💻 programming

llm-graph-builder

Neo4j application for building knowledge graph

#Large language model
#Knowledge graph
#data conversion
#Neo4j
#Langchain
llm-graph-builder

Product Details

llm-graph-builder is an application that uses large language models (such as OpenAI, Gemini, etc.) to extract nodes, relationships and their attributes from unstructured data (PDF, DOCS, TXT, YouTube videos, web pages, etc.), and uses the Langchain framework to create a structured knowledge graph. It supports uploading files from local machines, GCS or S3 buckets, or network resources, selecting LLM models and generating knowledge graphs.

Main Features

1
知识图谱创建:使用LLMs将非结构化数据转换为结构化知识图谱。
2
提供模式:自定义模式或使用设置中的现有模式生成图。
3
查看图谱:在Bloom中查看特定来源或多个来源的图谱。
4
与数据对话:通过对话式查询与Neo4j数据库中的数据进行交互,也可以检索有关查询响应来源的元数据。
5
本地部署:通过docker-compose运行,支持OpenAI和Diffbot。
6
云部署:支持在Google Cloud Platform上部署应用程序和包。
7
环境配置:根据需要配置环境变量以启用特定功能或集成。

How to Use

1
1. 确保拥有Neo4j数据库V5.15或更高版本,并安装APOC。
2
2. 创建并配置.env文件,输入必要的API密钥。
3
3. 选择文件来源,例如本地文件、YouTube视频或网页。
4
4. 上传文件到系统,选择LLM模型进行知识图谱生成。
5
5. 在Bloom中查看和分析生成的知识图谱。
6
6. 通过聊天机器人与数据库进行交互,提出问题并获取答案。
7
7. 根据需要调整环境变量和配置,以适应不同的部署环境。

Target Users

目标受众为数据科学家、开发者和任何需要从大量非结构化数据中提取信息并构建知识图谱的专业人士。该产品适合他们,因为它简化了从复杂数据源中提取有用信息的过程,提高了效率并促进了知识的可视化和分析。

Examples

从学术论文中提取关键概念并构建领域知识图谱。

分析社交媒体数据,识别趋势和影响力人物。

整合企业内部文档,构建内部知识管理系统。

Quick Access

Visit Website →

Categories

💻 programming
› AI development assistant
› AI knowledge graph

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