Merge pull request #448 from SciPhi-AI/Nolan/FixRelativeLinks

Fix broken relative links

README.md

@@ -320,7 +320,7 @@ The following demo offers a step-by-step guide on running the default R2R Retrie
 
    ### Client-Server Summary
 
-   By using the Client-Server model, you can extend the basic R2R demo to support more scalable and modular deployments. The server handles requests and performs heavy computations, while clients can communicate with the server to perform ingestion, search, RAG, and other operations, as shown in the examples above. For detailed setup and basic functionality, refer back to the [R2R Demo](#r2r-demo).
+   By using the Client-Server model, you can extend the basic R2R demo to support more scalable and modular deployments. The server handles requests and performs heavy computations, while clients can communicate with the server to perform ingestion, search, RAG, and other operations, as shown in the examples above. For detailed setup and basic functionality, refer back to the [R2R Demo](#quickstart).
 </details>
 
 # R2R Dashboard
@@ -335,7 +335,7 @@ We're here to help! Feel free to reach out for support on any of these channels:
 - [Github Issues](https://github.com/SciPhi-AI/R2R/issues) \(Bug reports and feature requests\)
 
 There are a number of helpful tutorials and cookbooks that can be found in the [R2R Docs](https://r2r-docs.sciphi.ai/):
-- [R2R Demo](https://r2r-docs.sciphi.ai/getting-started/r2r-demo): A basic demo script designed to get you started with an R2R RAG application. 
+- [R2R Demo](https://r2r-docs.sciphi.ai/getting-started/quickstart): A basic demo script designed to get you started with an R2R RAG application. 
 - [R2R Client-Server](https://r2r-docs.sciphi.ai/cookbooks/client-server): An extension of the basic `R2R Demo` with client-server interactions.
 - [Local RAG](https://r2r-docs.sciphi.ai/cookbooks/local-rag): A quick cookbook demonstration of how to run R2R with local LLMs.
 - [Hybrid Search](https://r2r-docs.sciphi.ai/cookbooks/hybrid-search): A brief introduction to running hybrid search with R2R.

docs/pages/cookbooks/client-server.mdx

@@ -5,7 +5,7 @@ The Client-Server architecture in R2R allows for a flexible and scalable approac
 
 ### Setting Up the Server
 
-This document extends the [R2R Demo](/getting-started/r2r-demo) by demonstrating how to set up and use the R2R framework with a Client-Server architecture. The R2R server can be stood up to handle requests, while the client can communicate with the server to perform various operations. The server API can be [viewed here](/getting-started/app-api).
+This document extends the [R2R Demo](/getting-started/quickstart) by demonstrating how to set up and use the R2R framework with a Client-Server architecture. The R2R server can be stood up to handle requests, while the client can communicate with the server to perform various operations. The server API can be [viewed here](/getting-started/app-api).
 
 
 To set up the R2R server, follow these steps:
@@ -47,7 +47,7 @@ This command starts the R2R container with the following options:
 </details>
 
 **Local Installation**:
-   Ensure you have all necessary dependencies installed as described in the [R2R Demo](/getting-started/r2r-demo#setup). Then, use the following command to start the server:
+   Ensure you have all necessary dependencies installed as described in the [R2R Demo](/getting-started/quickstart). Then, use the following command to start the server:
    ```bash filename="bash" copy
    python -m r2r.examples.demo serve
    ```
@@ -85,4 +85,4 @@ The R2R framework includes a [python client](https://github.com/SciPhi-AI/R2R/bl
 
 ## Summary
 
-By using the Client-Server model, you can extend the basic R2R demo to support more scalable and modular deployments. The server handles requests and performs heavy computations, while clients can communicate with the server to perform ingestion, search, RAG, and other operations, as shown in the examples above. For detailed setup and basic functionality, refer back to the [R2R Demo](/getting-started/r2r-demo).
+By using the Client-Server model, you can extend the basic R2R demo to support more scalable and modular deployments. The server handles requests and performs heavy computations, while clients can communicate with the server to perform ingestion, search, RAG, and other operations, as shown in the examples above. For detailed setup and basic functionality, refer back to the [R2R Demo](/getting-started/quickstart).

docs/pages/cookbooks/hybrid-search.mdx

@@ -6,7 +6,7 @@ Hybrid search combines full-text and semantic search to deliver more comprehensi
 
 ### Running with Postgres + pgvector
 
-This guide assumes R2R is already installed and the basic demo [located here](/getting-started/r2r-demo) has been completed.
+This guide assumes R2R is already installed and the basic demo [located here](/getting-started/quickstart) has been completed.
 
 By default, R2R ships with hybrid search enabled when using PostgreSQL and pgvector as the vector database provider. To run R2R with Postgres, override the default `config.json` with settings like those shown below:
 

docs/pages/cookbooks/local-rag.mdx

@@ -148,7 +148,7 @@ Here's what's happening under the hood:
 3. Each chunk is embedded using the `all-MiniLM-L6-v2` model from `sentence-transformers`.
 4. The chunks and embeddings are stored in the specified vector database, which defaults to a local SQLite database.
 
-With just one command, we've gone from a raw document to an embedded knowledge base we can query. In addition to the raw chunks, metadata such as user ID or document ID can be attached to enable easy filtering later. For more information on similar functionalities provided by the demo, refer to the [R2R Demo](/getting-started/r2r-demo).
+With just one command, we've gone from a raw document to an embedded knowledge base we can query. In addition to the raw chunks, metadata such as user ID or document ID can be attached to enable easy filtering later. For more information on similar functionalities provided by the demo, refer to the [R2R Demo](/getting-started/quickstart).
 
 ### Running Queries on the Local LLM
 

docs/pages/cookbooks/multiple-llms.mdx

@@ -10,7 +10,7 @@ LLMs are selected at runtime for maximum flexibility and ease of use. Use any pr
 
 ### Running RAG with Multiple LLMs
 
-This guide assumes R2R is already installed and the basic demo [located here](/getting-started/r2r-demo) has been completed.
+This guide assumes R2R is already installed and the basic demo [located here](/getting-started/quickstart) has been completed.
 
 #### Default (OpenAI)
 

docs/pages/cookbooks/starter.mdx

@@ -1,6 +1,6 @@
 ## Getting Started
 
-If you haven't completed the step-by-step R2R demo yet, please do so [here](/getting-started/r2r-demo) before proceeding to the cookbooks below.
+If you haven't completed the step-by-step R2R demo yet, please do so [here](/getting-started/quickstart) before proceeding to the cookbooks below.
 
 
 

docs/pages/deep-dive/configuring-your-pipeline.mdx

@@ -48,7 +48,7 @@ A simple example custom user configuration can be found in [`r2r/examples/data/e
 }
 ```
 
-You can serve the [R2R Demo](/getting-started/r2r-demo) using local embeddings with rerank, as shown above, with the following command sequence:
+You can serve the [R2R Demo](/getting-started/quickstart) using local embeddings with rerank, as shown above, with the following command sequence:
 
 ```bash filename="bash" copy
 # Be sure to install with pip install `r2r[local-embedding]`
@@ -110,7 +110,7 @@ An example configuration specifying Postgres as a logging provider can be found
 }
 ```
 
-You can serve the [R2R Demo](/getting-started/r2r-demo) using Postgres logging with the following command sequence:
+You can serve the [R2R Demo](/getting-started/quickstart) using Postgres logging with the following command sequence:
 
 ```bash filename="bash" copy
 # Set valid Postgres environment variables

docs/pages/index.mdx

@@ -23,14 +23,14 @@ R2R was conceived to help developers bridge the gap between local LLM experiment
 - **🔌 Extensible**: Develop your application further with a convenient builder and factory pattern.
 
 ## Demo(s)
-The [R2R Demo](/getting-started/r2r-demo) provides a step-by-step guide to running the default R2R Retrieval-Augmented Generation (RAG) backend. The demo ingests the provided documents and illustrates search and RAG functionality, logging, analytics, and document management.
+The [R2R Demo](/getting-started/quickstart) provides a step-by-step guide to running the default R2R Retrieval-Augmented Generation (RAG) backend. The demo ingests the provided documents and illustrates search and RAG functionality, logging, analytics, and document management.
 
 ## Getting Started
 
 To get started with R2R, we recommend setting up the framework and following an initial example.
 
 - [Quick Install](/getting-started/quick-install): Quick setup using `pip`.
-- [R2R Demo](/getting-started/r2r-demo): A basic demo script designed to get you started with an R2R RAG application. 
+- [R2R Demo](/getting-started/quickstart): A basic demo script designed to get you started with an R2R RAG application. 
 - [R2R Client-Server](/cookbooks/client-server): An extension of the basic `R2R Demo` with client-server interactions.
 - [Local RAG](/cookbooks/local-rag): A quick cookbook demonstration of how to run R2R with local LLMs.
 - [Hybrid Search](/cookbooks/hybrid-search): A brief introduction to running hybrid search with R2R.