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# ⛓️ LangFlow
~ A no-code flow builder for langchain ~
~ A Flow Interface For [LangChain](https://github.com/hwchase17/langchain) ~
<p>
<img alt="GitHub Contributors" src="https://img.shields.io/github/contributors/logspace-ai/langflow" />
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![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.
LangFlow is a UI for [LangChain](https://github.com/hwchase17/langchain), designed with [react-flow](https://github.com/wbkd/react-flow) to provide an effortless way to experiment and prototype flows with the drag-and-drop and chat interfaces.
## 📦 Installation
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`pip install langflow`
Next, set the `OPENAI_API_KEY` environment variable using one of the following methods:
Next, run:
- 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"`.
```
langflow
# or
python -m langflow
```
## 🎨 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.
Creating flows with LangFlow is easy. Simply drag sidebar components onto the canvas and connect them together to create your pipeline. LangFlow provides a range of [LangChain components](https://langchain.readthedocs.io/en/latest/reference.html) to choose from, including LLMs, prompt serializers, agents, and chains.
## 💻 Examples
Explore by editing prompt parameters, create chains and agents, track an agent's thought process, and export your flow.
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.
We welcome contributions from developers of all levels to our open-source project on GitHub. If you'd like to contribute, please check our contributing guidelines and help make LangFlow more accessible. 
## 📄 License