🐘 CSV scraper multi

"""
Basic example of scraping pipeline using CSVScraperMultiGraph from CSV documents
"""

import os
from dotenv import load_dotenv
import pandas as pd
from scrapegraphai.graphs import CSVScraperMultiGraph
from scrapegraphai.utils import convert_to_csv, convert_to_json, prettify_exec_info

load_dotenv()
# ************************************************
# Read the CSV file
# ************************************************

FILE_NAME = "inputs/username.csv"
curr_dir = os.path.dirname(os.path.realpath(__file__))
file_path = os.path.join(curr_dir, FILE_NAME)

text = pd.read_csv(file_path)

# ************************************************
# Define the configuration for the graph
# ************************************************

deepseek_key = os.getenv("DEEPSEEK_APIKEY")

graph_config = {
    "llm": {
        "model": "deepseek-chat",
        "openai_api_key": deepseek_key,
        "openai_api_base": 'https://api.deepseek.com/v1',
    },
     "embeddings": {
        "model": "ollama/nomic-embed-text",
        "temperature": 0,
        # "base_url": "http://localhost:11434",  # set ollama URL arbitrarily
    },
    "verbose": True,
}
# ************************************************
# Create the CSVScraperMultiGraph instance and run it
# ************************************************

csv_scraper_graph = CSVScraperMultiGraph(
    prompt="List me all the last names",
    source=[str(text), str(text)],
    config=graph_config
)

result = csv_scraper_graph.run()
print(result)

# ************************************************
# Get graph execution info
# ************************************************

graph_exec_info = csv_scraper_graph.get_execution_info()
print(prettify_exec_info(graph_exec_info))

# Save to json or csv
convert_to_csv(result, "result")
convert_to_json(result, "result")