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nisse/tests/integration/test_passthrough_live.py
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dongarandClaude Opus 5.5 83804fe02a
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Put work items in the state store, and bind the log to them (M1.1)
Development Plan M1.1, as discussed.

- Schema v4: a work_items table (id, scope, title, status, outcome,
  position, data) and an agent row whose active_item points at one
  (NULL: idle). Canonical events and intents carry their work item, and
  events their actor. Older stores are refused with a clear message:
  there was no production data, so no migration (the mechanism stays).
- The log is reached through a Transcript bound to one work item and
  one actor: store.transcript(item, actor) reads only that item and
  writes with both. The planner, executor, delegation and expert desk
  get one per call from the orchestrator instead of holding the store,
  so a component can neither read another task's events (the planner
  read every earlier task's, #78) nor write without attribution.
  store.all_events() is kept for readers that span items (evaluation
  capture, dumps). Intents are begun through the transcript or with
  work_item=, so each belongs to its item.
- The orchestrator opens a work item on 'use', closes it with its
  outcome (completed or abandoned), and carries what the operator said
  while idle into the new item as copies with their origin, so a task
  sent before 'use' is still planned from (D1). control.py keeps its
  state machine through get_state()/transition(), now over the active
  work item, until M2.6 retires it.
- nisse_dev.dump shows work items and each event's item and actor.

Tests: test_work_items.py (scoping, attribution, intent ownership,
restart, outcomes, carried messages, a second task never seeing the
first); the suites updated for the per-call transcript.

Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01PPQ14L3LikyefCMFBqEbKE
2026-10-01 23:20:29 +00:00

104 lines
3.5 KiB
Python

"""Live Anthropic passthrough: the vendor-native route delegations will use.
Proves the renderer's body is accepted as-is, that a tool call round-trips
through the canonical log, and — per L9 — that prompt caching survives the
passthrough rather than being flattened by the proxy.
"""
import io
from pathlib import Path
import httpx
import pytest
from nisse_dev.canonical import AssistantText, ToolCall, ToolResult, UserMessage
from nisse_dev.config import AgentConfig
from nisse_dev.llm import AnthropicPassthroughClient
from nisse_dev.oplog import OpLog
from nisse_dev.state import StateStore
from nisse_dev.tools import EXECUTOR_TOOLS
pytestmark = pytest.mark.integration
def store_with(tmp_path: Path, *events) -> StateStore:
store = StateStore(tmp_path / "state.db", oplog=OpLog("nisse-dev", io.StringIO()))
for event in events:
store.transcript("t", "helper").append(event)
return store
def test_passthrough_completes_a_plain_turn(
tmp_path: Path, passthrough: AnthropicPassthroughClient, live_model: str
) -> None:
store = store_with(
tmp_path, UserMessage(text="Reply with exactly: pong", source="live")
)
result = passthrough.complete(
store.transcript("t", "helper").read(), None, live_model, system="Be terse."
)
texts = [e.text for e in result if isinstance(e, AssistantText)]
assert texts and "pong" in texts[0].lower()
def test_passthrough_round_trips_a_tool_call(
tmp_path: Path, passthrough: AnthropicPassthroughClient, live_model: str
) -> None:
store = store_with(
tmp_path,
UserMessage(
text="List the files in the current directory using your tools.",
source="live",
),
)
client = passthrough
produced = client.complete(
store.transcript("t", "helper").read(),
EXECUTOR_TOOLS,
live_model,
system="Use a tool. Do not answer in prose.",
)
calls = [e for e in produced if isinstance(e, ToolCall)]
assert calls, f"expected a tool call, got {produced!r}"
# Feed the result back: the follow-up render must be accepted, which is
# what proves tool_result placement is right for this vendor.
for event in produced:
store.transcript("t", "helper").append(event)
store.transcript("t", "helper").append(
ToolResult(call_id=calls[0].call_id, result="app.py\ntests/", success=True)
)
follow_up = client.complete(
store.transcript("t", "helper").read(), EXECUTOR_TOOLS, live_model
)
assert follow_up, "the vendor rejected or ignored the tool_result turn"
def test_prompt_caching_survives_the_passthrough(
live_config: AgentConfig, live_model: str
) -> None:
# L9 asks for this to be verified rather than assumed: a proxy that
# flattened the request would silently drop cache control and turn a
# cost optimisation into a per-call expense.
base = live_config.llm_base_url.rstrip("/")
token = live_config.llm_token
response = httpx.post(
f"{base}/v1/messages",
headers={
"Authorization": f"Bearer {token}",
"x-api-key": token,
"anthropic-version": "2023-06-01",
},
json={
"model": live_model,
"max_tokens": 16,
"messages": [{"role": "user", "content": "Say pong."}],
},
timeout=120,
)
response.raise_for_status()
usage = response.json().get("usage", {})
assert "cache_read_input_tokens" in usage, (
f"cache accounting absent from passthrough usage: {usage}"
)