# AI Agents in Chemical Research: GVIM - An Intelligent Research Assistant System ๐งช๐ค
[English](README.md) | [็ฎไฝไธญๆ](README_zh.md)
[](https://pubs.rsc.org/en/content/articlelanding/2025/dd/d4dd00398e)
[](https://huggingface.co/datasets/KANGYONGMA/GVIM)
[](https://www.youtube.com/watch?v=1eMwus98BB8)
[](https://www.youtube.com/watch?v=fb8hdho_89s&t=128s)
An intelligent research assistant system designed specifically for chemical science, featuring fine-tuned language models and specialized chemistry capabilities.
## ๐ Highlights
### ๐งฌ Core Features
- Fine-tuned LLMs for chemistry
- Molecular visualization
- Literature retrieval & analysis
- Multimodal capabilities
|
### ๐ Key Benefits
- Specialized for chemical research
- Continuous learning ability
- Free GPU resources on Colab
- Comprehensive documentation
|
## ๐ Model Overview
GVIM combines several cutting-edge technologies:
### ๐ฌ Technical Features
- **Fine-tuned Models**: Trained on curated chemistry instruction data
- **Chemistry Tools**: Molecular visualization and SMILES processing
- **Smart Retrieval**: Advanced chemical literature search and analysis
- **Multimodal Support**: Formula recognition and image analysis
- **Knowledge Base**: Local document processing and continuous learning
### ๐ฏ Main Applications
1. Chemical research assistance and analysis
2. Molecular structure visualization
3. Literature review and knowledge extraction
4. Handwritten formula recognition
5. Document-based knowledge processing
## ๐ป Quick Start
### Requirements
```bash
# Create conda environment
conda create -n gvim python=3.9.19
conda activate gvim
# Install dependencies
pip install -r requirements.txt
```
### API Configuration โ๏ธ
Required API keys:
```python
TAVILY_API_KEY="your_key_here"
REPLICATE_API_TOKEN="your_token_here"
Groq_API_KEY="your_key_here"
```
### Launch ๐
```bash
python app.py
```
## ๐ฅ Key Features Showcase
๐ธ Click to view feature demonstrations
### 1. Nature Chemistry Search Interface

### 2. Multimodal Chemical Recognition

### 3. Local Document Analysis

## ๐ Free GPU Resources
Access GVIM's capabilities using Colab's free GPU resources:
[](https://youtu.be/QGwVVdinJPU)
## ๐ Citation
```bibtex
@article{Digital Discovery,
author = {Kangyong Ma},
affiliation = {College of Physics and Electronic Information Engineering, Zhejiang Normal University},
address = {Jinhua City, 321000, China},
doi = {10.1039/D4DD00398E},
email = {kangyongma@outlook.com, kangyongma@gmail.com}
}
```
## ๐ Contact
### ๐ง Email
- kangyongma@outlook.com
- kangyongma@gmail.com
|
### ๐ข Institution
College of Physics and Electronic Information Engineering
Zhejiang Normal University
Jinhua City, 321000, China
|
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