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Dify.AI Unveils AI Agent: Creating GPTs and Assistants with Various LLMs

Dify is an LLM application development platform that has helped built over 100,000 applications. It integrates BaaS and LLMOps, covering the essential tech stack for building generative AI-native applications, including a built-in RAG engine. Dify allows you to deploy your own version of Assistants API and GPTs, based on any LLMs.

You can try out Dify.AI Cloud now. It provides all the capabilities of the self-deployed version, and includes 200 free requests to OpenAI GPT-3.5.

1. LLM Support: Integration with OpenAI's GPT family of models, or the open-source Llama2 family models. In fact, Dify supports mainstream commercial models and open-source models (locally deployed or based on MaaS).

2. Prompt IDE: Visual orchestration of applications and services based on LLMs with your team.

3. RAG Engine: Includes various RAG capabilities based on full-text indexing or vector database embeddings, allowing direct upload of PDFs, TXTs, and other text formats.

4. AI Agent: Based on Function Calling and ReAct, the Agent inference framework allows users to customize tools, what you see is what you get. Dify provides more than a dozen built-in tool calling capabilities, such as Google Search, DELL·E, Stable Diffusion, WolframAlpha, etc.

5. Continuous Operations: Monitor and analyze application logs and performance, continuously improving Prompts, datasets, or models using production data.

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• Website
• Docs
• Deployment Docs
• FAQ

Before installing Dify, make sure your machine meets the following minimum system requirements:

• CPU >= 2 Core
• RAM >= 4GB

The easiest way to start the Dify server is to run our docker-compose.yml file. Before running the installation command, make sure that Docker and Docker Compose are installed on your machine:

cd docker
docker compose up -d

After running, you can access the Dify dashboard in your browser at https://localhost/install and start the initialization installation process.

Big thanks to @BorisPolonsky for providing us with a Helm Chart version, which allows Dify to be deployed on Kubernetes. You can go to https://github.com/BorisPolonsky/dify-helm for deployment information.

If you need to customize the configuration, please refer to the comments in our docker-compose.yml file and manually set the environment configuration. After making the changes, please run docker-compose up -d again. You can see the full list of environment variables in our docs.

For those who'd like to contribute code, see our Contribution Guide.

At the same time, please consider supporting Dify by sharing it on social media and at events and conferences.

We are looking for contributors to help with translating Dify to languages other than Mandarin or English. If you are interested in helping, please see the i18n README for more information, and leave us a comment in the global-users channel of our Discord Community Server.

• Canny. Best for: sharing feedback and checking out our feature roadmap.
• GitHub Issues. Best for: bugs you encounter using Dify.AI, and feature proposals. See our Contribution Guide.
• Email Support. Best for: questions you have about using Dify.AI.
• Discord. Best for: sharing your applications and hanging out with the community.
• Twitter. Best for: sharing your applications and hanging out with the community.
• Business Contact. Best for: business inquiries of licensing Dify.AI for commercial use.

Help us make Dify better. Reach out directly to us.

Point of Contact	Purpose
	Product design feedback, user experience discussions, feature planning and roadmaps.
	Technical support, issues, or feature requests

To protect your privacy, please avoid posting security issues on GitHub. Instead, send your questions to [email protected] and we will provide you with a more detailed answer.

This repository is available under the Dify Open Source License, which is essentially Apache 2.0 with a few additional restrictions.