renamed llmresponserephraser -> contextualresponserephraser

docs/docs/concepts/llm-configuration.mdx

@@ -43,7 +43,7 @@ endpoint configuration:
 
 ```yaml title="endpoints.yml"
 nlg:
-  type: rasa_plus.ml.LLMResponseRephraser
+  type: rasa_plus.ml.ContextualResponseRephraser
 ```
 
 Additional configuration parameters are explained in detail in the documentation
@@ -52,7 +52,7 @@ pages for each of these components:
 - [LLMCommandGenerator](./llm-command-generator.mdx)
 - [FlowPolicy](../llms/flow-policy.mdx)
 - [Docseach](../llms/llm-docsearch.mdx)
-- [LLMResponseRephraser](../llms/llm-nlg.mdx)
+- [ContextualResponseRephraser](../llms/contextual-response-rephraser.mdx)
 
 ## OpenAI Configuration
 
@@ -116,7 +116,7 @@ To configure models per component, follow these steps described on the
 pages for each component:
 
 1. [intent classification instructions](../llms/llm-intent.mdx#llm--embeddings)
-2. [rephrasing instructions](../llms/llm-nlg.mdx#llm-configuration)
+2. [rephrasing instructions](../llms/contextual-response-rephraser.mdx#llm-configuration)
 3. [intentless policy instructions](../llms/llm-intentless.mdx#llm--embeddings)
 4. [docsearch instructions](../llms/llm-docsearch.mdx#llm--embeddings)
 
@@ -344,7 +344,7 @@ should use the [Cohere](https://cohere.ai/) embeddings provider rather than Open
 :::note Only Some Components need Embeddings
 
 Not every component uses embeddings. For example, the
-[LLMResponseRephraser](../llms/llm-nlg.mdx) component does not use embeddings.
+[ContextualResponseRephraser](../llms/contextual-response-rephraser.mdx) component does not use embeddings.
 For these components, no `embeddings` property is needed.
 
 :::

docs/docs/llms/llm-nlg.mdx → docs/docs/llms/contextual-response-rephraser.mdx

@@ -1,5 +1,5 @@
 ---
-id: llm-nlg
+id: contextual-response-rephraser
 sidebar_label: NLG using LLMs
 title: LLMs for Natural Language Generation
 abstract: |
@@ -95,7 +95,7 @@ To use rephrasing, add the following lines to your `endpoints.yml` file:
 
 ```yaml-rasa title="endpoints.yml"
 nlg:
-  type: rasa_plus.ml.LLMResponseRephraser
+  type: rasa_plus.ml.ContextualResponseRephraser
 ```
 
 By default, rephrasing is only enabled for responses that specify
@@ -115,7 +115,7 @@ If you want to enable rephrasing for all responses, you can set the
 
 ```yaml-rasa title="endpoints.yml"
 nlg:
-  type: rasa_plus.ml.LLMResponseRephraser
+  type: rasa_plus.ml.ContextualResponseRephraser
   rephrase_all: true
 ```
 
@@ -131,7 +131,7 @@ by setting the `rephrase_all` property to `true` in the `endpoints.yml` file:
 
 ```yaml-rasa title="endpoints.yml"
 nlg:
-  type: rasa_plus.ml.LLMResponseRephraser
+  type: rasa_plus.ml.ContextualResponseRephraser
   rephrase_all: true
 ```
 
@@ -147,7 +147,7 @@ You can specify the openai model to use for rephrasing by setting the
 
 ```yaml-rasa title="endpoints.yml"
 nlg:
-  type: rasa_plus.ml.LLMResponseRephraser
+  type: rasa_plus.ml.ContextualResponseRephraser
   llm:
     model_name: text-davinci-003
 ```
@@ -170,7 +170,7 @@ The used LLM provider provider can be configured in the
 
 ```yaml-rasa title="endpoints.yml"
 nlg:
-  type: rasa_plus.ml.LLMResponseRephraser
+  type: rasa_plus.ml.ContextualResponseRephraser
   llm:
     type: "cohere"
 ```
@@ -188,7 +188,7 @@ You can specify the temperature to use for rephrasing by setting the
 
 ```yaml-rasa title="endpoints.yml"
 nlg:
-  type: rasa_plus.ml.LLMResponseRephraser
+  type: rasa_plus.ml.ContextualResponseRephraser
   llm:
     temperature: 0.3
 ```
@@ -241,7 +241,7 @@ property in the `endpoints.yml` file:
 
 ```yaml-rasa title="endpoints.yml"
 nlg:
-  type: rasa_plus.ml.LLMResponseRephraser
+  type: rasa_plus.ml.ContextualResponseRephraser
   prompt: |
     The following is a conversation with
     an AI assistant. The assistant is helpful, creative, clever, and very friendly.

docs/docs/llms/llm-configuration.mdx

@@ -43,7 +43,7 @@ endpoint configuration:
 
 ```yaml title="endpoints.yml"
 nlg:
-  type: rasa_plus.ml.LLMResponseRephraser
+  type: rasa_plus.ml.ContextualResponseRephraser
 ```
 
 Additional configuration parameters are explained in detail in the documentation
@@ -52,7 +52,7 @@ pages for each of these components:
 - [LLMCommandGenerator](./llm-command-generator.mdx)
 - [FlowPolicy](../llms/flow-policy.mdx)
 - [Docseach](../llms/llm-docsearch.mdx)
-- [LLMResponseRephraser](../llms/llm-nlg.mdx)
+- [ContextualResponseRephraser](../llms/contextual-response-rephraser.mdx)
 
 ## OpenAI Configuration
 
@@ -116,7 +116,7 @@ To configure models per component, follow these steps described on the
 pages for each component:
 
 1. [intent classification instructions](../llms/llm-intent.mdx#llm--embeddings)
-2. [rephrasing instructions](../llms/llm-nlg.mdx#llm-configuration)
+2. [rephrasing instructions](../llms/contextual-response-rephraser.mdx#llm-configuration)
 3. [intentless policy instructions](../llms/llm-intentless.mdx#llm--embeddings)
 4. [docsearch instructions](../llms/llm-docsearch.mdx#llm--embeddings)
 
@@ -344,7 +344,7 @@ should use the [Cohere](https://cohere.ai/) embeddings provider rather than Open
 :::note Only Some Components need Embeddings
 
 Not every component uses embeddings. For example, the
-[LLMResponseRephraser](../llms/llm-nlg.mdx) component does not use embeddings.
+[ContextualResponseRephraser](../llms/contextual-response-rephraser.mdx) component does not use embeddings.
 For these components, no `embeddings` property is needed.
 
 :::

docs/docs/llms/llm-custom.mdx

@@ -147,7 +147,7 @@ examples and doing a similarity search.
         """
 ```
 
-### LLMResponseRephraser
+### ContextualResponseRephraser
 
 #### rephrase
 

docs/docs/llms/llm-next-gen.mdx

@@ -91,7 +91,7 @@ Here's a breakdown of our approach:
   know where we are in the dialogue and what's been covered.
 - We employ LLMs to update the state of these Flows. These language models
   process user input, adjusting the conversation's course as needed.
-- We use LLMs to [improve the chatbot's responses](./llm-nlg.mdx). These
+- We use LLMs to [improve the chatbot's responses](./contextual-response-rephraser.mdx). These
   language models generate the chatbot's responses, ensuring they feel natural and
   fluent.
 

docs/docs/start-here.mdx

@@ -72,7 +72,7 @@ Out of the box, this assistant can already handle a variety of conversations. Th
 where the user always provides the information the assistant requests.
 But if users change their mind, answer indirectly, or interject with questions, this assistant can handle those cases as well.
 Try out some of these conversations yourself to get a feel for things.
-If you want your assistant to sound a bit more natural, you can activate [contextual rephrasing](./llms/llm-nlg.mdx) of responses.
+If you want your assistant to sound a bit more natural, you can activate [contextual rephrasing](./llms/contextual-response-rephraser.mdx) of responses.
 
 <Tabs
   values={[

docs/sidebars.js

@@ -307,7 +307,7 @@ module.exports = {
       items: [
         "llms/llm-intent",
         "llms/llm-command-generator",
-        "llms/llm-nlg",
+        "llms/contextual-response-rephraser",
         "llms/llm-docsearch",
         "llms/llm-intentless",
         "llms/flow-policy",