[PR #224] docs: add EasyGS integration guide

## 📋 Pull Request Information **Original PR:** https://github.com/deepseek-ai/awesome-deepseek-agent/pull/224 **Author:** [@lukegood](https://github.com/lukegood) **Created:** 6/16/2026 **Status:** 🔄 Open **Base:** `main` ← **Head:** `easygs` --- ### 📝 Commits (1) - [`cc58fc7`](https://github.com/deepseek-ai/awesome-deepseek-agent/commit/cc58fc7e36d8693fdee6ef536cfefa68dc2e414a) add EasyGS integration guide ### 📊 Changes **8 files changed** (+290 additions, -0 deletions) <details> <summary>View changed files</summary> 📝 `README.md` (+1 -0) 📝 `README.zh-CN.md` (+1 -0) ➕ `docs/assets/easygs_correlation_result.png` (+0 -0) ➕ `docs/assets/easygs_gwas_result.jpg` (+0 -0) ➕ `docs/assets/easygs_ui.png` (+0 -0) ➕ `docs/assets/easygs_ui_zh.png` (+0 -0) ➕ `docs/easygs.md` (+144 -0) ➕ `docs/easygs.zh-CN.md` (+144 -0) </details> ### 📄 Description ## What this PR adds This PR adds EasyGS to the DeepSeek agent guide collection with both English and Simplified Chinese documentation. **EasyGS** is designed to help bioinformatics researchers without a computer science background experience the power of large language models in practical research. It provides a natural-language-driven AI Agent for crop genomic selection analysis, enabling curated GS bioinformatics workflows through DeepSeek V4 via an OpenAI-compatible provider interface, with support for Web UI, CLI, and messaging-channel workflows. - **Repository**: https://github.com/lukegood/EasyGS - **License**: MIT --- ## Files changed | File | Change | |---|---| | `docs/easygs.md` | English integration guide for EasyGS | | `docs/easygs.zh-CN.md` | Simplified Chinese integration guide for EasyGS | | `docs/assets/easygs_ui.png` | Web UI screenshot | | `docs/assets/easygs_ui_zh.png` | Chinese Web UI screenshot | | `docs/assets/easygs_gwas_result.jpg` | GS/GWAS output example | | `docs/assets/easygs_correlation_result.png` | Correlation-analysis output example | | `README.md` | Added EasyGS to the tools table | | `README.zh-CN.md` | Added the corresponding Chinese table entry | ## EasyGS highlights **39 validated GS analysis tools** - EasyGS includes 39 manually reviewed and validated GS analysis tools, covering data quality control, population structure, genetic parameter estimation, genomic prediction, environmental interaction, GWAS, and functional annotation. **Conversation-first analysis workflow** - Users can submit VCF, phenotype, environmental-factor, and gene-annotation analysis tasks in natural language instead of writing scripts by hand. Help users without computational backgrounds use AI Agents. **Background execution** - Long-running GS workflows can continue in the background, making the tool more suitable for real analysis jobs that may take time. **Traceable analysis process** - EasyGS keeps workflow progress, intermediate outputs, and final results visible so users can review and reproduce the analysis path. **Multiple access modes** - EasyGS supports Web UI, command line, Telegram, Feishu, and other messaging-channel usage, making it accessible from different research environments. **DeepSeek V4-ready configuration** - The guide shows verified EasyGS configuration for `deepseek-v4-pro`, `maxTokens: 384000`, and `reasoningEffort: "max"`. --- I’m happy to update the guide if any wording or configuration detail needs to be ajusted. Thanks for reviewing this PR. ## Checklist ### Agent Configuration - [x] Model names are current (v4-pro / v4-flash, not v3 names) - [x] 1M context is configured or mentioned - [x] Max thinking effort level is supported - [x] Pricing is current (input, output, cache hit), verified against [DeepSeek API Docs](https://api-docs.deepseek.com/quick_start/pricing) - [x] Config fields are verified to work in the agent - [x] No workarounds for already-fixed upstream bugs ### Documentation - [x] Both English and Chinese versions included in a single PR - [x] README table entry inserted in alphabetical order - [x] One tool per PR; unrelated tools not combined - [x] Images placed in `docs/assets/` with descriptive filenames and reasonable sizes --- <sub>🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.</sub>

bsakaguchi commented

2026-10-26 09:47:29 +00:00

Owner

📋 Pull Request Information

Original PR: https://github.com/deepseek-ai/awesome-deepseek-agent/pull/224
Author: @lukegood
Created: 6/16/2026
Status: 🔄 Open

Base: main ← Head: easygs

📝 Commits (1)

cc58fc7 add EasyGS integration guide

📊 Changes

8 files changed (+290 additions, -0 deletions)

View changed files

📝 README.md (+1 -0)
📝 README.zh-CN.md (+1 -0)
➕ docs/assets/easygs_correlation_result.png (+0 -0)
➕ docs/assets/easygs_gwas_result.jpg (+0 -0)
➕ docs/assets/easygs_ui.png (+0 -0)
➕ docs/assets/easygs_ui_zh.png (+0 -0)
➕ docs/easygs.md (+144 -0)
➕ docs/easygs.zh-CN.md (+144 -0)

📄 Description

What this PR adds

This PR adds EasyGS to the DeepSeek agent guide collection with both English and Simplified Chinese documentation.

EasyGS is designed to help bioinformatics researchers without a computer science background experience the power of large language models in practical research. It provides a natural-language-driven AI Agent for crop genomic selection analysis, enabling curated GS bioinformatics workflows through DeepSeek V4 via an OpenAI-compatible provider interface, with support for Web UI, CLI, and messaging-channel workflows.

Repository: https://github.com/lukegood/EasyGS
License: MIT

Files changed

File	Change
`docs/easygs.md`	English integration guide for EasyGS
`docs/easygs.zh-CN.md`	Simplified Chinese integration guide for EasyGS
`docs/assets/easygs_ui.png`	Web UI screenshot
`docs/assets/easygs_ui_zh.png`	Chinese Web UI screenshot
`docs/assets/easygs_gwas_result.jpg`	GS/GWAS output example
`docs/assets/easygs_correlation_result.png`	Correlation-analysis output example
`README.md`	Added EasyGS to the tools table
`README.zh-CN.md`	Added the corresponding Chinese table entry

EasyGS highlights

39 validated GS analysis tools - EasyGS includes 39 manually reviewed and validated GS analysis tools, covering data quality control, population structure, genetic parameter estimation, genomic prediction, environmental interaction, GWAS, and functional annotation.

Conversation-first analysis workflow - Users can submit VCF, phenotype, environmental-factor, and gene-annotation analysis tasks in natural language instead of writing scripts by hand. Help users without computational backgrounds use AI Agents.

Background execution - Long-running GS workflows can continue in the background, making the tool more suitable for real analysis jobs that may take time.

Traceable analysis process - EasyGS keeps workflow progress, intermediate outputs, and final results visible so users can review and reproduce the analysis path.

Multiple access modes - EasyGS supports Web UI, command line, Telegram, Feishu, and other messaging-channel usage, making it accessible from different research environments.

DeepSeek V4-ready configuration - The guide shows verified EasyGS configuration for deepseek-v4-pro, maxTokens: 384000, and reasoningEffort: "max".

I’m happy to update the guide if any wording or configuration detail needs to be ajusted. Thanks for reviewing this PR.

Checklist

Agent Configuration

Model names are current (v4-pro / v4-flash, not v3 names)
1M context is configured or mentioned
Max thinking effort level is supported
Pricing is current (input, output, cache hit), verified against DeepSeek API Docs
Config fields are verified to work in the agent
No workarounds for already-fixed upstream bugs