mirror of
https://github.com/VinciGit00/Scrapegraph-ai.git
synced 2026-06-23 21:00:30 +08:00
61 lines
1.5 KiB
Python
61 lines
1.5 KiB
Python
"""
|
|
Example of custom graph using existing nodes
|
|
"""
|
|
|
|
import os
|
|
from dotenv import load_dotenv
|
|
#from scrapegraphai.models import OpenAI
|
|
from scrapegraphai.models import Gemini
|
|
from scrapegraphai.graphs import BaseGraph
|
|
from scrapegraphai.nodes import FetchHTMLNode, ParseNode, GenerateAnswerNodeVanilla
|
|
|
|
|
|
|
|
load_dotenv()
|
|
|
|
# Define the configuration for the language model
|
|
""" openai_key = os.getenv("OPENAI_APIKEY")
|
|
llm_config = {
|
|
"api_key": openai_key,
|
|
"model_name": "gpt-3.5-turbo",
|
|
"temperature": 0,
|
|
"streaming": True
|
|
}
|
|
model = OpenAI(llm_config) """
|
|
|
|
gemini_key = os.getenv("GOOGLE_API_KEY")
|
|
llm_config = {
|
|
"api_key": gemini_key,
|
|
"model_name": "gemini-pro",
|
|
}
|
|
|
|
model = Gemini(llm_config)
|
|
|
|
# define the nodes for the graph
|
|
fetch_html_node = FetchHTMLNode("fetch_html")
|
|
parse_document_node = ParseNode(doc_type="html", chunks_size=4000, node_name="parse_document")
|
|
generate_answer_node = GenerateAnswerNodeVanilla(model, "generate_answer")
|
|
|
|
# create the graph
|
|
graph = BaseGraph(
|
|
nodes={
|
|
fetch_html_node,
|
|
parse_document_node,
|
|
generate_answer_node
|
|
},
|
|
edges={
|
|
(fetch_html_node, parse_document_node),
|
|
(parse_document_node,generate_answer_node)
|
|
},
|
|
entry_point=fetch_html_node
|
|
)
|
|
|
|
# execute the graph
|
|
inputs = {"user_input": "List me the projects with their description",
|
|
"url": "https://perinim.github.io/projects/"}
|
|
result = graph.execute(inputs)
|
|
|
|
# get the answer from the result
|
|
answer = result.get("answer", "No answer found.")
|
|
print(answer)
|