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🌈 OmniSearchGraph Module

The OmniSearchGraph module defines a class for creating and executing a graph that searches the internet for answers to a given prompt. It combines web scraping and internet searching to generate an answer based on the user's query.

Classes​

OmniSearchGraph​

OmniSearchGraph 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.
  • max_results (int): The maximum number of results to return.
  • input_key (str): The key for the input source (either url or local_dir).
  • graph: The graph of nodes representing the workflow for web scraping and searching.
  • final_state: The final state of the graph after execution.
  • execution_info: Information about the execution of the graph.

Methods​

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

    • Initializes the OmniSearchGraph 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 and returns the answer to the prompt.
    • Returns: The answer to the prompt.

Example Usage​

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

from omni_search_graph import OmniSearchGraph

# Define the prompt and configuration
prompt = "What is Chioggia famous for?"
config = {
    "llm": {"model": "gpt-4o"},
    "max_results": 5,
    "headless": False,
}

# Create the search graph
omni_search = OmniSearchGraph(prompt, config)

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

print(result)