Reflect LLMIntentClassifier removal in docs

Author: maksim-m

docs/docs/docker/building-in-docker.mdx

@@ -67,7 +67,7 @@ The initial project files should all be there, as well as a `models` directory t
 :::note
 If you run into permission errors, it may be because the `rasa/rasa` images
 run as user `1001` as a best practice, to avoid giving the container `root` permissions.
-Hence, all files created by these containers will be owned by user `1001`. See the [Docker documentation](https://docs.docker.com/edge/engine/reference/commandline/run/)
+Hence, all files created by these containers will be owned by user `1001`. See the [Docker documentation](https://docs.docker.com/engine/containers/run/)
 if you want to run the containers as a different user.
 
 :::

docs/docs/llms/llm-intent.mdx

@@ -14,9 +14,13 @@ import LLMIntentClassifierImg from "./llm-IntentClassifier-docs.jpg";
 
 <RasaProLabel />
 
-<RasaLabsLabel />
+:::warning
 
-<RasaLabsBanner version="3.7.0b1" />
+The experimental `LLMIntentClassifier` described on this page has been removed in Rasa 3.10. Please use the
+[Conversational AI with Language Models (CALM)](https://rasa.com/docs/rasa-pro/calm) instead.
+CALM is an LLM-native approach to building reliable conversational AI.
+
+:::
 
 ## Key Features
 
@@ -111,7 +115,7 @@ pipeline:
 
 Defaults to `text-davinci-003`. The model name needs to be set to a generative
 model using the completions API of
-[OpenAI](https://platform.openai.com/docs/guides/text-generation/chat-completions-api).
+[OpenAI](https://platform.openai.com/docs/guides/chat-completions).
 
 If you want to use Azure OpenAI Service, you can configure the necessary 
 parameters as described in the 

docs/docs/llms/llm-nlg.mdx

@@ -157,7 +157,7 @@ nlg:
 
 Defaults to `text-davinci-003`. The model name needs to be set to a generative
 model using the completions API of
-[OpenAI](https://platform.openai.com/docs/guides/text-generation/chat-completions-api).
+[OpenAI](https://platform.openai.com/docs/guides/chat-completions).
 
 If you want to use Azure OpenAI Service, you can configure the necessary
 parameters as described in the

docs/package.json

@@ -115,7 +115,13 @@
             "\\.prototyping\\.rasa\\.com",
             "^https://github\\.com/mit-nlp/MITIE/releases/download/v0\\.4/MITIE-models-v0\\.2\\.tar\\.bz2$",
             "^https://forum.rasa.com/t/rasa-open-source-2-0-is-out-now-internal-draft/35577$",
-            "https://docs-test-001.openai.azure.com"
+            "https://docs-test-001.openai.azure.com",
+            "^https://platform\\.openai\\.com.*",
+            "^https://westus.dev.cognitive.microsoft.com/docs/services/luis-endpoint-api-v3-0$",
+            "^https://westcentralus.dev.cognitive.microsoft.com/docs/services/luis-endpoint-api-v3-0/$",
+            "^https://www.tensorflow.org/api_docs/python/tf/config$",
+            "^https://www.tensorflow.org/api_docs/python/tf/keras/callbacks/TensorBoard$"
+
           ]
         }
       ]