mirror of
https://github.com/labring/FastGPT.git
synced 2025-07-21 03:35:36 +00:00
a6fbfac96f
* Yuque dataset baseurl (#4512) * feat: 增加API数据集功能和国际化支持 * 在apiDataset.d.ts中添加uuid、slug、parent_uuid和children字段 * 更新英文、简体中文和繁体中文的dataset.json文件，增加多条提示信息 * 在ApiDatasetForm组件中实现目录选择功能，支持获取Yuque路径 * 新增BaseUrlSelector组件，用于选择根目录 * 实现getpath API，支持根据Yuque服务器获取路径 * 更新相关API调用，确保兼容性和功能完整性 * feat: 更新Yuque服务器的baseUrl处理逻辑 * 在apiDataset.d.ts中将YuqueServer的baseUrl属性改为必填 * 更新ApiDatasetForm组件，调整baseUrl的状态管理和路径加载逻辑 * 新增getcatalog API以支持获取数据集目录 * 修改相关API调用，确保baseUrl的正确传递和使用 * 优化路径返回值为中文“根目录” * feat: 更新数据集API调用逻辑 * 将getFeishuAndYuqueDatasetFileList替换为getProApiDatasetFileListRequest，统一API调用方式 * 更新相关文件以确保新API的正确使用 * 优化代码结构，提高可读性和维护性 * 清理代码：移除ApiDatasetForm、BaseUrlSelector和相关API中的调试日志 * 删除不必要的console.log语句，提升代码整洁性 * 确保API逻辑的清晰性，避免冗余输出 * 更新数据集相关类型和API逻辑 - 在apiDataset.d.ts中添加ApiDatasetDetailResponse类型，移除不必要的字段。 - 在proApi.ts中新增DETAIL操作类型及相关参数类型。 - 修改ApiDatasetForm.tsx以支持新的API调用逻辑，统一路径获取方式。 - 更新BaseUrlSelector组件，简化目录选择逻辑。 - 优化getpath.ts和getcatalog.ts中的路径处理逻辑，确保API调用的一致性和正确性。 - 清理不必要的代码和注释，提高代码可读性。 * 清理ApiDatasetForm组件中的调试日志，移除console.log语句以提升代码整洁性和可读性。 * fix * updata apidatasetform * remove console * updata * updata * updata editapiservermodal * updata i18n * add type * update getpath * add type * perf: yuque dataset baseurl * perf: remove rerank records * fix: ts --------- Co-authored-by: dreamer6680 <1468683855@qq.com>
FastGPT
FastGPT is a knowledge-based platform built on the LLMs, offers a comprehensive suite of out-of-the-box capabilities such as data processing, RAG retrieval, and visual AI workflow orchestration, letting you easily develop and deploy complex question-answering systems without the need for extensive setup or configuration.
🎥 Comprehensive Feature Demonstration
https://github.com/labring/FastGPT/assets/15308462/7d3a38df-eb0e-4388-9250-2409bd33f6d4
🛸 Online Use
Website: tryfastgpt.ai
| Conversational AI Setup | Workflow Automation |
 |
 |
| Knowledge Base Setup | Integration Process |
 |
 |
💡 Features
| Features | Details |
|---|---|
| Application Orchestration Features | ✅ Offers a straightforward mode, eliminating the need for complex orchestration ✅ Provides clear next-step instructions in dialogues ✅ Facilitates workflow orchestration ✅ Tracks references in source files ✅ Encapsulates modules for enhanced reuse at multiple levels ✅ Combines search and reordering functions 🔜 Includes a tool module 🔜 Integrates Laf for online HTTP module creation 🔜 Plugin encapsulation capabilities |
| Knowledge Base Features | ✅ Allows for the mixed use of multiple databases ✅ Keeps track of modifications and deletions in data chunks ✅ Enables specific vector models for each knowledge base ✅ Stores original source files ✅ Supports direct input and segment-based QA import ✅ Compatible with a variety of file formats: pdf, docx, txt, html, md, csv ✅ Facilitates URL reading and bulk CSV importing 🔜 Supports PPT and Excel file import 🔜 Features a file reader 🔜 Offers diverse data preprocessing options |
| Application Debugging Features | ✅ Enables targeted search testing within the knowledge base ✅ Allows feedback, editing, and deletion during conversations ✅ Presents the full context of interactions ✅ Displays all intermediate values within modules 🔜 Advanced Debug mode for orchestration |
| OpenAPI Interface | ✅ The completions interface (aligned with GPT's chat mode interface) ✅ CRUD operations for the knowledge base 🔜 CRUD operations for conversation |
| Operational Features | ✅ Share without requiring login ✅ Easy embedding with Iframe ✅ Customizable chat window embedding with features like default open, drag-and-drop ✅ Centralizes conversation records for review and annotation |
👨💻 Development
Project tech stack: NextJs + TS + ChakraUI + MongoDB + PostgreSQL (PG Vector plug-in)/Milvus
-
⚡ Fast Deployment
When using Sealos services, there is no need to purchase servers or domain names. It supports high concurrency and dynamic scaling, and the database application uses the kubeblocks database, which far exceeds the simple Docker container deployment in terms of IO performance.
[](https://cloud.sealos.io/?openapp=system-fastdeploy%3FtemplateName%3Dfastgpt&uid=fnWRt09fZP)Give it a 2-4 minute wait after deployment as it sets up the database. Initially, it might be a too slow since we're using the basic settings.
💪 Related Projects
- Laf: 3-minute quick access to third-party applications
- Sealos: Rapid deployment of cluster applications
- One API: Multi-model management, supports Azure, Wenxin Yiyuan, etc.
- TuShan: Build a backend management system in 5 minutes
🤝 Third-party Ecosystem
🏘️ Community & Support
- 🌐 Visit the FastGPT website for full documentation and useful links.
- 💬 Join our Discord server is to chat with FastGPT developers and other FastGPT users. This is a good place to learn about FastGPT, ask questions, and share your experiences.
- 🐞 Create GitHub Issues for bug reports and feature requests.
👀 Others
- FastGPT FAQ
- Docker Deployment Tutorial Video
- Official Account Integration Video Tutorial
- FastGPT Knowledge Base Demo
🌱 Contributors
We welcome all forms of contributions. If you are interested in contributing code, you can check out our GitHub Issues to show us your ideas.
|
|
|
|---|---|
|
|
|
|
🌟 Star History
📄 Usage Agreement
This repository complies with the FastGPT Open Source License open source agreement.
- Direct commercial use as a backend service is allowed, but provision of SaaS services is not allowed.
- Without commercial authorization, any form of commercial service must retain relevant copyright information.
- For full details, please see FastGPT Open Source License
- Contact: Dennis@sealos.io , click to view commercial version pricing strategy