landscape-search

name	landscape-search
description	Search the AI Native Landscape for open-source AI projects by natural language description. Find tools, frameworks, agents, runtimes, and infrastructure for AI native systems.

AI Native Landscape Search

Search 600+ curated open-source AI projects by natural language description. Find the right tool, framework, agent runtime, or infrastructure component for your AI native stack.

When to Use

• User asks to find open-source AI projects, tools, or frameworks
• User describes a need like "vector database for RAG", "AI agent framework", "LLM inference engine"
• User wants to explore what's available in a specific AI domain
• User says "find project", "search landscape", "recommend a tool", "找项目", "搜索全景图"
• User wants alternatives to a commercial AI tool

Steps

Step 1: Understand the User's Need

Parse the user's description to extract:

• Core need: What problem are they solving? (e.g., "vector search", "model serving", "agent orchestration")
• Keywords: Technical terms, product names, or domain concepts
• Filters: Language, license preference, category hints
• Language preference: Does the user write in Chinese (zh) or English (en)?

Step 2: Fetch Project Data

Fetch the project catalog:

curl -s https://landscape.jimmysong.io/data/projects.json

This returns a JSON array of 600+ projects. Each project has:

Field	Type	Description
name	string	Project display name
slug	string	URL-safe identifier
description	object	{zh: string, en: string} bilingual descriptions
repo	string	GitHub repository URL
homepage	string | null	Project website
license	string	SPDX license identifier
category	string	Main category key
subCategory	string	Sub-category key
tags	string[]	Topic tags
author	string	Maintainer org
ossDate	string	Open source date
status	string	tracked / incubating / graduated / archived
score	object	Health scores (activity, community, quality, sustainability)
content	object	{zh: string, en: string} detailed markdown descriptions

Step 3: Search and Rank

For each project, compute a relevance score by matching the user's keywords against these fields (in priority order):

1. Tags (weight 3.0) — exact or partial tag match is the strongest signal
2. Name (weight 2.5) — project name contains keywords
3. Category / SubCategory (weight 2.0) — domain match
4. Description (weight 1.5) — en and zh description text
5. Author (weight 0.5) — org name match

Matching rules:

• Split the user's query into individual words/terms
• Case-insensitive matching
• Each matching term contributes its field's weight to the project's total score
• Terms that match multiple fields get additive scores

Category keys for filtering:

Key	Domain
agents	Agent Systems (frameworks, orchestration, MCP, coding agents)
rag-knowledge	Knowledge & Context (vector DBs, retrieval, knowledge graphs)
models-modalities	Models & Modalities (LLMs, embedding, multimodal)
inference-serving	Inference & Serving (runtimes, gateways, model serving)
training-optimization	Training & Optimization (frameworks, fine-tuning, eval)
coding-devtools	Developer Tooling (SDKs, CLI, IDE tools)
applications-products	Applications & Products (chatbots, productivity)
platform-infra	Platform & Infrastructure (data platforms, cloud native)

Step 4: Present Results

Return the top 5-10 matches sorted by relevance score. For each match, display:

Format (English query):

### [Project Name](detail-page-url)
**Description:** One-line description from the project
**Repo:** github-url | **License:** license-id | **Category:** Category > SubCategory
**Tags:** tag1, tag2, tag3
**Status:** tracked/graduated/incubating

Format (Chinese query):

### [Project Name](detail-page-url)
**描述：** 中文描述
**仓库：** github-url | **许可证：** license-id | **分类：** 分类 > 子分类
**标签：** tag1, tag2, tag3
**状态：** tracked/graduated/incubating

Detail page URL format:

• English: https://landscape.jimmysong.io/projects/{slug}
• Chinese: https://landscape.jimmysong.io/zh/projects/{slug}

Step 5: Deep Dive (Optional)

If the user asks for more details on a specific project, show:

• Full description (zh and en)
• All tags
• Score breakdown (activity, community, quality, sustainability)
• Direct GitHub link
• Homepage link

Examples

Example 1 — English query:

User: "I need an open-source vector database for my RAG pipeline"

Search for projects with keywords: "vector database", "RAG", "retrieval", "embedding" Likely matches: projects in rag-knowledge category with tags like "vector db", "RAG", "retrieval"

Example 2 — Chinese query:

User: "帮我找一个开源的 AI Agent 框架"

Search for projects with keywords: "AI Agent", "框架", "agent framework", "orchestration" Likely matches: projects in agents category with tags like "agent framework", "multi-agent"

Example 3 — Specific need:

User: "What's a good open-source alternative to Vercel AI SDK?"

Search for projects with keywords: "SDK", "AI", "framework", matching tags like "SDK" Filter by coding-devtools category

Important Notes

• Always use the live API URL: https://landscape.jimmysong.io/data/projects.json
• The data is updated regularly — always fetch fresh data
• Respect bilingual content — show Chinese descriptions for Chinese queries, English for English queries
• If no results match, broaden the search terms or suggest browsing by category at https://landscape.jimmysong.io
• Never hallucinate projects — only recommend projects that exist in the fetched data
• Link to the landscape detail page so the user can explore further