chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
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from __future__ import annotations
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import argparse
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import asyncio
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import sys
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from pathlib import Path
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from agents import Runner, SQLiteSession
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from agents.run import RunConfig
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from agents.sandbox import Manifest, MemoryLayoutConfig, SandboxAgent, SandboxRunConfig
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from agents.sandbox.capabilities import Filesystem, Memory, Shell
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from agents.sandbox.entries import Dir, File
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from agents.sandbox.sandboxes.unix_local import UnixLocalSandboxClient
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if __package__ is None or __package__ == "":
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sys.path.insert(0, str(Path(__file__).resolve().parents[2]))
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DEFAULT_MODEL = "gpt-5.6-sol"
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GTM_SESSION_ID = "gtm-q2-pipeline-review"
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ENGINEERING_SESSION_ID = "eng-invoice-test-fix"
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GTM_TURN_1 = (
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"Analyze data/leads.csv. Find one promising GTM segment, explain why, and say what "
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"follow-up data you need."
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)
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GTM_TURN_2 = (
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"Using your previous GTM analysis, write a short outreach hypothesis and save it to "
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"gtm_hypothesis.md."
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)
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ENGINEERING_TURN = (
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"Fix the invoice total bug in src/acme_metrics/report.py, then run the test suite."
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)
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def _build_manifest() -> Manifest:
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return Manifest(
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entries={
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"data": Dir(
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children={
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"leads.csv": File(
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content=(
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b"account,segment,seats,trial_events,monthly_spend\n"
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b"Northstar Health,healthcare,240,98,18000\n"
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b"Beacon Retail,retail,75,18,4200\n"
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b"Apex Fintech,financial-services,180,76,13500\n"
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b"Summit Labs,healthcare,52,22,3900\n"
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)
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)
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}
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),
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"pyproject.toml": File(
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content=(
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b"[project]\n"
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b'name = "acme-metrics"\n'
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b'version = "0.1.0"\n'
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b'requires-python = ">=3.10"\n'
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b"\n"
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b"[tool.pytest.ini_options]\n"
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b'pythonpath = ["src"]\n'
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)
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),
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"src": Dir(
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children={
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"acme_metrics": Dir(
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children={
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"__init__.py": File(
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content=b"from .report import format_invoice_total\n"
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),
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"report.py": File(
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content=(
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b"from __future__ import annotations\n\n"
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b"def format_invoice_total(subtotal: float, tax_rate: float) -> str:\n"
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b" total = subtotal + tax_rate\n"
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b' return f"${total:.2f}"\n'
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)
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),
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}
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)
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}
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),
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"tests": Dir(
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children={
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"test_report.py": File(
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content=(
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b"from acme_metrics import format_invoice_total\n\n\n"
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b"def test_format_invoice_total_applies_tax_rate() -> None:\n"
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b' assert format_invoice_total(100.0, 0.075) == "$107.50"\n'
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)
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)
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}
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),
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}
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)
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def _build_gtm_agent(*, model: str, manifest: Manifest) -> SandboxAgent:
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return SandboxAgent(
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name="GTM analyst",
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model=model,
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instructions=(
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"You are a GTM analyst. Inspect the workspace data before answering. Keep analysis "
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"specific and cite file paths you used."
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),
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default_manifest=manifest,
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capabilities=[
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# Same layout + same SDK session across turns means one memory conversation.
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Memory(
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layout=MemoryLayoutConfig(
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memories_dir="memories/gtm",
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sessions_dir="sessions/gtm",
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)
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),
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Filesystem(),
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Shell(),
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Filesystem(),
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],
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)
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def _build_engineering_agent(*, model: str, manifest: Manifest) -> SandboxAgent:
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return SandboxAgent(
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name="Engineering fixer",
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model=model,
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instructions=(
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"You are an engineer. Inspect files before editing, make minimal changes, and verify "
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"with tests. Use a non-login POSIX shell for commands. Make one focused pytest attempt; "
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"if the local sandbox blocks Python or toolchain access, report that validation was "
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"blocked and finish instead of retrying repeatedly."
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),
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default_manifest=manifest,
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capabilities=[
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# Different layout keeps engineering memory separate even in the same sandbox workspace.
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Memory(
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layout=MemoryLayoutConfig(
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memories_dir="memories/engineering",
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sessions_dir="sessions/engineering",
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)
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),
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Shell(),
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Filesystem(),
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],
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)
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def _print_tree(
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root: Path, label: str, relative_path: str, *, print_file_contents: bool = False
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) -> None:
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print(f"\n[{label}]")
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base = root / relative_path
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if not base.exists():
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print(f"{relative_path} (missing)")
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return
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for path in sorted(base.rglob("*")):
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if path.is_file():
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print(path.relative_to(root))
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if print_file_contents:
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contents = path.read_text().rstrip()
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if not contents:
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print(" (empty)")
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else:
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for line in contents.splitlines():
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print(f" {line}")
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async def main(*, model: str) -> None:
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manifest = _build_manifest()
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gtm_agent = _build_gtm_agent(model=model, manifest=manifest)
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engineering_agent = _build_engineering_agent(model=model, manifest=manifest)
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client = UnixLocalSandboxClient()
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sandbox = await client.create(manifest=manifest)
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workspace_root = Path(sandbox.state.manifest.root)
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try:
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async with sandbox:
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gtm_conversation_session = SQLiteSession(GTM_SESSION_ID)
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gtm_config = RunConfig(
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sandbox=SandboxRunConfig(session=sandbox),
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workflow_name="GTM memory layout example",
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)
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gtm_first = await Runner.run(
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gtm_agent,
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GTM_TURN_1,
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session=gtm_conversation_session,
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run_config=gtm_config,
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)
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print("\n[gtm turn 1]")
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print(gtm_first.final_output)
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# Reuse the SDK session so the model sees prior turns and memory extracts them together.
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gtm_second = await Runner.run(
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gtm_agent,
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GTM_TURN_2,
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session=gtm_conversation_session,
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run_config=gtm_config,
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)
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print("\n[gtm turn 2]")
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print(gtm_second.final_output)
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engineering_conversation_session = SQLiteSession(ENGINEERING_SESSION_ID)
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engineering_config = RunConfig(
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sandbox=SandboxRunConfig(session=sandbox),
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workflow_name="Engineering memory layout example",
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)
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engineering = await Runner.run(
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engineering_agent,
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ENGINEERING_TURN,
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session=engineering_conversation_session,
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run_config=engineering_config,
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max_turns=20,
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)
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print("\n[engineering]")
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print(engineering.final_output)
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_print_tree(workspace_root, "gtm memory", "memories/gtm")
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_print_tree(workspace_root, "engineering memory", "memories/engineering")
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_print_tree(workspace_root, "gtm sessions", "sessions/gtm", print_file_contents=True)
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_print_tree(
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workspace_root,
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"engineering sessions",
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"sessions/engineering",
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print_file_contents=True,
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)
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finally:
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await client.delete(sandbox)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(
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description="Run two sandbox agents with separate memory layouts in one workspace."
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)
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parser.add_argument("--model", default=DEFAULT_MODEL, help="Model name to use.")
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args = parser.parse_args()
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asyncio.run(main(model=args.model))
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