update pyvespa links

Author: kkraune

README.md

@@ -12,8 +12,8 @@ This sample application is used to demonstrate multi-vector indexing with Vespa.
 Multi-vector indexing was introduced in Vespa 8.144.19.
 Read the [blog post](https://blog.vespa.ai/semantic-search-with-multi-vector-indexing/) announcing multi-vector indexing.
 
-Go to [multi-vector-indexing](https://pyvespa.readthedocs.io/en/latest/examples/multi-vector-indexing.html)
-to run this sample application using [pyvespa](https://pyvespa.readthedocs.io/en/latest/index.html).
+Go to [multi-vector-indexing](https://vespa-engine.github.io/pyvespa/examples/multi-vector-indexing.html)
+to run this sample application using [pyvespa](https://vespa-engine.github.io/pyvespa/index.html).
 
 The app uses a small sample of Wikipedia articles, where each paragraph is embedded in embedding
 vector space.

examples/fasthtml-demo/deploy_app.ipynb

@@ -14,7 +14,7 @@ Build a text-video search from scratch based on CLIP models with Vespa python AP
 ## Create the application in a Jupyter Notebook
 
 Create, deploy, feed and query the application from [a single notebook](src/python/create-feed-query-text-video-search.ipynb)
-with [Pyvespa](https://pyvespa.readthedocs.io/en/latest/index.html).
+with [Pyvespa](https://vespa-engine.github.io/pyvespa/index.html).
 
 
 ### Demo the search app

multi-vector-indexing/README.md

@@ -121,7 +121,7 @@
    "id": "international-question",
    "metadata": {},
    "source": [
-    "The function `create_text_video_app` below uses [Pyvespa](https://pyvespa.readthedocs.io/en/latest/)\n",
+    "The function `create_text_video_app` below uses [Pyvespa](https://vespa-engine.github.io/pyvespa/)\n",
     "to create an application package with fields to store image embeddings extracted from the videos\n",
     "that we want to search based on the selected CLIP models.\n",
     "It also declares the types of the text embeddings that we are going to send along with the query when searching for images,\n",
@@ -212,7 +212,7 @@
    "id": "assured-possible",
    "metadata": {},
    "source": [
-    "Refer to [Authenticating with Vespa Cloud](https://pyvespa.readthedocs.io/en/latest/authenticating-to-vespa-cloud.html)\n",
+    "Refer to [Authenticating with Vespa Cloud](https://vespa-engine.github.io/pyvespa/authenticating-to-vespa-cloud.html)\n",
     "for any issues with the below (replace with your tenant name):"
    ]
   },
@@ -248,9 +248,7 @@
    "cell_type": "markdown",
    "id": "foreign-complaint",
    "metadata": {},
-   "source": [
-    "Alternatively, check [this guide](https://pyvespa.readthedocs.io/en/latest/getting-started-pyvespa.html) to deploy locally in a Docker container.\n"
-   ]
+   "source": "Alternatively, check [this guide](https://vespa-engine.github.io/pyvespa/getting-started-pyvespa.html) to deploy locally in a Docker container.\n"
   },
   {
    "cell_type": "markdown",

text-video-search/README.md

@@ -22,7 +22,7 @@ Also, 👇
 
 <a href="https://imgflip.com/i/98mhch"><img src="https://i.imgflip.com/98mhch.jpg" title="made at imgflip.com" alt="Funny meme about json output in demo"/></a>
 
-As a prerequisite, you should run [this notebook](https://pyvespa.readthedocs.io/en/latest/examples/visual_pdf_rag_with_vespa_colpali_cloud.html) 
+As a prerequisite, you should run [this notebook](https://vespa-engine.github.io/pyvespa/examples/visual_pdf_rag_with_vespa_colpali_cloud.html) 
 to prepare the data and deploy the Vespa application. 
 
 ## Setting up your .env variables

text-video-search/src/python/create-feed-query-text-video-search.ipynb

@@ -351,7 +351,7 @@ def AboutThisDemo():
         },
         {
             "text": "Notebook to set up Vespa application and feed dataset",
-            "href": "https://pyvespa.readthedocs.io/en/latest/examples/visual_pdf_rag_with_vespa_colpali_cloud.html",
+            "href": "https://vespa-engine.github.io/pyvespa/examples/visual_pdf_rag_with_vespa_colpali_cloud.html",
         },
         {
             "text": "Web App (FastHTML) Code",