> ## Documentation Index
> Fetch the complete documentation index at: https://upstash-dx-3081-agentkit-tanstack-ai-backends.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Langflow with Upstash Vector

Langflow provides an intuitive, visual interface to design LLM workflows. You can seamlessly integrate Upstash Vector into your Langflow projects to enable vector-based semantic search and context retrieval.

<Frame>
  <img src="https://mintcdn.com/upstash-dx-3081-agentkit-tanstack-ai-backends/RDzYeyLeDrIqZOOD/img/vector/integrations/langflow/final-workflow.png?fit=max&auto=format&n=RDzYeyLeDrIqZOOD&q=85&s=d19269c7ccb84dd33483aba2ff34e7f1" alt="Completed Langflow workflow with Upstash Vector" width="3010" height="938" data-path="img/vector/integrations/langflow/final-workflow.png" />
</Frame>

## Install

To get started, install Langflow and Upstash Vector locally or use the Langflow dashboard from [DataStax](https://www.datastax.com/products/langflow). For local installation, run:

```bash theme={null}
pip install langflow upstash-vector
```

## Usage

### Creating an Upstash Vector Index

Visit the [Upstash Console](https://console.upstash.com/vector) to create a vector index. To learn more about index creation, you can check out [this page](https://docs.upstash.com/vector/overall/getstarted).

### Adding Upstash Vector to Langflow

In Langflow, you can integrate Upstash Vector for document indexing and semantic search. Use the following steps:

1. Create a workflow with the **File**, **Split**, and **Upstash** components to process and store documents in the Upstash Vector index.
2. Perform a vector search by connecting the **Upstash** component to your query input.

<Frame>
  <img src="https://mintcdn.com/upstash-dx-3081-agentkit-tanstack-ai-backends/RDzYeyLeDrIqZOOD/img/vector/integrations/langflow/insert-workflow.png?fit=max&auto=format&n=RDzYeyLeDrIqZOOD&q=85&s=8ef4b6a0f68212042451351a9587df62" alt="Insert workflow in Langflow" width="2228" height="1308" data-path="img/vector/integrations/langflow/insert-workflow.png" />
</Frame>

### Example Workflow

Enhance your chatbot by combining Langflow’s OpenAI integration with Upstash Vector. Create a RAG workflow to retrieve relevant context from your index and use it to answer user queries.

<Frame>
  <img src="https://mintcdn.com/upstash-dx-3081-agentkit-tanstack-ai-backends/RDzYeyLeDrIqZOOD/img/vector/integrations/langflow/final-workflow.png?fit=max&auto=format&n=RDzYeyLeDrIqZOOD&q=85&s=d19269c7ccb84dd33483aba2ff34e7f1" alt="Completed Langflow workflow with Upstash Vector" width="3010" height="938" data-path="img/vector/integrations/langflow/final-workflow.png" />
</Frame>

## Learn More

For a detailed guide on building a RAG chatbot with Langflow and Upstash Vector, check out this [blog post](https://upstash.com/blog/langflow-upstash-vector).


## Related topics

- [What is Upstash Vector?](/vector/overall/whatisvector.md)
- [Flowise with Upstash Vector and Redis](/vector/integrations/flowise.md)
- [LangChain with Upstash Vector](/vector/integrations/langchain.md)
- [LlamaIndex with Upstash Vector](/vector/integrations/llamaindex.md)
- [LlamaParse with Upstash Vector](/vector/integrations/llamaparse.md)