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")