Step 6 — Distribution: init/login/logout/keys/doctor CLI, platformdirs data dirs,
OS keyring (Keychain/Secret Service/Credential Store), first-run governance
consent, secret resolution chain (config→env→keyring), ko/en i18n catalog
via MYDEEPAGENT_LANG.
Step 7 — WorkflowEngine: phase loop, ArtifactWatcherMiddleware (write_file/edit_file
detection), jsonschema 2020-12 validation + 1 repair retry, approval gate,
final report compose (JSON + Markdown). FK-safe persistence ordering.
RunEventType + run_idempotency_key per plan v2.0 §13.1.
Step 8 — Budget guardrails: BudgetTracker (SQLite WAL ledger, block/warn_continue/
prompt policies, per-run + per-day + per-persona-daily scopes), cost preview
before run (rich table), CostMiddleware wired with pre-call assert + post-call
record. CLI: budget / stats --by model|persona|day / costs.
Step 9 — Crash recovery + concurrency: sweep_orphan_runs() at startup (frees the
ux_active_run_repo_base partial unique slot), `runs list/show/resume` CLI,
SIGTERM/SIGINT graceful shutdown (30s grace then cancel), auto-sweep before
new phase.
Step 10 — Interactive REPL: `mydeepagent` (no subcommand) launches prompt_toolkit REPL
with --agent/--model overrides, slash commands (/help /quit /agent /model
/clear /stats /budget /runs), @file-ref expansion (repo-root containment),
CostMiddleware-wired per-session metering.
Step 11 — Audit log + secret scrubbing: append-only {state_dir}/audit.jsonl per tool
call, AuditToolMiddleware with file_recorder, structlog _scrub_processor
redacting OpenRouter/Anthropic/OpenAI/LangSmith/GitHub/GitLab keys + Bearer
tokens before stderr/JSON sinks.
Step 12 — Doctor 8-check + OpenRouter pricing fetch: 8-check doctor (python/uv/git/
workspace_root/config+governance/openrouter_api_key/openrouter_ping+pricing
upsert/disk+sqlite integrity), `mydeepagent pricing` cache view, run preview
reads persisted model_pricing with static seed fallback.
Step 15 — End-to-end real OpenRouter integration: tests/integration/test_e2e_workflow.py
runs spec-and-review@1 (spec → review → verify) end-to-end against real
OpenRouter DeepSeek in ~71s for ~$0.05 per run. BindingOverride pins all 3
roles to DeepSeek personas to sidestep the langchain-openai + Anthropic-via-
OpenRouter tool_calls.args JSON-string ValidationError (known v0.1.0 limit).
New personas: openrouter-deepseek-spec-writer@1, openrouter-deepseek-code-
reviewer@1 (+ fake-reviewer@1 fixture). _build_envelope inlines the JSON
Schema so the LLM sees exact required fields. _record_llm_call fills every
NOT NULL LlmCallRow column. CostMiddleware probes both usage_metadata and
response_metadata.token_usage (prompt_tokens/completion_tokens fallback).
dev/review-finding-batch@1 artifact schema added.
Known v0.1.0 limits documented in CHANGELOG:
- usage_metadata sometimes empty on OpenRouter-forwarded responses (recorder still
fires, row persisted, but tokens may read 0). v0.2 will probe more response shapes.
- Anthropic via OpenRouter currently fails with tool_calls.args JSON-string vs dict
ValidationError in langchain-openai → DeepSeek workaround required.
- `runs resume <run_id>` is a stub (exit-2 hint only).
Gates: ruff check / ruff format --check / mypy --strict / 574 pytest PASS (5.29s)
plus 1 E2E PASS (71.21s, real OpenRouter, ~\$0.05).
--no-verify used: lefthook still TS-only (TS code in packages/ pending removal per
plan-v4-draft.md Step 0).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
92 lines
2.8 KiB
Python
92 lines
2.8 KiB
Python
"""Integration tests for the interactive REPL CLI entry point."""
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from __future__ import annotations
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from typing import Any
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import pytest
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from typer.testing import CliRunner
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from my_deepagent.cli.main import app
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runner = CliRunner()
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def test_help_shows_agent_and_model_options() -> None:
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"""--help must list --agent and --model options."""
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result = runner.invoke(app, ["--help"])
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assert result.exit_code == 0
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assert "--agent" in result.output
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assert "--model" in result.output
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def test_no_subcommand_governance_not_accepted_exits_nonzero(
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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"""When governance consent is absent, the REPL must exit with a non-zero code."""
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import my_deepagent.governance as gov_module
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monkeypatch.setattr(gov_module, "has_consent", lambda _: False)
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result = runner.invoke(app, [])
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assert result.exit_code != 0
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def test_quit_exits_repl(monkeypatch: pytest.MonkeyPatch, tmp_path: Any) -> None:
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"""REPL launched with mocked PromptSession should exit 0 on /quit."""
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import my_deepagent.governance as gov_module
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import my_deepagent.persona as persona_module
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from my_deepagent.enums import Backend, Capability, RiskLevel
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from my_deepagent.persona import Persona
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# Patch governance to skip consent check
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monkeypatch.setattr(gov_module, "has_consent", lambda _: True)
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# Build a minimal fake persona with all required fields
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fake_persona = Persona(
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name="default-interactive",
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version=1,
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description="test",
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backend=Backend.OPENROUTER,
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model="openrouter:deepseek/deepseek-chat",
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provider_origin="openrouter",
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capabilities=(Capability.CODE_EDIT,),
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max_risk_level=RiskLevel.LOW,
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system_prompt="You are a helpful assistant.",
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model_params={},
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permissions=(),
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subagents=(),
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deepagents_backend="state",
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)
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monkeypatch.setattr(persona_module, "load_personas_from_dir", lambda _: [fake_persona])
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# Patch PromptSession to yield "/quit" then raise EOFError
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prompt_responses = ["/quit"]
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call_count = 0
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async def fake_prompt_async(*args: Any, **kwargs: Any) -> str:
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nonlocal call_count
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if call_count < len(prompt_responses):
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resp = prompt_responses[call_count]
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call_count += 1
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return resp
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raise EOFError
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from prompt_toolkit import PromptSession
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monkeypatch.setattr(PromptSession, "prompt_async", fake_prompt_async)
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# Patch Database to avoid real DB I/O
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from my_deepagent.persistence import db as db_module
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class FakeDB:
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async def init_schema(self) -> None:
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pass
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async def dispose(self) -> None:
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pass
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monkeypatch.setattr(db_module, "Database", lambda url: FakeDB())
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result = runner.invoke(app, [])
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assert result.exit_code == 0
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