mirror of
https://github.com/andrewyng/openworker.git
synced 2026-09-03 13:00:37 +00:00
Devika Verma
330010cc66
The live smoke exposed a harness trap: driving each turn through its own asyncio.run() binds the engine asyncio primitives to the first loop, and every later stream silently takes the interrupted path - full provider replies persisted as empty assistant messages. The scripted smoke had the same latent artifact and did not assert reply content, so it stayed green. Now the whole scenario runs on ONE loop (like the real server) and every turn asserts a real reply.
115 lines
5.3 KiB
Python
115 lines
5.3 KiB
Python
"""OPE-27 smoke (4/4) — a long multi-turn session driven through the real SessionManager
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across REPEATED forced compactions: the provider must actually receive the compacted
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view (summary block + verbatim tail), user intent must survive every compaction, and the
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state must survive a save/rebuild mid-conversation. This is the scripted stand-in for
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the live-model smoke (which needs a configured provider key)."""
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import json
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import asyncio
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from coworker.providers import AssistantTurn, ModelCapabilities, ProviderClient
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from coworker.providers.base import TokenUsage
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from coworker.server.manager import SessionManager
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BULK = "analysis paragraph " * 400 # ~7.6k chars (~1.9k tokens) per turn → triggers by turn 2
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class LongSessionProvider(ProviderClient):
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"""Main turns: bulky text answers with realistic (growing) usage reporting.
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Summarizer turns: a structured summary echoing the required sections."""
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def __init__(self):
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self.main_messages_seen: list[list[dict]] = []
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self.summary_prompts: list[str] = []
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def complete(self, *, model, messages, tools=None, **settings):
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if messages and "compacting an AI coworker" in str(
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messages[0].get("content", "")
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):
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self.summary_prompts.append(str(messages[1]["content"]))
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return AssistantTurn(
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text=(
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"## Primary request and intent\nBuild the Q3 report; never email "
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"it without approval.\n## Current work\nDrafting section "
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f"{len(self.summary_prompts)}.\n## Next step\nContinue drafting."
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),
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finish_reason="stop",
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)
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self.main_messages_seen.append([dict(m) for m in messages])
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# Usage mirrors the outbound size (chars/4), like a real provider would bill it.
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prompt_tokens = sum(len(json.dumps(m, default=str)) for m in messages) // 4
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return AssistantTurn(
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text=f"turn {len(self.main_messages_seen)}: {BULK}",
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finish_reason="stop",
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usage=TokenUsage(input=prompt_tokens, output=500),
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)
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def capabilities(self, model):
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return ModelCapabilities()
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def test_long_session_survives_repeated_compaction(tmp_path):
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provider = LongSessionProvider()
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mgr = SessionManager(workspace=tmp_path, provider=provider)
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# Force tiny windows straight through the real Settings plumbing.
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mgr._prefs["compaction_cap_tokens"] = 3_000
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sid = "smoke-long"
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boundaries = []
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# ONE event loop for the whole session, like the real server — the engine's asyncio
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# primitives bind to the loop they first run on, so a per-turn asyncio.run() would
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# silently drop every stream after the first (found the hard way in the live smoke).
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async def scenario():
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engine = mgr.get_engine(sid, agent="cowork", workspace=str(tmp_path))
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for i in range(8):
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async for _ in engine.run(f"user step {i}: keep drafting the Q3 report"):
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pass
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# Every turn must produce a real reply — an empty assistant message means
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# the stream got dropped, not answered.
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last = next(
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m for m in reversed(engine.messages) if m.get("role") == "assistant"
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)
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assert f"turn {i + 1}:" in str(last.get("content", ""))
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if engine.compaction_state is not None:
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if (
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not boundaries
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or engine.compaction_state.boundary_index != boundaries[-1]
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):
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boundaries.append(engine.compaction_state.boundary_index)
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mgr.save(sid, engine)
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if i == 4: # mid-conversation restart: state must survive the rebuild
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mgr._engines.pop(sid)
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engine = mgr.get_engine(sid, agent="cowork", workspace=str(tmp_path))
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assert engine.compaction_state is not None
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return engine
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engine = asyncio.run(scenario())
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# Repeated compaction actually happened, moving forward each time.
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assert len(boundaries) >= 2
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assert boundaries == sorted(boundaries)
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# Later summarizer calls fold the previous summary in (summary is message zero).
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assert any("previous compaction summary" in p for p in provider.summary_prompts)
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# What the MODEL actually received after the last compaction: the block + the tail,
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# bounded — not the whole ever-growing canonical history.
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final_view = provider.main_messages_seen[-1]
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assert final_view[0]["role"] == "system"
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block = final_view[1]["content"]
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assert "<compacted-history>" in block
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assert "Q3 report" in block # the summary carries the intent
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assert "user step 0" in block # mechanical user-message preservation, from turn 0
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assert "do not recap" in block # the continuation contract
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assert len(final_view) < len(engine.messages)
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# Canonical transcript: untouched (every turn still present) + the divider notices.
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texts = [str(m.get("content", "")) for m in engine.messages]
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assert all(any(f"user step {i}" in t for t in texts) for i in range(8))
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assert sum(1 for m in engine.messages if m.get("kind") == "compacted") >= 2
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# The persisted record round-trips the final state.
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record = mgr.session_store.load(sid)
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assert record.compaction["boundary_index"] == engine.compaction_state.boundary_index
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