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chore: drop AGE-90 manual dev runner script
Removes scripts/age90_file_input_runner.py, a manual development test runner for PDF input handling that was never meant to ship in the repo. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
This commit is contained in:
lorenzejay
@@ -1,226 +0,0 @@
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# ruff: noqa: T201
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"""Manual runner for AGE-90 PDF input handling.
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Usage examples:
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uv run python scripts/age90_file_input_runner.py
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uv run python scripts/age90_file_input_runner.py --mode fallback
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uv run python scripts/age90_file_input_runner.py --mode payload --pdf ./sample_story.pdf
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uv run python scripts/age90_file_input_runner.py --mode kickoff --pdf ./sample_story.pdf
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"""
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from __future__ import annotations
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import argparse
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from collections.abc import Mapping, Sequence
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from contextlib import nullcontext
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import os
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from pathlib import Path
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from typing import Any
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from unittest.mock import patch
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from crewai_files import PDFFile, format_multimodal_content, get_supported_content_types
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ROOT = Path(__file__).resolve().parents[1]
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DEFAULT_PDF = ROOT / "lib" / "crewai-files" / "tests" / "fixtures" / "agents.pdf"
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def _content_summary(block: dict[str, Any]) -> dict[str, str]:
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"""Return a compact, non-base64 summary of a content block."""
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summary: dict[str, str] = {"type": str(block.get("type"))}
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for key in ("file_id", "file_url", "filename", "image_url"):
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if key in block:
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value = str(block[key])
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summary[key] = value[:100] + ("..." if len(value) > 100 else "")
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if "file_data" in block:
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value = str(block["file_data"])
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summary["file_data"] = value[:80] + f"... ({len(value)} chars)"
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return summary
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def _sanitize_payload(value: Any) -> Any:
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"""Shorten large fields before printing API payloads."""
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if isinstance(value, Mapping):
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sanitized: dict[str, Any] = {}
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for key, item in value.items():
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if key == "file_data" and isinstance(item, str):
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sanitized[key] = item[:100] + f"... ({len(item)} chars)"
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else:
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sanitized[str(key)] = _sanitize_payload(item)
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return sanitized
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if isinstance(value, Sequence) and not isinstance(value, str | bytes):
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return [_sanitize_payload(item) for item in value]
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return value
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def inspect_native_path(pdf_path: Path, provider: str, api: str | None) -> None:
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"""Show whether the PDF is treated as a native multimodal input."""
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pdf = PDFFile(source=str(pdf_path))
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supported_types = get_supported_content_types(provider, api=api)
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blocks = format_multimodal_content(
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{"document": pdf},
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provider=provider,
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api=api,
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text="Summarize this PDF.",
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)
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print("\n== Native File Formatting ==")
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print(f"PDF: {pdf_path}")
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print(f"Provider/API: {provider} / {api or 'default'}")
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print(f"Supported content types: {supported_types}")
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print(f"Content block count: {len(blocks)}")
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for index, block in enumerate(blocks, start=1):
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print(f" {index}. {_content_summary(block)}")
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has_pdf_block = any(block.get("type") == "input_file" for block in blocks)
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print(f"PDF native input_file block: {'YES' if has_pdf_block else 'NO'}")
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def inspect_fallback_tool(pdf_path: Path) -> None:
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"""Show what read_file returns if a PDF falls back to the tool path."""
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from crewai.tools.agent_tools.read_file_tool import ReadFileTool
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tool = ReadFileTool()
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tool.set_files({"document": PDFFile(source=str(pdf_path))})
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result = tool._run("document")
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print("\n== read_file Fallback ==")
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print(f"Returned {len(result)} chars")
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print(f"Contains Base64 marker: {'YES' if 'Base64:' in result else 'NO'}")
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print("\nPreview:")
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print(result[:1200])
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if len(result) > 1200:
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print("...")
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def run_crew_kickoff(
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pdf_path: Path,
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model: str,
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api: str | None,
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prompt: str,
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*,
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payload_only: bool = False,
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) -> None:
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"""Run a real Crew kickoff against the supplied model."""
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from crewai import LLM, Agent, Crew, Task
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if model.startswith("openai/") and not os.getenv("OPENAI_API_KEY") and not payload_only:
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raise SystemExit(
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"OPENAI_API_KEY is not set. Export it before running --mode kickoff."
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)
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kwargs: dict[str, Any] = {"model": model, "temperature": 0}
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if api:
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kwargs["api"] = api
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llm = LLM(**kwargs)
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agent = Agent(
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role="PDF Analyst",
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goal="Read the provided PDF and answer accurately from its contents",
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backstory="You inspect uploaded files carefully and avoid guessing.",
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llm=llm,
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verbose=True,
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)
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task = Task(
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description=prompt,
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expected_output="A concise answer grounded in the uploaded PDF.",
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agent=agent,
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)
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crew = Crew(agents=[agent], tasks=[task], verbose=True)
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print("\n== Crew Kickoff ==")
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print(f"Model/API: {model} / {api or 'default'}")
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print(f"PDF: {pdf_path}")
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context = nullcontext()
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if payload_only:
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from crewai.llms.providers.openai.completion import OpenAICompletion
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def print_payload_and_stop(
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self: OpenAICompletion,
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params: dict[str, Any],
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*_args: Any,
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**_kwargs: Any,
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) -> str:
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print("\n== Sanitized Responses Payload ==")
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print(_sanitize_payload(params))
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return "Payload debug complete."
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context = patch.object(
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OpenAICompletion,
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"_handle_responses",
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print_payload_and_stop,
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)
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with context:
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result = crew.kickoff(input_files={"document": PDFFile(source=str(pdf_path))})
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print("\n== Final Output ==")
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print(result.raw)
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def parse_args() -> argparse.Namespace:
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument(
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"--mode",
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choices=("inspect", "fallback", "payload", "kickoff", "all"),
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default="inspect",
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help="What to run. 'inspect', 'fallback', and 'payload' do not call an LLM.",
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)
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parser.add_argument(
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"--pdf",
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type=Path,
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default=DEFAULT_PDF,
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help="PDF file to test.",
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)
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parser.add_argument(
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"--provider",
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default="gpt-4o-mini",
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help="Provider/model string for file formatting inspection.",
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)
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parser.add_argument(
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"--model",
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default="openai/gpt-4o-mini",
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help="CrewAI model for real kickoff mode.",
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)
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parser.add_argument(
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"--api",
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default="responses",
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help="API variant. Use '' to omit.",
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)
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parser.add_argument(
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"--prompt",
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default="Summarize the uploaded PDF in 3 bullet points. Do not guess.",
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help="Task prompt for kickoff mode.",
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)
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return parser.parse_args()
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def main() -> None:
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args = parse_args()
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pdf_path = args.pdf.expanduser().resolve()
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api = args.api or None
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if not pdf_path.exists():
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raise SystemExit(f"PDF not found: {pdf_path}")
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if args.mode in ("inspect", "all"):
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inspect_native_path(pdf_path, args.provider, api)
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if args.mode in ("fallback", "all"):
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inspect_fallback_tool(pdf_path)
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if args.mode == "payload":
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run_crew_kickoff(pdf_path, args.model, api, args.prompt, payload_only=True)
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if args.mode in ("kickoff", "all"):
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run_crew_kickoff(
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pdf_path,
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args.model,
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api,
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args.prompt,
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payload_only=args.mode == "all",
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)
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if __name__ == "__main__":
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main()
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