fix merge

docs/docs/getting-started/creating-flows.mdx

@@ -1,55 +0,0 @@
-import ThemedImage from "@theme/ThemedImage";
-import useBaseUrl from "@docusaurus/useBaseUrl";
-import ZoomableImage from "/src/theme/ZoomableImage.js";
-import ReactPlayer from "react-player";
-
-# 🎨 Creating Flows
-
-## Compose
-
-Creating flows with Langflow is easy. Drag sidebar components onto the canvas and connect them together to create your pipeline.
-Langflow provides a range of Components to choose from, including **Chat Input**, **Chat Output**, **API Request** and **Prompt**.
-
-<ZoomableImage
-  alt="Docusaurus themed image"
-  sources={{
-    light: "img/langflow_canvas.png",
-    dark: "img/langflow_canvas.png",
-  }}
-  style={{
-    width: "70%",
-    margin: "20px auto",
-    display: "flex",
-    justifyContent: "center",
-  }}
-/>
-
-## Starter Flows
-
-Langflow provides a range of starter flows to help you get started. These flows are pre-built and can be used as a starting point for your own flows.
-
-<div
-  style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
->
-  <ReactPlayer playing controls url="/videos/langflow_fork.mp4" />
-</div>
-
-## Defining Inputs and Outputs
-
-Each flow can have multiple inputs and outputs. These can be defined by placing **Inputs** and **Outputs** components on the canvas.
-
-The **Inputs** components define the inputs to the flow.
-Whenever you place an Input component on the canvas, it will allow you to interactively define change its value
-from the Interactive Panel.
-
-The **Text Input** component allows you to define a text input, and the **Chat Input** component allows you to use the chat input from the Interactive Panel.
-
-The **Outputs** components define the outputs of the flow and work similarly to the Inputs components.
-
-Both Inputs and Outputs components can be connected to other components on the canvas and are used to define how the API works too.
-
-<div
-  style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
->
-  <ReactPlayer playing controls url="/videos/langflow_build.mp4" />
-</div>

docs/docs/guides/async-tasks.mdx

@@ -1,44 +0,0 @@
-import Admonition from "@theme/Admonition";
-
-# Async API
-
-## Introduction
-
-<Admonition type="info" caption="In development">
-  This implementation is still in development. Contributions are welcome!
-</Admonition>
-
-The Async API is an implementation of the Langflow API that uses [Celery](https://docs.celeryproject.org/en/stable/)
-to run the tasks asynchronously, using a message broker to send and receive messages, a result backend to store the results and a cache to store the task states and session data.
-
-### Configuration
-
-The folder _`./deploy`_ in the [Github repository](https://github.com/logspace-ai/langflow) contains a _`.env.example`_ file that can be used to configure a Langflow deployment.
-The file contains the variables required to configure a Celery worker queue, Redis cache and result backend and a RabbitMQ message broker.
-
-To set it up locally you can copy the file to _`.env`_ and run the following command:
-
-```bash
-docker compose up -d
-```
-
-This will set up the following containers:
-
-- Langflow API
-- Celery worker
-- RabbitMQ message broker
-- Redis cache
-- PostgreSQL database
-- PGAdmin
-- Flower
-- Traefik
-- Grafana
-- Prometheus
-
-### Testing
-
-To run the tests for the Async API, you can run the following command:
-
-```bash
-docker compose -f docker-compose.with_tests.yml up --exit-code-from tests tests result_backend broker celeryworker db --build
-```

docs/docs/whats-new/a-new-chapter-langflow.mdx

@@ -61,11 +61,11 @@ We wanted to create start projects that would help you learn about new features
 
 For now, we have:
 
-- **[Basic Prompting (Ahoy World!)](/starter-projects/basic-prompting)**: A simple flow that shows you how to use the Prompt Component and how to talk like a pirate.
+- **[Basic Prompting (Ahoy World!)](/getting-started/basic-prompting)**: A simple flow that shows you how to use the Prompt Component and how to talk like a pirate.
-- **[Vector Store RAG](/starter-projects/rag-with-astradb)**: A flow that shows you how to ingest data into a Vector Store and then use it to run a RAG application.
+- **[Vector Store RAG](/getting-started/rag-with-astradb)**: A flow that shows you how to ingest data into a Vector Store and then use it to run a RAG application.
-- **[Memory Chatbot](/starter-projects/memory-chatbot)**: This one shows you how to create a simple chatbot that can remember things about the user.
+- **[Memory Chatbot](/getting-started/memory-chatbot)**: This one shows you how to create a simple chatbot that can remember things about the user.
-- **[Document QA](/starter-projects/document-qa)**: This flow shows you how to build a simple flow that helps you get answers about a document.
+- **[Document QA](/getting-started/document-qa)**: This flow shows you how to build a simple flow that helps you get answers about a document.
-- **[Blog Writer](/starter-projects/blog-writer)**: Shows you how you can expand on the Prompt variables and be creative about what inputs you add to it.
+- **[Blog Writer](/getting-started/blog-writer)**: Shows you how you can expand on the Prompt variables and be creative about what inputs you add to it.
 
 As always, your feedback is invaluable, so please let us know what you think of the new starter projects and what you would like to see in the future.
 

docs/sidebars.js

@@ -4,7 +4,15 @@ module.exports = {
       type: "category",
       label: " Getting Started",
       collapsed: false,
-      items: ["index", "getting-started/cli", "getting-started/creating-flows"],
+      items: [
+        "index",
+        "getting-started/cli",
+        "getting-started/basic-prompting",
+        "getting-started/document-qa",
+        "getting-started/blog-writer",
+        "getting-started/memory-chatbot",
+        "getting-started/rag-with-astradb",
+      ],
     },
     {
       type: "category",
@@ -15,28 +23,11 @@ module.exports = {
         "whats-new/migrating-to-one-point-zero",
       ],
     },
-    {
-      type: "category",
-      label: " Starter Projects",
-      collapsed: false,
-      items: [
-        "starter-projects/rag-with-astradb",
-        "starter-projects/basic-prompting",
-        "starter-projects/memory-chatbot",
-        "starter-projects/document-qa",
-        "starter-projects/blog-writer",
-      ],
-    },
     {
       type: "category",
       label: " Step-by-Step Guides",
       collapsed: false,
-      items: [
+      items: ["guides/langfuse_integration"],
-        "guides/async-tasks",
-        "guides/loading_document",
-        "guides/chatprompttemplate_guide",
-        "guides/langfuse_integration",
-      ],
     },
     {
       type: "category",
@@ -56,7 +47,7 @@ module.exports = {
         // "migration/connecting-output-components",
         // "migration/renaming-and-editing-components",
         // "migration/passing-tweaks-and-inputs",
-        // "migration/global-variables",
+        "migration/global-variables",
         // "migration/experimental-components",
         // "migration/state-management",
       ],

src/backend/base/langflow/components/embeddings/OpenAIEmbeddings.py

@@ -94,10 +94,10 @@ class OpenAIEmbeddingsComponent(CustomComponent):
         disallowed_special: List[str] = ["all"],
         chunk_size: int = 1000,
         client: Optional[Any] = None,
-        deployment: str = "text-embedding-3-small",
+        deployment: str = "text-embedding-ada-002",
         embedding_ctx_length: int = 8191,
         max_retries: int = 6,
-        model: str = "text-embedding-3-small",
+        model: str = "text-embedding-ada-002",
         model_kwargs: NestedDict = {},
         openai_api_base: Optional[str] = None,
         openai_api_type: Optional[str] = None,