jstamagal · Copilot · Apr 5, 2026 · Apr 5, 2026
diff --git a/index.html b/index.html
@@ -294,6 +294,8 @@
   'ai-trending-en':  'GitHub AI Trends',
   'ai-hn':           'HN 社区动态',
   'ai-hn-en':        'HN Community Digest',
+  'ai-landscape':    'AI 生态全景图',
+  'ai-landscape-en': 'AI Ecosystem Landscape',
 };
 
 // ── Theme ──

diff --git a/src/generate-manifest.ts b/src/generate-manifest.ts
@@ -22,6 +22,8 @@ const REPORT_FILES = [
   "ai-weekly-en",
   "ai-monthly",
   "ai-monthly-en",
+  "ai-landscape",
+  "ai-landscape-en",
 ] as const;
 const MAX_FEED_ITEMS = 30;
 

diff --git a/src/github.ts b/src/github.ts
@@ -203,6 +203,8 @@ const LABEL_COLORS: Record<string, string> = {
   "web-en": "6366f1",
   "trending-en": "fbbf24",
   "hn-en": "fb923c",
+  landscape: "0ea5e9",
+  "landscape-en": "38bdf8",
 };
 
 /**

diff --git a/src/i18n.ts b/src/i18n.ts
@@ -86,12 +86,25 @@ export const MONTHLY_REPORT = {
   issueTitle: (monthStr: string) => `📆 AI 工具生态月报 ${monthStr}`,
 } as const;
 
+export const LANDSCAPE_REPORT = {
+  title: t("AI 生态全景图", "AI Ecosystem Landscape"),
+  sources: t(
+    "数据来源: GitHub Trending + GitHub Search API",
+    "Sources: GitHub Trending + GitHub Search API",
+  ),
+  issueTitle: (dateStr: string, lang: Lang) =>
+    lang === "en"
+      ? `🗺️ AI Ecosystem Landscape ${dateStr}`
+      : `🗺️ AI 生态全景图 ${dateStr}`,
+} as const;
+
 export const ISSUE_LABELS = {
   cli: t("digest", "digest-en"),
   openclaw: t("openclaw", "openclaw-en"),
   web: t("web", "web-en"),
   trending: t("trending", "trending-en"),
   hn: t("hn", "hn-en"),
+  landscape: t("landscape", "landscape-en"),
 } as const;
 
 export const CLI_ISSUE_TITLE = (dateStr: string, lang: Lang) =>
@@ -131,6 +144,8 @@ export const REPORT_LABELS: Record<string, string> = {
   "ai-weekly-en": "AI Tools Weekly Digest",
   "ai-monthly": "AI 工具生态月报",
   "ai-monthly-en": "AI Tools Monthly Digest",
+  "ai-landscape": "AI 生态全景图",
+  "ai-landscape-en": "AI Ecosystem Landscape",
 };
 
 export const NOTIFY_LABELS: Record<string, Record<Lang, string>> = {
@@ -141,4 +156,5 @@ export const NOTIFY_LABELS: Record<string, Record<Lang, string>> = {
   "ai-hn": t("HN 社区动态", "HN Community"),
   "ai-weekly": t("AI 工具生态周报", "AI Tools Weekly"),
   "ai-monthly": t("AI 工具生态月报", "AI Tools Monthly"),
+  "ai-landscape": t("AI 生态全景图", "AI Ecosystem Landscape"),
 };
diff --git a/src/index.ts b/src/index.ts
@@ -30,7 +30,7 @@ import {
 import { buildTrendingPrompt, buildHighlightsPrompt, type ReportHighlights } from "./prompts-data.ts";
 import { callLlm, saveFile, autoGenFooter, LLM_TOKENS_TRENDING } from "./report.ts";
 import { buildCliReportContent, buildOpenclawReportContent } from "./report-builders.ts";
-import { saveWebReport, saveTrendingReport, saveHnReport } from "./report-savers.ts";
+import { saveWebReport, saveTrendingReport, saveHnReport, saveLandscapeReport } from "./report-savers.ts";
 import { loadWebState, fetchSiteContent, type WebFetchResult, type WebState } from "./web.ts";
 import { fetchTrendingData, type TrendingData } from "./trending.ts";
 import { fetchHnData, type HnData } from "./hn.ts";
@@ -341,6 +341,8 @@ async function main(): Promise<void> {
     ),
     saveHnReport(hnData, utcStr, dateStr, digestRepo, autoGenFooter("zh"), "zh"),
     saveHnReport(hnData, utcStr, dateStr, digestRepo, autoGenFooter("en"), "en"),
+    saveLandscapeReport(trendingData, utcStr, dateStr, digestRepo, autoGenFooter("zh"), "zh"),
+    saveLandscapeReport(trendingData, utcStr, dateStr, digestRepo, autoGenFooter("en"), "en"),
   ]);
 
   // 5. Generate highlights for Telegram notification
@@ -355,6 +357,7 @@ async function main(): Promise<void> {
     ["ai-trending", "ai-trending.md", "ai-trending-en.md"],
     ["ai-web", "ai-web.md", "ai-web-en.md"],
     ["ai-hn", "ai-hn.md", "ai-hn-en.md"],
+    ["ai-landscape", "ai-landscape.md", "ai-landscape-en.md"],
   ] as const) {
     const zh = readReport(zhFile);
     const en = readReport(enFile);

diff --git a/src/prompts-data.ts b/src/prompts-data.ts
@@ -509,3 +509,148 @@ ${storiesText}
 语言要求：中文，简洁专业，保留所有原文链接。
 `;
 }
+
+export function buildLandscapePrompt(data: TrendingData, dateStr: string, lang: Lang = "zh"): string {
+  const trendingSection =
+    data.trendingFetchSuccess && data.trendingRepos.length > 0
+      ? data.trendingRepos
+          .map(
+            (r) =>
+              `- [${r.fullName}](${r.url})` +
+              (r.language ? ` [${r.language}]` : "") +
+              ` ⭐${r.totalStars.toLocaleString()}` +
+              (r.todayStars > 0 ? ` (+${r.todayStars} today)` : "") +
+              (r.forks > 0 ? ` 🍴${r.forks.toLocaleString()}` : "") +
+              (r.description ? `\n  ${r.description}` : ""),
+          )
+          .join("\n")
+      : lang === "en"
+        ? "(Unable to fetch today's GitHub Trending list)"
+        : "（未能抓取今日 GitHub Trending 榜单）";
+
+  const searchSection =
+    data.searchRepos.length > 0
+      ? data.searchRepos
+          .map(
+            (r) =>
+              `- [${r.fullName}](${r.url})` +
+              (r.language ? ` [${r.language}]` : "") +
+              ` ⭐${r.stargazersCount.toLocaleString()}` +
+              ` [topic:${r.searchQuery}]` +
+              (r.description ? `\n  ${r.description}` : ""),
+          )
+          .join("\n")
+      : lang === "en"
+        ? "(No search results)"
+        : "（无搜索结果）";
+
+  if (lang === "en") {
+    return `You are a senior AI ecosystem analyst. The following is ${dateStr} GitHub AI-related data covering both trending repositories and topic-tagged projects. Your task is to synthesize ALL signals into a single coherent "wide view" of the AI open-source landscape.
+
+## Data Sources
+- **Trending List** (github.com/trending): Today's hottest repositories by new stars
+- **Topic Search** (GitHub Search API): AI-tagged projects active in last 7 days
+
+---
+
+## GitHub Today's Trending (${data.trendingRepos.length} repositories)
+${trendingSection}
+
+---
+
+## AI Topic Search Results (${data.searchRepos.length} repositories)
+${searchSection}
+
+---
+
+Generate a comprehensive **AI Ecosystem Landscape Report** in English with the following sections:
+
+### 1. The Wide View — One-Paragraph Executive Summary
+Write a single dense paragraph (150-200 words) that captures the full AI open-source ecosystem as of today. What is the overarching narrative? What is the community collectively building toward?
+
+### 2. The Ecosystem Stack
+Show the AI ecosystem as a layered architecture. For each layer, list the top 3-5 representative projects from today's data (with GitHub links and star counts):
+
+| Layer | Purpose | Key Projects |
+|-------|---------|--------------|
+| 🏗️ **Foundation** | Models, training, fine-tuning | ... |
+| ⚙️ **Infrastructure** | Inference, orchestration, data pipelines | ... |
+| 🔌 **Integration** | RAG, vector DBs, knowledge retrieval | ... |
+| 🤖 **Agency** | Agent frameworks, workflow automation | ... |
+| 📦 **Applications** | End-user products, vertical solutions | ... |
+
+### 3. Signal Matrix — All ${data.trendingRepos.length + data.searchRepos.length} Signals at a Glance
+For every AI-relevant project in the dataset, create a compact table:
+
+| Project | Stars | Today | Category | Key Capability |
+|---------|-------|-------|----------|----------------|
+(include all relevant AI projects, one row each)
+
+### 4. Cross-Category Dependencies
+Identify and explain 3-5 meaningful dependency or synergy relationships between projects from different layers. Format as:
+- **[Project A]** enables **[Project B]**: one sentence explaining how
+
+### 5. Momentum Map
+Rank the top 10 projects by today's momentum (new stars + community signal), regardless of category. Include a brief note on what's driving each project's traction today.
+
+### 6. Gaps & Emerging Directions
+Based on what's trending, identify 2-3 capability gaps or emerging directions that the community is beginning to address but no dominant solution has emerged yet.
+
+Style: English, highly structured, must include GitHub links for all projects. Prioritize breadth — this is the "wide view" that shows everything together.
+`;
+  }
+
+  return `你是一位 AI 生态系统高级分析师。以下是 ${dateStr} 的 GitHub AI 相关数据，涵盖热门仓库和主题标签项目。你的任务是将所有信号综合成一份 AI 开源生态的"全景视图"。
+
+## 数据说明
+- **Trending 榜单**（github.com/trending）：今日新增 stars 最多的热门仓库
+- **主题搜索**（GitHub Search API）：7 天内活跃的 AI 标签项目
+
+---
+
+## GitHub 今日 Trending 榜单（共 ${data.trendingRepos.length} 个仓库）
+${trendingSection}
+
+---
+
+## AI 主题搜索结果（共 ${data.searchRepos.length} 个仓库）
+${searchSection}
+
+---
+
+请生成一份完整的《AI 开源生态全景图》，包含以下部分：
+
+### 1. 全景速览 — 一段式执行摘要
+用一段话（150~200 字）描述今日 AI 开源生态的全貌。整体叙事是什么？社区正在共同构建什么？
+
+### 2. 生态技术栈
+将 AI 生态展示为分层架构。对于每一层，从今日数据中列出 3~5 个代表项目（附 GitHub 链接和 star 数）：
+
+| 层次 | 用途 | 代表项目 |
+|------|------|---------|
+| 🏗️ **基础层** | 模型、训练、微调 | ... |
+| ⚙️ **基础设施层** | 推理、编排、数据管道 | ... |
+| 🔌 **集成层** | RAG、向量数据库、知识检索 | ... |
+| 🤖 **智能体层** | Agent 框架、工作流自动化 | ... |
+| 📦 **应用层** | 最终用户产品、垂直解决方案 | ... |
+
+### 3. 信号矩阵 — 所有 ${data.trendingRepos.length + data.searchRepos.length} 个信号一览
+对数据集中每个 AI 相关项目，生成一张精简表格：
+
+| 项目 | Stars | 今日新增 | 分类 | 核心能力 |
+|------|-------|---------|------|---------|
+（包含所有相关 AI 项目，每个一行）
+
+### 4. 跨层依赖关系
+识别并解释不同层次之间 3~5 个有意义的依赖或协同关系。格式：
+- **[项目 A]** 赋能 **[项目 B]**：一句话说明如何关联
+
+### 5. 势能地图
+不论分类，按今日势能（今日新增 stars + 社区信号）对 Top 10 项目排名，并简短说明每个项目今日获得关注的原因。
+
+### 6. 空白与新兴方向
+基于趋势，识别 2~3 个社区开始关注但尚未出现主导解决方案的能力空白或新兴方向。
+
+语言要求：中文，高度结构化，所有项目必须附 GitHub 链接。注重广度——这是展示全貌的"全景视图"。
+`;
+}
diff --git a/src/report-savers.ts b/src/report-savers.ts
@@ -3,9 +3,9 @@
  * Extracted from index.ts for separation of concerns.
  */
 
-import { type Lang, WEB_REPORT, TRENDING_REPORT, HN_REPORT, ISSUE_LABELS } from "./i18n.ts";
-import { buildWebReportPrompt, buildHnPrompt } from "./prompts-data.ts";
-import { callLlm, saveFile, LLM_TOKENS_WEB } from "./report.ts";
+import { type Lang, WEB_REPORT, TRENDING_REPORT, HN_REPORT, LANDSCAPE_REPORT, ISSUE_LABELS } from "./i18n.ts";
+import { buildWebReportPrompt, buildHnPrompt, buildLandscapePrompt } from "./prompts-data.ts";
+import { callLlm, saveFile, LLM_TOKENS_WEB, LLM_TOKENS_TRENDING } from "./report.ts";
 import { createGitHubIssue } from "./github.ts";
 import { saveWebState, type WebFetchResult, type WebState } from "./web.ts";
 import type { HnData } from "./hn.ts";
@@ -157,3 +157,44 @@ export async function saveHnReport(
     console.error(`  [hn/${lang}] Report generation failed: ${err}`);
   }
 }
+
+// ---------------------------------------------------------------------------
+// Landscape (wide view) report
+// ---------------------------------------------------------------------------
+
+export async function saveLandscapeReport(
+  trendingData: TrendingData,
+  utcStr: string,
+  dateStr: string,
+  digestRepo: string,
+  footer: string,
+  lang: Lang = "zh",
+): Promise<void> {
+  const hasData = trendingData.trendingRepos.length > 0 || trendingData.searchRepos.length > 0;
+  if (!hasData) {
+    console.log(`  [landscape/${lang}] No data available, skipping report.`);
+    return;
+  }
+
+  console.log(`  [landscape/${lang}] Calling LLM for landscape report...`);
+  try {
+    const landscapeSummary = await callLlm(buildLandscapePrompt(trendingData, dateStr, lang), LLM_TOKENS_TRENDING);
+    const fileName = lang === "en" ? "ai-landscape-en.md" : "ai-landscape.md";
+    const header =
+      `# ${LANDSCAPE_REPORT.title[lang]} ${dateStr}\n\n` +
+      `> ${LANDSCAPE_REPORT.sources[lang]} | ${lang === "en" ? "Generated" : "生成时间"}: ${utcStr} UTC\n\n---\n\n`;
+
+    const landscapeContent = header + landscapeSummary + footer;
+
+    console.log(`  Saved ${saveFile(landscapeContent, dateStr, fileName)}`);
+
+    if (digestRepo) {
+      const landscapeTitle = LANDSCAPE_REPORT.issueTitle(dateStr, lang);
+      const landscapeLabel = ISSUE_LABELS.landscape[lang];
+      const landscapeUrl = await createGitHubIssue(landscapeTitle, landscapeContent, landscapeLabel);
+      console.log(`  Created landscape issue (${lang}): ${landscapeUrl}`);
+    }
+  } catch (err) {
+    console.error(`  [landscape/${lang}] Report generation failed: ${err}`);
+  }
+}