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当前应用不需要配置任何参数
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.
https://github.com/labring/FastGPT/assets/15308462/7d3a38df-eb0e-4388-9250-2409bd33f6d4
Website: tryfastgpt.ai
Conversational AI Setup | Workflow Automation |
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Knowledge Base Setup | Integration Process |
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Features | Details |
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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 |
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.
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.
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.
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This repository complies with the FastGPT Open Source License open source agreement.