Adding deploy button in LLM-app examples (#6633)

GitOrigin-RevId: f6881ef8d6d52b9afd285ece36996a65e47e68a5
pathwaycom · Jun 10, 2024 · ca43ce6 · ca43ce6
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diff --git a/assets/render.png b/assets/render.png
diff --git a/examples/pipelines/adaptive-rag/README.md b/examples/pipelines/adaptive-rag/README.md
@@ -1,3 +1,13 @@
+<p align="left">
+  <a href="https://pathway.com/developers/user-guide/deployment/gcp-deploy" style="display: inline-flex; align-items: center;">
+    <img src="https://www.gstatic.com/pantheon/images/welcome/supercloud.svg" alt="GCP Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with GCP</span>
+  </a> | 
+  <a href="https://pathway.com/developers/user-guide/deployment/render-deploy" style="display: inline-flex; align-items: center;">
+    <img src="../../../assets/render.png" alt="Render Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with Render</span>
+  </a>
+</p>
+
+
 ## End to end Adaptive RAG with Pathway
 
 This is the accompanying code for deploying the `adaptive RAG` technique with Pathway.

diff --git a/examples/pipelines/alert/README.md b/examples/pipelines/alert/README.md
@@ -1,3 +1,12 @@
+<p align="left">
+  <a href="https://pathway.com/developers/user-guide/deployment/gcp-deploy" style="display: inline-flex; align-items: center;">
+    <img src="https://www.gstatic.com/pantheon/images/welcome/supercloud.svg" alt="GCP Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with GCP</span>
+  </a> | 
+  <a href="https://pathway.com/developers/user-guide/deployment/render-deploy" style="display: inline-flex; align-items: center;">
+    <img src="../../../assets/render.png" alt="Render Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with Render</span>
+  </a>
+</p>
+
 # Alert Pipeline
 
 This example implements a pipeline that answers questions based on documents in a given folder. Additionally, in your prompts you can ask to be notified of any changes - in such case an alert will be sent to a Slack channel.

diff --git a/examples/pipelines/contextful/README.md b/examples/pipelines/contextful/README.md
@@ -1,3 +1,12 @@
+<p align="left">
+  <a href="https://pathway.com/developers/user-guide/deployment/gcp-deploy" style="display: inline-flex; align-items: center;">
+    <img src="https://www.gstatic.com/pantheon/images/welcome/supercloud.svg" alt="GCP Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with GCP</span>
+  </a> | 
+  <a href="https://pathway.com/developers/user-guide/deployment/render-deploy" style="display: inline-flex; align-items: center;">
+    <img src="../../../assets/render.png" alt="Render Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with Render</span>
+  </a>
+</p>
+
 # Contextful Pipeline
 
 This example implements a simple pipeline that answers questions based on documents in a given folder.

diff --git a/examples/pipelines/contextful_geometric/README.md b/examples/pipelines/contextful_geometric/README.md
@@ -1,4 +1,13 @@
-# Contextful Pipeline
+<p align="left">
+  <a href="https://pathway.com/developers/user-guide/deployment/gcp-deploy" style="display: inline-flex; align-items: center;">
+    <img src="https://www.gstatic.com/pantheon/images/welcome/supercloud.svg" alt="GCP Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with GCP</span>
+  </a> | 
+  <a href="https://pathway.com/developers/user-guide/deployment/render-deploy" style="display: inline-flex; align-items: center;">
+    <img src="../../../assets/render.png" alt="Render Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with Render</span>
+  </a>
+</p>
+
+# Contextful Geometric Pipeline
 
 This example implements a pipeline that answers questions based on documents in a given folder. To get the answer it sends increasingly more documents to the LLM chat until it can find an answer. You can read more about the reasoning behind this approach [here](https://pathway.com/developers/showcases/adaptive-rag).
 

diff --git a/examples/pipelines/contextful_parsing/README.md b/examples/pipelines/contextful_parsing/README.md
@@ -1,3 +1,12 @@
+<p align="left">
+  <a href="https://pathway.com/developers/user-guide/deployment/gcp-deploy" style="display: inline-flex; align-items: center;">
+    <img src="https://www.gstatic.com/pantheon/images/welcome/supercloud.svg" alt="GCP Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with GCP</span>
+  </a> | 
+  <a href="https://pathway.com/developers/user-guide/deployment/render-deploy" style="display: inline-flex; align-items: center;">
+    <img src="../../../assets/render.png" alt="Render Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with Render</span>
+  </a>
+</p>
+
 # Contextful Parsing Pipeline
 
 This example implements a RAG pipeline, similarly to [contextful pipeline](). It uses, however, [Unstructured](https://unstructured.io/) library for parsing documents, e.g. PDFs, which are then split into smaller chunks. 

diff --git a/examples/pipelines/contextful_s3/README.md b/examples/pipelines/contextful_s3/README.md
@@ -1,3 +1,12 @@
+<p align="left">
+  <a href="https://pathway.com/developers/user-guide/deployment/gcp-deploy" style="display: inline-flex; align-items: center;">
+    <img src="https://www.gstatic.com/pantheon/images/welcome/supercloud.svg" alt="GCP Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with GCP</span>
+  </a> | 
+  <a href="https://pathway.com/developers/user-guide/deployment/render-deploy" style="display: inline-flex; align-items: center;">
+    <img src="../../../assets/render.png" alt="Render Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with Render</span>
+  </a>
+</p>
+
 # Contextful S3 Pipeline
 
 This example implements a simple pipeline that answers questions based on documents stored in S3.

diff --git a/examples/pipelines/contextless/README.md b/examples/pipelines/contextless/README.md
@@ -1,3 +1,12 @@
+<p align="left">
+  <a href="https://pathway.com/developers/user-guide/deployment/gcp-deploy" style="display: inline-flex; align-items: center;">
+    <img src="https://www.gstatic.com/pantheon/images/welcome/supercloud.svg" alt="GCP Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with GCP</span>
+  </a> | 
+  <a href="https://pathway.com/developers/user-guide/deployment/render-deploy" style="display: inline-flex; align-items: center;">
+    <img src="../../../assets/render.png" alt="Render Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with Render</span>
+  </a>
+</p>
+
 # Contextless Pipeline
 
 This example implements a pipeline that answers a single question, without any context.

diff --git a/examples/pipelines/demo-document-indexing/README.md b/examples/pipelines/demo-document-indexing/README.md
@@ -1,3 +1,12 @@
+<p align="left">
+  <a href="https://pathway.com/developers/user-guide/deployment/gcp-deploy" style="display: inline-flex; align-items: center;">
+    <img src="https://www.gstatic.com/pantheon/images/welcome/supercloud.svg" alt="GCP Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with GCP</span>
+  </a> | 
+  <a href="https://pathway.com/developers/user-guide/deployment/render-deploy" style="display: inline-flex; align-items: center;">
+    <img src="../../../assets/render.png" alt="Render Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with Render</span>
+  </a>
+</p>
+
 # Realtime Document Indexing with Pathway
 
 This is a basic service for a real-time document indexing pipeline powered by [Pathway](https://github.com/pathwaycom/pathway).

diff --git a/examples/pipelines/demo-question-answering/README.md b/examples/pipelines/demo-question-answering/README.md
@@ -1,3 +1,12 @@
+<p align="left">
+  <a href="https://pathway.com/developers/user-guide/deployment/gcp-deploy" style="display: inline-flex; align-items: center;">
+    <img src="https://www.gstatic.com/pantheon/images/welcome/supercloud.svg" alt="GCP Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with GCP</span>
+  </a> | 
+  <a href="https://pathway.com/developers/user-guide/deployment/render-deploy" style="display: inline-flex; align-items: center;">
+    <img src="../../../assets/render.png" alt="Render Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with Render</span>
+  </a>
+</p>
+
 # Pathway RAG app with always up-to-date knowledge
 
 This demo shows how to create a RAG application using [Pathway](https://github.com/pathwaycom/pathway) that provides always up-to-date knowledge to your LLM without the need for a separate ETL. 

diff --git a/examples/pipelines/gpt_4o_multimodal_rag/README.md b/examples/pipelines/gpt_4o_multimodal_rag/README.md
@@ -1,4 +1,13 @@
-## Multimodal RAG with Pathway: Process your Financial Reports and Tables with GPT-4o
+<p align="left">
+  <a href="https://pathway.com/developers/user-guide/deployment/gcp-deploy" style="display: inline-flex; align-items: center;">
+    <img src="https://www.gstatic.com/pantheon/images/welcome/supercloud.svg" alt="GCP Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with GCP</span>
+  </a> | 
+  <a href="https://pathway.com/developers/user-guide/deployment/render-deploy" style="display: inline-flex; align-items: center;">
+    <img src="../../../assets/render.png" alt="Render Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with Render</span>
+  </a>
+</p>
+
+# Multimodal RAG with Pathway: Process your Financial Reports and Tables with GPT-4o
 
 Get started with multimodal RAG using `GPT-4o` and Pathway. This showcase demonstrates how you can launch a document processing pipeline that utilizes `GPT-4o` in the parsing stage. Pathway extracts information from unstructured financial documents in your folders, updating results as documents change or new ones arrive. 
 

diff --git a/examples/pipelines/local/README.md b/examples/pipelines/local/README.md
@@ -1,3 +1,12 @@
+<p align="left">
+  <a href="https://pathway.com/developers/user-guide/deployment/gcp-deploy" style="display: inline-flex; align-items: center;">
+    <img src="https://www.gstatic.com/pantheon/images/welcome/supercloud.svg" alt="GCP Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with GCP</span>
+  </a> | 
+  <a href="https://pathway.com/developers/user-guide/deployment/render-deploy" style="display: inline-flex; align-items: center;">
+    <img src="../../../assets/render.png" alt="Render Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with Render</span>
+  </a>
+</p>
+
 # Local Pipeline
 
 This pipeline is similar to the [contextful pipeline](),  but relies on local computations, rather than querying external API. To do that it uses [HuggingFace](https://huggingface.co/) for the chat model and [Sentence Transformers](https://www.sbert.net/) for the embedding model.

diff --git a/examples/pipelines/private-rag/README.md b/examples/pipelines/private-rag/README.md
@@ -1,4 +1,13 @@
-## Fully private RAG with Pathway
+<p align="left">
+  <a href="https://pathway.com/developers/user-guide/deployment/gcp-deploy" style="display: inline-flex; align-items: center;">
+    <img src="https://www.gstatic.com/pantheon/images/welcome/supercloud.svg" alt="GCP Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with GCP</span>
+  </a> | 
+  <a href="https://pathway.com/developers/user-guide/deployment/render-deploy" style="display: inline-flex; align-items: center;">
+    <img src="../../../assets/render.png" alt="Render Logo" height="1.2em"> <span style="margin-left: 5px;">Deploy with Render</span>
+  </a>
+</p>
+
+# Fully private RAG with Pathway
 
 This is the accompanying code for deploying the `adaptive RAG` technique with Pathway.