化学分子智能对话与可视化系统 — 面向中小学生的化学学习助手
Project description
ChemChat — 化学分子智能对话与可视化系统
面向中小学生的化学学习助手,支持分子2D/3D可视化、LLM智能对话、化学实体自动识别。
安装
pip install chemchat
可选依赖
# RDKit 分子处理(推荐,支持更精确的2D/3D结构生成)
conda install rdkit
# 或
pip install rdkit-pypi
# PySide6 WebEngine(3D分子查看器需要)
pip install PySide6-WebEngine
使用
启动 GUI
chemchat
或在 Python 中:
from chemchat.__main__ import main
main()
Python API
from chemchat.engine.mol_parser import MoleculeParser
from chemchat.engine.entity_extractor import EntityExtractor
from chemchat.engine.element_data import ELEMENTS, format_element_info, get_element
from chemchat.db.knowledge_base import init_db, search_molecules
# 初始化知识库
init_db()
# 分子解析
parser = MoleculeParser()
result = parser.parse("H2O")
print(result["formula"]) # H2O
print(result["elements"]) # ['O', 'H', 'H']
# 实体提取
ext = EntityExtractor()
entities = ext.extract("苯和乙醇是常见溶剂")
# [(苯, c1ccccc1, 0, 1), (乙醇, CCO, 2, 4)]
# 元素信息
info = format_element_info("Fe")
# <b>铁 (Fe)</b> <i>Iron</i><br>原子序数: 26...
功能特性
- 分子可视化:2D/3D切换,支持球棒模型、空间填充等多种显示风格
- 智能对话:集成 Ollama LLM,自动识别对话中的化学物质并可视化
- 实体提取:自动识别中文化学名、化学式、SMILES等
- 知识库:内置57+种常见化学物质的详细数据
- 元素信息:46种常见元素的完整周期表数据,点击原子即时查看
- 数据库管理:支持CRUD、JSON/CSV导入导出
技术栈
- PySide6 + WebEngine (3D分子渲染)
- RDKit (分子结构解析)
- 3Dmol.js (3D可视化)
- Ollama (LLM对话)
- SQLite (知识库)
License
MIT
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