomputer/Llama-2-7B-32K-Instruct", device_map="cpu")

lida = Manager(text_gen = llm("openai")) 

print("Model Loaded Successfully!")

textgen_config = TextGenerationConfig(n=1, temperature=0.5, model="gpt-3.5-turbo-0301", use_cache=True)

summary = lida.summarize("2019.csv", summary_method="default", textgen_config=textgen_config)

print(summary)

goals = lida.goals(summary, n=2, textgen_config=textgen_config)

for goal in goals:
    print(goal)

i = 0
library = "seaborn"
textgen_config = TextGenerationConfig(n=1, temperature=0.2, use_cache=True)
charts = lida.visualize(summary=summary, goal=goals[i], textgen_config=textgen_config, library=library)  
image_base64 = charts[0].raster


save_image(image_base64, "filename.png")