ScrapeGraphAI/Scrapegraph-ai · error · ImportError

The 'graphviz' library is required for this functionality. P

Error message

The 'graphviz' library is required for this functionality. Please install it from 'https://graphviz.org/download/'.

What it means

GraphIteratorNode raises this ValueError in its async execution path when node_config has no 'graph_instance'. The node fans out one graph instance per URL for concurrent scraping, so it must be told which graph class to clone; without it there is nothing to execute.

Source

Thrown at scrapegraphai/builders/graph_builder.py:150

            dict: A JSON representation of the graph configuration.
        """
        return self.chain.invoke(self.prompt)

    @staticmethod
    def convert_json_to_graphviz(json_data, format: str = "pdf"):
        """
        Converts a JSON graph configuration to a Graphviz object for visualization.

        Args:
            json_data (dict): A JSON representation of the graph configuration.

        Returns:
            graphviz.Digraph: A Graphviz object representing the graph configuration.
        """
        try:
            import graphviz
        except ImportError:
            raise ImportError(
                "The 'graphviz' library is required for this functionality. "
                "Please install it from 'https://graphviz.org/download/'."
            )

        graph = graphviz.Digraph(
            comment="ScrapeGraphAI Generated Graph",
            format=format,
            node_attr={"color": "lightblue2", "style": "filled"},
        )

        graph_config = json_data["text"][0]

        # Retrieve nodes, edges, and the entry point from the JSON data
        nodes = graph_config.get("nodes", [])
        edges = graph_config.get("edges", [])
        entry_point = graph_config.get("entry_point")

        for node in nodes:

View on GitHub (pinned to 532dfffbf6)

Solutions

1. Provide the graph class under node_config['graph_instance'] (e.g. a lambda/class reference like SmartScraperGraph).
2. Also pass 'scraper_config' with the LLM/embeddings config so the cloned graphs are fully configured.
3. Check the examples/ folder for the specific iterator graph to confirm the expected config shape.

Example fix

# before
node_config = {"scraper_config": scraper_config}

# after
from scrapegraphai.graphs import SmartScraperGraph
node_config = {
    "graph_instance": SmartScraperGraph,
    "scraper_config": scraper_config,
}

if not node_config.get("graph_instance"):
    raise ValueError("node_config['graph_instance'] must be the graph class to fan out")

def has_graph_instance(node_config: dict) -> bool:
    return callable(node_config.get("graph_instance"))

try:
    result = iterator_graph.run()
except ValueError as e:
    if "graph instance is required" in str(e):
        # add graph_instance to node_config and retry
        ...

When it happens

Trigger: Configuring GraphIteratorNode without node_config['graph_instance'], passing None explicitly, or passing an instance instead of the class (though the None check here fires only when the key is missing/None).

Common situations: Copy-pasting a SmartScraperGraph config into a ScriptScraperMultisourceGraph or similar iterator-based graph and dropping the graph_instance entry; assuming the node reuses the parent graph automatically.

Related errors

• LLM configuration must include an 'api_key'.
• langchain_google_genai is not installed. Please install it u
• The browserbase module is not installed. Please install it u
• Cannot deep copy object of type {type(obj)}
• Unsupported service tier {service_tier!r} for {model_name}

AI-assisted analysis of ScrapeGraphAI/Scrapegraph-ai@532dfffbf6 (2026-08-28). Data as JSON: /api/errors/fc7f1d9dbecc7e03. Report an issue: GitHub.