docs: Pipedream App (#950)

qdrant-landing/content/documentation/frameworks/_index.md

@@ -28,6 +28,7 @@ weight: 33
 | [OpenLIT](./openlit/)                 | OpenTelemetry-native Observability & Evals for LLMs and Vector Databases.                            |
 | [OpenLLMetry](./openllmetry/)         | Set of OpenTelemetry extensions to add Observability for your LLM application.                       |
 | [Pandas-AI](./pandas-ai/)             | Python library to query/visualize your data (CSV, XLSX, PostgreSQL, etc.) in natural language        |
+| [Pipedream](./pipedream/)             | Platform for connecting apps and developing event-driven automations.                                |
 | [PrivateGPT](./privategpt/)           | Tool to ask questions about your documents using local LLMs emphasising privacy.                     |
 | [Rivet](./rivet/)                     | A visual programming environment for building AI agents with LLMs.                                   |
 | [Semantic Router](./semantic-router/) | Python library to build a decision-making layer for AI applications using vector search.             |

qdrant-landing/content/documentation/frameworks/langchain.md

@@ -101,4 +101,4 @@ If you'd like to know more about running Qdrant in a LangChain-based application
 [Question Answering with LangChain and Qdrant without boilerplate](/articles/langchain-integration/). Some more information
 might also be found in the [LangChain documentation](https://python.langchain.com/docs/integrations/vectorstores/qdrant).
 
-- [Source Code](https://github.com/langchain-ai/langchain/blob/master/libs/community/langchain_community/vectorstores/qdrant.py)
+- [Source Code](https://github.com/langchain-ai/langchain/tree/master/libs%2Fpartners%2Fqdrant)

qdrant-landing/content/documentation/frameworks/pipedream.md

@@ -0,0 +1,43 @@
+---
+title: Pipedream
+weight: 3300
+---
+
+# Pipedream
+
+[Pipedream](https://pipedream.com/) is a development platform that allows developers to connect many different applications, data sources, and APIs in order to build automated cross-platform workflows. It also offers code-level control with Node.js, Python, Go, or Bash if required.
+
+You can use the [Qdrant app](https://pipedream.com/apps/qdrant) in Pipedream to add vector search capabilities to your workflows.
+
+## Prerequisites
+
+1. A Qdrant instance to connect to. You can get a free cloud instance at [cloud.qdrant.io](https://cloud.qdrant.io/).
+2. A [Pipedream project](https://pipedream.com/) to develop your workflows.
+
+## Setting Up
+
+Search for the Qdrant app in your workflow apps.
+
+![Qdrant Pipedream App](/documentation/frameworks/pipedream/qdrant-app.png)
+
+The Qdrant app offers extensible API interface and pre-built actions.
+
+![Qdrant App Features](/documentation/frameworks/pipedream/app-features.png)
+
+Select any of the actions of the app to set up a connection.
+
+![Qdrant Connect Account](/documentation/frameworks/pipedream/app-upsert-action.png)
+
+Configure connection with the credentials of your Qdrant instance.
+
+![Qdrant Connection Credentials](/documentation/frameworks/pipedream/app-connection.png)
+
+You can verify your credentials using the "Test Connection" button.
+
+Once a connection is set up, you can use the app to build workflows with the [2000+ apps supported by Pipedream](https://pipedream.com/apps/).
+
+## Further Reading
+
+- [Pipedream Documentation](https://pipedream.com/docs).
+- [Qdrant Cloud Authentication](https://qdrant.tech/documentation/cloud/authentication/).
+- [Source Code](https://github.com/PipedreamHQ/pipedream/tree/master/components/qdrant)