fix(release): harden embedding store and plugins for ReMe 0.4.1.9 (#503)

* chore(release): prepare ReMe 0.4.1.9 * refactor(config): remove daily_cookbook and streamline plugin configs - Delete the entire daily_cookbook.yaml standalone application config - Remove qwenpaw dependencies verification and related CI workflow steps - Simplify release workflows by removing qwenpaw verification and enforcing reme-ai >=0.4.1.9 - Update plugin start commands and examples to use 'default' or 'demo' configs instead of daily_cookbook - Adjust imports and tests related to daily_cookbook removal and injected_job_kwargs enhancements - Refactor agent wrapper to support injected_job_kwargs for job parameter injection in auto-fin and daily-paper - Improve daily_paper digest prompt to include configured daily directory and correct historical search constraints - Update dependency versions in pyproject.toml files to require reme-ai >=0.4.1.9 and remove qwenpaw optional dependencies - Clean up unused environment variables and obsolete test cases related to daily_cookbook and verification steps * fix(local_embedding_store): retry batch computation on vector space changes - Add up to 3 attempts to recompute embedding batch if vector space changes during processing - Log warnings when maximum retries reached and discard stale results - Prevent caching results from outdated vector spaces to maintain consistency - Add tests to verify retry behavior and abort after continuous vector space churn fix(daily_paper): update digest search logic and tests - Change search to query existing memory, not only previous articles in daily_dir - Allow multiple searches outside daily_dir but limit links to dated markdown in daily_dir before today - Update test assertions to reflect revised search and linking rules * fix(embedding): retry vector space changes per request
2026-10-08 03:10:24 +00:00 · 2026-08-28 11:35:04 +08:00 · 2026-08-28 11:35:04 +08:00 · 99afc2604f
commit 99afc2604f
parent 2dd2255760
31 changed files with 293 additions and 642 deletions
--- a/.github/workflows/_build-python-packages.yml
+++ b/.github/workflows/_build-python-packages.yml
@ -13,11 +13,6 @@ on:
        required: false
        default: false
        type: boolean
-      verify_qwenpaw_dependencies:
-        description: Verify that independently published qwenpaw plugins are installable
-        required: false
-        default: true
-        type: boolean

 permissions:
  contents: read
@ -84,22 +79,6 @@ jobs:
          assert (static_dir() / "index.html").is_file()
          PY

-      # qwenpaw composes independently released plugins. Bootstrap releases may
-      # skip this check to publish the reme-ai version required by those plugins.
-      - name: Verify released qwenpaw dependencies
-        if: inputs.expected_version != '' && inputs.verify_qwenpaw_dependencies
-        run: |
-          REME_WHEEL="$(pwd)/$(ls dist/reme/reme_ai-[0-9]*.whl)"
-          python -m venv "${RUNNER_TEMP}/reme-qwenpaw-package-smoke"
-          "${RUNNER_TEMP}/reme-qwenpaw-package-smoke/bin/python" -m pip install "${REME_WHEEL}[qwenpaw]"
-          cd "${RUNNER_TEMP}"
-          "${RUNNER_TEMP}/reme-qwenpaw-package-smoke/bin/python" - <<'PY'
-          from importlib.metadata import distribution
-
-          assert distribution("reme-auto-fin")
-          assert distribution("reme-daily-paper")
-          PY
-
      - name: Upload ReMe distributions
        if: inputs.upload_artifacts
        uses: actions/upload-artifact@b7c566a772e6b6bfb58ed0dc250532a479d7789f # v6
--- a/.github/workflows/release-auto-fin.yml
+++ b/.github/workflows/release-auto-fin.yml
@ -73,8 +73,10 @@ jobs:
          if len(requirements) != 1:
              raise SystemExit(f"Expected one reme-ai dependency, found {requirements!r}")
          reme_requirement = Requirement(requirements[0])
-          if reme_requirement.name != "reme-ai" or set(reme_requirement.extras) != {"core"}:
-              raise SystemExit(f"Expected a reme-ai[core] dependency, found {requirements[0]!r}")
+          if reme_requirement.name != "reme-ai" or reme_requirement.extras:
+              raise SystemExit(f"Expected a base reme-ai dependency, found {requirements[0]!r}")
+          if Version("0.4.1.8") in reme_requirement.specifier or Version("0.4.1.9") not in reme_requirement.specifier:
+              raise SystemExit(f"Expected reme-ai>=0.4.1.9, found {requirements[0]!r}")
          with Path(os.environ["GITHUB_OUTPUT"]).open("a", encoding="utf-8") as output:
              print(f"reme_requirement={reme_requirement}", file=output)
          print(f"Publishing {project['name']} {actual}")
@ -88,7 +90,7 @@ jobs:
          REME_REQUIREMENT: ${{ steps.package.outputs.reme_requirement }}
        run: |
          python -m pip download --no-deps \
-            --dest "${RUNNER_TEMP}/reme-auto-fin-core" \
+            --dest "${RUNNER_TEMP}/reme-auto-fin-base" \
            "${REME_REQUIREMENT}"

      - name: Build and check distributions
@ -104,7 +106,8 @@ jobs:
          python -m zipfile -l "${AUTO_FIN_WHEEL}" | grep 'dist-info/licenses/LICENSE'
          python -m tarfile -l "${AUTO_FIN_SDIST}" | grep '/LICENSE'
          python -m venv "${RUNNER_TEMP}/reme-auto-fin-smoke"
-          "${RUNNER_TEMP}/reme-auto-fin-smoke/bin/python" -m pip install "${AUTO_FIN_WHEEL}"
+          "${RUNNER_TEMP}/reme-auto-fin-smoke/bin/python" -m pip install \
+            "agentscope[model-ollama]==2.0.7" "${AUTO_FIN_WHEEL}"
          cd "${RUNNER_TEMP}"
          "${RUNNER_TEMP}/reme-auto-fin-smoke/bin/python" - <<'PY'
          from importlib.metadata import distribution
@ -122,9 +125,7 @@ jobs:
          }
          assert set(manifest.application_defaults["jobs"]) == {
              "auto_fin",
-              "auto_fin_0930_cron",
-              "auto_fin_1130_cron",
-              "auto_fin_1800_cron",
+              "auto_fin_cron",
          }
          PY

--- a/.github/workflows/release-daily-paper.yml
+++ b/.github/workflows/release-daily-paper.yml
@ -70,8 +70,10 @@ jobs:
              raise SystemExit(f"Package version is {actual}, but workflow input is {expected}")
          requirements = [Requirement(value) for value in project["dependencies"]]
          reme_requirements = [requirement for requirement in requirements if requirement.name == "reme-ai"]
-          if len(reme_requirements) != 1 or set(reme_requirements[0].extras) != {"core"}:
-              raise SystemExit(f"Expected one reme-ai[core] dependency, found {reme_requirements!r}")
+          if len(reme_requirements) != 1 or reme_requirements[0].extras:
+              raise SystemExit(f"Expected one base reme-ai dependency, found {reme_requirements!r}")
+          if Version("0.4.1.8") in reme_requirements[0].specifier or Version("0.4.1.9") not in reme_requirements[0].specifier:
+              raise SystemExit(f"Expected reme-ai>=0.4.1.9, found {reme_requirements!r}")
          if sum(requirement.name == "pypdf" for requirement in requirements) != 1:
              raise SystemExit("Expected exactly one pypdf dependency")
          with Path(os.environ["GITHUB_OUTPUT"]).open("a", encoding="utf-8") as output:
@ -87,7 +89,7 @@ jobs:
          REME_REQUIREMENT: ${{ steps.package.outputs.reme_requirement }}
        run: |
          python -m pip download --no-deps \
-            --dest "${RUNNER_TEMP}/reme-daily-paper-core" \
+            --dest "${RUNNER_TEMP}/reme-daily-paper-base" \
            "${REME_REQUIREMENT}"

      - name: Build and check distributions
@ -105,7 +107,8 @@ jobs:
          python -m zipfile -l "${DAILY_PAPER_WHEEL}" | grep 'dist-info/licenses/LICENSE'
          python -m tarfile -l "${DAILY_PAPER_SDIST}" | grep '/LICENSE'
          python -m venv "${RUNNER_TEMP}/reme-daily-paper-smoke"
-          "${RUNNER_TEMP}/reme-daily-paper-smoke/bin/python" -m pip install "${DAILY_PAPER_WHEEL}"
+          "${RUNNER_TEMP}/reme-daily-paper-smoke/bin/python" -m pip install \
+            "agentscope[model-ollama]==2.0.7" "${DAILY_PAPER_WHEEL}"
          cd "${RUNNER_TEMP}"
          "${RUNNER_TEMP}/reme-daily-paper-smoke/bin/python" - <<'PY'
          from importlib.metadata import distribution
--- a/.github/workflows/release-python.yml
+++ b/.github/workflows/release-python.yml
@ -1,8 +1,5 @@
 name: Release / Python packages

-# reme-ai[qwenpaw] is normally verified before publication. For a bootstrap
-# release where the plugins require this new reme-ai version, disable that
-# verification, publish reme-ai first, and then publish the plugins.
 # Configure a PyPI Trusted Publisher for this repository, workflow, and its
 # pypi environment before running the manual release.

@ -13,11 +10,6 @@ on:
        description: Release version
        required: true
        type: string
-      verify_qwenpaw_dependencies:
-        description: Verify already-published Auto Fin and Daily Paper packages
-        required: true
-        default: true
-        type: boolean

 permissions:
  contents: read
@ -33,7 +25,6 @@ jobs:
    with:
      expected_version: ${{ inputs.version }}
      upload_artifacts: true
-      verify_qwenpaw_dependencies: ${{ inputs.verify_qwenpaw_dependencies }}

  publish-reme:
    needs: build
--- a/docs/en/plugin_management.md
+++ b/docs/en/plugin_management.md
@ -64,7 +64,7 @@ reme plugins list --json
 To compare installed plugins with one application config:

 ```bash
-reme plugins list --config daily_cookbook
+reme plugins list --config default
 ```

 The optional `ENABLED` column reflects only the `plugins` list resolved from that config. A command-line override used
@ -173,11 +173,8 @@ curl -s http://127.0.0.1:2333/auto_fin \

 When the application uses an MCP service, service-enabled plugin Jobs appear as MCP tools instead.

-To add the plugin to another application config, select it explicitly:
-
-```bash
-reme start config=daily_cookbook plugins='["auto-fin"]'
-```
+Custom application configs must provide the plugin's runtime dependencies, including an `agent_wrapper.default` and
+the `search` and `read` Jobs used by Auto Fin.

 ## Uninstall a plugin

--- a/docs/zh/plugin_management.md
+++ b/docs/zh/plugin_management.md
@ -61,7 +61,7 @@ reme plugins list --json
 对照某个应用配置查看启用状态：

 ```bash
-reme plugins list --config daily_cookbook
+reme plugins list --config default
 ```

 可选的 `ENABLED` 列只反映该配置解析出的 `plugins` 列表。其他运行中进程使用的 CLI override 不是全局启用状态。
@ -167,11 +167,7 @@ curl -s http://127.0.0.1:2333/auto_fin \

 当应用使用 MCP service 时，允许对外服务的插件 Job 会显示为 MCP tool。

-如果需要将插件叠加到其他应用配置，则显式选择该配置：
-
-```bash
-reme start config=daily_cookbook plugins='["auto-fin"]'
-```
+自定义应用配置需要提供插件的运行依赖，包括 `agent_wrapper.default`，以及 Auto Fin 使用的 `search` 和 `read` Jobs。

 ## 卸载插件

--- a/plugins/auto-fin/README.md
+++ b/plugins/auto-fin/README.md
@ -17,7 +17,7 @@ through `plugins=["auto-fin"]`.
 ### 1. Install ReMe and Auto Fin

 ```bash
-python -m pip install "reme-ai[core]>=0.4.1.8"
+python -m pip install "reme-ai[core]>=0.4.1.9"
 reme plugins install reme-auto-fin
 ```

@ -59,11 +59,7 @@ reme start plugins='["auto-fin"]' \
  service.backend=http
 ```

-To add Auto Fin to another application instead, select that config explicitly, for example:
-
-```bash
-reme start config=daily_cookbook plugins='["auto-fin"]'
-```
+Custom application configs must provide `agent_wrapper.default` and the `search` and `read` Jobs used by Auto Fin.

 ## Pipeline

@ -74,7 +70,7 @@ normalize and deduplicate in RuntimeContext
        ↓
 topic Agent selects real news IDs in bounded batches
        ↓
-research Agent uses memory_search + read on historical memory
+research Agent uses search + read on historical memory
        ↓
 validate historical wikilinks in code
        ↓
@ -89,8 +85,8 @@ records outside the window are discarded.
 IDs and deduplicates repeated IDs, then preserves the source-news order. If nothing is relevant, the job succeeds as a
 skip without writing or sending a report.

-`auto_fin_merge_step` receives only selected current news. It exposes `memory_search` and `read`, instructs the Agent to
-search no later than yesterday, and keeps current CLS IDs, times, and titles as plain evidence. The prompt limits
+`auto_fin_merge_step` receives only selected current news. It exposes `search` and `read`, and keeps current CLS IDs,
+times, and titles as plain evidence. The prompt limits
 wikilinks to historical Markdown actually used by the Agent; the code-level boundary independently keeps only existing,
 workspace-relative Markdown targets. Missing, absolute, escaping, backslash, and self-referential targets are degraded
 to their readable aliases.
@ -109,7 +105,7 @@ refreshes the daily index. No JSONL, intermediate Markdown, or structured Agent
 | `request_interval` |                   `10` | Minimum delay in seconds after every CLS request attempt; may be zero    |
 | `max_retries`      |                    `3` | Maximum attempts for each CLS page request; must be at least one         |

-The three plugin cron Jobs start with the application and run daily at 09:30, 11:30, and 18:00 in `Asia/Shanghai`.
+The plugin cron Job starts with the application and runs daily at 18:00 in the application timezone.

 ## Output

--- a/plugins/auto-fin/README_ZH.md
+++ b/plugins/auto-fin/README_ZH.md
@ -14,7 +14,7 @@ distribution：单个 `reme.plugins` entry point 暴露 `plugin.yaml`，其中
 ### 1. 安装 ReMe 和 Auto Fin

 ```bash
-python -m pip install "reme-ai[core]>=0.4.1.8"
+python -m pip install "reme-ai[core]>=0.4.1.9"
 reme plugins install reme-auto-fin
 ```

@ -54,11 +54,7 @@ reme start plugins='["auto-fin"]' \
  service.backend=http
 ```

-如果需要将 Auto Fin 叠加到其他应用，则显式选择相应配置，例如：
-
-```bash
-reme start config=daily_cookbook plugins='["auto-fin"]'
-```
+自定义应用配置需要提供 `agent_wrapper.default`，以及 Auto Fin 使用的 `search` 和 `read` Jobs。

 ## 流程

@ -69,7 +65,7 @@ reme start config=daily_cookbook plugins='["auto-fin"]'
        ↓
 Topic Agent 分批选择真实 news_id
        ↓
-Research Agent 使用 memory_search + read 检索历史记忆
+Research Agent 使用 search + read 检索历史记忆
        ↓
 代码校验历史 wikilink
        ↓
@ -82,8 +78,8 @@ daily/YYYY-MM-DD/auto_fin.md
 `auto_fin_topic_step` 分批接收当前新闻，只返回相关的 `news_id`。代码会忽略未知 ID、去除重复 ID，并保持源新闻顺序。如果没有相关新闻，Job
 会成功跳过，不写报告也不发送通知。

-`auto_fin_merge_step` 只接收筛选后的当前新闻，并向 Agent 开放 `memory_search` 和 `read`。历史检索截止到昨天；当前新闻以
-CLS ID、时间和标题作为普通证据。Prompt 要求 Agent 只链接实际使用过的历史 Markdown；代码边界则独立保证只保留真实存在、相对
+`auto_fin_merge_step` 只接收筛选后的当前新闻，并向 Agent 开放 `search` 和 `read`。当前新闻以 CLS ID、时间和标题作为普通证据。
+Prompt 要求 Agent 只链接实际使用过的历史 Markdown；代码边界则独立保证只保留真实存在、相对
 workspace 的 Markdown 目标。不存在、绝对路径、越界、带反斜杠和自引用的目标都会降级为可读 alias。

 同日重跑会参考当天已有报告并覆盖为修订结果。最终写入使用原子替换并刷新当天索引；流程不会写入 JSONL、中间 Markdown 或 Agent
@ -100,7 +96,7 @@ workspace 的 Markdown 目标。不存在、绝对路径、越界、带反斜杠
 | `request_interval` |                   `10` | 每次财联社请求尝试后的最小等待秒数，可设为 0 |
 | `max_retries`      |                    `3` | 每页财联社请求的最大尝试次数，至少为 1       |

-插件的三个 cron Job 随应用启动，并按 `Asia/Shanghai` 时区在每天 09:30、11:30 和 18:00 运行。
+插件的 cron Job 随应用启动，并按应用配置的时区在每天 18:00 运行。

 ## 产物

--- a/plugins/auto-fin/pyproject.toml
+++ b/plugins/auto-fin/pyproject.toml
@ -1,13 +1,13 @@
 [project]
 name = "reme-auto-fin"
-version = "0.1.1"
+version = "0.1.2"
 description = "Auto Fin example plugin for ReMe."
 readme = "README.md"
 license = "Apache-2.0"
 license-files = ["LICENSE"]
 requires-python = ">=3.11"
 dependencies = [
-    "reme-ai[core]>=0.4.1.8",
+    "reme-ai>=0.4.1.9",
 ]

 [project.entry-points."reme.plugins"]
--- a/plugins/auto-fin/src/reme_auto_fin/base.py
+++ b/plugins/auto-fin/src/reme_auto_fin/base.py
@ -76,6 +76,7 @@ class AutoFinStep(BaseStep):
        prompt_name: str,
        model: type[BaseModel],
        job_tools: list[str] | None = None,
+        injected_job_kwargs: dict[str, Any] | None = None,
        **values: str,
    ) -> BaseModel:
        if self.agent_wrapper is None:
@ -89,6 +90,8 @@ class AutoFinStep(BaseStep):
        kwargs: dict[str, Any] = {"output_schema": model}
        if job_tools:
            kwargs["job_tools"] = job_tools
+        if injected_job_kwargs:
+            kwargs["injected_job_kwargs"] = injected_job_kwargs
        result = await self.agent_wrapper.reply(prompt, **kwargs)
        if not isinstance(result, dict) or result.get("structured_output") is None:
            raise ValueError(f"Auto Fin Agent returned no structured output: {self._preview(result)}")
--- a/plugins/auto-fin/src/reme_auto_fin/merge.py
+++ b/plugins/auto-fin/src/reme_auto_fin/merge.py
@ -102,17 +102,24 @@ class AutoFinMergeStep(AutoFinStep):
        )

    async def execute(self):
+        """Research the selected news and persist the validated report."""
        assert self.context is not None
        if self.context.get("auto_fin_skipped"):
            return self.context.response
        run_date = date.fromisoformat(str(self._required("auto_fin_date")))
+        historical_search = {
+            "limit": 5,
+            "min_score": 0.0,
+            "start_date": None,
+            "end_date": (run_date - timedelta(days=1)).isoformat(),
+        }
        output = await self._reply(
            "merge_user",
            AutoFinReportOutput,
            job_tools=list(self.kwargs.get("job_tools") or []),
+            injected_job_kwargs=historical_search,
            decision_at=str(self._required("auto_fin_decision_at")),
            window_start=str(self._required("auto_fin_window_start")),
-            historical_end=(run_date - timedelta(days=1)).isoformat(),
            topics=json.dumps(self._required("auto_fin_topics"), ensure_ascii=False),
            news=json.dumps(self._required("auto_fin_selected_news"), ensure_ascii=False),
            current_report=self._current_report(run_date),
--- a/plugins/auto-fin/src/reme_auto_fin/merge.yaml
+++ b/plugins/auto-fin/src/reme_auto_fin/merge.yaml
@ -1,5 +1,5 @@
 merge_user: |
-  你是主题新闻研究 Agent。当前新闻已经按 topics 做过语义筛选。你可以使用 `memory_search` 搜索历史记忆，
+  你是主题新闻研究 Agent。当前新闻已经按 topics 做过语义筛选。你可以使用 `search` 搜索历史记忆，
  并使用 `read` 阅读可能相关的完整 Markdown。不得使用外部搜索，不得虚构行情、收益、价格或未提供的数据。

  研究窗口：{window_start} 至 {decision_at}
@ -8,7 +8,7 @@ merge_user: |
  今天早些时段的报告（如有，请保留仍成立的判断，只修订变化部分）：
  {current_report}

-  先围绕 topics 和当前重要事件多次调用 `memory_search`，并将 end_date 设为 {historical_end}，避免召回今天的旧报告。
+  先围绕 topics 和当前重要事件多次调用 `search` 检索历史记忆。
  只对明显相关的结果调用 `read`。说明历史事件与当前事件的相同点、关键差异，以及旧判断是否仍适用。
  给出值得回顾的新闻、应继续观察的信息，以及哪些条件会强化或推翻判断，但不要给出投资建议。

--- a/plugins/auto-fin/src/reme_auto_fin/plugin.yaml
+++ b/plugins/auto-fin/src/reme_auto_fin/plugin.yaml
@ -42,19 +42,9 @@ application_defaults:
        - backend: auto_fin_data_step
        - backend: auto_fin_topic_step
        - backend: auto_fin_merge_step
-          job_tools: [memory_search, read]
+          job_tools: [search, read]

-    auto_fin_0930_cron:
-      backend: cron
-      cron: "30 9 * * *"
-      steps: *auto_fin_steps
-
-    auto_fin_1130_cron:
-      backend: cron
-      cron: "30 11 * * *"
-      steps: *auto_fin_steps
-
-    auto_fin_1800_cron:
+    auto_fin_cron:
      backend: cron
      cron: "0 18 * * *"
      steps: *auto_fin_steps
--- a/plugins/auto-fin/tests/test_auto_fin.py
+++ b/plugins/auto-fin/tests/test_auto_fin.py
@ -195,14 +195,23 @@ async def test_merge_writes_only_final_report_and_validates_historical_links(tmp
    response = await AutoFinMergeStep(
        app_context=app_context,
        agent_wrapper=agent,
-        job_tools=["memory_search", "read"],
+        job_tools=["search", "read"],
    )(context)

    prompt, kwargs = agent.calls[0]
-    assert "end_date 设为 2026-08-09" in prompt
-    assert "调用 `memory_search`" in prompt
+    assert "end_date" not in prompt
+    assert "调用 `search`" in prompt
    assert "调用 `read`" in prompt
-    assert kwargs == {"output_schema": AutoFinReportOutput, "job_tools": ["memory_search", "read"]}
+    assert kwargs == {
+        "output_schema": AutoFinReportOutput,
+        "job_tools": ["search", "read"],
+        "injected_job_kwargs": {
+            "limit": 5,
+            "min_score": 0.0,
+            "start_date": None,
+            "end_date": "2026-08-09",
+        },
+    }
    report = (tmp_path / "daily" / "2026-08-10" / "auto_fin.md").read_text(encoding="utf-8")
    assert "[[daily/2026-08-01/auto_fin.md|历史黄金观察]]" in report
    assert "](daily/2026-08-01/auto_fin.md)" not in report
@ -254,14 +263,17 @@ def test_plugin_config_has_default_topics_and_no_intermediate_index_step():
        "auto_fin_topic_step",
        "auto_fin_merge_step",
    ]
-    assert job["steps"][2]["job_tools"] == ["memory_search", "read"]
-    for name, schedule in {
-        "auto_fin_0930_cron": "30 9 * * *",
-        "auto_fin_1130_cron": "30 11 * * *",
-        "auto_fin_1800_cron": "0 18 * * *",
-    }.items():
-        assert jobs[name]["cron"] == schedule
-        assert jobs[name]["steps"] == job["steps"]
+    assert job["steps"][2]["job_tools"] == ["search", "read"]
+    assert jobs["auto_fin_cron"]["cron"] == "0 18 * * *"
+    assert jobs["auto_fin_cron"]["steps"] == job["steps"]
+    assert (
+        not {
+            "auto_fin_0930_cron",
+            "auto_fin_1130_cron",
+            "auto_fin_1800_cron",
+        }
+        & jobs.keys()
+    )


 def test_agent_schemas_are_small_and_required():
--- a/plugins/daily_paper/README.md
+++ b/plugins/daily_paper/README.md
@ -13,7 +13,7 @@ their Job configuration under `application_defaults`. Enable the installed plugi
 ### 1. Install ReMe and Daily Paper

 ```bash
-python -m pip install "reme-ai[core]>=0.4.1.8"
+python -m pip install "reme-ai[core]>=0.4.1.9"
 reme plugins install reme-daily-paper
 ```

@ -62,7 +62,7 @@ rank with RRF and let an Agent select three papers
                 ↓
 download and parse arXiv PDFs, then write three Chinese analyses
                 ↓
-use memory_search + read to connect prior memory and generate a brief
+use search + read to connect prior memory and generate a brief
                 ↓
 refresh the daily index and optionally send the brief to DingTalk
 ```
@ -80,7 +80,7 @@ the configured page, character, and file-size limits. It writes the three Chines
 PDFs and files without a text layer fail explicitly.

 `daily_paper_digest_step` treats those three analyses as the factual source and receives only the read-only
-`memory_search` and `read` tools for linking earlier memory. Code validates historical wikilinks, appends links to all
+`search` and `read` tools for linking earlier memory. Code validates historical wikilinks, appends links to all
 three source notes, and rebuilds the daily index. The optional `dingtalk_markdown_send_step` sends the final brief when
 conversation IDs are configured and otherwise skips without side effects.

--- a/plugins/daily_paper/README_ZH.md
+++ b/plugins/daily_paper/README_ZH.md
@ -11,7 +11,7 @@ Step backend，并在 `application_defaults` 下提供 Job 配置；通过 `plug
 ### 1. 安装 ReMe 和每日论文插件

 ```bash
-python -m pip install "reme-ai[core]>=0.4.1.8"
+python -m pip install "reme-ai[core]>=0.4.1.9"
 reme plugins install reme-daily-paper
 ```

@ -58,7 +58,7 @@ RRF 排序后由 Agent 精选三篇
          ↓
 下载并解析 arXiv PDF，生成三篇中文解读
          ↓
-使用 memory_search + read 关联历史记忆并生成简报
+使用 search + read 关联历史记忆并生成简报
          ↓
 写入当日索引，并按需发送到钉钉
 ```
@ -72,7 +72,7 @@ RRF 排序后由 Agent 精选三篇
 `daily_paper_analyze_step` 下载 PDF 到 `resource/papers/`，复用已有的有效文件，并在页数、字符数和文件大小限制内提取
 文本。三篇中文解读按精选顺序写入当天目录；扫描版或没有文本层的 PDF 会明确失败。

-`daily_paper_digest_step` 以本次生成的三篇解读为事实来源，只开放只读的 `memory_search` 和 `read` 来关联较早记忆。
+`daily_paper_digest_step` 以本次生成的三篇解读为事实来源，只开放只读的 `search` 和 `read` 来关联较早记忆。
 代码会校验历史 wikilink、追加三篇源笔记链接，并重建当日索引。可选的 `dingtalk_markdown_send_step` 在配置群会话后
 发送最终简报；未配置时无副作用跳过。

--- a/plugins/daily_paper/pyproject.toml
+++ b/plugins/daily_paper/pyproject.toml
@ -1,6 +1,6 @@
 [project]
 name = "reme-daily-paper"
-version = "0.1.1"
+version = "0.1.2"
 description = "Daily Paper research and reading-note plugin for ReMe."
 readme = "README.md"
 license = "Apache-2.0"
@ -8,7 +8,7 @@ license-files = ["LICENSE"]
 requires-python = ">=3.11"
 dependencies = [
    "pypdf>=5.0.0",
-    "reme-ai[core]>=0.4.1.8",
+    "reme-ai>=0.4.1.9",
 ]

 [project.entry-points."reme.plugins"]
--- a/plugins/daily_paper/src/reme_daily_paper/digest.py
+++ b/plugins/daily_paper/src/reme_daily_paper/digest.py
@ -64,6 +64,7 @@ class DailyPaperDigestStep(DailyPaperStep):
        return _WIKILINK_RE.sub(replace, body)

    async def execute(self):
+        """Generate and persist the final brief from analyzed papers."""
        assert self.context is not None
        if self._skip():
            self.logger.info(f"[{self.name}] skip existing digest")
@ -79,16 +80,23 @@ class DailyPaperDigestStep(DailyPaperStep):

        documents = [{"title": item.title, "desc": item.desc, "body": item.body} for item in analyses]
        wikilinks = [f"[[{item.note_path}]]" for item in analyses]
-        previous_day = (dt.date.fromisoformat(self._run_day()) - dt.timedelta(days=1)).isoformat()
+        run_day = dt.date.fromisoformat(self._run_day())
+        daily_dir = str(self.config_value("daily_dir")).strip("/")
        self.logger.info(f"[{self.name}] agent start notes={len(analyses)}")
        result = await self.agent_wrapper.reply(
            self.prompt_format(
                "digest_user",
                documents=json.dumps(documents, ensure_ascii=False, indent=2),
-                previous_day=previous_day,
+                daily_dir=daily_dir,
            ),
            output_schema=DailyPaperMarkdownOutput,
            job_tools=list(self.kwargs.get("job_tools") or []),
+            injected_job_kwargs={
+                "limit": 20,
+                "min_score": 0.0,
+                "start_date": None,
+                "end_date": (run_day - dt.timedelta(days=1)).isoformat(),
+            },
        )
        self.logger.info(f"[{self.name}] agent done notes={len(analyses)}")
        output = structured_output(result, DailyPaperMarkdownOutput)
@ -96,8 +104,7 @@ class DailyPaperDigestStep(DailyPaperStep):
        if not output.desc.strip() or not body:
            raise ValueError("Agent returned an empty daily paper brief")

-        day = self._run_day()
-        daily_dir = str(self.config_value("daily_dir")).strip("/")
+        day = run_day.isoformat()
        title = normalize_chinese_title(output.title, f"每日论文简报-{day}")
        existing_rel = str(self._state("existing_digest_path") or "").strip()
        existing_path = self.workspace_path / existing_rel if existing_rel else None
@ -110,7 +117,7 @@ class DailyPaperDigestStep(DailyPaperStep):
            existing=existing_path,
        )
        digest_rel = digest_path.relative_to(self.workspace_path).as_posix()
-        body = self._validate_historical_wikilinks(body, dt.date.fromisoformat(day), digest_path)
+        body = self._validate_historical_wikilinks(body, run_day, digest_path)
        body += "\n\n## 详细论文\n\n" + "\n".join(f"- {link}" for link in wikilinks)
        selected_ids = [item.arxiv_id for item in analyses]
        await write_markdown(
--- a/plugins/daily_paper/src/reme_daily_paper/digest.yaml
+++ b/plugins/daily_paper/src/reme_daily_paper/digest.yaml
@ -4,12 +4,13 @@ digest_user: |
  内容只能依据输入文档，不得补充文档中没有提供的事实。
  保留技术准确性，同时解释三篇论文为什么值得关注，以及它们之间有什么联系。

-  在写作前，先调用 `memory_search` 检索以前的文章：围绕三篇论文的核心问题、方法、关键词和同义表达组织查询，
-  使用 end_date={previous_day}、limit=20。主题跨度较大时可以多次检索。只把 `daily/` 下日期早于今天、
-  且与本期内容确实相似或互补的 Markdown 文章作为候选；必要时调用 `read` 核验全文，不要仅凭标题判断。
+  在写作前，先调用 `search` 检索已有记忆：围绕三篇论文的核心问题、方法、关键词和同义表达组织查询。
+  主题跨度较大时可以多次检索，搜索结果不必局限于 `{daily_dir}/`。只有 `{daily_dir}/` 下日期早于今天、
+  且与本期内容确实相似或互补的 Markdown 文章才可作为正文中的历史链接候选；必要时调用 `read` 核验全文，
+  不要仅凭标题判断。
  将确认相关的旧文章以 Wikilink 自然织入正文，并用句子说明关联（延续、对比、补充或方法相似）；
  链接必须采用带 `.md` 的完整 workspace-relative 路径，例如
-  `[[daily/2026-07-01/旧文章.md|此前的相关解读]]`。不要输出裸链接、独立关系字段，也不要虚构搜索未命中的路径。
+  `[[{daily_dir}/2026-07-01/旧文章.md|此前的相关解读]]`。不要输出裸链接、独立关系字段，也不要虚构搜索未命中的路径。
  旧文章只用于判断关联和建立链接，不得用来补充本期事实。如果没有真正相关的旧文章，不要强行添加；
  当日三篇详细解读的链接会由系统统一附在文末。

--- a/plugins/daily_paper/src/reme_daily_paper/plugin.yaml
+++ b/plugins/daily_paper/src/reme_daily_paper/plugin.yaml
@ -53,7 +53,7 @@ application_defaults:
        - backend: daily_paper_select_step
        - backend: daily_paper_analyze_step
        - backend: daily_paper_digest_step
-          job_tools: [memory_search, read]
+          job_tools: [search, read]
        - backend: dingtalk_markdown_send_step
          input_mapping:
            daily_paper_digest_path: markdown_path
--- a/plugins/daily_paper/tests/test_daily_paper.py
+++ b/plugins/daily_paper/tests/test_daily_paper.py
@ -627,6 +627,27 @@ def test_daily_paper_cron_hf_mirror_defaults_enabled_with_environment_override(m
    assert _plugin_config()["jobs"]["daily_paper_cron"]["use_hf_mirror"] is False


+def test_digest_prompt_uses_configured_daily_directory(tmp_path: Path):
+    """Use the host application's daily directory in historical-link guidance."""
+    step = DailyPaperDigestStep(
+        app_context=ApplicationContext(
+            workspace_dir=str(tmp_path),
+            daily_dir="memory",
+        ),
+    )
+
+    prompt = step.prompt_format(
+        "digest_user",
+        documents="[]",
+        daily_dir=str(step.config_value("daily_dir")).strip("/"),
+    )
+
+    assert "`memory/`" in prompt
+    assert "搜索结果不必局限于 `memory/`" in prompt
+    assert "[[memory/2026-07-01/旧文章.md" in prompt
+    assert "[[daily/2026-07-01/" not in prompt
+
+
 def test_paper_pick_list_uses_an_object_root_for_tool_output():
    """AgentScope function arguments require an object-root JSON schema."""
    schema = PaperPickList.model_json_schema()
@ -846,7 +867,7 @@ async def test_pipeline_filters_strict_yesterday_and_writes_outputs(
    await DailyPaperDigestStep(
        app_context=app_context,
        agent_wrapper=cc_wrapper,
-        job_tools=["memory_search", "read"],
+        job_tools=["search", "read"],
    )(context)

    assert _FakeHfClient.requested_daily == ["2026-07-20"]
@ -886,7 +907,13 @@ async def test_pipeline_filters_strict_yesterday_and_writes_outputs(
    assert all(call["kwargs"] == {"output_schema": DailyPaperMarkdownOutput} for call in cc_wrapper.calls[1:-1])
    assert cc_wrapper.calls[-1]["kwargs"] == {
        "output_schema": DailyPaperMarkdownOutput,
-        "job_tools": ["memory_search", "read"],
+        "job_tools": ["search", "read"],
+        "injected_job_kwargs": {
+            "limit": 20,
+            "min_score": 0.0,
+            "start_date": None,
+            "end_date": "2026-07-20",
+        },
    }
    assert [call["kwargs"]["output_schema"] for call in cc_wrapper.calls] == [
        PaperPickList,
@ -906,8 +933,10 @@ async def test_pipeline_filters_strict_yesterday_and_writes_outputs(
    assert "调用 Read" not in digest_prompt
    assert "daily/2026-07-21" not in digest_prompt
    assert "长期记忆" not in digest_prompt
-    assert "先调用 `memory_search` 检索以前的文章" in digest_prompt
-    assert "end_date=2026-07-20" in digest_prompt
+    assert "先调用 `search` 检索已有记忆" in digest_prompt
+    assert "搜索结果不必局限于 `daily/`" in digest_prompt
+    assert "end_date" not in digest_prompt
+    assert "limit=" not in digest_prompt
    assert "Wikilink" in digest_prompt

    rerun = RuntimeContext(date="2026-07-21")
--- a/pyproject.toml
+++ b/pyproject.toml
@ -42,7 +42,7 @@ dependencies = [

 [project.optional-dependencies]
 as = [
-    "agentscope[model-ollama]==2.0.6",
+    "agentscope[model-ollama]==2.0.7",
 ]
 web = [
    "reme_studio",
@ -62,11 +62,6 @@ core = [
    "polars>=1.43.0",
    "reme_studio",
 ]
-qwenpaw = [
-    "reme-ai[core]",
-    "reme-auto-fin>=0.1.1",
-    "reme-daily-paper>=0.1.1",
-]
 dev = [
    "packaging>=24.2",
    "pre-commit>=4.6.1",
--- a/reme/init.py
+++ b/reme/init.py
@ -1,6 +1,6 @@
 """ReMe CLI package."""

-__version__ = "0.4.1.8"
+__version__ = "0.4.1.9"

 from . import config
 from . import constants
--- a/reme/components/embedding_store/local_embedding_store.py
+++ b/reme/components/embedding_store/local_embedding_store.py
@ -12,6 +12,7 @@ from ..component_registry import R
 from ..as_embedding import BaseAsEmbedding

 Miss = tuple[int, str, str]  # (result_index, text, cache_key)
+_MAX_VECTOR_SPACE_ATTEMPTS = 3


@R.register("local")
@ -103,12 +104,25 @@ class LocalEmbeddingStore(BaseEmbeddingStore):
    # -- Public API --

    async def get_embeddings(self, input_text: list[str], **kwargs) -> list[np.ndarray | None]:
-        await self._sync_cache_space()
        texts = [self._truncate(t) for t in input_text]
-        results, misses = self._partition_by_cache(texts)
-        if misses:
-            await self._fill_misses(misses, results, **kwargs)
-        return results
+        for attempt in range(1, _MAX_VECTOR_SPACE_ATTEMPTS + 1):
+            await self._sync_cache_space()
+            vector_space_id = self._cache_space
+            results, misses = self._partition_by_cache(texts)
+            stable = not misses or await self._fill_misses(misses, results, vector_space_id, **kwargs)
+            if stable and vector_space_id == self.vector_space_id == self._cache_space:
+                return results
+            if attempt == _MAX_VECTOR_SPACE_ATTEMPTS:
+                self.logger.warning(
+                    f"Embedding vector space kept changing while computing a request; "
+                    f"discarding all result(s) after {attempt} attempts",
+                )
+            else:
+                self.logger.info(
+                    f"Embedding vector space changed while computing a request; "
+                    f"discarding all result(s) and retrying ({attempt}/{_MAX_VECTOR_SPACE_ATTEMPTS})",
+                )
+        return [None] * len(texts)

    # -- Batching --

@ -124,15 +138,26 @@ class LocalEmbeddingStore(BaseEmbeddingStore):
                misses.append((idx, text, key))
        return results, misses

-    async def _fill_misses(self, misses: list[Miss], results: list[np.ndarray | None], **kwargs) -> None:
-        vector_space_id = self._cache_space
+    async def _fill_misses(
+        self,
+        misses: list[Miss],
+        results: list[np.ndarray | None],
+        vector_space_id: str,
+        **kwargs,
+    ) -> bool:
+        """Fill every miss only while the request remains in one vector space."""
        size = self.max_batch_size
        for start in range(0, len(misses), size):
+            if vector_space_id != self.vector_space_id or vector_space_id != self._cache_space:
+                return False
            batch = misses[start : start + size]
-            for idx, key, emb in await self._compute_batch(batch, **kwargs):
+            computed = await self._compute_batch(batch, **kwargs)
+            if vector_space_id != self.vector_space_id or vector_space_id != self._cache_space:
+                return False
+            for idx, key, emb in computed:
                results[idx] = emb
-                if vector_space_id == self.vector_space_id == self._cache_space:
-                    self._cache_put(key, emb)
+                self._cache_put(key, emb)
+        return True

    async def _compute_batch(self, batch: list[Miss], **kwargs) -> list[tuple[int, str, np.ndarray]]:
        texts = [text for _, text, _ in batch]
--- a/reme/config/daily_cookbook.yaml
+++ b/reme/config/daily_cookbook.yaml
@ -1,416 +0,0 @@
-app_name: ReMe Daily Cookbook
-workspace_dir: ${DAILY_PAPER_WORKSPACE_DIR:-reme_workspace}
-timezone: Asia/Shanghai
-language: zh
-
-# This is a standalone application config. It intentionally does not inherit
-# default.yaml and listens on a separate port so it can run beside ReMe.
-service:
-  backend: http
-  host: ${DAILY_PAPER_HOST:-127.0.0.1}
-  port: ${DAILY_PAPER_PORT:-8001}
-
-jobs:
-  index_update_loop:
-    backend: background
-    watch_dirs: [daily_dir, digest_dir]
-    watch_suffixes: [md, jsonl]
-    steps:
-      - backend: init_changes_step
-        monitor_type: file_store
-        monitor_name: default
-        dispatch_steps: [update_index_step]
-      - backend: watch_changes_step
-        dispatch_steps:
-          - backend: update_index_step
-            persist: false
-
-  auto_dream:
-    backend: base
-    description: "Auto-dream: consolidate recent daily notes into digest memory and interest topics."
-    parameters:
-      type: object
-      properties:
-        date:
-          type: string
-          description: "YYYY-MM-DD to scan; defaults to today in the configured timezone."
-          default: ""
-        hint:
-          type: string
-          description: "Optional guidance for extraction and integration."
-          default: ""
-        scan_days:
-          type: integer
-          description: "Number of recent daily directories to scan."
-          default: 2
-        max_units:
-          type: integer
-          description: "Maximum number of extracted memory units."
-          default: 5
-        topic_count:
-          type: integer
-          description: "Maximum number of interest topics to write."
-          default: 3
-        topic_diversity_days:
-          type: integer
-          description: "Previous interest-topic days used for de-duplication."
-          default: 7
-    steps:
-      - backend: dream_extract_step
-        file_catalog: dream
-        topic_session_id: interests
-        scan_days: 2
-        max_units: 5
-      - backend: dream_integrate_step
-      - backend: dream_topics_step
-        topic_count: 3
-        topic_diversity_days: 7
-      - backend: dream_finish_step
-        file_catalog: dream
-
-  auto_memory:
-    backend: base
-    description: "Auto-memory: record conversation facts into a daily note."
-    parameters:
-      type: object
-      properties:
-        messages:
-          type: array
-          description: "Conversation messages."
-          items:
-            type: object
-        session_id:
-          type: string
-          description: "Source conversation session identifier."
-          default: ""
-        memory_hint:
-          type: string
-          description: "Optional memory-writing guidance."
-        date:
-          type: string
-          description: "YYYY-MM-DD daily-note date; empty infers it from messages or current time."
-          default: ""
-      required: [messages]
-    steps:
-      - backend: auto_memory_step
-
-  reindex:
-    backend: base
-    description: "Wipe the derived search store and rebuild it from memory files."
-    watch_dirs: [daily_dir, digest_dir]
-    watch_suffixes: [md, jsonl]
-    parameters:
-      type: object
-      properties: {}
-    steps:
-      - backend: clear_store_step
-      - backend: init_changes_step
-        monitor_type: file_store
-        monitor_name: default
-        dispatch_steps: [update_index_step]
-
-  memory_search:
-    backend: base
-    description: "Long-term memory retrieval via hybrid workspace search (vector + BM25, RRF-fused)."
-    parameters:
-      type: object
-      properties:
-        query:
-          type: string
-          description: "Search query."
-        limit:
-          type: integer
-          description: "Maximum number of results."
-          default: 5
-        min_score:
-          type: number
-          description: "Minimum fused score."
-          default: 0.0
-        start_date:
-          type: string
-          description: "Optional inclusive start date (YYYY-MM-DD)."
-        end_date:
-          type: string
-          description: "Optional inclusive end date (YYYY-MM-DD)."
-      required: [query]
-    steps:
-      - backend: search_step
-        vector_weight: 0.7
-        candidate_multiplier: 5.0
-        expand_links: true
-        max_links_per_direction: 10
-
-  node_search:
-    backend: base
-    description: "Recall digest nodes for auto-dream de-duplication and linking."
-    parameters:
-      type: object
-      properties:
-        query:
-          type: string
-          description: "Candidate memory-node name and description."
-        limit:
-          type: integer
-          description: "Maximum number of digest nodes."
-          default: 20
-      required: [query]
-    steps:
-      - backend: node_search_step
-        vector_weight: 0.7
-        candidate_multiplier: 5.0
-
-  daily_list:
-    backend: base
-    description: "List notes under one day."
-    parameters:
-      type: object
-      properties:
-        date:
-          type: string
-          description: "YYYY-MM-DD; empty means today."
-          default: ""
-    steps:
-      - backend: daily_list_step
-
-  frontmatter_read:
-    backend: base
-    description: "Read a file's frontmatter."
-    parameters:
-      type: object
-      properties:
-        path:
-          type: string
-          description: "Workspace-relative path."
-      required: [path]
-    steps:
-      - backend: frontmatter_read_step
-
-  frontmatter_update:
-    backend: base
-    description: "Merge key-values into a file's frontmatter."
-    parameters:
-      type: object
-      properties:
-        path:
-          type: string
-          description: "Workspace-relative path."
-        metadata:
-          type: object
-          description: "Key-values to merge."
-      required: [path, metadata]
-    steps:
-      - backend: frontmatter_update_step
-
-  move:
-    backend: base
-    description: "Move or rename a workspace file and retarget inbound wikilinks."
-    parameters:
-      type: object
-      properties:
-        src_path:
-          type: string
-          description: "Workspace-relative source path."
-        dst_path:
-          type: string
-          description: "Workspace-relative destination path."
-        overwrite:
-          type: boolean
-          default: false
-        retarget:
-          type: boolean
-          default: true
-      required: [src_path, dst_path]
-    steps:
-      - backend: move_step
-
-  read:
-    backend: base
-    description: "Read a markdown file under the workspace."
-    parameters:
-      type: object
-      properties:
-        path:
-          type: string
-          description: "Workspace-relative markdown path."
-        start_line:
-          type: integer
-        end_line:
-          type: integer
-      required: [path]
-    steps:
-      - backend: read_step
-        with_neighbors: false
-        max_neighbors_per_direction: 10
-
-  write:
-    backend: base
-    description: "Create or overwrite a markdown file with frontmatter."
-    parameters:
-      type: object
-      properties:
-        path:
-          type: string
-          description: "Workspace-relative markdown path."
-        name:
-          type: string
-          description: "Frontmatter name."
-        description:
-          type: string
-          description: "Frontmatter description."
-        content:
-          type: string
-          description: "Markdown body."
-        metadata:
-          type: object
-          description: "Optional extra frontmatter fields."
-      required: [path, name, description, content]
-    steps:
-      - backend: write_step
-
-  daily_write:
-    backend: base
-    description: "Write a daily markdown note linked to its source conversation."
-    parameters:
-      type: object
-      properties:
-        name:
-          type: string
-          description: "Filename stem and frontmatter name."
-        description:
-          type: string
-          description: "Frontmatter description."
-        session_id:
-          type: string
-          description: "Source conversation session identifier."
-        content:
-          type: string
-          description: "Markdown body."
-        date:
-          type: string
-          description: "YYYY-MM-DD; empty means today."
-          default: ""
-        metadata:
-          type: object
-          description: "Optional extra frontmatter fields."
-      required: [name, description, session_id, content]
-    steps:
-      - backend: daily_write_step
-
-  edit:
-    backend: base
-    description: "Find and replace text in a markdown file."
-    parameters:
-      type: object
-      properties:
-        path:
-          type: string
-          description: "Workspace-relative path."
-        old:
-          type: string
-          description: "Text to replace."
-        new:
-          type: string
-          description: "Replacement text."
-          default: ""
-      required: [path, old, new]
-    steps:
-      - backend: edit_step
-
-  dingtalk_wait:
-    backend: background
-    supervisor: true
-    close_timeout: 10
-    steps:
-      - backend: dingtalk_wait_step
-        app_key: ${DINGTALK_APP_KEY:-}
-        app_secret: ${DINGTALK_APP_SECRET:-}
-        robot_code: ${DINGTALK_ROBOT_CODE:-}
-        worker_count: 4
-        builtin_tools: [bash]
-        job_tools:
-          - memory_search
-          - read
-          - write
-          - edit
-          - daily_list
-          - daily_write
-          - frontmatter_read
-          - frontmatter_update
-
-components:
-  tokenizer:
-    default:
-      backend: regex
-
-  as_llm:
-    default:
-      backend: openai
-      model: ${LLM_MODEL_NAME:-qwen3.7-plus}
-      stream: true
-      context_size: 200000
-      max_retries: 3
-      credential:
-        api_key: ${LLM_API_KEY:-}
-        base_url: ${LLM_BASE_URL:-}
-      parameters:
-        max_tokens: 65536
-        thinking_enable: false
-
-  agent_wrapper:
-    default:
-      backend: agentscope
-      as_llm: default
-      builtin_tools: false
-
-#  as_embedding:
-#    default:
-#      backend: openai
-#      model: ${EMBEDDING_MODEL_NAME:-text-embedding-v4}
-#      dimensions: 1024
-#      max_retries: 0
-#      credential:
-#        api_key: ${EMBEDDING_API_KEY:-}
-#        base_url: ${EMBEDDING_BASE_URL:-https://dashscope.aliyuncs.com/compatible-mode/v1}
-#      parameters: {}
-#
-#  embedding_store:
-#    default:
-#      backend: local
-#      as_embedding: default
-#      max_retries: 3
-#      quota_retry_delay: 60.0
-
-  file_graph:
-    default:
-      backend: local
-
-  file_catalog:
-    dream:
-      backend: local
-
-  file_chunker:
-    markdown:
-      backend: markdown
-      supported_extensions: [md]
-      embed_toc: true
-      max_ast_sections: 100
-      include_frontmatter_in_metadata: false
-      include_frontmatter_keys_in_metadata: []
-    jsonl:
-      backend: jsonl
-      supported_extensions: [jsonl]
-      max_lines_per_chunk: 1
-
-  keyword_index:
-    default:
-      backend: bm25
-      tokenizer: default
-
-  file_store:
-    default:
-      backend: local
-      store_name: local
-#      embedding_store: default
-      embedding_store: ""
-      keyword_index: default
-      file_graph: default
--- a/tests/unit/test_config_parser.py
+++ b/tests/unit/test_config_parser.py
@ -123,14 +123,6 @@ def test_default_config_keeps_frontmatter_chunk_metadata_opt_in():
    ) in (None, [])


-def test_daily_cookbook_chunks_jsonl_one_line_at_a_time():
-    """Daily cookbook keeps JSONL records as individually addressable chunks."""
-    cfg = _load_config("daily_cookbook.yaml")
-
-    jsonl = cfg["components"]["file_chunker"]["jsonl"]
-    assert jsonl["max_lines_per_chunk"] == 1
-
-
 def test_parse_args_rejects_non_key_value_extra_argument():
    """Extra CLI arguments must use key=value syntax."""
    with pytest.raises(ValueError, match="expected key=value"):
--- a/tests/unit/test_dingtalk_wait.py
+++ b/tests/unit/test_dingtalk_wait.py
@ -9,10 +9,8 @@ from unittest.mock import MagicMock

 import pytest

-from reme.components import ApplicationContext, R
+from reme.components import ApplicationContext
 from reme.components.agent_wrapper.base_agent_wrapper import BaseAgentWrapper
-from reme.config.config_parser import _load_config
-from reme.enumeration import ComponentEnum
 from reme.steps.cookbook.dingtalk.wait import DingTalkWaitStep, _session_key


@ -203,54 +201,6 @@ async def test_final_reply_injects_only_configured_tools(tmp_path):
    ]


-def test_daily_cookbook_registers_one_step_background_wait_job(monkeypatch):
-    for name in ("DINGTALK_APP_KEY", "DINGTALK_APP_SECRET", "DINGTALK_ROBOT_CODE"):
-        monkeypatch.delenv(name, raising=False)
-    config = _load_config("daily_cookbook")
-    job = config["jobs"]["dingtalk_wait"]
-    assert job["backend"] == "background"
-    assert job["steps"] == [
-        {
-            "backend": "dingtalk_wait_step",
-            "app_key": "",
-            "app_secret": "",
-            "robot_code": "",
-            "worker_count": 4,
-            "builtin_tools": ["bash"],
-            "job_tools": [
-                "memory_search",
-                "read",
-                "write",
-                "edit",
-                "daily_list",
-                "daily_write",
-                "frontmatter_read",
-                "frontmatter_update",
-            ],
-        },
-    ]
-    assert config["components"]["agent_wrapper"] == {
-        "default": {
-            "backend": "agentscope",
-            "as_llm": "default",
-            "builtin_tools": False,
-        },
-    }
-    assert R.get(ComponentEnum.STEP, "dingtalk_wait_step") is DingTalkWaitStep
-
-
-def test_daily_cookbook_passes_dingtalk_environment_to_step(monkeypatch):
-    monkeypatch.setenv("DINGTALK_APP_KEY", "app-key")
-    monkeypatch.setenv("DINGTALK_APP_SECRET", "app-secret")
-    monkeypatch.setenv("DINGTALK_ROBOT_CODE", "robot-code")
-    step = _load_config("daily_cookbook")["jobs"]["dingtalk_wait"]["steps"][0]
-    assert (step["app_key"], step["app_secret"], step["robot_code"]) == (
-        "app-key",
-        "app-secret",
-        "robot-code",
-    )
-
-
@pytest.mark.asyncio
 async def test_stream_client_closes_when_background_stop_is_set(monkeypatch):
    websocket = _WebSocket()
--- a/tests/unit/test_injected_job_kwargs.py
+++ b/tests/unit/test_injected_job_kwargs.py
@ -65,6 +65,31 @@ def test_strip_injected_parameters_hides_keys_from_schema():
    assert "date" in job.parameters["properties"]


+def test_search_injection_exposes_only_query():
+    parameters = {
+        "type": "object",
+        "properties": {
+            "query": {"type": "string"},
+            "limit": {"type": "integer"},
+            "min_score": {"type": "number"},
+            "start_date": {"type": "string"},
+            "end_date": {"type": "string"},
+        },
+        "required": ["query"],
+    }
+    injected = {
+        "limit": 20,
+        "min_score": 0.0,
+        "start_date": None,
+        "end_date": "2026-07-20",
+    }
+
+    stripped = BaseAgentWrapper._strip_injected_parameters(parameters, injected)
+
+    assert stripped["properties"] == {"query": {"type": "string"}}
+    assert stripped["required"] == ["query"]
+
+
 # -- AgentScope wrapper -----------------------------------------------------------


@ -139,7 +164,7 @@ class _RecordingWrapper(BaseAgentWrapper):
        super().__init__(**kwargs)
        self.calls: list[dict] = []

-    async def reply(self, inputs, **kwargs) -> dict:
+    async def reply(self, _inputs, **kwargs) -> dict:
        self.calls.append(kwargs)
        return {"session_id": "s-1", "last_message": {}, "result": "ok"}

--- a/tests/unit/test_local_embedding_store.py
+++ b/tests/unit/test_local_embedding_store.py
@ -509,24 +509,95 @@ def test_cache_space_is_rechecked_after_async_load(monkeypatch, tmp_path):
    run(go())


-def test_completed_request_only_writes_to_its_active_cache_space():
-    """A v3 request must not populate v4 after the provider switches back to v3."""
+def test_whole_request_retries_after_vector_space_changes_between_batches():
+    """Completed batches must be discarded when a later batch changes vector space."""

    async def go():
-        embedding = OpenAIAsEmbedding(name="t_space_write_race", backend="openai", model="v3", dimensions=2)
-        store = LocalEmbeddingStore(name="t_local_write_race")
+        embedding = FakeAsEmbedding()
+        embedding.vector_space_id = "v3"
+        store = LocalEmbeddingStore(name="t_local_write_race", max_batch_size=1, enable_cache=False)
        store.as_embedding = embedding
        store._cache_space = embedding.vector_space_id
+        calls = 0

-        async def compute_after_round_trip(_batch, **_kwargs):
-            embedding.model = FakeProviderModel("v4")
-            store._cache_space = embedding.vector_space_id
-            embedding.model = FakeProviderModel("v3")
-            return [(0, "key", np.array([3.0, 0.0], dtype=np.float16))]
+        async def switch_during_second_batch(batch, **_kwargs):
+            nonlocal calls
+            calls += 1
+            if calls == 2:
+                embedding.vector_space_id = "v4"
+            idx, _text, key = batch[0]
+            version = 3.0 if calls < 3 else 4.0
+            return [(idx, key, np.array([version, 0.0], dtype=np.float16))]

-        store._compute_batch = compute_after_round_trip
-        await store._fill_misses([(0, "text", "key")], [None])
+        store._compute_batch = switch_during_second_batch
+        results = await store.get_embeddings(["first", "second"])

+        assert calls == 4
+        assert store._cache_space == embedding.vector_space_id
+        for result in results:
+            np.testing.assert_array_equal(result, np.array([4.0, 0.0], dtype=np.float16))
+
+    run(go())
+
+
+def test_whole_request_rereads_cache_after_vector_space_changes(monkeypatch, tmp_path):
+    """A cache hit from the old space must not survive a later provider switch."""
+
+    async def go():
+        monkeypatch.setattr(
+            LocalEmbeddingStore,
+            "component_metadata_path",
+            property(lambda _self: tmp_path),
+        )
+        embedding = FakeAsEmbedding()
+        embedding.vector_space_id = "v3"
+        store = LocalEmbeddingStore(name="t_local_cache_race", enable_cache=True)
+        store.as_embedding = embedding
+        store._cache_space = embedding.vector_space_id
+        first_key = store._cache_key("first")
+        store._cache[first_key] = np.array([3.0, 0.0], dtype=np.float16)
+        calls = 0
+
+        async def switch_on_miss(batch, **_kwargs):
+            nonlocal calls
+            calls += 1
+            if calls == 1:
+                embedding.vector_space_id = "v4"
+            version = 3.0 if calls == 1 else 4.0
+            return [(idx, key, np.array([version, 0.0], dtype=np.float16)) for idx, _text, key in batch]
+
+        store._compute_batch = switch_on_miss
+        results = await store.get_embeddings(["first", "second"])
+
+        assert calls == 2
+        for result in results:
+            np.testing.assert_array_equal(result, np.array([4.0, 0.0], dtype=np.float16))
+
+    run(go())
+
+
+def test_whole_request_stops_retrying_when_vector_space_keeps_changing():
+    """Continuous configuration churn must discard the whole request instead of blocking forever."""
+
+    async def go():
+        embedding = FakeAsEmbedding()
+        embedding.vector_space_id = "v3"
+        store = LocalEmbeddingStore(name="t_local_write_churn")
+        store.as_embedding = embedding
+        store._cache_space = embedding.vector_space_id
+        calls = 0
+
+        async def change_space_every_time(_batch, **_kwargs):
+            nonlocal calls
+            calls += 1
+            embedding.vector_space_id = f"v{calls + 3}"
+            return [(0, "key", np.array([float(calls), 0.0], dtype=np.float16))]
+
+        store._compute_batch = change_space_every_time
+        results = await store.get_embeddings(["text"])
+
+        assert calls == 3
+        assert results == [None]
        assert "key" not in store._cache

    run(go())
--- a/tests/unit/test_package_versions.py
+++ b/tests/unit/test_package_versions.py
@ -7,6 +7,7 @@ import tomllib
 from types import ModuleType

 from packaging.requirements import Requirement
+from packaging.version import Version
 import pytest

 REPOSITORY = Path(__file__).resolve().parents[2]
@ -41,17 +42,13 @@ def test_studio_packages_have_independent_identity() -> None:
    assert studio_config["project"]["name"] == "reme_studio"
    assert npm_config["name"] == "@agentscope-ai/reme_studio"
    assert studio_config["project"]["version"] == npm_config["version"]
-    assert main_config["project"]["optional-dependencies"]["as"] == ["agentscope[model-ollama]==2.0.6"]
+    assert main_config["project"]["optional-dependencies"]["as"] == ["agentscope[model-ollama]==2.0.7"]
    assert main_config["project"]["optional-dependencies"]["web"] == ["reme_studio"]
    assert main_config["project"]["optional-dependencies"]["core"].count("reme-ai[as]") == 1
    assert main_config["project"]["optional-dependencies"]["core"].count("reme_studio") == 1
-    assert main_config["project"]["optional-dependencies"]["qwenpaw"] == [
-        "reme-ai[core]",
-        "reme-auto-fin>=0.1.1",
-        "reme-daily-paper>=0.1.1",
-    ]
-    assert auto_fin_config["project"]["version"] == "0.1.1"
-    assert daily_paper_config["project"]["version"] == "0.1.1"
+    assert "qwenpaw" not in main_config["project"]["optional-dependencies"]
+    assert auto_fin_config["project"]["version"] == "0.1.2"
+    assert daily_paper_config["project"]["version"] == "0.1.2"
    assert main_config["tool"]["setuptools"]["packages"]["find"]["include"] == ["reme", "reme.*"]
    assert "reme_studio*" in main_config["tool"]["setuptools"]["packages"]["find"]["exclude"]

@ -153,14 +150,16 @@ def test_auto_fin_license_matches_repository() -> None:
    ).read_text(encoding="utf-8")


-def test_auto_fin_requires_reme_core() -> None:
-    """Install the optional runtime packages needed while loading Auto Fin's entry points."""
+def test_auto_fin_requires_reme_base() -> None:
+    """Keep the plugin dependency limited to ReMe's public base package."""
    config = tomllib.loads((REPOSITORY / "plugins" / "auto-fin" / "pyproject.toml").read_text(encoding="utf-8"))
    requirements = [Requirement(value) for value in config["project"]["dependencies"]]
    reme_requirements = [requirement for requirement in requirements if requirement.name == "reme-ai"]

    assert len(reme_requirements) == 1
-    assert set(reme_requirements[0].extras) == {"core"}
+    assert not reme_requirements[0].extras
+    assert Version("0.4.1.8") not in reme_requirements[0].specifier
+    assert Version("0.4.1.9") in reme_requirements[0].specifier


 def test_daily_paper_license_matches_repository() -> None:
@ -171,12 +170,14 @@ def test_daily_paper_license_matches_repository() -> None:


 def test_daily_paper_declares_runtime_dependencies() -> None:
-    """Keep Daily Paper's ReMe feature set and PDF parser explicit in its own distribution."""
+    """Keep Daily Paper's minimal ReMe and PDF dependencies explicit."""
    config = tomllib.loads((REPOSITORY / "plugins" / "daily_paper" / "pyproject.toml").read_text(encoding="utf-8"))
    requirements = [Requirement(value) for value in config["project"]["dependencies"]]
    by_name = {requirement.name: requirement for requirement in requirements}

-    assert set(by_name["reme-ai"].extras) == {"core"}
+    assert not by_name["reme-ai"].extras
+    assert Version("0.4.1.8") not in by_name["reme-ai"].specifier
+    assert Version("0.4.1.9") in by_name["reme-ai"].specifier
    assert "pypdf" in by_name


--- a/tests/unit/test_plugin_cli.py
+++ b/tests/unit/test_plugin_cli.py
@ -76,7 +76,7 @@ def test_list_plugins_marks_configured_plugins(monkeypatch, tmp_path, capsys):
    )
    monkeypatch.setattr(plugin_cli_module, "_enabled_plugins", lambda _config: {"auto-fin"})

-    assert plugin_cli_module.plugin_cli(["list", "--config", "daily_cookbook"]) == 0
+    assert plugin_cli_module.plugin_cli(["list", "--config", "default"]) == 0

    output = capsys.readouterr().out
    assert "ENABLED" in output