content-find-agent-new/tests/test_walk_engine_author.py

from content_agent.business_modules.walk_engine import run_bounded_walk
from tests.p6_walk_helpers import FakeWalkPlatformClient, build_initial_walk_context


def test_walk_engine_author_works_reenter_content_decision_flow(tmp_path):
    context = build_initial_walk_context(tmp_path)
    client = FakeWalkPlatformClient()

    result = run_bounded_walk(platform_client=client, **context)

    assert client.author_calls
    assert any(item["previous_discovery_step"] == "author_works" for item in result["discovered_content_items"])
    assert all(decision["decision_target_type"] == "content" for decision in result["rule_decisions"])
    assert any(row["edge_id"] == "author_to_works" for row in result["walk_actions"])


def test_walk_engine_author_edge_skips_missing_author_id(tmp_path):
    context = build_initial_walk_context(tmp_path)
    context["discovered_content_items"][0]["platform_author_id"] = ""
    context["discovered_content_items"][0]["has_more"] = False
    context["discovered_content_items"][0]["tags"] = []
    client = FakeWalkPlatformClient()

    run_bounded_walk(platform_client=client, **context)

    assert client.author_calls == []


def _override_decisions(context, action, effect_status):
    for decision in context["rule_decisions"]:
        decision["decision_action"] = action
        decision["search_query_effect_status"] = effect_status


def test_author_edge_skips_rejected_content(tmp_path):
    context = build_initial_walk_context(tmp_path)
    _override_decisions(context, "REJECT_CONTENT", "rule_blocked")
    client = FakeWalkPlatformClient()

    result = run_bounded_walk(platform_client=client, **context)

    assert client.author_calls == []
    skipped = [
        row for row in result["walk_actions"]
        if row["edge_id"] == "author_to_works" and row["walk_status"] == "skipped"
    ]
    assert len(skipped) == 1
    assert skipped[0]["reason_code"] == "blocked_by_rule_decision"
    assert skipped[0]["budget_tier"] == "blocked"
    assert skipped[0]["raw_payload"]["decision_action"] == "REJECT_CONTENT"


def test_author_edge_allows_add_content_pool(tmp_path):
    context = build_initial_walk_context(tmp_path)
    # M3: mock judgment scores 60 (review/low_budget); promote the seed decision to
    # pool so the author edge runs at normal budget, which is what this test asserts.
    _override_decisions(context, "ADD_TO_CONTENT_POOL", "success")
    client = FakeWalkPlatformClient()

    result = run_bounded_walk(platform_client=client, **context)

    assert client.author_calls
    author_actions = [
        row for row in result["walk_actions"]
        if row["edge_id"] == "author_to_works" and row["walk_status"] == "success"
    ]
    assert author_actions
    assert author_actions[0]["budget_tier"] == "normal"
    # M4 砍包受控变化:future 包 binding 已删,戳回退内容包(=executed_rule_pack_id)。
    assert author_actions[0]["rule_pack_id"] == "douyin_content_discovery_rule_pack_v1"


def test_author_edge_keeps_review_low_budget(tmp_path):
    context = build_initial_walk_context(tmp_path)
    _override_decisions(context, "KEEP_CONTENT_FOR_REVIEW", "pending")
    client = FakeWalkPlatformClient()

    result = run_bounded_walk(platform_client=client, **context)

    assert client.author_calls
    author_actions = [
        row for row in result["walk_actions"]
        if row["edge_id"] == "author_to_works" and row["walk_status"] == "success"
    ]
    assert author_actions
    assert author_actions[0]["budget_tier"] == "low_budget"
    assert author_actions[0]["raw_payload"]["rule_pack_execution"]["executed"] is True


def test_author_works_skip_already_discovered_content(tmp_path):
    # 真实 E2E(v1_run_e6ba21f7543b)实证:作者近期作品包含首轮已发现的同一条视频,
    # 不去重会撞 DB 唯一索引 uk_ca_items_run_policy_content。
    context = build_initial_walk_context(tmp_path)
    context["discovered_content_items"][0]["has_more"] = False
    context["discovered_content_items"][0]["tags"] = []
    first_round_id = context["discovered_content_items"][0]["platform_content_id"]

    class OverlappingWorksClient(FakeWalkPlatformClient):
        def fetch_author_works(self, query):
            self.author_calls.append(dict(query))
            duplicate = _dup_platform_result(query, first_round_id)
            fresh = _dup_platform_result(query, "7390000000000000399")
            return [duplicate, fresh]

    client = OverlappingWorksClient()
    result = run_bounded_walk(platform_client=client, **context)

    assert client.author_calls
    content_ids = [item["platform_content_id"] for item in result["discovered_content_items"]]
    # 重复视频不得二次进入 discovered;新作品正常进入。
    assert content_ids.count(first_round_id) == 1
    assert "7390000000000000399" in content_ids


def _dup_platform_result(query, platform_content_id):
    from tests.p6_walk_helpers import _platform_result

    return _platform_result(query, platform_content_id, "作者作品", [])


def test_author_works_have_search_query_lineage(tmp_path):
    # 真实 E2E(v1_run_3a3bc9f0d72d)实证:作者作品内容引用合成 query id 但
    # search_queries 无此行,validate_run 报 missing_search_query_ref 等 8 条 fail。
    # 血缘补全后:query 行落盘 → pattern_to_search_query 路径与 search_clue 经既有机制生成。
    from content_agent.business_modules import run_record
    from content_agent.business_modules.run_record.validation import validate_run

    context = build_initial_walk_context(tmp_path)
    context["discovered_content_items"][0]["has_more"] = False
    context["discovered_content_items"][0]["tags"] = []
    client = FakeWalkPlatformClient()

    result = run_bounded_walk(platform_client=client, **context)

    author_queries = [
        q for q in result["search_queries"]
        if q["search_query_generation_method"] == "author_works"
    ]
    assert len(author_queries) == 1
    author_query = author_queries[0]
    assert author_query["search_query_id"].startswith("author_")
    assert author_query["previous_discovery_step"] == "author_to_works"
    # 作者作品内容引用的 query id 必须真实存在。
    author_items = [
        i for i in result["discovered_content_items"]
        if i.get("previous_discovery_step") == "author_works"
    ]
    assert author_items
    assert all(i["search_query_id"] == author_query["search_query_id"] for i in author_items)

    # 端到端血缘:M4 后终端边+血缘由 run_bounded_walk 一体产出,record_run 后 validate_run 必须 pass。
    record = run_record.run(
        context["run_id"],
        context["policy_run_id"],
        result["search_queries"],
        result["discovered_content_items"],
        result["rule_decisions"],
        result["source_path_record_basis"],
        context["policy_bundle"],
        context["runtime"],
        walk_actions=result["walk_actions"],
    )
    from content_agent.business_modules import learning_review, result_source_lookup

    result_source_lookup.run(
        context["run_id"],
        context["policy_run_id"],
        context["policy_bundle"],
        result["discovered_content_items"],
        result["content_media_records"],
        result["rule_decisions"],
        record["source_path_records"],
        record["search_clues"],
        context["runtime"],
    )
    learning_review.run(context["run_id"], context["policy_run_id"], context["runtime"])
    validation = validate_run(context["run_id"], context["runtime"])
    fails = [f for f in validation["findings"] if f["level"] == "fail"]
    assert validation["status"] == "pass", fails