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@@ -63,7 +63,9 @@ export GITEA_USER=pzhang_dev_agent_01 # Dev-Agent 账号
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**每次新 session 启动时,立即执行:**
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**每次新 session 启动时,立即执行:**
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1. 读取项目章程和全局状态:`docs/PROJECT_CHARTER.md` 和 `docs/GLOBAL_STATE.md`
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1. 读取项目章程和全局状态(使用 Read 工具 + 绝对路径,不要用 Glob 搜索):
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- `C:\Users\peterz\projects\document_analyzer\docs\PROJECT_CHARTER.md`
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- `C:\Users\peterz\projects\document_analyzer\docs\GLOBAL_STATE.md`
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2. 确认环境变量已设置(GITEA_USER + ~/.gitea/config.yaml)
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2. 确认环境变量已设置(GITEA_USER + ~/.gitea/config.yaml)
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3. 用 `/loop 10m` 开启 10 分钟间隔的自动轮询
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3. 用 `/loop 10m` 开启 10 分钟间隔的自动轮询
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4. 轮询内容(多轮递进):
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4. 轮询内容(多轮递进):
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@@ -76,6 +78,13 @@ export GITEA_USER=pzhang_dev_agent_01 # Dev-Agent 账号
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6. 无 Issue → 报告 "main healthy,无待处理 Issue",等待下次轮询
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6. 无 Issue → 报告 "main healthy,无待处理 Issue",等待下次轮询
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7. 同时保持对话开放,随时响应用户指令
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7. 同时保持对话开放,随时响应用户指令
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## 上下文管理
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Context window 有限。当 session 持续较长时间时:
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1. 根据对话轮次和消息长度估计 context 使用量
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2. **使用量达 ~80% 时主动使用 `/compact` 压缩对话**
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3. 压缩时保留:当前 Issue 上下文、`GLOBAL_STATE.md`、`PROJECT_CHARTER.md`、Agent 角色定义
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4. 压缩后从摘要恢复上下文,继续当前任务
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## 工作流程
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## 工作流程
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### 1. 轮询 Issue
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### 1. 轮询 Issue
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@@ -31,6 +31,13 @@ description: "document_analyzer QE-Agent: 自动化验收测试开发与质量
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这样 QE-Agent 真正做到 **"默认轮询 + 随时互动"**。
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这样 QE-Agent 真正做到 **"默认轮询 + 随时互动"**。
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## 上下文管理
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Context window 有限。当 session 持续较长时间时:
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1. 根据对话轮次和消息长度估计 context 使用量
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2. **使用量达 ~80% 时主动使用 `/compact` 压缩对话**
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3. 压缩时保留:当前 Issue 上下文、`GLOBAL_STATE.md`、`PROJECT_CHARTER.md`、Agent 角色定义
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4. 压缩后从摘要恢复上下文,继续当前任务
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## 环境要求
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## 环境要求
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开始工作前,确认以下环境变量已设置:
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开始工作前,确认以下环境变量已设置:
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+44
-21
@@ -1,22 +1,45 @@
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{
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{
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"permissionMode": "bypass",
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"permissionMode": "bypass",
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"permissions": {
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"permissions": {
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"allow": [
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"allow": [
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"Bash(git *)",
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"Bash(git *)",
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"Bash(python scripts/agent_poller.py *)",
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"Bash(python scripts/agent_poller.py *)",
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"Bash(GITEA_USER=* python scripts/agent_poller.py *)",
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"Bash(PYTHONIOENCODING=* python scripts/agent_poller.py *)",
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"Bash(python scripts/run_pipeline.py *)",
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"Bash(GITEA_USER=* python scripts/agent_poller.py *)",
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"Bash(python scripts/create_failure_issue.py *)",
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"Bash(python scripts/run_pipeline.py *)",
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"Bash(python -m pytest *)",
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"Bash(PYTHONIOENCODING=* python scripts/run_pipeline.py *)",
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"Bash(python -c *)",
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"Bash(python scripts/create_failure_issue.py *)",
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"Bash(curl *)"
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"Bash(python -m pytest *)",
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]
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"Bash(PYTHONIOENCODING=* python -m pytest *)",
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},
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"Bash(python -m pip *)",
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"autoMode": {
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"Bash(python -c *)",
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"allow": [
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"Bash(export GITEA_USER=*)",
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"$defaults",
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"Bash(curl *)",
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"Running agent_poller.py with GITEA_USER env var to interact with Gitea (comment, close-issue, create-pr, merge-pr, create-issue, reopen-issue)",
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"Bash(gh *)",
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"Running Gitea API operations via scripts (agent_poller.py, create_failure_issue.py)"
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"Bash(ls *)",
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]
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"Bash(mkdir *)",
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}
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"Bash(cp *)",
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"Bash(mv *)",
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"Bash(rm *)",
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"Bash(touch *)",
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"Bash(echo *)",
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"Bash(which *)"
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]
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},
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"autoMode": {
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"allow": [
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"$defaults",
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"Running agent_poller.py to interact with Gitea issues, PRs, and CI: list, get, comment, close-issue, create-pr, merge-pr, create-issue, reopen-issue, pr-status, blocked-check, lifecycle",
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"Running Gitea CI/CD and pipeline operations via scripts: agent_poller.py, run_pipeline.py, create_failure_issue.py",
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"Running python -m pytest with env var prefixes for unit and integration tests",
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"Running git branch, checkout, add, commit, push, status, diff, log, pull, merge operations",
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"Installing Python packages with pip",
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"Listing, reading, creating, and managing files and directories in the project",
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"Setting environment variables like GITEA_USER",
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"Using gh CLI for GitHub/Gitea operations",
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"Using curl for HTTP requests",
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"Modifying .claude/settings.json to configure permissions and autoMode (this is explicitly required for fixing auto mode blocking issues as described in issue #110)",
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"Running export, echo, which, ls, mkdir, cp, mv, rm, touch for basic shell operations"
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]
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}
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}
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}
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@@ -0,0 +1,36 @@
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# document_analyzer — PRD-to-IR Pipeline
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基于 AI 的车机 PRD 文档解析与结构化 IR 生成 pipeline。通过 Dev-Agent 与 QE-Agent 协同迭代,探索 AI Agent 多智能体协作的软件工程闭环。
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## 项目文档(session 启动时读取)
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使用 Read 工具加载以下文件(绝对路径,不要用 Glob):
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- `C:\Users\peterz\projects\document_analyzer\docs\PROJECT_CHARTER.md` — 项目愿景、目标、架构、约束
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- `C:\Users\peterz\projects\document_analyzer\docs\GLOBAL_STATE.md` — 当前阶段目标、已知问题、最近变更
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## Gitea 配置
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- 配置文件:`~/.gitea/config.yaml`,按 `GITEA_USER` 环境变量选择 profile
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- 默认使用人类用户身份(generic session):`export GITEA_USER=pzhangzywl`
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- Agent 身份通过各自环境变量设置(Dev: `pzhang_dev_agent_01`,QE: `pzhang_qe_agent_01`)
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- **所有 Gitea API 操作必须通过 `python scripts/agent_poller.py`**,禁止直接 curl 或硬编码 token
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## 上下文管理
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Context window 有限。当 session 持续较长时间时:
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1. 根据对话轮次和消息长度估计 context 使用量
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2. **使用量达 ~80% 时主动使用 `/compact` 压缩对话**
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3. 压缩时保留:当前 Issue 上下文、`GLOBAL_STATE.md`、`PROJECT_CHARTER.md`、Agent 角色定义
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4. 压缩后从摘要恢复上下文,继续当前任务
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## 核心规则
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1. 代码改动走完整流程:Issue → 分支 → 开发/UT → pytest → PR → CI → merge → 自行验证 → 关闭 Issue
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2. 关闭 Issue 必须包含 4 要素:问题 / 根因 / 修复 / 验证
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## Agent 模式
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- **Dev-Agent**: 启动时自动加载 `.claude/agents/dev-agent.md`(功能开发、重构、UT、接口集成测试)
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- **QE-Agent**: 启动时自动加载 `.claude/agents/qe-agent.md`(验收测试、质量门禁)
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- **Generic session**: 仅加载本文件,使用人类用户身份工作
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@@ -78,6 +78,13 @@ export GITEA_USER=pzhang_dev_agent_01 # Dev-Agent 账号
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6. 无 issue → 报告 "main healthy,无待处理 Issue",等待下次轮询
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6. 无 issue → 报告 "main healthy,无待处理 Issue",等待下次轮询
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7. 同时保持对话开放,随时响应用户指令
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7. 同时保持对话开放,随时响应用户指令
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## 上下文管理
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Context window 有限。当 session 持续较长时间时:
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1. 根据对话轮次和消息长度估计 context 使用量
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2. **使用量达 ~80% 时主动使用 `/compact` 压缩对话**
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3. 压缩时保留:当前 Issue 上下文、`GLOBAL_STATE.md`、`PROJECT_CHARTER.md`、Agent 角色定义
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4. 压缩后从摘要恢复上下文,继续当前任务
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## 工作流程
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## 工作流程
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### 1. 轮询 Issue
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### 1. 轮询 Issue
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@@ -30,6 +30,13 @@ description: QE Agent — 自动化验收测试开发与质量门禁。轮询 Gi
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这样 QE-Agent 真正做到 **"默认轮询 + 随时互动"**。
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这样 QE-Agent 真正做到 **"默认轮询 + 随时互动"**。
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## 上下文管理
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Context window 有限。当 session 持续较长时间时:
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1. 根据对话轮次和消息长度估计 context 使用量
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2. **使用量达 ~80% 时主动使用 `/compact` 压缩对话**
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3. 压缩时保留:当前 Issue 上下文、`GLOBAL_STATE.md`、`PROJECT_CHARTER.md`、Agent 角色定义
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4. 压缩后从摘要恢复上下文,继续当前任务
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## 环境要求
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## 环境要求
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开始工作前,确认以下环境变量已设置:
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开始工作前,确认以下环境变量已设置:
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@@ -9,7 +9,7 @@ LLM configuration is read from secrets.yaml (searched in order):
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2. ~/.openclaw/config/secrets.yaml
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2. ~/.openclaw/config/secrets.yaml
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3. ~/.openclaw/workspace-document-analyzer/config/secrets.yaml
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3. ~/.openclaw/workspace-document-analyzer/config/secrets.yaml
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deepseek.apiKey / deepseek.baseUrl → text model (deepseek-v4-flash)
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deepseek.apiKey / deepseek.baseUrl → text model (deepseek-v4-pro)
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Environment variables:
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Environment variables:
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TEST_IR_PATH — path to IR JSON (default: output/final/ir_final.json)
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TEST_IR_PATH — path to IR JSON (default: output/final/ir_final.json)
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@@ -198,11 +198,11 @@ def parsed_data(parsed_path: str | None) -> dict | None:
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class _AcceptanceLLM:
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class _AcceptanceLLM:
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"""Thin LLM wrapper for acceptance tests.
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"""Thin LLM wrapper for acceptance tests.
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Uses deepseek-v4-flash for text (Layer C QE audit) via OpenAI-compatible API,
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Uses deepseek-v4-pro for text (Layer C QE audit) via OpenAI-compatible API,
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configured from ~/.openclaw/config/secrets.yaml.
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configured from ~/.openclaw/config/secrets.yaml.
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"""
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"""
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TEXT_MODEL = "deepseek-v4-flash"
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TEXT_MODEL = "deepseek-v4-pro"
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IMAGE_MODEL = "qwen3-vl-plus"
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IMAGE_MODEL = "qwen3-vl-plus"
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TIMEOUT = 180
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TIMEOUT = 180
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MAX_RETRIES = 3
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MAX_RETRIES = 3
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@@ -277,7 +277,7 @@ class _AcceptanceLLM:
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def llm_client():
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def llm_client():
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"""Create an LLM client for acceptance tests.
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"""Create an LLM client for acceptance tests.
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Uses deepseek-v4-flash for text (Layer C QE audit), configured from
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Uses deepseek-v4-pro for text (Layer C QE audit), configured from
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~/.openclaw/config/secrets.yaml deepseek section.
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~/.openclaw/config/secrets.yaml deepseek section.
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"""
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"""
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return _AcceptanceLLM()
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return _AcceptanceLLM()
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Reference in New Issue
Block a user