Compare two scraping results, optionally ignoring certain keys. Args: result1: First result result2: Second result ignore

Converts a JSON graph configuration to a Graphviz object for visualization. Args: json_data (dict): A JSON representatio

Create a mock graph execution result. Args: answer: The answer/result exec_info: Execution info dictionary error: Optiona

Create a mock LLM response. Args: content: Response content **kwargs: Additional response attributes Returns: Mock r

Handle GET requests.

Fixture for a GenerateAnswerNode instance using DummyLLM. Uses a valid input keys string ("dummy_input & doc") to avoid parsing errors.

Fixture for creating a GenerateAnswerNode instance for testing the process() method success case.

Fixture for a GenerateAnswerNode instance using DummyLLMWithPipe. Uses a valid input keys string ("dummy_input & doc") to avoid parsing error

A dummy scraper function that is not asynchronous.

A dummy scraping function that returns dummy HTML content for the URL.

Evaluate an expression with parentheses.

Evaluate an expression without parentheses.

Execute the markdownify graph. Args: initial_state: A dictionary containing either: - "url": The URL to

Generate text from an image using an image-to-text model. The method retrieves the image from the list of URLs provided in the state

Executes the node's logic to concatenate the answers from multiple graph instances into a single answer. Args: s

Generates an answer by constructing a prompt from the user's input and the scraped content, querying the language model, and parsing

Generates an answer by constructing a prompt from the user's input and the scraped content, querying the language model, and parsing

Generates Python code for a function that extracts data from HTML based on a output schema. Args: state (dict): The curr

Generate a refined prompt using the user's prompt, the schema, and additional context. Args: state (dict): The current s

Checks if a website is scrapeable based on the robots.txt file and updates the state with the scrapeability status. The method constr

Executes the node's logic to parse the HTML documents content. Args: state (dict): The current state of the graph. The i

Executes the node's logic to fetch the HTML content of a specified URL and its sub-links recursively, then updates the graph's state

Checks if the specified key is present in the state and decides the next node accordingly. Args: state (dict): The curre

Executes the node's logic to merge the answers from multiple graph instances into a single answer. Args: state (

Generate a refined prompt for the reasoning task based on the user's input and the JSON schema. Args: state (dic

Executes the node's logic to instantiate and run multiple graph instances in parallel. Args: state (dict): The current s

Filter out relevant links from the webpage that are relavant to prompt. Out of the filtered links, also ensure that all links are nav

Executes the node's logic to parse the HTML document content and split it into chunks. Args: state (dict): The current s

Generates a list of probable HTML tags based on the user's input and updates the state with this list. The method constructs a prompt

Generates an answer by constructing a prompt from the user's input and the scraped content, querying the language model, and parsing

Generates an answer by constructing a prompt from the user's input and the scraped content, querying the language model, and parsing

Execute the node's logic based on the current state and update it accordingly. Args: state (dict): The current state of

Executes the node's logic to merge the answers from multiple graph instances into a single answer. Args: state (d

Converts text to speech using the specified text-to-speech model. Args: state (dict): The current state of the graph. Th

Generates an analysis of the provided HTML code based on the wanted infromations to be extracted. Args: state (dict): Th

Generates a python script for scraping a website using the specified library. Args: state (dict): The current state of t

Captures screenshots from the input URL and stores them in the state dictionary as bytes.

Wrapper to run the asynchronous execute_async function in a synchronous context.

Executes the node's logic to convert HTML content to Markdown. Args: state (dict): The current state of the graph. The i

Executes the node's logic to index the content present in the state. Args: state (dict): The current state of the graph.

Export data to an XML file. :param data: List of dictionaries containing the data to export :param filename: Name of the file to save th

Call the scrapegraph-py extract endpoint across SDK versions.

Check if two strings are similar enough. Args: str1: First string str2: Second string threshold: Similarity threshold (0-

Google Gemini configuration for testing.

Generate a human-readable performance report. Returns: Formatted report string

Generate test CSV data. Args: num_rows: Number of data rows to generate Returns: CSV string

Generate test HTML with customizable content. Args: title: Page title num_items: Number of list items to generate item_te

Generate test JSON data. Args: num_records: Number of records to generate Returns: Dictionary with test data

Get the current verbosity level of the root logger for the library. Returns: int: The current verbosity level of the root logger for

Configuration of the graph

Configuration of the graph

Configuration for the CodeGeneratorGraph

Configuration for the SearchGraph

Configuration of the graph

Configuration of the graph

Configuration of the graph

Configuration for the XMLScraperGraph

Configuration for the DepthSearchGraph

Configuration of the graph

Creation of the graph

Configuration of the graph

Configuration of the graph

Configuration of the graph fixture.

Groq configuration for testing.

Handles the directory by compressing the source document and updating the state. Parameters: state (dict): The current state