AI 仓库情报摘要

FR-AI / ANALYSIS

为什么值得关注

它将微调的大语言模型与检索增强生成相结合，能够提供准确且可解释的计划推荐，并在信息缺失时智能地提出追问。

适合谁使用

印度农民
农业推广人员
政府福利顾问
关注人工智能社会效益的开发者

典型使用场景

查询 PM-KISAN、PMFBY、Kisan Credit Card 等计划的资格
根据农民档案获取所需文件清单
交互式浏览政府计划选项
辅助农村数字服务交付

项目优势

使用 QLoRA 对 3B 参数模型进行领域微调
集成 ChromaDB 的 RAG 实现计划信息检索
包含评估流水线，可对比基础 LLM、仅 RAG 以及 RAG+微调的效果
Gradio 聊天界面便于交互和测试

使用前须知

依赖合成训练数据，可能影响真实场景的鲁棒性
仅支持印度政府计划
暂无内置实时计划更新（列为未来改进）
需要技术安装步骤（pip install、Colab），非开发者难以直接使用

README 快速开始

🌾 Krishi Sahayak

AI-Powered Farm Scheme Eligibility Assistant using RAG & Fine-Tuned LLM

Krishi Sahayak is an AI-powered assistant designed to help Indian farmers identify the government agricultural schemes they are eligible for. Instead of relying on static rule-based systems or generic chatbots, the project combines Retrieval-Augmented Generation (RAG) with a QLoRA fine-tuned Qwen2.5-3B language model to provide accurate, explainable, and context-aware recommendations.

The assistant retrieves the latest scheme information from a vector database and reasons over the farmer's profile before generating a response. When essential information is missing, the model intelligently asks follow-up questions instead of making incorrect assumptions.

🚀 Features

🌾 Government scheme eligibility prediction
🤖 Fine-tuned Qwen2.5-3B using QLoRA
📚 Retrieval-Augmented Generation (RAG)
🔍 ChromaDB vector database
🌐 Multilingual sentence embeddings
📄 PDF/knowledge retrieval support
💬 Intelligent clarification questions
📊 Evaluation pipeline
🎯 Gradio-based interactive chatbot
⚡ Google Colab compatible

🛠 Tech Stack

AI & Machine Learning

Python
Hugging Face Transformers
PEFT (QLoRA)
BitsAndBytes
Sentence Transformers

RAG

ChromaDB
Cross Encoder Reranker
Multilingual Embeddings

LLM

Qwen2.5-3B
LoRA Fine-Tuning

Frontend

Gradio

Data

JSON Knowledge Base
Synthetic Instruction Dataset

📂 Project Structure

krishi-sahayak/
│
├── app/
│   └── app.py
│
├── rag/
│   ├── build_index.py
│   └── retriever.py
│
├── finetune/
│   ├── train_qlora.py
│   └── inference.py
│
├── data/
│   ├── schemes.json
│   └── generate_synthetic_data.py
│
├── eval/
│   ├── evaluate.py
│   └── test_profiles.json
│
├── requirements.txt
├── README.md
└── LICENSE

🏗 System Architecture

              Farmer Query
                    │
                    ▼
        ┌────────────────────┐
        │   User Profile      │
        └─────────┬───────────┘
                  │
                  ▼
        ┌────────────────────┐
        │   RAG Retriever     │
        │ (Chroma + Embedding)│
        └─────────┬───────────┘
                  │
          Relevant Documents
                  │
                  ▼
      ┌────────────────────────┐
      │ Fine-Tuned Qwen2.5-3B   │
      │

项目描述

Krishi Sahayak is an AI-powered agricultural assistant that combines RAG (Retrieval-Augmented Generation) and QLoRA fine-tuned Qwen2.5-3B to help Indian farmers determine eligibility for government schemes using multilingual embeddings, ChromaDB, and intelligent reasoning.

krishi-sahayak