diff --git a/README.md b/README.md
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--- a/README.md
+++ b/README.md
@@ -1,96 +1,168 @@
-[](https://dify.ai)
+
+
- English |
- 简体中文 |
- 日本語 |
- Español |
- Klingon |
- Français
+ Dify Cloud ·
+ Self-hosting ·
+ Documentation ·
+ Commercial inquiry
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+ 
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- 📌 Check out Dify Premium on AWS and deploy it to your own AWS VPC with one-click.
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+ 
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+ 
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+ 
-**Dify** is an open-source LLM app development platform. Dify's intuitive interface combines a RAG pipeline, AI workflow orchestration, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production.
-
-https://github.com/langgenius/dify/assets/13230914/979e7a68-f067-4bbc-b38e-2deb2cc2bbb5
-
-
-## Using Dify Cloud
-
-You can try out [Dify Cloud](https://dify.ai) now. It provides all the capabilities of the self-deployed version, and includes 200 free GPT-4 calls.
-
-## Dify for Enterprise / Organizations
-
-[Schedule a meeting with us](#Direct-Meetings) or [send us an email](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry) to discuss enterprise needs.
-
-For startups and small businesses using AWS, check out [Dify Premium on AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) and deploy it to your own AWS VPC with one-click. It's an affordable AMI offering with the option to create apps with custom logo and branding.
-
-## Features
-
-
-
-**1. Workflow**: Create and test complex AI workflows on a visual canvas, with pre-built nodes taking advantage of the power of all the following features and beyond.
-
-**2. Extensive LLM support**: Seamless integration with hundreds of proprietary / open-source LLMs and dozens of inference providers, including GPT, Mistral, Llama2, and OpenAI API-compatible models. A full list of supported model providers is kept [here](https://docs.dify.ai/getting-started/readme/model-providers).
-
-**3. Prompt IDE**: Visual orchestration of applications and services based on any LLMs. Easily share with your team.
-
-**4. 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.
-
-**5. 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 tools for AI agents, such as Google Search, DELL·E, Stable Diffusion, WolframAlpha, etc.
-
-**6. LLMOps**: Monitor and analyze application logs and performance, continuously improving Prompts, datasets, or models based on production data.
-
-
-## Dify vs. LangChain vs. Assistants API
-
-| Feature | Dify.AI | Assistants API | LangChain |
-|---------|---------|----------------|-----------|
-| **Programming Approach** | API-oriented | API-oriented | Python Code-oriented |
-| **Ecosystem Strategy** | Open Source | Close Source | Open Source |
-| **RAG Engine** | Supported | Supported | Not Supported |
-| **Prompt IDE** | Included | Included | None |
-| **Supported LLMs** | Rich Variety | OpenAI-only | Rich Variety |
-| **Local Deployment** | Supported | Not Supported | Not Applicable |
-
-
-## Before You Start
-
-**Star us on GitHub, and be instantly notified for new releases!**
-
-- [Website](https://dify.ai)
-- [Docs](https://docs.dify.ai)
-- [Deployment Docs](https://docs.dify.ai/getting-started/install-self-hosted)
-- [FAQ](https://docs.dify.ai/getting-started/faq)
-
-
-## Install the Community Edition
-
-### System Requirements
-
-Before installing Dify, make sure your machine meets the following minimum system requirements:
-
-- CPU >= 2 Core
-- RAM >= 4GB
-
-### Quick Start
+#
+Dify is an open-source LLM app development platform. Its intuitive interface combines RAG pipeline, AI workflow, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production.
+
+
+[](https://github.com/langgenius/dify/assets/13230914/979e7a68-f067-4bbc-b38e-2deb2cc2bbb5)
+
+**1. Workflow**:
+ Build and test powerful AI workflows on a visual canvas, leveraging all the following features and beyond.
+
+**2. Comprehensive model support**:
+ Seamless integration with hundreds of proprietary / open-source LLMs from dozens of inference providers and self-hosted solutions, covering GPT, Mistral, Llama2, and any OpenAI API-compatible models. A full list of supported model providers can be found [here](https://docs.dify.ai/getting-started/readme/model-providers).
+
+
+
+
+**3. Prompt IDE**:
+ Intuitive interface for crafting prompts, comparing model performance, and adding additional features such as text-to-speech to a chat-based app.
+
+**4. RAG Pipeline**:
+ Extensive RAG capabilities that cover everything from document ingestion to retrieval, with out-of-box support for text extraction from PDFs, PPTs, and other common document formats.
+
+**5. Agent capabilities**:
+ You can define agents based on LLM Function Calling or ReAct, and add pre-built or custom tools for the agent. Dify provides 50+ built-in tools for AI agents, such as Google Search, DELL·E, Stable Diffusion and WolframAlpha.
+
+**6. LLMOps**:
+ Monitor and analyze application logs and performance over time. You could continuously improve prompts, datasets, and models based on production data and annotations.
+
+**7. Backend-as-a-Service**:
+ All of Dify's offerings come with corresponding APIs, so you could effortlessly integrate Dify into your own business logic.
+
+
+## Feature Comparison
+
+
+ | Feature |
+ Dify.AI |
+ LangChain |
+ Flowise |
+ OpenAI Assistants API |
+
+
+ | Programming Approach |
+ API + App-oriented |
+ Python Code |
+ App-oriented |
+ API-oriented |
+
+
+ | Supported LLMs |
+ Rich Variety |
+ Rich Variety |
+ Rich Variety |
+ OpenAI-only |
+
+
+ | RAG Engine |
+ ✅ |
+ ✅ |
+ ✅ |
+ ✅ |
+
+
+ | Agent |
+ ✅ |
+ ✅ |
+ ✅ |
+ ✅ |
+
+
+ | Workflow |
+ ✅ |
+ ❌ |
+ ✅ |
+ ❌ |
+
+
+ | Observability |
+ ✅ |
+ ✅ |
+ ❌ |
+ ❌ |
+
+
+ | Enterprise Feature (SSO/Access control) |
+ ✅ |
+ ❌ |
+ ❌ |
+ ❌ |
+
+
+ | Local Deployment |
+ ✅ |
+ ✅ |
+ ✅ |
+ ❌ |
+
+
+
+## Using Dify
+
+- **Cloud **
+We host a [Dify Cloud](https://dify.ai) service for anyone to try with zero setup. It provides all the capabilities of the self-deployed version, and includes 200 free GPT-4 calls in the sandbox plan.
+
+- **Self-hosting Dify Community Edition**
+Quickly get Dify running in your environment with this [starter guide](#quick-start).
+Use our [documentation](https://docs.dify.ai) for further references and more in-depth instructions.
+
+- **Dify for Enterprise / Organizations**
+We provide additional enterprise-centric features. [Schedule a meeting with us](https://cal.com/guchenhe/30min) or [send us an email](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry) to discuss enterprise needs.
+ > For startups and small businesses using AWS, check out [Dify Premium on AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) and deploy it to your own AWS VPC with one-click. It's an affordable AMI offering with the option to create apps with custom logo and branding.
+
+
+## Staying ahead
+
+Star Dify on GitHub and be instantly notified of new releases.
+
+
+
+
+## Quick Start
+> 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](docker/docker-compose.yaml) file. Before running the installation command, make sure that [Docker](https://docs.docker.com/get-docker/) and [Docker Compose](https://docs.docker.com/compose/install/) are installed on your machine:
@@ -99,58 +171,63 @@ cd docker
docker compose up -d
```
-After running, you can access the Dify dashboard in your browser at [http://localhost/install](http://localhost/install) and start the initialization installation process.
+After running, you can access the Dify dashboard in your browser at [http://localhost/install](http://localhost/install) and start the initialization process.
-#### Deploy with Helm Chart
+> If you'd like to contribute to Dify or do additional development, refer to our [guide to deploying from source code](https://docs.dify.ai/getting-started/install-self-hosted/local-source-code)
-[Helm Chart](https://helm.sh/) version, which allows Dify to be deployed on Kubernetes.
+## Next steps
-- [Helm Chart by @LeoQuote](https://github.com/douban/charts/tree/master/charts/dify)
-- [Helm Chart by @BorisPolonsky](https://github.com/BorisPolonsky/dify-helm)
-
-### Configuration
+If you need to customize the configuration, please refer to the comments in our [docker-compose.yml](docker/docker-compose.yaml) 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 [here](https://docs.dify.ai/getting-started/install-self-hosted/environments).
-If you need to customize the configuration, please refer to the comments in our [docker-compose.yml](docker/docker-compose.yaml) 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](https://docs.dify.ai/getting-started/install-self-hosted/environments).
+If you'd like to configure a highly-available setup, there are community-contributed [Helm Charts](https://helm.sh/) which allow Dify to be deployed on Kubernetes.
+- [Helm Chart by @LeoQuote](https://github.com/douban/charts/tree/master/charts/dify)
+- [Helm Chart by @BorisPolonsky](https://github.com/BorisPolonsky/dify-helm)
-## Star History
-
-[](https://star-history.com/#langgenius/dify&Date)
## Contributing
For those who'd like to contribute code, see our [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
-
At the same time, please consider supporting Dify by sharing it on social media and at events and conferences.
-### Projects made by community
-- [Chatbot Chrome Extension by @charli117](https://github.com/langgenius/chatbot-chrome-extension)
+> 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](https://github.com/langgenius/dify/blob/main/web/i18n/README.md) for more information, and leave us a comment in the `global-users` channel of our [Discord Community Server](https://discord.gg/8Tpq4AcN9c).
-### Contributors
+**Contributors**
-### Translations
-
-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](https://github.com/langgenius/dify/blob/main/web/i18n/README.md) for more information, and leave us a comment in the `global-users` channel of our [Discord Community Server](https://discord.gg/8Tpq4AcN9c).
-
-## Community & Support
+## Community & Contact
* [Github Discussion](https://github.com/langgenius/dify/discussions). Best for: sharing feedback and asking questions.
* [GitHub Issues](https://github.com/langgenius/dify/issues). Best for: bugs you encounter using Dify.AI, and feature proposals. See our [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
-* [Email Support](mailto:hello@dify.ai?subject=[GitHub]Questions%20About%20Dify). Best for: questions you have about using Dify.AI.
+* [Email](mailto:support@dify.ai?subject=[GitHub]Questions%20About%20Dify). Best for: questions you have about using Dify.AI.
* [Discord](https://discord.gg/FngNHpbcY7). Best for: sharing your applications and hanging out with the community.
* [Twitter](https://twitter.com/dify_ai). Best for: sharing your applications and hanging out with the community.
-### Direct Meetings
+Or, schedule a meeting directly with a team member:
+
+
+
+ | Point of Contact |
+ Purpose |
+
+
+  |
+ Business enquiries & product feedback |
+
+
+  |
+ Contributions, issues & feature requests |
+
+
+
+## Star History
+
+[](https://star-history.com/#langgenius/dify&Date)
-| Point of Contact | Purpose |
-| :----------------------------------------------------------: | :----------------------------------------------------------: |
-| 
| Business enquiries & product feedback. |
-| 
| Contributions, issues & feature requests |
## Security Disclosure