refactor: 导图生成仅使用学习报告

fix: 流水线kubeconfig改用临时目录
docs: 更新提交规范
2026-08-03 23:08:40 +08:00 · 2026-08-02 10:51:03 +08:00 · 2026-08-01 00:15:59 +08:00 · 2026-08-01 00:13:08 +08:00 · 2026-07-26 21:35:51 +08:00 · 2026-07-26 20:52:03 +08:00
10 changed files with 204 additions and 242 deletions
@@ -4,7 +4,7 @@ on:
  workflow_dispatch:
    inputs:
      environment:
-        description: '部署环境'
+        description: '部署环境（本仓库仅 main 分支；dev/prod 均从 main 部署）'
        required: true
        type: choice
        options:
@@ -19,67 +19,137 @@ env:
 jobs:
  build-and-deploy:
    runs-on: ubuntu-latest
+    env:
+      KUBECONFIG: /tmp/kubeconfig
    steps:
+      - name: Validate branch ↔ environment
+        run: |
+          set -euo pipefail
+          REF="${{ gitea.ref }}"
+          BRANCH="${REF#refs/heads/}"
+          if [[ "$REF" == refs/tags/* ]]; then
+            echo "ERROR: 请从分支触发部署，不要用 tag。当前 ref=$REF"
+            exit 1
+          fi
+          ENV="${{ inputs.environment }}"
+          echo "branch=$BRANCH environment=$ENV sha=${{ gitea.sha }}"
+          # lpt-ai 仅维护 main：dev/prod 都从 main 出包，靠 environment 区分 namespace/镜像 tag
+          case "$BRANCH" in
+            main|master)
+              echo "OK: lpt-ai 从 $BRANCH 部署到 $ENV"
+              ;;
+            *)
+              echo "ERROR: lpt-ai 只能从 main/master 部署，当前分支是 '$BRANCH'"
+              exit 1
+              ;;
+          esac
+          case "$ENV" in
+            dev|prod) ;;
+            *)
+              echo "ERROR: 未知 environment=$ENV"
+              exit 1
+              ;;
+          esac
+
      - name: Checkout code
        run: |
-          git clone $REPO_URL .
-          git checkout ${{ gitea.sha }}
+          set -euo pipefail
+          git clone "$REPO_URL" .
+          git checkout "${{ gitea.sha }}"

      - name: Login to Docker Registry
        run: |
-          echo "${{ secrets.REGISTRY_PASSWORD }}" | docker login $REGISTRY -u "${{ secrets.REGISTRY_USERNAME }}" --password-stdin
+          set -euo pipefail
+          echo "${{ secrets.REGISTRY_PASSWORD }}" | docker login "$REGISTRY" -u "${{ secrets.REGISTRY_USERNAME }}" --password-stdin

      - name: Build & Push Docker image
        run: |
-          TAG=${{ gitea.sha }}-$(date +%s)
-          docker build -t $REGISTRY/$APP:$TAG -t $REGISTRY/$APP:${{ inputs.environment }} .
-          docker push $REGISTRY/$APP:$TAG
-          docker push $REGISTRY/$APP:${{ inputs.environment }}
-          echo "IMAGE_TAG=$TAG" >> $GITHUB_ENV
+          set -euo pipefail
+          ENV="${{ inputs.environment }}"
+          TAG="${{ gitea.sha }}-$(date +%s)"
+          echo "Building $REGISTRY/$APP:$TAG (env tag=$ENV)"
+          docker build -t "$REGISTRY/$APP:$TAG" -t "$REGISTRY/$APP:$ENV" .
+          docker push "$REGISTRY/$APP:$TAG"
+          docker push "$REGISTRY/$APP:$ENV"
+          if [ -n "${GITHUB_ENV:-}" ]; then
+            echo "IMAGE_TAG=$TAG" >> "$GITHUB_ENV"
+          fi
+          if [ -n "${GITEA_ENV:-}" ]; then
+            echo "IMAGE_TAG=$TAG" >> "$GITEA_ENV"
+          fi
+          echo "$TAG" > image_tag.txt
+          if [ -n "${{ runner.temp }}" ]; then
+            echo "$TAG" > "${{ runner.temp }}/image_tag.txt" || true
+          fi
+          echo "IMAGE_TAG=$TAG"

      - name: Setup kubectl
        run: |
+          set -euo pipefail
          curl -sLO "https://dl.k8s.io/release/v1.30.0/bin/linux/amd64/kubectl"
          chmod +x kubectl
          mv kubectl /usr/local/bin/
-          mkdir -p ~/.kube
-          echo "${{ secrets.KUBECONFIG_B64 }}" | base64 -d > ~/.kube/config
+          echo "${{ secrets.KUBECONFIG_B64 }}" | base64 -d > /tmp/kubeconfig
+          chmod 600 /tmp/kubeconfig

      - name: Create/Update imagePullSecret
        run: |
+          set -euo pipefail
          kubectl create secret docker-registry regcred \
-            --docker-server=$REGISTRY \
+            --docker-server="$REGISTRY" \
            --docker-username="${{ secrets.REGISTRY_USERNAME }}" \
            --docker-password="${{ secrets.REGISTRY_PASSWORD }}" \
-            -n lpt-${{ inputs.environment }} \
+            -n "lpt-${{ inputs.environment }}" \
            --dry-run=client -o yaml | kubectl apply -f -

      - name: Deploy to K8s
        run: |
-          kubectl set image deployment/$APP $APP=$REGISTRY/$APP:$IMAGE_TAG -n lpt-${{ inputs.environment }} --record
-          kubectl rollout status deployment/$APP -n lpt-${{ inputs.environment }} --timeout=5m
+          set -euo pipefail
+          ENV="${{ inputs.environment }}"
+          IMAGE_TAG="${IMAGE_TAG:-}"
+          if [ -z "$IMAGE_TAG" ] && [ -f image_tag.txt ]; then
+            IMAGE_TAG="$(cat image_tag.txt)"
+          fi
+          if [ -z "$IMAGE_TAG" ] && [ -f "${{ runner.temp }}/image_tag.txt" ]; then
+            IMAGE_TAG="$(cat "${{ runner.temp }}/image_tag.txt")"
+          fi
+          if [ -z "$IMAGE_TAG" ]; then
+            echo "ERROR: IMAGE_TAG 为空，无法部署"
+            exit 1
+          fi
+          echo "Deploying $REGISTRY/$APP:$IMAGE_TAG -> namespace lpt-$ENV"
+          kubectl set image "deployment/$APP" \
+            "$APP=$REGISTRY/$APP:$IMAGE_TAG" \
+            -n "lpt-$ENV" --record
+          kubectl rollout status "deployment/$APP" \
+            -n "lpt-$ENV" --timeout=5m

      - name: Debug on failure
        if: failure()
        run: |
+          ENV="${{ inputs.environment }}"
          echo "=== Deployment Status ==="
-          kubectl get deployment $APP -n lpt-${{ inputs.environment }}
+          kubectl get deployment "$APP" -n "lpt-$ENV" || true
          echo ""
          echo "=== Pod Status ==="
-          kubectl get pods -n lpt-${{ inputs.environment }} -l app=$APP
+          kubectl get pods -n "lpt-$ENV" -l "app=$APP" || true
          echo ""
          echo "=== Recent Events ==="
-          kubectl get events -n lpt-${{ inputs.environment }} --sort-by='.lastTimestamp' | tail -20
+          kubectl get events -n "lpt-$ENV" --sort-by='.lastTimestamp' | tail -20 || true
          echo ""
          echo "=== Pod Describe (latest) ==="
-          POD=$(kubectl get pods -n lpt-${{ inputs.environment }} -l app=$APP --sort-by=.metadata.creationTimestamp -o jsonpath='{.items[-1].metadata.name}')
-          kubectl describe pod $POD -n lpt-${{ inputs.environment }} || true
+          POD=$(kubectl get pods -n "lpt-$ENV" -l "app=$APP" --sort-by=.metadata.creationTimestamp -o jsonpath='{.items[-1].metadata.name}' 2>/dev/null || true)
+          if [ -n "${POD:-}" ]; then
+            kubectl describe pod "$POD" -n "lpt-$ENV" || true
            echo ""
            echo "=== Pod Logs (latest) ==="
-          kubectl logs $POD -n lpt-${{ inputs.environment }} --tail=50 || true
+            kubectl logs "$POD" -n "lpt-$ENV" --tail=50 || true
+          fi

      - name: Rollback on failure
        if: failure()
        run: |
-          kubectl rollout undo deployment/$APP -n lpt-${{ inputs.environment }}
-          kubectl rollout status deployment/$APP -n lpt-${{ inputs.environment }}
+          set -euo pipefail
+          ENV="${{ inputs.environment }}"
+          kubectl rollout undo "deployment/$APP" -n "lpt-$ENV" || true
+          kubectl rollout status "deployment/$APP" -n "lpt-$ENV" || true
@@ -0,0 +1,104 @@
+# LPT AI 服务（lpt-ai）
+
+> TypeScript + Fastify 独立 AI 服务，集成 SiliconFlow LLM，为后端提供异步 AI 任务。
+
+## Git 提交规范
+
+- 提交信息必须简短且使用中文，不要使用英文长句。
+- 格式：`类型: 简述`，例如 `feat: 新增思维导图生成任务`、`fix: 修复任务队列TTL清理`、`docs: 补充环境变量说明`。
+
+## 技术栈
+
+- 运行时：Node.js 20+
+- 框架：Fastify 5
+- LLM：SiliconFlow OpenAI 兼容接口（Qwen/Qwen2.5-32B-Instruct）
+- 运行时依赖：除 fastify 外无其他外部依赖
+
+## 项目结构
+
+```text
+lpt-ai/src/
+├── index.ts          → 服务入口（加载 .env，启动 Fastify）
+├── routes/ai.ts      → AI 路由（health, tasks, fetch-title）
+├── llm/
+│   ├── client.ts     → LLM 客户端（SiliconFlow 接口）
+│   ├── prompts.ts    → Prompt 模板（3 种任务类型）
+│   └── prompts.test.ts
+├── task-queue.ts     → 异步任务队列
+└── admin/
+    ├── index.ts      → 管理面板路由
+    ├── routes.ts
+    └── store.ts      → 日志存储
+```
+
+## API 端点（5 个）
+
+| 方法 | 路径 | 说明 |
+|------|------|------|
+| GET | `/health` | 健康检查（返回 LLM 可用状态和模型名） |
+| POST | `/ai/tasks` | 提交异步任务（返回 taskId） |
+| GET | `/ai/tasks/:taskId` | 轮询任务结果 |
+| POST | `/fetch-title` | 抓取网页标题 |
+| GET | `/admin` | 管理面板（查看最近 200 条日志） |
+
+## 支持的任务类型
+
+| 类型 | 说明 | 温度 | Max Tokens |
+|------|------|------|------------|
+| `aggregate-report` | 残片聚合为学习报告 | 0.3 | 2048 |
+| `generate-mind-map` | 从报告/残片生成思维导图大纲 | 0.3 | 4096 |
+| `compare-recall` | 用户回忆 vs 标准导图语义对比 | 0.2 | 4096 |
+
+## 任务队列设计
+
+- 异步任务模式：submit + poll，避免 LLM 长耗时（10-60s）超时。
+- 单线程 Worker：`setImmediate` 链，同一时刻只处理一个 LLM 调用，防止 API 限流。
+- TTL 清理：5 分钟一次，移除完成超过 1 小时的记录。
+- 异常隔离：单个任务失败不影响后续任务。
+- 管理面板日志：复用 `logStore`，记录最近 200 条请求/响应。
+
+## LLM 配置
+
+```env
+LLM_API_URL=https://api.siliconflow.cn/v1/chat/completions
+LLM_API_KEY=                    # 必填，未配置时 /health 返回 llmAvailable: false
+LLM_MODEL=Qwen/Qwen2.5-32B-Instruct
+LLM_TIMEOUT_MS=60000            # 单次 LLM 调用超时
+PORT=5199
+```
+
+## 降级策略
+
+- LLM API Key 未配置 → `/health` 返回 `llmAvailable: false`。
+- 后端（lpt-be）检测到 AI 不可用 → 自动切换到内置规则引擎（`BuiltinMindMapGenerator`）。
+- Java 后端是唯一调用方；本服务不直接暴露给前端，不做鉴权（部署在内网）。
+
+## 启动命令
+
+```bash
+npm install
+npm run dev        # 开发模式（tsx watch，热重载）
+npm run build      # 编译 TypeScript
+npm run start      # 生产模式
+npm run test       # 测试
+```
+
+## Docker
+
+- 多阶段构建：`node:20-alpine` 编译 → `node:20-alpine` 运行。
+- 暴露端口：5199。
+- 健康检查：`curl http://localhost:5199/health`。
+
+## 关联项目
+
+| 项目 | 路径 | 端口 | 说明 |
+|------|------|------|------|
+| lpt-be | `../lpt-be/` | 5157 | Spring Boot 后端，通过 `lpt.ai-service.url` 调用本服务 |
+| lpt-fe | `../lpt-fe/` | 5158 | Vue 3 前端，不直接调用本服务 |
+
+## 调用关系
+
+```text
+lpt-be (5157) ──HTTP POST /ai/tasks──→ lpt-ai (5199)
+lpt-be (5157) ──HTTP GET  /ai/tasks/:id──→ lpt-ai (5199)
+```
@@ -85,7 +85,7 @@ curl http://localhost:5199/ai/tasks/550e8400-e29b-41d4-a716-446655440000
 | type | 说明 | params 字段 |
 |------|------|------------|
 | `aggregate-report` | 聚合学习残片为报告 | `taskName`, `expectation`, `fragments[]` |
-| `generate-mind-map` | 生成思维导图大纲 | `taskName`, `reports[]`, `fragments[]`, `applications[]` |
+| `generate-mind-map` | 生成思维导图大纲 | `taskName`, `reports[]`, `applications[]` |
 | `compare-recall` | 对比用户回忆与标准导图 | `taskName`, `standardOutline`, `recallOutline` |

 ## 架构位置
@@ -1,131 +0,0 @@
-# Kubernetes Configuration for LPT Project
-
-This directory contains the shared Kubernetes configuration files for the LPT (Learning Progress Tracker) project.
-
-## Files
-
-### ConfigMap
- **`configmap.yaml`** - Shared environment variables for all services
-  - LLM API configuration (URL, model, timeout)
-  - Database connection string
-  - Service URLs
-
-### Secrets (Templates)
- **`lpt-secrets.yaml`** - Application secrets template
-  - LLM API key
-  - MySQL root password
-  - **⚠️ DO NOT commit real secrets!** Use the template to create secrets manually.
-
- **`regcred-secret.yaml`** - Docker registry authentication template
-  - Used for pulling images from private registry (192.168.123.199:5000)
-  - **⚠️ Managed by Gitea Actions workflow** - DO NOT commit real credentials!
-
-### Service-Specific Configurations
-Each service has its own `k8s/` directory with deployment and service configs:
- **`lpt-fe/k8s/`** - Frontend deployment (Nginx + Vue 3)
- **`lpt-be/k8s/`** - Backend deployment (Spring Boot)
- **`lpt-ai/k8s/`** - AI service deployment (Python FastAPI)
-
-## Deployment
-
-### Initial Setup
-
-1. **Create namespace**:
-   ```bash
-   kubectl create namespace lpt-dev
-   ```
-
-2. **Apply shared ConfigMap**:
-   ```bash
-   kubectl apply -f k8s/configmap.yaml
-   ```
-
-3. **Create secrets** (replace with actual values):
-   ```bash
-   # Application secrets
-   kubectl create secret generic lpt-secrets \
-     --from-literal=llm-api-key=<YOUR_LLM_API_KEY> \
-     --from-literal=mysql-root-password=<YOUR_MYSQL_ROOT_PASSWORD> \
-     --namespace=lpt-dev
-
-   # Registry credentials (for manual creation, or use Gitea workflow)
-   kubectl create secret docker-registry regcred \
-     --docker-server=192.168.123.199:5000 \
-     --docker-username=admin \
-     --docker-password=<REGISTRY_PASSWORD> \
-     --namespace=lpt-dev
-   ```
-
-4. **Deploy services**:
-   ```bash
-   # Frontend
-   kubectl apply -f lpt-fe/k8s/
-
-   # Backend
-   kubectl apply -f lpt-be/k8s/
-
-   # AI Service
-   kubectl apply -f lpt-ai/k8s/
-   ```
-
-### CI/CD Workflow
-
-The Gitea Actions workflows (`.gitea/workflows/deploy.yml` in each service) automatically:
-1. Build Docker images
-2. Push to private registry (192.168.123.199:5000)
-3. Create/update `regcred` secret with credentials from Gitea secrets
-4. Update deployment image tags
-
-**Required Gitea Secrets** (per repository):
- `REGISTRY_USERNAME`: Docker registry username (admin)
- `REGISTRY_PASSWORD`: Docker registry password
-
-## Verification
-
-Check deployment status:
-```bash
-kubectl get all -n lpt-dev
-kubectl get configmap -n lpt-dev
-kubectl get secret -n lpt-dev
-```
-
-View logs:
-```bash
-kubectl logs -f deployment/lpt-fe -n lpt-dev
-kubectl logs -f deployment/lpt-be -n lpt-dev
-kubectl logs -f deployment/lpt-ai -n lpt-dev
-```
-
-## Architecture
-
-```
-┌─────────────────┐
-│   lpt-fe:3000   │ (NodePort 30080)
-│   Vue 3 + Nginx │
-└────────┬────────┘
-         │
-         ▼
-┌─────────────────┐
-│   lpt-be:8080   │ (NodePort 30088)
-│   Spring Boot   │
-└────────┬────────┘
-         │
-         ├─────────► MySQL (external)
-         │
-         ▼
-┌─────────────────┐
-│  lpt-ai:5199    │ (ClusterIP)
-│  FastAPI        │
-└─────────────────┘
-         │
-         ▼
-   LLM API (external)
-```
-
-## Notes
-
- **Namespace**: All resources use `lpt-dev` namespace
- **Registry**: Private Docker registry at `192.168.123.199:5000`
- **Image Pull**: All deployments use `imagePullSecrets: [name: regcred]`
- **ConfigMap**: Shared config is mounted as environment variables
- **Secrets**: Sensitive data (API keys, passwords) stored in `lpt-secrets`
@@ -1,15 +0,0 @@
-apiVersion: v1
-kind: ConfigMap
-metadata:
-  name: lpt-config
-  namespace: lpt-dev
-data:
-  # LPT AI Service
-  LLM_API_URL: https://api.siliconflow.cn/v1/chat/completions
-  LLM_MODEL: Qwen/Qwen2.5-32B-Instruct
-  LLM_TIMEOUT_MS: "60000"
-  LPT_AI-SERVICE_URL: http://lpt-ai:5199
-  PORT: "5199"
-
-  # Spring Boot Database
-  SPRING_DATASOURCE_URL: jdbc:mysql://mysql:3306/learning_progress_tracker?allowPublicKeyRetrieval=true&characterEncoding=utf-8&useSSL=false&serverTimezone=GMT%2B8
@@ -1,33 +0,0 @@
-# LPT Application Secrets
-#
-# This file is a TEMPLATE - DO NOT commit real secrets to git!
-#
-# To create this secret:
-# kubectl create secret generic lpt-secrets \
-#   --from-literal=llm-api-key=<YOUR_LLM_API_KEY> \
-#   --from-literal=mysql-root-password=<YOUR_MYSQL_ROOT_PASSWORD> \
-#   --namespace=lpt-dev
-#
-# Or use kubectl apply with stringData:
-# kubectl apply -f - <<EOF
-# apiVersion: v1
-# kind: Secret
-# metadata:
-#   name: lpt-secrets
-#   namespace: lpt-dev
-# type: Opaque
-# stringData:
-#   llm-api-key: "your-actual-api-key"
-#   mysql-root-password: "your-actual-mysql-password"
-# EOF
-
-apiVersion: v1
-kind: Secret
-metadata:
-  name: lpt-secrets
-  namespace: lpt-dev
-type: Opaque
-data:
-  # Base64 encoded values - use stringData for plain text when applying
-  # llm-api-key: <base64-encoded-api-key>
-  # mysql-root-password: <base64-encoded-password>
@@ -1,26 +0,0 @@
-# Docker Registry Secret for pulling images from private registry
-#
-# This file is a TEMPLATE - the actual secret is managed by Gitea Actions workflow
-# and should NOT be committed with real credentials.
-#
-# To create this secret manually:
-# kubectl create secret docker-registry regcred \
-#   --docker-server=192.168.123.199:5000 \
-#   --docker-username=admin \
-#   --docker-password=<REGISTRY_PASSWORD> \
-#   --namespace=lpt-dev
-#
-# Or use the workflow which reads from Gitea secrets:
-# - REGISTRY_USERNAME
-# - REGISTRY_PASSWORD
-
-apiVersion: v1
-kind: Secret
-metadata:
-  name: regcred
-  namespace: lpt-dev
-type: kubernetes.io/dockerconfigjson
-data:
-  # .dockerconfigjson: <base64-encoded-docker-config>
-  # This is generated by the workflow - DO NOT commit real values here
-  .dockerconfigjson: ""
@@ -32,15 +32,14 @@ describe("aggregateReportPrompt", () => {
 });

 describe("generateMindMapPrompt", () => {
-  it("要求输出缩进大纲且包含全部输入", () => {
+  it("要求输出缩进大纲且只包含学习报告", () => {
    const messages = generateMindMapPrompt(
      "Java 并发",
      "并发编程学习",
      ["报告一"],
-      ["残片一", "残片二"],
    );
    expect(messages[0].content).toContain("缩进");
    expect(messages[1].content).toContain("报告一");
-    expect(messages[1].content).toContain("残片二");
+    expect(messages[1].content).not.toContain("学习残片");
  });
 });
@@ -50,20 +50,19 @@ export function aggregateReportPrompt(
 }

 /**
- * 从学习报告和残片生成标准思维导图（预留，用于替代 Java 端 BuiltinMindMapGenerator）。
+ * 从学习报告生成标准思维导图（预留，用于替代 Java 端 BuiltinMindMapGenerator）。
 * 输出为缩进大纲文本，与后端 MindMapTreeTool.parseOutline 格式一致。
 */
 export function generateMindMapPrompt(
  taskName: string,
  taskDescription: string,
  reports: string[],
-  fragments: string[],
 ): ChatMessage[] {
  return [
    {
      role: "system",
      content: [
-        "你是一名知识结构整理助手。请阅读某个学习任务的全部学习报告和残片，",
+        "你是一名知识结构整理助手。请阅读某个学习任务的全部学习报告，",
        "将其中的知识点整理成一份思维导图大纲。要求：",
        "1. 第一行是导图根标题（任务主题）；",
        "2. 之后每行一个节点，用两个空格的缩进表示层级；",
@@ -81,9 +80,6 @@ export function generateMindMapPrompt(
        "",
        "学习报告：",
        ...reports.map((r, i) => `${i + 1}. ${r}`),
-        "",
-        "学习残片：",
-        ...fragments.map((f, i) => `${i + 1}. ${f}`),
      ]
        .filter(Boolean)
        .join("\n"),
@@ -160,12 +160,10 @@ function buildMessages(task: TaskRecord) {
    }
    case "generate-mind-map": {
      const reports = p.reports as string[] | undefined;
-      const fragments = p.fragments as string[] | undefined;
      return generateMindMapPrompt(
        p.taskName as string,
        (p.taskDescription as string) ?? "",
        reports ?? [],
-        fragments ?? [],
      );
    }
    case "compare-recall": {
Author	SHA1	Message	Date
cat-shark	435beaffbb	refactor: 导图生成仅使用学习报告	2026-08-03 23:08:40 +08:00
cat-shark	3f504976ea	fix: 流水线kubeconfig改用临时目录	2026-08-02 10:51:03 +08:00
cat-shark	81dfb4fc3e	docs: 更新提交规范	2026-08-01 00:15:59 +08:00
cat-shark	a71feea4fd	docs: migrate .pi/SYSTEM.md to AGENTS.md	2026-08-01 00:13:08 +08:00
cat-shark	9f620e84f8	chore: remove k8s/ — migrated to lpt-infra	2026-07-26 21:35:51 +08:00
cat-shark	a1cfb045ba	feat: add deployment.yaml and service.yaml for lpt-ai K8s deployment	2026-07-26 20:52:03 +08:00
cat-shark	e106a8bfdc	docs: 补充Git提交规范	2026-07-23 23:03:21 +08:00
cat-shark	e6bcf0db15	docs: add .pi/SYSTEM.md with project overview	2026-07-23 23:01:47 +08:00
cat-sharkandClaude Opus 4.8	943faf0ba9	fix(ci): 限制仅 main 部署并加固 IMAGE_TAG 传递 - lpt-ai 仅 main/master 可部署；dev/prod 靠 environment 区分 namespace - IMAGE_TAG 写 env 文件 + 工作区文件兜底 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>	2026-07-20 22:47:13 +08:00