fix(docs): overall fixes in docs (#844)

pages/concepts/agent-services/agent-hosting.mdx

@@ -15,7 +15,7 @@ With the world moving every increasingly towards an automated future where techn
 Deploying a new agent is quick and easy. You can have a new running agent deployed in a matter of a few clicks, and with many pre-made examples you can have an active agents doing tasks for you with ease. You can either choose to build an agent from a blank script, by clicking on **+ Agents**, or you can choose to create your agent based on a specified template, by clicking on **+ Use Case**.
 
     <Callout type="info" emoji="ℹ️">
-      You can checkout the [Creating an Agentverse hosted agent 🤖 ↗️](/guides/agentverse/creating-a-hosted-agent) guide to get yourself started with creating an AI agent within the Agentverse.
+      You can check out the [Creating an Agentverse hosted agent 🤖 ↗️](/guides/agentverse/creating-a-hosted-agent) guide to get yourself started with creating an AI agent within the Agentverse.
     </Callout>
 
 The **My Agents** section manages all the important steps about making sure that your agent stays online. With a targeted 100% uptime, your agent will not sleep unless you tell it to. By it being a hosted agent on the Agentverse, the agent will always be kept up-to-date on the [Almanac ↗️](/references/contracts/uagents-almanac/almanac-overview) contract. This latter one also manages your agent private keys for you too, keeping these safe and secure.

pages/concepts/agent-services/agentverse-intro.mdx

@@ -47,7 +47,7 @@ The [Agentverse: Mailroom ↗️](/concepts/agent-services/agent-mail) is very u
 You can also take advantage of the [Agentverse Functions ↗️](/guides/services/services) feature. In this section, you can enrol agents into the Agentverse offering specific Agent Functions to be retrieved by other users. For example, you can create multiple agents for a hotel to represent a specific function (e.g. one agent for reception, one for individual rooms, and so on). This is important when considering the [DeltaV ↗️](/concepts/ai-engine/deltav) chat. **DeltaV** is a chat interface that allows users to provide human input, which is then translated into several different tasks to guide the [AI Engine ↗️](/concepts/ai-engine/ai-engine-intro) running in the background to find Agents registered on the network offering Functions akin to the ones required by users. For example, users can use DeltaV chat interface to request a specific Function execution (e.g. book a hotel room in London for four nights for two people) and the AI Engine will find agents offering a similar Functions to the one they are looking for.
 
     <Callout type="info" emoji="ℹ️">
-      Checkout the [DeltaV guides ↗️](/guides#deltav) for a better understanding of types of services being retrievable using this tool.
+      check out the [DeltaV guides ↗️](/guides#deltav) for a better understanding of types of services being retrievable using this tool.
     </Callout>
 
     <Callout type="info" emoji="ℹ️">

pages/concepts/ai-engine/ai-engine-intro.mdx

@@ -27,7 +27,9 @@ Check our additional resources to better grasp the concepts and functioning of t
     </Callout>
 
     <Callout type="info" emoji="ℹ️">
-      Checkout the [AI Engine package ↗️](https://pypi.org/project/uagents-ai-engine/) to download it and start integrating your Agents with this tool!
+      check out the [AI Engine package ↗️](https://pypi.org/project/uagents-ai-engine/) to download it and start integrating your Agents with this tool!
+
+      Current version of the package is **0.5.0**.
 
       If you wish to **register your Agents as Functions** on the Agentverse, have a look at the following [guide ↗️](/guides/agentverse/registering-agent-services). Also, if you developed your Agent **locally** and want to register it to be retrievable on DeltaV, here is a [guide ↗️](/guides/agents/running-locally) for you.
     </Callout>

pages/concepts/ai-engine/ai-engine-personalities.mdx

@@ -23,13 +23,13 @@ The following AI Engine personality types are available for users: **Talkative V
 
     - With version **v0.22**, the NextGeneration personality received significant updates, including support for classical [`UAgentResponse` ↗️](/guides/agents/intermediate/ai-engine-compatible-agent) type agents, secondary function execution, and interactive UI elements. Notably, Talkative V3 was set to be replaced by NextGeneration in future updates.
     - Version **v0.23** introduced enhanced session-level memory, tracking credit usage, parallel execution in sync worker, and session termination control within the NextGeneration personality.
-    - Version **v0.24** deployed **NextGeneration personality as the default**, and thus replacing **Talkative V3** personality type. This version focuses on significant stability and scalability improvements, supporting millions of agents. This version also introduced immediate agent registration, enhanced message reliability, UI enhancements, privacy compliance, robust timeout and monitoring systems, infrastructure upgrades, and database and deployment improvements.
+    - Version **v0.24** deployed **NextGeneration personality as the default**, and thus replacing **Talkative** personality type. This version focuses on significant stability and scalability improvements, supporting millions of agents. This version also introduced immediate agent registration, enhanced message reliability, UI enhancements, privacy compliance, robust timeout and monitoring systems, infrastructure upgrades, and database and deployment improvements.
 
 ## Exploring the Feature Set of AI Engine Personalities
 
 Here's a breakdown of the key functionalities offered by each personality:
 
-### Talkative V3 - AI Engine V1
+### Talkative - AI Engine V1
 
     **Focus**: General conversation and task handling.
 

pages/guides/agent-courses/agents-for-ai.mdx

@@ -13,7 +13,7 @@ At any stage, if you encounter issues or have questions about specific terms or
     <Callout type="info" emoji="ℹ️">
       Checkout the [AI Engine package ↗️](https://pypi.org/project/uagents-ai-engine/) to download it and start integrating your Agents with this tool!
 
-      Current version of the package is **0.4.0**.
+      Current version of the package is **0.5.0**.
     </Callout>
 
 ## Quick overview of Fetch.ai
@@ -97,7 +97,7 @@ If you've never installed anything for Agent development, checkout these guides:
 We're going to run our agents locally, and set up a Mailbox on Agentverse.
 
     <Callout type="info" emoji="ℹ️">
-       Checkout the [Utilizing the Agentverse Mailroom service 📬 ↗️](/guides/agentverse/utilising-the-mailbox) for a better understanding of the Agentverse Mailroom feature.
+       Check out the [Utilizing the Agentverse Mailroom service 📬 ↗️](/guides/agentverse/utilising-the-mailbox) for a better understanding of the Agentverse Mailroom feature.
     </Callout>
 
 In this guide, our first agent takes any text and returns a sentiment of contents with **openAI**.
@@ -378,7 +378,7 @@ This Agent is simple again, hopefully you're seeing a pattern here. These Agents
 compliment one another.
 
     <Callout type="info" emoji="ℹ️">
-       Checkout the [Communicating with other agents 📱🤖↗️](/guides/agents/communicating-with-other-agents) guide to check how agents communication works without the AI Engine.
+       Check out the [Communicating with other agents 📱🤖↗️](/guides/agents/communicating-with-other-agents) guide to check how agents communication works without the AI Engine.
     </Callout>
 
 Aside from the different logic, the primary difference in `web_summary_agent.py` is that this agent does not rely on a separate function, and wraps the whole logic in the message handler.

pages/guides/agent-courses/introductory-course.mdx

@@ -275,7 +275,7 @@ The output of the above would look similar to:
     ```
 
     <Callout type="info" emoji="ℹ️">
-      Checkout our [Getting an agent addresses 🤖📫↗️](/guides/agents/getting-uagent-address) guide for an in-depth understanding of these topics.
+      Check out our [Getting an agent addresses 🤖📫↗️](/guides/agents/getting-uagent-address) guide for an in-depth understanding of these topics.
     </Callout>
 
 ### Agents and interval tasks

pages/guides/agents/advanced/agent-envelopes.mdx

@@ -9,7 +9,7 @@ Within the Fetch.ai uAgents Framework, effective communication between [Agents 
 In particular, envelopes provide a secure and reliable way to exchange messages by encapsulating them along with essential metadata. This metadata includes details about the sender and recipient, the session in which the communication occurs, and other information needed to ensure the integrity and authenticity of the messages. By using envelopes, we ensure that messages are correctly routed, verified, and processed, thereby enabling straightforward interoperability among multiple agents and related functions.
 
     <Callout type="info" emoji="ℹ️">
-      Checkout the [Exchange protocol ↗️](/references/uagents/uagents-protocols/exchange-protocol) resource for a better comprehension on this topic.
+      Check out the [Exchange protocol ↗️](/references/uagents/uagents-protocols/exchange-protocol) resource for a better comprehension on this topic.
     </Callout>
 
 ## What Are Envelopes?

pages/guides/agents/getting-started/whats-an-agent.mdx

@@ -8,6 +8,8 @@ The **uAgents Framework** is a lightweight library designed to facilitate the de
 
     <Callout type="info" emoji="ℹ️">
       Head over to the [uagents package ↗️](https://pypi.org/project/uagents/) to download it and start developing your Agents!
+
+      Current version of the package is **0.15.1**.
     </Callout>
 
 ![](src/images/concepts/ai-agents/Agents_interacting.svg)
@@ -38,7 +40,7 @@ Visit the [GitHub repository ↗️](https://github.com/fetchai/uAgents) for mor
 To learn more about how to create and connect Agents technology, check out the resources and guides for the [Agentverse ↗️](/concepts/agent-services/agentverse-intro), [AI Engine ↗️](/concepts/ai-engine/ai-engine-intro), and [DeltaV ↗️](/concepts/deltav/intro)!
 
     <Callout type="info" emoji="ℹ️">
-      If you wish to create AI Engine compatible Agents, you will need to get the `uagents-ai-engine` package installed. Checkout the [package ↗️](https://pypi.org/project/uagents/) to download it and start developing your AI Engine compatible Agents.
+      If you wish to create AI Engine compatible Agents, you will need to get the `uagents-ai-engine` package installed. Check out the [package ↗️](https://pypi.org/project/uagents/) to download it and start developing your AI Engine compatible Agents.
 
       Also, do not miss the [Make your agents AI Engine compatible ↗️](/guides/agents/intermediate/ai-engine-compatible-agent) resource to get yourself started!
     </Callout>

pages/guides/agents/intermediate/agent-functions.mdx

@@ -9,7 +9,7 @@ your agent. Checkout the [Agents 101 for AI Engine ↗️](/guides/agent-courses
     <Callout type="info" emoji="ℹ️">
       Checkout the [AI Engine package ↗️](https://pypi.org/project/uagents-ai-engine/) to download it and start integrating your Agents with this tool!
 
-      Current version of the package is **0.4.0**.
+      Current version of the package is **0.5.0**.
     </Callout>
 
 ## Prerequisites
@@ -140,7 +140,7 @@ Similarly, a **Secondary Function** is an Agent Sub-function providing secondary
 
 ## Functions registration resources
 
-For further information and examples on how to register an Agent Function make it discoverable on DeltaV, checkout our dedicated resources:
+For further information and examples on how to register an Agent Function make it discoverable on DeltaV, check out our dedicated resources:
 
    - [Register Agentverse Functions ↗️](/guides/agentverse/agentverse-functions/registering-agent-services).
    - [Register a coin toss agent as a Function ↗️](/guides/agentverse/agentverse-functions/registering-agent-coin-toss).

pages/guides/agents/intermediate/ai-engine-compatible-agent.mdx

@@ -6,9 +6,9 @@ import { Callout } from 'nextra/components'
  returned a dice roll, however this agent was already ready to be callable by [AI Engine ↗️](/concepts/ai-engine/ai-engine-intro). Let's get into how.
 
     <Callout type="info" emoji="ℹ️">
-      Checkout the [AI Engine package ↗️](https://pypi.org/project/uagents-ai-engine/) to download it and start integrating your Agents with this tool!
+      Check out the [AI Engine package ↗️](https://pypi.org/project/uagents-ai-engine/) to download it and start integrating your Agents with this tool!
 
-      Current version of the package is **0.4.0**.
+      Current version of the package is **0.5.0**.
     </Callout>
 
 ## Prerequisites

pages/guides/agents/intermediate/hosted-agent.mdx

@@ -54,6 +54,6 @@ Output in Agentverse would be:
 
 You can see from this output, **global is never updated**.
 
-To learn more about Agents storage and how it works in Agentverse, take a look at [Storage Functions ↗️]((/guides/agents/intermediate/storage-function).
+To learn more about Agents storage and how it works in Agentverse, take a look at [Storage Functions ↗️](/guides/agents/intermediate/storage-function).
 
 

pages/guides/agents/intermediate/primary-secondary-functions.mdx

@@ -266,7 +266,7 @@ After your function has been executed you can see the `Agent Response` message.
 With that, **you have got a hugging face service which can be discovered and contacted with DeltaV. Awesome!**
 
     <Callout type="info" emoji="ℹ️">
-      Checkout the [AI Engine package ↗️](https://pypi.org/project/uagents-ai-engine/) to download it and start integrating your Agents with this tool!
+      Check out the [AI Engine package ↗️](https://pypi.org/project/uagents-ai-engine/) to download it and start integrating your Agents with this tool!
 
-      Current version of the package is **0.4.0**.
+      Current version of the package is **0.5.0**.
     </Callout>

pages/guides/agents/intermediate/public-private-agents.mdx

@@ -31,7 +31,7 @@ In particular, public and private agents are demarcated by whether the specifica
     <Callout type="warning" emoji="⚠️">
       By default, all agents are public and contactable by everyone but you need to know how to talk to them otherwise they will not answer back to you!
 
-      Checkout [The Almanac ↗️](/concepts/fetch-network/almanac) resource to understand the role of protocols and the Almanac contract in creating private and public agents.
+      Check out [The Almanac ↗️](/concepts/fetch-network/almanac) resource to understand the role of protocols and the Almanac contract in creating private and public agents.
     </Callout>
 
 The distinction between public and private agents is valuable for users, developers and companies within the Fetch.ai ecosystem, as it allows for a flexible approach to data protection while enabling agents to interact efficiently. It is also consistent with the general principles of decentralization and trustless interactions that underpin blockchain and decentralized system technologies.

pages/guides/agentverse/agentverse-functions/registering-agent-coin-toss.mdx

@@ -7,13 +7,13 @@ import { Callout } from 'nextra/components'
 In the [Agentverse Functions: register your Functions on the Agentverse! ↗️](/guides/agentverse/registering-agent-services) guide, you have gotten familiar with the creation of an agent that can be registered as a Function and then be used in [DeltaV ↗️](/concepts/ai-engine/deltav).
 
     <Callout type="info" emoji="ℹ️">
-      Checkout the [Functions ↗️](/guides/agents/intermediate/agent-functions) guide for additional information needed for Agent Functions and their registration on the Agentverse and Fetch network.
+      Check out the [Functions ↗️](/guides/agents/intermediate/agent-functions) guide for additional information needed for Agent Functions and their registration on the Agentverse and Fetch network.
     </Callout>
 
     <Callout type="info" emoji="ℹ️">
-      Checkout the [AI Engine package ↗️](https://pypi.org/project/uagents-ai-engine/) to download it and start integrating your Agents with this tool!
+      Check out the [AI Engine package ↗️](https://pypi.org/project/uagents-ai-engine/) to download it and start integrating your Agents with this tool!
 
-      Current version of the package is **0.4.0**.
+      Current version of the package is **0.5.0**.
     </Callout>
 
 ## Prerequisites

pages/guides/agentverse/agentverse-functions/registering-agent-services.mdx

@@ -168,5 +168,5 @@ Then, this is the full output:
 With that, **you have got an Agent Function which can be discovered and contacted with DeltaV! Awesome!**
 
     <Callout type="info" emoji="ℹ️">
-      For an example on how to register a Local Agent Function on the Agentverse and subsequently retrieve it on DeltaV, checkout this [guide ↗️](/guides/agents/running-locally) helping you to create a locally run Agent with an Agent Function, which is then registered on the Agentverse and retrievable on DeltaV!
+      For an example on how to register a Local Agent Function on the Agentverse and subsequently retrieve it on DeltaV, check out this [guide ↗️](/guides/agents/running-locally) helping you to create a locally run Agent with an Agent Function, which is then registered on the Agentverse and retrievable on DeltaV!
     </Callout>

pages/guides/agentverse/creating-agentverse-agents/creating-a-hosted-agent.mdx

@@ -147,7 +147,7 @@ Additionally, you can now use `agent.run()` method, but this is also not require
 - For security reasons, imports are still restricted to those listed in [Agentverse: allowed imports ↗️](/guides/agentverse/allowed-imports). Soon we will be making available a new hosting environment which much fewer restrictions on the imports.
 
     <Callout type="info" emoji="ℹ️">
-      Checkout the [AVCTL - Agentverse Command Line Interface ↗️](/guides/avctl/avctl) to better understand how to possibly interact with the Agentverse. AVCTL provides multiple features (e.g., authorization and hosting management) allowing developers to log in, set up projects, and deploy Agents on the Agentverse.
+      Check out the [AVCTL - Agentverse Command Line Interface ↗️](/guides/avctl/avctl) to better understand how to possibly interact with the Agentverse. AVCTL provides multiple features (e.g., authorization and hosting management) allowing developers to log in, set up projects, and deploy Agents on the Agentverse.
     </Callout>
 
 ## Register Domain Name

pages/guides/agentverse/creating-agentverse-agents/simple-dice-roll-agent.mdx

@@ -64,7 +64,7 @@ Now click on the **Run** button in the upper right corner of the editor so that
 
 **Great! You have just created your agent starting from a predefined template in Agentverse!** You are now ready to understand how to enroll your agent on the Agentverse and make it retrievable by the [AI Engine ↗️](/concepts/ai-engine/ai-engine-intro) and subsequently [DeltaV↗️](/concepts/ai-engine/deltav).
 
-Checkout the following resources to better grasps all of these concepts:
+Check out the following resources to better grasps all of these concepts:
 
     - [Agentverse Functions ↗️](/guides/agents/intermediate/agent-functions).
     - [Agentverse Functions: register your Agents Functions on the Agentverse! ↗️](/guides/agentverse/agentverse-functions/registering-agent-services).