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ai-agent

AgriMa: Unlock Chinese Open-Source AI for Modern Agriculture

Leverage the first Chinese open-source agricultural large model to boost crop analytics and decision‑making. Ideal for founders building ag‑tech solutions.

From the repo · “首个中文开源农业大模型”

187 stars+1★ this week29 forksPythonGuide quality 9/10 · reviewed Oct 11Updated 3/19/2026100% free · open source
What it does

AgriMa is an open-source, Chinese-language agricultural large model that can be used for tasks such as crop yield prediction, agricultural text classification, and farming knowledge graph construction.

When to use it
  • •You need to analyze large amounts of Chinese agricultural data
  • •You want to build a farming-related chatbot or virtual assistant
  • •You need to predict crop yields or detect diseases in plants using machine learning
Ready-to-paste prompt
Run `python inference.py --input "一股本水股料"` to classify a piece of agricultural text
Heads up: Make sure you have the correct version of Python (>=3.8) and the required libraries installed, as specified in the `requirements.txt` file
Saves to your device
Use with Claude
New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

🛠️ Technical setup

Expect 20–40 minutes in a terminal — or let your AI agent drive it.

Try it instantly — no install
Claude Code
mkdir -p ~/.claude/skills/agrima && curl -fsSL https://workflowstacks.com/api/skills/agrima/claude-skill -o ~/.claude/skills/agrima/SKILL.md
Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)
claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

How AgriMa: Unlock Chinese Open-Source AI for Modern Agriculture works
Codeflow
Free to inspect

AgriMa: Unlock Chinese Open-Source AI for Modern Agriculture is a medium Python project (~8.8k lines across 88 code files, plus 6 test files). Expect some technical setup — comfortable with a terminal, or ask a developer. Last commit 7 months ago, no license file, has a test suite.

Size
Medium codebase
~8.8k lines · 88 code files · ~1 h to skim
Setup
Some technical setup
Comfortable with a terminal? 20–40 min. Otherwise ask a dev.
Runs on
Python
No API keys detected
Python 100%
Where to start reading
  1. 1
    README.md
    Start here — what it does and how to install it
  2. 2
    requirements.txt
    Dependencies and the commands it exposes
  3. 3
    src/llmtuner/__init__.py
    Inside src/ — the main logic begins here
What's in each folder
src/Core code — the actual logic82 files
evaluation/Folder9 files
cache/Folder1 files
data/Data files1 files
pics/Folder1 files
tests/Tests — proof it works6 files
READMEHas testsThin docsNo CINo licenseLast update 7 mo ago
Quick Actions
Details
Creator
zhiweihu1103
Language
Python
Category
ai-agent
Published
1/15/2024

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Featured on WorkflowStacks
[![Featured on WorkflowStacks](https://workflowstacks.com/api/badge/agrima.svg)](https://workflowstacks.com/skills/agrima?utm_source=github&utm_medium=badge)
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