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ArtificialAnalysisWorkflow

What it is​

  • A workflow that fetches model data from the Artificial Analysis API, optionally filters the results to only providers that have corresponding local agent modules, and saves the result as a timestamped JSON file under a fixed storage path.

Public API​

  • ArtificialAnalysisWorkflowConfiguration (WorkflowConfiguration, dataclass)
    • api_key: str: Artificial Analysis API key (required).
    • base_url: str = "https://artificialanalysis.ai/api/v2": API base URL.
  • ArtificialAnalysisWorkflowParameters (WorkflowParameters)
    • endpoint: str = "llms": Endpoint to fetch (e.g., "llms" or media endpoints like "text-to-image").
    • include_categories: bool = False: Adds include_categories=true query param for media endpoints.
    • validate_agents_only: bool = True: If True, filters models to those with corresponding local agent modules.
  • ArtificialAnalysisWorkflow (Workflow)
    • __init__(configuration: ArtificialAnalysisWorkflowConfiguration): Stores configuration.
    • run_workflow(parameters: ArtificialAnalysisWorkflowParameters) -> dict: Fetches API data, optionally filters, writes JSON to disk, returns summary dict.
    • as_tools() -> list[BaseTool]: Exposes a LangChain StructuredTool named artificial_analysis_data_fetch.
    • as_api(...) -> None: Present but intentionally does nothing (returns None).

Internal helpers (not public API): _fetch_models_data, _get_modules_with_agents, _filter_data_for_valid_modules, _extract_module_name_from_model.

Configuration/Dependencies​

  • Network/API
    • Uses requests.get with header x-api-key: <api_key>.
    • URL logic:
      • If endpoint == "llms": .../data/llms/models
      • Else: .../data/media/{endpoint}
  • Filesystem
    • Scans for modules with agents under: src/core/modules/<module>/agents/*Agent.py
    • Saves output JSON under:
      • storage/datastore/core/modules/abi/ArtificialAnalysisWorkflow/<timestamp>_<endpoint>_data.json
  • Key libraries
    • requests, pydantic, langchain_core.tools, naas_abi_core.workflow

Usage​

from naas_abi.workflows.ArtificialAnalysisWorkflow import (
    ArtificialAnalysisWorkflow,
    ArtificialAnalysisWorkflowConfiguration,
    ArtificialAnalysisWorkflowParameters,
)

wf = ArtificialAnalysisWorkflow(
    ArtificialAnalysisWorkflowConfiguration(api_key="YOUR_ARTIFICIAL_ANALYSIS_API_KEY")
)

result = wf.run_workflow(
    ArtificialAnalysisWorkflowParameters(
        endpoint="llms",
        include_categories=False,
        validate_agents_only=True,
    )
)

print(result["status"], result["output_file"])

Caveats​

  • Filtering via validate_agents_only=True depends on the local repository layout existing at src/core/modules and containing agents/*Agent.py files; if the path is missing, no modules are considered valid.
  • as_api(...) is a no-op and does not register any routes.
  • Provider-to-module matching uses a fixed mapping (e.g., "openai" -> "chatgpt", "anthropic" -> "claude") and fallbacks based on provider/model name heuristics; mismatches may cause models to be filtered out.