dongarandClaude Opus 5.5
6ae2375194
nisse-dev now runs only the conversational loop. The gated state machine it was built alongside is gone: - Removed control.py, planner.py, executor.py, approvals.py, gates.py (command_form moves to loop/reader.py), publish.py and poller.py, the old assembly in agent.py (its shared helpers move to loop/build.py), the store's state-machine view (get_state, transition), their tests, the old end-to-end and live planning/milestone/gate tests, and specs/orchestrator.qnt with its scenarios. - Roles are driver, helper, expert and classifier; driver is required. loop:, roles.planner, roles.executor and tuning.executor are refused with what to use instead; tuning.driver takes the turn cap and failure limit. - The benchmark and the capability matrix measure the driver: the loop's own system prompt and tools, the task's plan as the agreed restatement. Task plans end with finish_milestone, so earlier runs show as (old); stored runs' executor tuning reads as the driver's. - A delegation on the loop records what its helper's alias resolved to (L9), as the old path's did. - The dump shows a work item's revision and what it waits for. - Behaviour the old tests covered and the loop shares stays covered: driver runs that fail on a model call, stop mid-turn, reset the failure count; go-aheads ignoring case and punctuation; a request too big to fit is never sent; the assembly tests, now on build_loop_agent. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01PPQ14L3LikyefCMFBqEbKE
104 lines
3.5 KiB
Python
104 lines
3.5 KiB
Python
"""Live Anthropic passthrough: the vendor-native route delegations will use.
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Proves the renderer's body is accepted as-is, that a tool call round-trips
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through the canonical log, and — per L9 — that prompt caching survives the
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passthrough rather than being flattened by the proxy.
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"""
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import io
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from pathlib import Path
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import httpx
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import pytest
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from nisse_dev.canonical import AssistantText, ToolCall, ToolResult, UserMessage
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from nisse_dev.config import AgentConfig
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from nisse_dev.llm import AnthropicPassthroughClient
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from nisse_dev.oplog import OpLog
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from nisse_dev.state import StateStore
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from nisse_dev.tools import EXECUTION_TOOLS
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pytestmark = pytest.mark.integration
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def store_with(tmp_path: Path, *events) -> StateStore:
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store = StateStore(tmp_path / "state.db", oplog=OpLog("nisse-dev", io.StringIO()))
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for event in events:
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store.transcript("t", "helper").append(event)
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return store
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def test_passthrough_completes_a_plain_turn(
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tmp_path: Path, passthrough: AnthropicPassthroughClient, live_model: str
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) -> None:
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store = store_with(
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tmp_path, UserMessage(text="Reply with exactly: pong", source="live")
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)
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result = passthrough.complete(
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store.transcript("t", "helper").read(), None, live_model, system="Be terse."
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)
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texts = [e.text for e in result if isinstance(e, AssistantText)]
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assert texts and "pong" in texts[0].lower()
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def test_passthrough_round_trips_a_tool_call(
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tmp_path: Path, passthrough: AnthropicPassthroughClient, live_model: str
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) -> None:
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store = store_with(
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tmp_path,
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UserMessage(
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text="List the files in the current directory using your tools.",
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source="live",
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),
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)
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client = passthrough
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produced = client.complete(
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store.transcript("t", "helper").read(),
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EXECUTION_TOOLS,
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live_model,
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system="Use a tool. Do not answer in prose.",
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)
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calls = [e for e in produced if isinstance(e, ToolCall)]
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assert calls, f"expected a tool call, got {produced!r}"
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# Feed the result back: the follow-up render must be accepted, which is
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# what proves tool_result placement is right for this vendor.
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for event in produced:
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store.transcript("t", "helper").append(event)
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store.transcript("t", "helper").append(
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ToolResult(call_id=calls[0].call_id, result="app.py\ntests/", success=True)
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)
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follow_up = client.complete(
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store.transcript("t", "helper").read(), EXECUTION_TOOLS, live_model
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)
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assert follow_up, "the vendor rejected or ignored the tool_result turn"
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def test_prompt_caching_survives_the_passthrough(
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live_config: AgentConfig, live_model: str
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) -> None:
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# L9 asks for this to be verified rather than assumed: a proxy that
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# flattened the request would silently drop cache control and turn a
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# cost optimisation into a per-call expense.
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base = live_config.llm_base_url.rstrip("/")
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token = live_config.llm_token
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response = httpx.post(
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f"{base}/v1/messages",
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headers={
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"Authorization": f"Bearer {token}",
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"x-api-key": token,
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"anthropic-version": "2023-06-01",
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},
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json={
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"model": live_model,
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"max_tokens": 16,
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"messages": [{"role": "user", "content": "Say pong."}],
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},
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timeout=120,
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)
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response.raise_for_status()
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usage = response.json().get("usage", {})
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assert "cache_read_input_tokens" in usage, (
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f"cache accounting absent from passthrough usage: {usage}"
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)
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