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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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<!-- Title -->
# ⛓️ LangFlow
~ A no-code flow builder for langchain ~
<p>
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</p>
![LangFlow Logo](https://github.com/logspace-ai/langflow/blob/main/img/llm_simple_flow.png)
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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