Update amazon-bedrock.md - typo fix

Author: oenerayca

content/en/docs/appstore/use-content/platform-supported-content/modules/aws/amazon-bedrock.md

@@ -208,7 +208,7 @@ For additional information about available operations, refer to the sections bel
 
 ### GenAICommons-Based Operations
 
-#### ChatCompletions (With History) {#chat-completions-with-history}
+#### ChatCompletions (With History) and ChatCompletions (Without History) {#chat-completions}
 
 The `ChatCompletions (with history)` and `ChatCompletions (without history)` activities can be used with a variety of supported LLMs. More information can be found about the operations [here](/appstore/modules/genai/commons/#chat-completions).
 
@@ -267,7 +267,7 @@ The history can be enabled using the `SessionId` parameter on the RetrieveAndGen
 This activity was introduced in Amazon Bedrock Connector version 3.1.0.
 {{% /alert %}}
 
-The `Generate Image` operation can be used to generate one or more images. More information can be found about the operations [here](/appstore/modules/genai/commons/#generate-image). Currently *Amazon Titan Image Generator G1* is the only supported model for image generation of the Amazon Bedrock Connector. 
+The `Generate Image` operation can be used to generate one or more images. More information can be found about the operation [here](/appstore/modules/genai/commons/#generate-image). Currently *Amazon Titan Image Generator G1* is the only supported model for image generation of the Amazon Bedrock Connector. 
 
 `GenAICommons.ImageOptions` can be an empty object. If provided, it allows you to set additional options for Image Generation and can be created by using the `Image: Create Options` operation of GenAI Commons.
 
@@ -277,15 +277,15 @@ For Titan Image models, the `Image Generation: Add Titan Image Extension` operat
 
 #### Generate Embeddings (String) {#embeddings-single-string}
 
-The `Generate Embeddings (String)` activity can be used to generate an embedding vector for a given input string with one of the Cohere Embed models or Titan Embeddings v2. More information can be found about the operations [here](/appstore/modules/genai/commons/#embeddings-string).
+The `Generate Embeddings (String)` activity can be used to generate an embedding vector for a given input string with one of the Cohere Embed models or Titan Embeddings v2. More information can be found about the operation [here](/appstore/modules/genai/commons/#embeddings-string).
 
 For Cohere Embed and Titan Embeddings, the request can be associated to their respective EmbeddingsOptions extension object which can be created with the [Embeddings Options: Add Cohere Embed Extension](#add-cohere-embed-extension) or [Embeddings Options: Add Titan Embeddings Extension](#add-titan-embeddings-extension) operation. Through this extension, it is possible to tailor the operation to more specific needs. This operation can easily be replaced or combined with the Embeddings (single string) operation inside of the [OpenAI connector](https://marketplace.mendix.com/link/component/220472). 
 
 Currently, embeddings are available for the Cohere Embed family and or Titan Embeddings v2.
 
 #### Generate Embeddings (Chunk Collection) {#embeddings-chunk-collection}
 
-The `Generate Embeddings (Chunk Collection)` activity can be used to generate a collection of embedding vectors for a given collection of text chunks with one of the Cohere Embed models or Titan Embeddings v2. More information can be found about the operations [here](/appstore/modules/genai/commons/#embeddings-chunk-collection).
+The `Generate Embeddings (Chunk Collection)` activity can be used to generate a collection of embedding vectors for a given collection of text chunks with one of the Cohere Embed models or Titan Embeddings v2. More information can be found about the operation [here](/appstore/modules/genai/commons/#embeddings-chunk-collection).
 
 For each model family, the request can be associated to an extension of the EmbeddingsOptions object which can be created with either the [Embeddings Options: Add Cohere Embed Extension](#add-cohere-embed-extension) or the [Embeddings Options: Add Titan Embeddings Extension](#add-titan-embeddings-extension) operation. Through this extension, it is possible to tailor the operation to more specific needs. This operation can easily be replaced or combined with the Embeddings (chunk collection) operation inside of the [OpenAI connector](https://marketplace.mendix.com/link/component/220472).