diff --git a/LICENSE b/LICENSE
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+MIT License
+
+Copyright (c) 2023 Logspace
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
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+
+
+# ⛓️ LangFlow
+
+~ A no-code flow builder for langchain ~
+
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+LangFlow is a no-code flow builder for LangChain, designed to provide a drag-and-drop UI, combining the capabilities of LangChain with reactFlow and a chat interface.
+
+## 📦 Installation
+
+You can install LangFlow from pip:
+
+`pip install langflow`
+
+Next, set the `OPENAI_API_KEY` environment variable using one of the following methods:
+
+- Use the following command in your terminal: `export OPENAI_API_KEY=your-api-key`.
+- In a Python script or Jupyter notebook, use the following code: `import os; os.environ["OPENAI_API_KEY"] = "your-api-key"`.
+
+## 🎨 Creating Flows
+
+Creating flows with LangFlow is easy, thanks to its intuitive drag-and-drop interface. Simply drag components from the sidebar onto the canvas, and connect them together to create your custom NLP pipeline. LangFlow provides a range of pre-built components to choose from, including LLMs, prompt serializers, agents, and chains.
+
+## 💻 Examples
+
+LangFlow comes with a number of example flows to help you get started. These examples cover a range of use cases, from chatbots and question-answering systems to data augmentation and model comparison. You can use these examples as a starting point for your own custom flows, or modify them to suit your needs.
+
+## 🧰 Components
+
+LangFlow provides support for LangChain main components, including prompts, LLMs, document loaders, utils, chains, indexes, agents, and memory. For each module, we provide examples to get started, how-to guides, reference docs, and conceptual guides.
+
+For more information on each component, please refer to the [Modules section of the LangChain documentation](https://langchain-docs.example.com/modules).
+
+## 🔧 Contributing
+
+We welcome contributions to LangFlow! If you'd like to contribute, please follow our contributing guidelines. You can also get in touch with us via GitHub issues or our community forum.
+
+## 📄 License
+
+LangFlow is released under the MIT License. See the LICENSE file for details.
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