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😽 SearchGraph Module

The SearchGraph module defines a class for creating and executing a graph that searches the internet for answers to a given prompt.

Classes​

SearchGraph​

SearchGraph is a scraping pipeline that searches the internet for answers to a given prompt. It only requires a user prompt to search the internet and generate an answer.

Attributes​

  • prompt (str): The user prompt to search the internet.
  • llm_model (dict): The configuration for the language model.
  • embedder_model (dict): The configuration for the embedder model.
  • headless (bool): A flag to run the browser in headless mode.
  • verbose (bool): A flag to display the execution information.
  • model_token (int): The token limit for the language model.

Methods​

  • __init__(self, prompt: str, config: dict, schema: Optional[str] = None)

    • Initializes the SearchGraph with a prompt, configuration, and schema.
    • Args:
      • prompt (str): The user prompt to search the internet.
      • config (dict): Configuration parameters for the graph.
      • schema (Optional[str]): The schema for the graph output.

  • _create_graph(self) -> BaseGraph

    • Creates the graph of nodes representing the workflow for web scraping and searching.
    • Returns: An instance of BaseGraph.

  • run(self) -> str

    • Executes the web scraping and searching process.
    • Returns: The answer to the prompt.

Example Usage​

Here is an example of how to use the SearchGraph class:

from search_graph import SearchGraph

# Define the prompt and configuration
prompt = "What is Chioggia famous for?"
config = {
    "llm": {"model": "gpt-3.5-turbo"}
}

# Create the search graph
search_graph = SearchGraph(prompt, config)

# Run the search graph
result = search_graph.run()

print(result)