Scrapegraph-ai/examples/local_models/Docker/csv_scraper_docker.py
2024-05-01 20:17:01 +02:00

55 lines
1.6 KiB
Python

"""
Basic example of scraping pipeline using CSVScraperGraph from CSV documents
"""
import pandas as pd
from scrapegraphai.graphs import CSVScraperGraph
from scrapegraphai.utils import convert_to_csv, convert_to_json, prettify_exec_info
# ************************************************
# Read the csv file
# ************************************************
text = pd.read_csv("inputs/username.csv")
# ************************************************
# Define the configuration for the graph
# ************************************************
graph_config = {
"llm": {
"model": "ollama/mistral",
"temperature": 0,
"format": "json", # Ollama needs the format to be specified explicitly
# "model_tokens": 2000, # set context length arbitrarily
},
"embeddings": {
"model": "ollama/nomic-embed-text",
"temperature": 0,
}
}
# ************************************************
# Create the CSVScraperGraph instance and run it
# ************************************************
csv_scraper_graph = CSVScraperGraph(
prompt="List me all the last names",
source=str(text), # Pass the content of the file, not the file object
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")