ScrapeGraphAI/Scrapegraph-ai · warning · InvalidCorrectionStateError

Analysis must be a non-empty string

Error message

Analysis must be a non-empty string

What it means

syntax_focused_code_generation rejects an analysis argument that is falsy or not a str. The analysis string is supposed to come from the preceding syntax_focused_analysis step, so this means the pipeline was wired incorrectly or the analysis returned None/empty.

Source

Thrown at scrapegraphai/utils/code_error_correction.py:117

    Raises:
        InvalidCorrectionStateError: If state is missing required keys.

    Example:
        >>> state = {
            'generated_code': 'print("Hello World"'
        }
        >>> analysis = "Missing closing parenthesis in print statement"
        >>> corrected_code = syntax_focused_code_generation(state, analysis, mock_llm)
    """
    try:
        # Validate state using Pydantic model
        validated_state = CorrectionState(
            generated_code=state.get("generated_code", "")
        )

        if not analysis or not isinstance(analysis, str):
            raise InvalidCorrectionStateError("Analysis must be a non-empty string")

        # Create prompt template and chain
        prompt = PromptTemplate(
            template=get_optimal_correction_template("syntax"),
            input_variables=["analysis", "generated_code"],
        )
        chain = prompt | llm_model | StrOutputParser()

        # Execute chain with validated state
        return chain.invoke(
            {"analysis": analysis, "generated_code": validated_state.generated_code}
        )

    except KeyError as e:
        raise InvalidCorrectionStateError(
            f"Missing required key in state dictionary: {e}"
        )
    except Exception as e:

View on GitHub (pinned to 532dfffbf6)

Solutions

1. Pass the string output of syntax_focused_analysis as analysis
2. If the analysis came from parsing, coerce: analysis = str(parsed) if parsed else raise/stop
3. Short-circuit the correction loop when analysis is empty instead of calling

Example fix

# before
code = syntax_focused_code_generation(state, None, llm)
# after
if analysis:
    code = syntax_focused_code_generation(state, analysis, llm)

assert isinstance(analysis, str) and analysis, "analysis must be a non-empty string"

def is_analysis_text(a) -> bool:
    return isinstance(a, str) and bool(a.strip())

from scrapegraphai.utils.code_error_correction import InvalidCorrectionStateError
try:
    syntax_focused_code_generation(state, analysis, llm_model)
except InvalidCorrectionStateError:
    analysis = str(analysis) if analysis else None
    if analysis is None:
        raise

When it happens

Trigger: Calling syntax_reasoning_loop / syntax_focused_code_generation(state, analysis, llm_model) with analysis=None, '' or a non-string (e.g. a dict returned by an LLM parse step).

Common situations: Chaining steps manually and passing the wrong variable (state instead of analysis); analysis step returned an object rather than its string content; empty analysis from an LLM that returned nothing.

Understand the failure class

Background: Invalid argument type errors: "must be of type string", "expected X, got Y", and ERR_INVALID_ARG_TYPE explained — this error's family across 15 libraries.

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
• ConditionalNode '{node.node_name}' must have exactly two out
• Missing required key in state dictionary: {e}

AI-assisted analysis of ScrapeGraphAI/Scrapegraph-ai@532dfffbf6 (2026-08-28). Data as JSON: /api/errors/87208dd7c6a74778. Report an issue: GitHub.