mirror of
https://github.com/VinciGit00/Scrapegraph-ai.git
synced 2026-06-23 21:00:30 +08:00
106 lines
4.4 KiB
Python
106 lines
4.4 KiB
Python
"""
|
|
Module for generating the answer node
|
|
"""
|
|
from typing import List
|
|
from langchain.output_parsers import CommaSeparatedListOutputParser
|
|
from langchain.prompts import PromptTemplate
|
|
from ..utils.research_web import search_on_web
|
|
from .base_node import BaseNode
|
|
|
|
|
|
class SearchInternetNode(BaseNode):
|
|
"""
|
|
A node that generates an answer by querying a language model (LLM) based on the user's input
|
|
and the content extracted from a webpage. It constructs a prompt from the user's input
|
|
and the scraped content, feeds it to the LLM, and parses the LLM's response to produce
|
|
an answer.
|
|
|
|
Attributes:
|
|
node_name (str): The unique identifier name for the node.
|
|
node_type (str): The type of the node, set to "node" indicating a standard operational node.
|
|
input (str): The user input used to construct the prompt.
|
|
output (List[str]): The keys in the state dictionary
|
|
where the generated answer will be stored.
|
|
model_config (dict): Configuration parameters for the language model client.
|
|
|
|
Args:
|
|
input (str): The user input used to construct the prompt.
|
|
output (List[str]): The keys in the state dictionary where the
|
|
generated answer will be stored.
|
|
model_config (dict): Configuration parameters for the language model client.
|
|
node_name (str, optional): The unique identifier name for the node.
|
|
|
|
Methods:
|
|
execute(state): Processes the input and document from the state to generate an answer,
|
|
updating the state with the generated answer under the 'answer' key.
|
|
"""
|
|
|
|
def __init__(self, input: str, output: List[str], node_config: dict,
|
|
node_name: str = "SearchInternet"):
|
|
"""
|
|
Initializes the SearchInternetNode with input, output, model configuration, and a node name.
|
|
Args:
|
|
input (str): The user input used to construct the prompt.
|
|
output (List[str]): The keys in the state dictionary where the
|
|
generated answer will be stored.
|
|
model_config (dict): Configuration parameters for the language model client.
|
|
node_name (str): The unique identifier name for the node.
|
|
"""
|
|
super().__init__(node_name, "node", input, output, 1, node_config)
|
|
self.llm_model = node_config["llm"]
|
|
|
|
def execute(self, state):
|
|
"""
|
|
Generates an answer by constructing a prompt from the user's input and the scraped
|
|
content, querying the language model, and parsing its response.
|
|
|
|
The method updates the state with the generated answer under the 'answer' key.
|
|
|
|
Args:
|
|
state (dict): The current state of the graph, expected to contain 'user_input',
|
|
and optionally 'parsed_document' or 'relevant_chunks' within 'keys'.
|
|
|
|
Returns:
|
|
dict: The updated state with the 'answer' key containing the generated answer.
|
|
|
|
Raises:
|
|
KeyError: If 'user_input' or 'document' is not found in the state, indicating
|
|
that the necessary information for generating an answer is missing.
|
|
"""
|
|
|
|
print(f"--- Executing {self.node_name} Node ---")
|
|
|
|
input_keys = self.get_input_keys(state)
|
|
|
|
# Fetching data from the state based on the input keys
|
|
input_data = [state[key] for key in input_keys]
|
|
|
|
user_prompt = input_data[0]
|
|
|
|
output_parser = CommaSeparatedListOutputParser()
|
|
|
|
search_template = """
|
|
PROMPT:
|
|
Given the following user prompt, return a query that can be
|
|
used to search the internet for relevant information. \n
|
|
You should return only the query string without any additional sentences. \n
|
|
You are taught to reply directly giving the search query. \n
|
|
USER PROMPT: {user_prompt}"""
|
|
|
|
search_prompt = PromptTemplate(
|
|
template=search_template,
|
|
input_variables=["user_prompt"],
|
|
)
|
|
|
|
# Execute the chain to get the search query
|
|
search_answer = search_prompt | self.llm_model | output_parser
|
|
search_query = search_answer.invoke({"user_prompt": user_prompt})[0]
|
|
|
|
print(f"Search Query: {search_query}")
|
|
# TODO: handle multiple URLs
|
|
answer = search_on_web(query=search_query, max_results=1)[0]
|
|
|
|
# Update the state with the generated answer
|
|
state.update({self.output[0]: answer})
|
|
return state
|