diff --git a/pages/concepts.mdx b/pages/concepts.mdx index 23c56788d..9022ee7f4 100644 --- a/pages/concepts.mdx +++ b/pages/concepts.mdx @@ -1,104 +1,335 @@ -# Concepts - -
- The place where you can get yourself familiar with the needed concepts to - start developing on the uAgents Framework and Agentverse services. -
- -import GuidesMdx from "../components/guide-mdx" -import { AgentsIcon, AgentverseIcon ,FetchNetwork, LedgerIcon} from "src/icons/main-page-icons"; - - - -
\ No newline at end of file +import { ImageByTheme } from "../components/mdx"; +import DarkHighLevelDiagram from 'src/images/concepts/about/Dark-high-level-system-diagram.svg'; +import techStack from 'src/images/concepts/tech/I1.png' +import communication from 'src/images/concepts/tech/I2.svg' +import ScalingHosting from 'src/images/scaling-hosting.png'; +import DarkScalingHosting from 'src/images/dark-scaling-hosting.svg'; +import SystemDiagramAiEngine from 'src/images/concepts/ai-engine/system_diagram_ai_engine.png'; +import DarkSystemDiagramAiEngine from 'src/images/concepts/ai-engine/dark_system_diagram_ai_engine.svg'; +import FetPayements from 'src/images/concepts/ai-agents/fetpayment.png'; +import SearchSniuppet from 'src/images/concepts/agentverse/search.png'; +import HotelTasksGoThroughTheEngineToRepresentativeAgents from 'src/images/concepts/ai-engine/hotel_tasks_go_through_the_engine_to_representative_agents.png'; +import DarkHotelTasksGoThroughTheEngineToRepresentativeAgents from 'src/images/concepts/ai-engine/dark_hotel_tasks_go_through_the_engine_to_representative_agents.svg'; +import { Callout } from 'nextra/components' + +# Introducing Fetch.ai; + +Fetch.ai is developing a platform to enable the development of an AI empowered agent based decentralized digital economy. Agents are programs that can make choices on their own for individuals, companies, and devices. Agents are the 'doers' of Fetch.ai ecosystem. + +Agents are flexible problem solvers, capable of completing tasks and tackling difficult issues across many domains. They have the adaptability to handle different activities inside the decentralized economy, whether it's improving supply chain logistics, maintaining solid record-keeping systems, executing computational tasks, or enabling buying and selling interactions. They can even book a train ticket room for you. For this we have developed the uAgents python library, which defines an open communication layer for simple message-based communication and free communication defined by a graph. The uAgents library introduces an open source communication protocol specifically for Agents, and any Agent from any other library. + +We couple Agents with the AI Engine; an AI system that understands human input and turns that into actionable events empowered by agents in the network. AI Engine is an intelligence system that creates dynamic agent workflows. Fetch.ai is also developing Agentverse.ai, the web portal to online Agent functions and offering affordable agent hosting. Agentverse is also the service that wraps the Almanac, allowing you to search and discover Agents within the Ecosystem. + +This all builds into the agent marketplace, a service that allows AI Engine and other Agents to find your agent. This is where our Agent system shines, as any agent from anywhere can register with the uAgents library. + +Underneath this all is the Fetch.ai ledger, it's a blockchain that facilitates the FET token transactions, and decentralized smart contracts. It's essential for tiny payments that agents may make. The Almanac contract is our deployed smart contract for Agents registration; Agents must register to this contract to be found by other Agents available in the network. Agents transact FET tokens to purchase information or actions. You can read more about that [here](). + + + +### The Fetch.ai architecture + +**Agents**, **Agentverse**, **AI Engine**, and **Fetch network**. + + + +View a full resolution of this image [this image](/_next/image?url=%2Fdocs%2F_next%2Fstatic%2Fmedia%2FI1.b224d139.png&w=3840&q=75) + +Agents work across the Fetch.ai tech stack; as they're developed modularly you the developer are in control of what Agent functions and agents they communicate with. + + +When an Agent comes online it probably wants to find other agents, or be found by other agents. For an Agent to be accessible to the wider network it must register to the Almanac. The Almanac is a smart contract storing agents addresses, and their services, referred to as functions. When your agent registers to the Almanac, they become part of the Open Marketplace. This is all facilitated, and paid for with the FET token. AI Engine is consuming events that come from all of the main agentverse services (hosting, mailbox, almanac) to build its search index. Agentverse is the web portal to all of the online Agent functions, as well as the explorer for Open Marketplace. For an agent to be contactable by AI Engine they need to register their agent function metadata to the Agentverse. + + +At a high level, the system isn't too complicated, but let's get into the details. + + +### Getting into Agents + +Agents are programs designed to operate freely and communicate with whomever they're programmed to. Agents can connect, search, and transact in order to create dynamic markets, and they can be programmed to interact both within their environment and with other agents in the network. Because they're siloed, and decentralized they can safely accomplish particular activities and objectives without requiring human participation. We have a very simple guide in our documentation that gets you started on building an agent to be part [of the network ↗️](/guides/agents/getting-started/create-a-uagent). + + +At the simplest level, and agent would work as follows: + + + + + +Of course, many agents in the above workflow can come together to become multi-agents workflows, where single Agents call one another to complete a task. Agents that you design could be programmed to contact known agents, whereas in a dynamic marketplace you may need an agent that you haven't created, searching and interacting with that agent may be the more optimal strategy. + + + +A simple Agent using the uAgents library could be: + +``` +from uagents import Agent, Context, Model + +agent = Agent(name="concept", seed="secret_seed_phrase_concept", endpoint="127.0.0.1", port="8001") + +class Message(Model): + message : str + + +@agent.on_message(model=Message) +async def print_message(ctx: Context, msg : Message): + ctx.logger.info(f"Message received: {msg.message}") + +if __name__ == "__main__": + agent.run() +``` + +This Agent defines it's communication as receiving any Object of `Class Message`, with a value for `message` of type `string`. You can see how this agent behaves, and how to extend this in [our guides](>>) + + +Agents are lightweight programs that can be inserted to existing systems with the ability to simplify the way we see complicated systems. As an example, supply chain management could deploy Agents using the uAgents Framework to improve operations at various stages. Demand forecasting, inventory control, logistics optimization, supplier relationships monitoring, quality control and risk mitigation in all areas can be done with their help. Agents could transform supply chain operations by increasing efficiency, reducing costs, improving accuracy and providing real-time visibility. + +You can view the source code for an agent that monitors inventory levels in [our examples](https://github.com/fetchai/uAgent-Examples/blob/main/2-solutions/inventory-monitoring/src/main.py) + + +Agents thrive on iOT devices such as Raspberry Pi, and there are some great examples of multi agent simulations using uAgents on Raspberry Pi available on [Github](https://github.com/Agents-Lab/sensor-agent) + +### Integrating FET token in your agents + + + +FET token is the necessary payment token to create economic opportunity to your agents. FET allows for token transactions of a tiny size 10^-18 of a FET, we call this a nano fet. This system is built for agent economic gain, the best agents should be profitable. + + +``` +from uagents import Agent, Bureau, Context, Model +from uagents.network import wait_for_tx_to_complete +from uagents.setup import fund_agent_if_low + + ... + +@agent.on_message(model=PaymentRequest, replies=TransactionInfo) + async def send_payment(ctx: Context, sender: str, msg: PaymentRequest): + ctx.logger.info(f"Received payment request from {sender}: {msg}") + + # send the payment + transaction = ctx.ledger.send_tokens( + msg.wallet_address, msg.amount, msg.denom, bob.wallet + ) + + # send the tx hash so other agent can confirm + await ctx.send(alice.address, TransactionInfo(tx_hash=transaction.tx_hash)) + + + ... +``` + +Its very easy to create an agent which sends and received FET. We have two excellent guides to get you started; [Getting Fet token](guides/fetch-network/intro-fet-token) and [Sending tokens with an agent](guides/intermediate/send-tokens) + + +#### LLMs + +Agents can wrap and orchestrate LLMs to create personalized Agents for any task. With the rise of Large Language Models (LLMs) and AI-related products, autonomous intelligent Agents have become the link between these models and tools. They are revolutionizing the way we solve problems, make decisions and collaborate with each other. + +Integrating LLMs into an Agent is relatively trivial, [we have a guide for that too](guides/agents/intermediate/langchain-rag-agent) + + +### Getting started with Agent development! + +Visit the [GitHub repository ↗️](https://github.com/fetchai/uAgents) to see the source code for uAgents, and to keep up-to-date with any update made to the uAgents Framework. + +From there, view the examples on uAgents repository, or start reading our guides, we’d recommend starting with [agent to agent communication]() + + +## The Agentverse + +The Agentverse is a web based platform created so that agents have a human accessible interface. Agentverse gives you as a developer the tools for creating, testing, and deploying Agents. Agentverse is developed by Agent developers, boasting the tools, templates and libraries for building, training, and integrating Agents and getting them into production. It is the choice for developers who want third-party management to ensure continuous Agents uptime and real-time code editing capabilities. + + +The [Agentverse ↗️](https://agentverse.ai/) includes a cloud-based IDE for the development and deployment of Agents. The Agentverse is designed to help you understand the Fetch.ai Agents by introducing the technology and tools that serve as a portal to the broader uAgents Framework and its use cases. + +![](../src/images/guides/agentverse/agentverse_intro.png) + +## Agentverse Marketplace + +The Agentverse Marketplace lets you look for and connect with other Agents. Agents being developed on Agentverse are automatically registered to the [Almanac ↗️](/references/contracts/uagents-almanac/almanac-overview), meaning all agents in the network can find your agent (if you allow). The explore functionality of the marketplace is a twin to the Almanac contract, every agent in the marketplace is on Almanac. Agents in this marketplace *can earn over time for their use. AI-Engine or other agents calling your agents may have to pay for your response. The explore functionality of the marketplace is a twin to the Almanac contract, every agent in the marketplace is on Almanac. +As we just hinted, you may not be willing to share agents' information but rather wanting to keep them private. This is achievable by defining public and private agents. Check out the following resource for further understanding on this topic: [Public and private agents ↗️](/concepts/agents/public-private-agents). + + + + +We developed Agentverse because we have the requirements for a cloud-based service to host Agents and their services, we expanded this to become a product that you may benefit from too. + + +### Integration with wallets + +As we touched on earlier, FET payments between agents are embedded into the uAgents library, as in an open decentralized marketplace it is essential that agents can transact. What we didn’t cover is that by default the uAgents library has support for Fetch.ai wallets. This means that not only can agents interact with the Fetch.ai Ledger to send and receive transactions but it can also query balances, interact with smart contracts, and deploy them. + +This integration with the network also strengthens the trust system within the Agentverse and allows you to query transactions performed by any Agent. You can easily see transactions against an agent address, which allows you to infer the history, or trust of an agent. Of course, there are agents for that too. + +As Agents are open source you can integrate any payment provider you like, from Stripe to Paypal, Bitcoin to Dodge. Take a look at some of [our examples](https://github.com/fetchai/uAgent-Examples/tree/main/2-solutions/stripe-payment-agent) + + + +### Deploy and run Agents + +When it comes to deploying an agent on Agentverse, it's a simple process from start to deploy. You can either choose to build an Agent from a blank script, or you can choose to create your Agent based on a specified template. +On Agentverse.ai you will see we have a My Agents tab, this page allows you to manage your agents and see Agent stats. 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. + +### Scaling + +Agents deployed on Agentverse scale automatically with the number of messages that the Agent receives. The benefit for you is that you do not have to carry the hassle of continuously deploying your Agents, or rolling out your own load balancer. This means that your Agents will continue running and receiving messages without the need of your presence for them to be deployed. Thus, as a developer, you can focus on making the most awesome of Agents. + + + + + + +### Secure runtime + +Agents are built and run in a secure partitioned Python environment. This is important to make sure that your code is safe from malicious attempts to access your information. We also give you the option to subscribe to ban lists, in which there are Agents seen as bad actors which you can ignore easily! + + +### Agentverse: Mailroom / IoT Gateway + +The Agentverse has an additional feature that allows you to set up Mailboxes for your Agents. A mailbox allows you to not have your Agents online all the time. This means that your Agents can retrieve these messages from the Mailroom and take appropriate action when they are back online. + +## AI Engine + +### Introduction + +The AI Engine is a system that understands human text input to convert these into actions, or agent calls. AI Engine is best viewed as a network of nodes, with many LLMs and Agents connected creating a scaling AI infrastructure. The more agents connected, the greater the service of AI Engine becomes. The goal of the AI Engine is to analyze, understand and link human input to agents by facilitating natural language interactions. The AI Engine reads user input, converts it into actionable tasks and selects the most appropriate AI agent registered in the Agentverse to perform the Objective Tasks provided by users. + + + + + +AI Engine shines by its ability to understand users' preferences and goals through contextual understanding. The AI Engine examines trends and turns random inputs into meaningful insights by evaluating previous interactions, these interactions are your own and millions of others. When uncertainty comes into play, the AI Engine solicits feedback from the user to verify that its suggestions and recommendations match the user's end goal, however this is only during training and current open beta release. The goal here is that the AI Engine actively anticipates the needs of users and adapts to them. + + +n addition to the AI Engine's ability to understand different contexts, its smart routing ability allows the AI Engine to perform a careful evaluation of the available agents registered in the [Almanac ↗️](/concepts/agent-services/agentverse-intro); taking into account their performance spectrum and past performance data. This ensures that objectives are assigned to agents with the appropriate expertise and Functions. Basically, AI Engine picks the best agents. + + +AI-Engine understands that a request for an action can't always be completed by one agent, so AI Engine builds dynamic multi agent workflows in the background, on the fly. Enabling agents to solve complex requests as individual actors linked by AI-Engine. + + + +### DeltaV and the AI Engine: enabling user interactions + +DeltaV is a developer tool in the form of a web based chat interface that acts as a link between users and registered agents in the Agentverse. Currently in public beta, it shows how AI Engine streamlines input from humans into actions to be taken by Agents. This webpage is primarily designed for developers to test their agents as part of the open marketplace, and AI Engine agent function pipelines. + + +### Objectives, Primary and Secondary Functions + +At the heart of the AI Engine, there is an architecture consisting of the following components: + + - Objectives are the encapsulation of the user's general goals, communicated in natural language via the DeltaV chat. + + - Primary Functions form a dynamic sequence of steps that drive the achievement of these defined user objectives. Primary functions involve complicated processes, including the allocation of resources and dependencies. Primary Functions are expected to fully or partially fulfill an objective provided by users. + + - Secondary Functions are Agent Sub-functions providing secondary services that likely need additional context or information to carry out the Primary Function. Secondary Functions are executed in combination with the Objective task. The AI Engine would see that the Agent Primary Function can be fulfilled by executing a Secondary Function, thus, it will contact this latter one which may or may not require gaining context directly from the user. + +In this context, a Primary function refers to an agent function that provides a specific action or information requested by the user that is directly accessible via DeltaV. In contrast, a Secondary function also responds to user requests within DeltaV, but typically provides additional or complementary functions that often rely on a prior context or additional information for their execution. For example, while a Primary function might be an agent that provides the user's current account balance, a Secondary function might involve converting the account balance to a different currency, which requires additional context or user input. + + +### Deconstructing tasks + +When a user makes a request, such as “book me a hotel in New York” the AI Engine takes the input and breaks it down into a series of smaller primary and secondary functions, each representing an integral step towards the desired end result. This coordination may be automatic, or in certain situations where the AI Engine is unsure, it may require user input to confirm the function selection. + + + + +Context building plays a crucial role, allowing the AI Engine to continuously improve its understanding by transforming data. Context building is an ongoing process within the AI Engine that involves the continuous improvement of the knowledge base during the AI Engine session. In other words, context building is the continuous act of collecting and/or transforming new knowledge to complete a task. This takes a very similar approach to reinforcement learning, however user interactions are training and evaluating responses. + + +The final step of the AI Engine is smart routing, that is the ongoing process within the AI Engine that makes it aware of all registered Agents and Agent Function according to the objective for which they are best suited for. This process takes into account the context and past performance history of these agents to guide the AI Engine's decision-making process. In this way, the AI Engine selects the most suitable agents, taking into account the agents' functions and their past performance metrics. Trust becomes a key factor, favoring agents with a track record of reliable behavior. Smart routing not only ensures the completion of objectives, but also creates a sense of reliability and efficiency in the operations. + +## The Fetch Network + +### Introduction + +The Fetch Network represents the foundation of the Fetch.ai Ecosystem as it enables the decentralized digital economy driven by [Agents ↗️](/guides/agents/getting-started/whats-an-agent), AI Engine, Agentverse and DeltaV. The Network provides integration with Fetch blockchain technology and ensures security, transparency, and scalability of transactions, and enhanced trust across the overall Ecosystem. + +### The Almanac Contract + +The Almanac contract is an important component within the Fetch Network. It connects together Agents, the Agentverse, and the AI Engine by working as decentralized registry and allowing for agents discoverability and coordination. Whenever agents are registered in the Almanac, they become accessible across the entire Fetch Ecosystem, allowing the AI Engine to dynamically locate and engage with them based on users' or agents' requests and queries. This ensures the accurate and reliable execution of objectives, as the Almanac supports the AI Engine in identifying and deploying the most appropriate agents for any given function being requested for execution, amongst all those registered agents in the Agentverse and Fetch Network. + +The Almanac facilitates remote communication between agents but also provides a layer of trust and verification, ensuring that accurate and up-to-date information is available at all times for everybody. By maintaining an organized directory of agents and their functions, the Almanac empowers the AI Engine to coordinate complex multi-agents workflows efficiently. + +Agents must register within the Almanac to enable remote interactions and be found via the Agentverse Marketplace. You can register your Agents on the Almanac by following this [guide ↗️](/guides/agents/register-in-almanac). You can also explore the [Communicating with other agents ↗️](/guides/agents/communicating-with-other-agents) guide to understand how Agents leverage the Almanac to communicate remotely. + +Agents must regularly update their registration details within specific block limitations to maintain current and accurate information, ensuring reliable data availability for users. + +Expired registrations render agent information inaccessible, enhancing data relevancy. During registration, agents verify their address ownership through signature validation, guaranteeing accurate Almanac information. + + + Head over to the [Almanac contract overview ↗️](/references/contracts/uagents-almanac/almanac-overview) and the [Registration and endpoints weighting ↗️](/references/contracts/uagents-almanac/endpoints) resources for a better overview of the Almanac, its features and how to register agents on it. + + +#### Public and private agents: the role of protocols and Almanac + +Agents offer the flexibility of being designated as either public or private during their development, adapting to your specific requirements. This flexibility is made possible thanks to the Almanac and protocols within the uAgents Framework + + + Checkout the [public and private agents ↗️](/concepts/agents/public-private-agents) resource for a better clarification on this topic. + + +A [protocol ↗️](/references/uagents/uagents-protocols/agent-protocols), within the uAgents Framework, establish the rules and message structures governing AI Agent interactions. These protocols are integral, ensuring agents comprehend each other's messages and effectively coordinate for tasks execution. + +Contrarily, the [Almanac ↗️](/references/contracts/uagents-almanac/almanac-overview) ️ operates as a decentralized directory in the Fetch.ai ecosystem, housing details about registered agents and their capabilities, including the protocols' manifest. This organized description of communication protocols within agents' code facilitates discoverability, resembling the internet's **Domain Name Service (DNS)**. Users can explore and interact with agents via the Agentverse Explorer, filtering agents based on unique protocols' digests. + + + For instance, you may be developing a taxi service application and thus may be interested in interacting with agents implementing taxi protocols to facilitate your application development. + + + + For additional information on the Agentverse and its tools, visit our dedicated [concepts ↗️](/concepts/agent-services/agentverse-intro) and [guides ↗️](/guides#agentverse) resources to start developing your Agents straightforwardly using the Agentverse **Agent Editor**. + + +### Fetch Name Service - FNS + +The [Fetch Name Service (FNS) ↗️](/guides/agents/advanced/name-service) is another key element providing human-readable names for interacting with Agents and Functions. The FNS simplifies resource identification and makes it easier for developers and users to access agents and functions and thus enhancing overall user accessibility. + +### Jenesis + +An additional tool is [Jenesis ↗️](/guides/fetch-network/jenesis/getting-started); it simplifies the development and deployment of smart contracts and decentralized applications (i.e., dApps) on the Fetch Network and other CosmWasm-enabled platforms. Jenesis offers a streamlined environment for developers that reduces the complexity of building blockchain-based solutions and accelerates the deployment of decentralized services and applications. + +### CosmPy + +As a complementary tool to the above ones, [CosmPy ↗️](/guides/fetch-network/cosmpy/install) is a Python-based library that facilitates interactions with Cosmos SDK-based blockchains, including the Fetch Network. CosmPy provides developers with a straightforward way to manage blockchain transactions, write and test smart contracts but also interact with agents; all within the familiar Python environment. + +### Conclusions + +These components together constitute the backbone structure of the Fetch Network. These tools are essential in enabling a decentralized economy of autonomous Agents and AI-driven Agent Functions. By leveraging the Fetch Ledger, Almanac Contract, FNS, Indexer, Jenesis, and CosmPy, the Fetch Network focuses on creating an environment where agents can autonomously manage tasks, interact with each other, and create value in a secure and scalable way. + +The FET token empowers the Fetch Ecosystem, providing the economic incentive and governance framework necessary for the sustainability and evolution of the Network itself. The token acts both as the medium of exchange and the incentive structure for participants, while supporting the Network's governance and staking mechanisms. + + + +\* payments are in closed beta +\** additional payment methods are supported + +\*** \ No newline at end of file diff --git a/pages/concepts/_meta.json b/pages/concepts/_meta.json deleted file mode 100644 index 65b7dfe58..000000000 --- a/pages/concepts/_meta.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - "introducing-fetchai": { - "title": "Introduction to Fetch.ai", - "timestamp": true - }, - "agent-services": { "title": "Agentverse", "timestamp": true }, - "ai-engine": { "title": "AI Engine", "timestamp": true }, - "fetch-network": { "title": "Fetch Network", "timestamp": true } -} diff --git a/pages/concepts/agent-services/_meta.json b/pages/concepts/agent-services/_meta.json deleted file mode 100644 index 60d443890..000000000 --- a/pages/concepts/agent-services/_meta.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "agentverse-intro": { - "title": "Introduction", - "timestamp": true - }, - "agent-hosting": { - "title": "Agentverse: My Agents", - "timestamp": true - }, - "agent-mail": { - "title": "Agentverse: Mailroom / IoT Gateway", - "timestamp": true - } -} diff --git a/pages/concepts/agent-services/agent-hosting.mdx b/pages/concepts/agent-services/agent-hosting.mdx deleted file mode 100644 index 8cbc74a4c..000000000 --- a/pages/concepts/agent-services/agent-hosting.mdx +++ /dev/null @@ -1,63 +0,0 @@ -import { Callout } from 'nextra/components' -import { ImageByTheme } from "components/mdx"; -import AnAgentForEveryone from 'src/images/an-agent-for-everyone.png'; -import DarkAnAgentForEveryone from 'src/images/dark-an-agent-for-everyone.svg'; -import ScalingHosting from 'src/images/scaling-hosting.png'; -import DarkScalingHosting from 'src/images/dark-scaling-hosting.svg'; -import HostingNameService1 from 'src/images/hosting-name-service_1.png'; -import DarkHostingNameService1 from 'src/images/dark-hosting-name-service_1.svg'; - -# Agentverse: My Agents - -The Agentverse My Agents tab enables all users to get quickly started and to deploy agents to the cloud to start connecting and automating operations in an easy and intuitive way. - -## An agent for everyone - -With the world moving every increasingly towards an automated future where technology will play a greater central role in everyone's life, we will all require an agent to represent and help us in interacting and carry out operations with one other. - - - -## Deploy and run agents - -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**. - - - 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. - - -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. - -## Scaling - -The **My Agents** section is designed to scale automatically with the number of messages that your agent receives. The benefit for you is that you do not have to carry the hassle of continuously deploying your agents, given that we run them for you using cloud technology. This means that your agents will continue running and receiving messages without the need of your presence for them to be deployed. Thus, as a developer, you can focus on making the most awesome agent code! - - - -## Secure runtime - -Agents are built and run in a secure partitioned Python environment. This is important to make sure that your code is safe from malicious attempts to access your information. We also give you the option to subscribe to **ban lists**, in which there are agents seen as bad actors which you can ignore easily! - -## Only pay for what an agent does - -Crucially to you and us, **you only pay for what you use!** - -An agent that only checks for an oracle value every 12 hours will be much cheaper to run that an agent which is part of a prediction model. - -## Give your agent a human readable name - -Hosted agents on the Agentverse can be given a human name so that you can find them faster, as can others for any type of development purposes. - - - diff --git a/pages/concepts/agent-services/agent-mail.mdx b/pages/concepts/agent-services/agent-mail.mdx deleted file mode 100644 index 2d133de90..000000000 --- a/pages/concepts/agent-services/agent-mail.mdx +++ /dev/null @@ -1,24 +0,0 @@ -import { Callout } from 'nextra/components' -import { ImageByTheme } from "components/mdx"; -import Mailroom from 'src/images/mailroom.png'; -import DarkMailroom from 'src/images/dark-mailroom.svg'; - -# Agentverse: Mailroom / IoT Gateway - -The **Agentverse Mailroom** is a service that allows you to set up mailboxes for your agents. This mailbox allows you to not have your agents online all the time. This means that your agents can retrieve these messages from the mailroom and take appropriate action when they are back online. - - - The mailroom is particularly valuable when running a server becomes a challenge and an operator service is required. It manages incoming messages sent by other agents and serves as a trusted intermediary for these messages. This way, you can download the messages later without having to maintain a constantly running server for this purpose - - -The mailroom service also enables communication between agents registered in Agentverse and local agents: your local agents can access the APIs in the Agentverse to retrieve the information needed to communicate with the hosted agents registered in the Agentverse platform. - - - -## Next steps - -Have a look at our [Agentverse guides ↗️](/guides#agentverse) and in particular at the [Utilizing the Agentverse Mailroom service ↗️](/guides/agentverse/utilising-the-mailbox) guide for a better understanding of the registration process and to see how local and Agentverse agents communicate with one another using this tool. diff --git a/pages/concepts/agent-services/agentverse-intro.mdx b/pages/concepts/agent-services/agentverse-intro.mdx deleted file mode 100644 index 3e113473d..000000000 --- a/pages/concepts/agent-services/agentverse-intro.mdx +++ /dev/null @@ -1,61 +0,0 @@ -import { Callout } from 'nextra/components' - -# The Agentverse - -The Agentverse is an intuitive platform designed for creating, testing, and deploying customizable Agents. It offers tools and libraries for building, training, and integrating agents into various systems. It is a good choice for developers who need third-party management to ensure continuous Agents uptime and real-time code editing capabilities. - -## Introduction - -The [Agentverse ↗️](https://agentverse.ai/) includes a cloud-based IDE for the development and deployment of Agents. The Agentverse is designed to help you get to grips with Fetch.ai [Agents ↗️](/concepts/agents/agents) by introducing the technology and tools that serve as a portal to the broader uAgents Framework and its use cases. - -![](../../../src/images/guides/agentverse/agentverse_intro.png) - -Agents hosted in the Agentverse are registered in the [Almanac ↗️](/references/contracts/uagents-almanac/almanac-overview) and thus in the Fetch.ai network, where they can be discovered and used to provide a variety of services and use cases. - -## Why Agentverse - -We developed Agentverse because we recognized the need for a cloud-based service to host Agents and the services they can provide. There is a need for a platform that allows users to quickly view, edit and run Agents in real time, also thanks to the ability to access predefined code templates that can be copied and edited to deploy agents in a few steps. - -### Security and decentralization all in one place - -The Agentverse is built on top of Fetch.ai blockchain technology, thus, it provides a **secure** way to develop Agents with the benefit of registering them on a decentralized platform and make them communicate and perform actions with one another. - -### User-friendly approach - -Agentverse is an **easy-to-use platform** that provides users with a straightforward graphical user interface that makes it easy to create and use agents of any kind. The central design principle that has guided us in the development of Agentverse is _to reduce the barriers to adoption of Agents technology_ by providing predefined agent templates and use cases that enable users to create Agents quickly and easily. - - - Have a look at the [Creating an Agentverse hosted agent 🤖 ↗️](/guides/agentverse/creating-a-hosted-agent) for further guidance on how to create Agents on the Agentverse. - - -### More power with template based agents - -There are pre-built agent templates and use cases available in the Agentverse. These easily programmable, template-based agents can be used to guide users and speed up the development process. Template agents can be customized to serve a variety of purposes, even with only basic Python knowledge. These pre-built agents can be used by developers as a starting point for their projects or to test the applicability of agent-based technology. - -### Integration with wallets - -**Agents have wallets**! This means that agents can interact with the [Fetch.ai Ledger ↗️](/concepts/fetch-network/ledger/intro) to send and receive transactions, query balances, interact with contracts, and more. We consider integration with the network layer to be fundamental, as it allows transactions to take place, be registered in the blockchain and enable the use of smart contracts. - -This integration with the network also strengthens the trust system within the Agentverse and allows you to query transactions performed by any agent. - -### More than a simple search and discovery platform! - -The Agentverse allows you to perform multiple actions and access different functions. Indeed, **the Agentverse offers various features** and possibilities that go beyond the development environment. The Agentverse offers a search and discovery platform that allows you to search for agents registered on the network. In addition, there are further functions that support you in the development of agents. - -The [Agentverse: Mailroom ↗️](/concepts/agent-services/agent-mail) is very useful for setting up email-like mailboxes for your agents, allowing them to receive messages even when they are offline and retrieve them when the agent is back online. This means that your agents do not need to be online all the time, saving you costs as a developer. - -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. - - - check out the [DeltaV guides ↗️](/guides#deltav) for a better understanding of types of services being retrievable using this tool. - - - - In this context, it is also possible for you to develop an Agent locally offering some Functions and then register it on the Agentverse and subsequently retrieve it on DeltaV chat interface. Just check our dedicated [guide ↗️](/guides/agents/running-locally) for this. - - -### Shape the future of automation - -Whether you are an experienced developer or a newcomer, the Agentverse welcomes you in the journey of developing Agents for all kinds of your needs! Have a look at our [Agentverse guides ↗️](/guides#agentverse) and the [Agentverse APIs ↗️](/apis#agentverse-apis) to get started. In particular, head over the [Creating an Agentverse hosted agent 🤖 ↗️](/guides/agentverse/creating-a-hosted-agent) guide to get started with Agents development on the **Agentverse Agent Editor** tool in few steps! - -For any additional questions, the Team is waiting for you on [Discord ↗️](https://discord.gg/fetchai) and [Telegram ↗️](https://t.me/fetch_ai) channels. diff --git a/pages/concepts/ai-engine/_meta.json b/pages/concepts/ai-engine/_meta.json deleted file mode 100644 index e2a6eea22..000000000 --- a/pages/concepts/ai-engine/_meta.json +++ /dev/null @@ -1,18 +0,0 @@ -{ - "ai-engine-intro": { - "title": "Introduction", - "timestamp": true - }, - "powering-connections-and-smart-operations-in-deltav": { - "title": "Powering connections and smart operations in DeltaV", - "timestamp": true - }, - "deltav": { - "title": "DeltaV", - "timestamp": true - }, - "ai-engine-personalities": { - "title": "AI Engine Personalities", - "timestamp": true - } -} diff --git a/pages/concepts/ai-engine/ai-engine-intro.mdx b/pages/concepts/ai-engine/ai-engine-intro.mdx deleted file mode 100644 index 8fe216ddf..000000000 --- a/pages/concepts/ai-engine/ai-engine-intro.mdx +++ /dev/null @@ -1,48 +0,0 @@ -import { Callout } from 'nextra/components' -import PackageVersion from 'components/package-version' -import { ImageByTheme } from "components/mdx"; -import SystemDiagramAiEngine from 'src/images/concepts/ai-engine/system_diagram_ai_engine.png'; -import DarkSystemDiagramAiEngine from 'src/images/concepts/ai-engine/dark_system_diagram_ai_engine.svg'; - -# AI Engine - -## Introduction - -The **AI Engine** is a system that combines [Agents ↗️](/concepts/agents/agents) with human-readable text input to create a scalable AI infrastructure that supports Large Language Models (LLMs). It is at the heart of [DeltaV ↗️](/concepts/ai-engine/deltav) and its functionalities. The goal of the AI Engine is to analyze, understand and link human input to agents by facilitating natural language interactions. The AI Engine reads user input, converts it into actionable tasks and selects the most appropriate AI agent registered in the Agentverse to perform the Objective Tasks provided by users. - - - -The AI Engine is characterized by a variety of different tasks. It is able to provide answers to complex queries and then carry out various actions, such as making a booking for a hotel. This is achieved through its ability to understand users' preferences and goals through **contextual understanding**. The AI Engine examines trends and turns random inputs into meaningful insights by evaluating previous interactions. When uncertainty comes into play, the AI Engine solicits feedback from the user to verify that its suggestions and recommendations match the user's end goal. In this way, the AI Engine actively anticipates the needs of users and adapts to them. We look forward to creating an ecosystem in which technology becomes an ally in achieving users' goals. - -In addition to the AI Engine's ability to understand different contexts, its **smart routing** ability also plays a fundamental role. This allows the AI Engine to perform a careful evaluation of the available agents registered in the [Almanac ↗️](/concepts/agent-services/agentverse-intro), taking into account their performance spectrum and past performance data. This ensures that objectives are assigned to agents with the appropriate expertise and Functions. - -## Next steps - -Check our additional resources to better grasp the concepts and functioning of the AI Engine and get yourself started with [DeltaV ↗️](https://deltav.agentverse.ai/) and operations executable on it. Also, head over to the [AI Engine APIs ↗️](/apis#ai-engine-apis) to start building with DeltaV. - - - **Rich Text and Hyperlinks in DeltaV** - - DeltaV supports the use of rich text and hyperlinks within its interface, allowing for enhanced formatting and improved content navigation. - - You can include hyperlinks in DeltaV by using standard HTML link tags. This enables users to create clickable links that can direct to external websites, internal pages, or other resources. For example: - - ``` - Visit Example - ``` - - This feature provides flexibility in linking relevant information directly within your DeltaV content, making it easier for users to access additional resources. Check out this [guide ↗️](/guides/agentverse/agentverse-functions/hyperlinks-and-rich-text-deltav) for further information. - - - - - 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 AI Engine package is . - - 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. - diff --git a/pages/concepts/ai-engine/ai-engine-personalities.mdx b/pages/concepts/ai-engine/ai-engine-personalities.mdx deleted file mode 100644 index fb76601bb..000000000 --- a/pages/concepts/ai-engine/ai-engine-personalities.mdx +++ /dev/null @@ -1,59 +0,0 @@ -# AI Engine Personalities - -## Introduction - -This guide explores the **AI Engine personalities** within Fetch.ai's ecosystem. Let's delve into how these personalities enhance user interactions when operating with AI Engine and DeltaV! - -## The AI Engine personalities: Powering Fetch.ai's Intelligence - -The [AI Engine ↗️](/concepts/ai-engine/ai-engine-intro) stands as the heart of Fetch.ai's AI infrastructure, translating human language inputs into actionable [functions ↗️](/guides/agents/intermediate/agent-functions) for a network of [Agents ↗️](/guides/agents/getting-started/whats-an-agent) to fulfill them. The AI Engine bridges the gap between users and AI by leveraging powerful Large Language Models (LLMs) to understand complex requests. Here's how it works: - - 1. **User input**: the user provide instructions via [DeltaV ↗️](/concepts/ai-engine/deltav) which facilitates smooth interaction with the AI Engine. - 2. **Understanding the request**: the AI Engine employs LLMs to analyze the user's request, grasping the intent and identifying the necessary actions. - 3. **Function delegation**: based on the analysis, the AI Engine breaks down the user's request into executable functions. - 4. **Agent coordination**: the AI Engine then orchestrates a network of agents registered on the Fetch Network to execute those functions, ultimately achieving the initial user's objective. - -AI Engine personalities are not primarily about user experience or preference. Instead, they represent different versions or iterations of the AI Engine itself, each with its own set of features and capabilities. - -The primary reason for introducing different personalities is to manage the development and rollout of new features without disrupting existing functionality. By creating a new personality, developers can experiment with and test new features without affecting the core system. Once these features are stable and mature, they can be integrated into the default personality. - -## A Journey through personality types evolution - -The following AI Engine personality types are available for users: **Talkative V3** and **NextGeneration**. - - - 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** 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. - - With version **v0.25** the Talkative personality (previously associated with AI Engine V1) started to refer to AI Engine V2 (previously available under the Next Generation personality). To preserve AI Engine V1, a new **Legacy personality** had been introduced, with a scheduled removal date of September 13, 2024. With this release the following features were introduced: _Functions Metadata_ (location settings can now be assigned to functions), _Permission System_ (users can now share private function groups with others via email), _Dialogue Execution Improvements_, _Permission Sharing in Python SDK_ (added functionality to the Python SDK) and _Next Generation Personality (i.e., This was a new iteration of the Next Generation personality, now called Talkative) supports location filtering on functions with location metadata based on objectives_. - - Version **v0.26** introduced significant enhancements to the AI Engine; in particular, it introduced **GPT-4o-mini** for enhanced recommendation accuracy within the NextGeneration personality. - -## Exploring the Feature Set of AI Engine Personalities - -Here's a breakdown of the key functionalities offered by each personality: - -### Talkative - - **Focus**: General conversation and task handling. - - **Key Functionalities**: - - Enhanced Function recommendations for improved efficiency. - - Improved context building for natural conversation flow. - - Agent health checks to ensure optimal performance. - -### NextGeneration - - **Focus**: Broad conversational capabilities, advanced functionalities, and scalability. - - **Key Functionalities**: - - _Supports a variety of [Dialogue ↗️](/guides/agents/advanced/dialogues) protocols_ for flexible user interactions and thus allows for agent interactions with websites and PDFs. - - Tracks resource usage for transparency. - - Increased processing speed for faster responses. - - Manages session endings efficiently. - - Offers superior stability and scalability for large-scale applications. - - Completely revamped AI Engine backend for improved performance and future-proofing. - - Utilizes a more sophisticated LLM for enhanced context understanding. - - Employs an advanced recommender system to select optimal functions based on your needs. - -## Choosing the right personality - -We encourage everyone operating on DeltaV to select the **Next Generation** AI Engine personality type. This AI Engine personality stands as a significant personality type offering _enhanced scalability_, _reliability_, and _flexibility_. The major key features include advanced context understanding, improved function recommendations, and most importantly, **the ability to handle multiple dialogue formats**. \ No newline at end of file diff --git a/pages/concepts/ai-engine/deltav.mdx b/pages/concepts/ai-engine/deltav.mdx deleted file mode 100644 index 68ad84d64..000000000 --- a/pages/concepts/ai-engine/deltav.mdx +++ /dev/null @@ -1,19 +0,0 @@ -import { Callout } from 'nextra/components' - -# DeltaV - -## Introduction - -DeltaV works as an AI-based chat interface. DeltaV acts as a front-end interface to the AI Engine, enabling a simple chat interface through which users can enter their requests, which are then translated by the AI Engine into a series of tasks to be performed. - -DeltaV has been developed with the intent to connect users to Agents. DeltaV is the portal to the [AI Engine ↗️](/concepts/ai-engine/ai-engine-intro), [Agents ↗️](/concepts/agents/agents), and the [Agentverse ↗️](/concepts/agent-services/agentverse-intro) platform. - -Developers can employ Fetch.ai Agents technology and encapsulate **Large Language Models (LLMs)**, **Machine Learning (ML)** models, **existing APIs**, and other **business logic** to make [Agent Functions ↗️](/guides/agents/intermediate/agent-functions) accessible via DeltaV. - -Start developing your Agents to encapsulate Agent Functions and register your agents within the **Agentverse** to make such Functions retrievable on DeltaV. - -Checkout the dedicated resources for a better understanding of Agent Functions and registration process on the Agentverse: [Agentverse Functions ↗️](/guides/services/services) and [registering agents as Agent Functions on the Agentverse ↗️](/guides/agentverse/registering-agent-services). Also, checkout this dedicated [guide ↗️](/guides/agents/running-locally) in case you are developing your agents locally. - - - Head to [DeltaV ↗️](https://deltav.agentverse.ai/), sign in and get started with your first request! - diff --git a/pages/concepts/ai-engine/powering-connections-and-smart-operations-in-deltav.mdx b/pages/concepts/ai-engine/powering-connections-and-smart-operations-in-deltav.mdx deleted file mode 100644 index f826eaac8..000000000 --- a/pages/concepts/ai-engine/powering-connections-and-smart-operations-in-deltav.mdx +++ /dev/null @@ -1,55 +0,0 @@ -import { ImageByTheme } from "components/mdx"; -import AiWithPersonalData from 'src/images/concepts/ai-engine/ai_with_personal_data.png'; -import DarkAiWithPersonalData from 'src/images/concepts/ai-engine/dark_ai_with_personal_data.svg'; -import HumanTextIn from 'src/images/concepts/ai-engine/human_text_in.png'; -import DarkHumanTextIn from 'src/images/concepts/ai-engine/dark_human_text_in.svg'; -import HotelTasksGoThroughTheEngineToRepresentativeAgents from 'src/images/concepts/ai-engine/hotel_tasks_go_through_the_engine_to_representative_agents.png'; -import DarkHotelTasksGoThroughTheEngineToRepresentativeAgents from 'src/images/concepts/ai-engine/dark_hotel_tasks_go_through_the_engine_to_representative_agents.svg'; - -# Powering connections and smart operations in DeltaV - -The AI Engine stands at the core of [DeltaV ↗️](https://deltav.agentverse.ai/login) and its features, as it allows users and developers to connect to a wide range of agent-based [functions ↗️](/guides/agents/intermediate/agent-functions). Once an agent is [registered ↗️](/guides/agentverse/registering-agent-services), the offered Agent Function is visible to the AI Engine and it can start connecting users and Agent functionalities. - - - -This system is equipped with personalized capabilities, supported by an internal agent that performs tasks efficiently. An internal agent is created by the AI Engine and made available for communication via the DeltaV user interface. The AI Engine interprets the human text input provided to the agent and starts working asynchronously on your behalf as soon as it receives your intent. This customized method uses Large Language Models (LLMs), which are essential for improving the AI Engine's understanding, coordination and problem-solving capabilities. - -## Establishing connections - -The AI Engine introduces users and developers to a unified ecosystem of agent-based Functions. Once an agent and its Functions are registered in the [Agentverse ↗️](/concepts/agent-services/agentverse-intro) and consequently in the [Almanac ↗️](/references/contracts/uagents-almanac/almanac-overview), they become an integral part of the AI Engine landscape and coordinate dynamic connections between users and Functions. For example, if you ask the DeltaV agent what the weather will be like tomorrow at your location, it will connect to a registered agent in the Almanac and receive the latitude and longitude values of your current location. The weather forecast for that day is then retrieved by the chat agent via a connection to another registered agent which specializes in weather-related Agent Functions. - -## Objectives, Primary and Secondary Functions - -At the heart of the AI Engine, there is an architecture consisting of the following components: - - - **Objectives** are the encapsulation of the user's general goals, communicated in natural language via the DeltaV chat. - - - **Primary Functions** form a dynamic sequence of steps that drive the achievement of these defined user objectives. Primary functions involve complicated processes, including the allocation of resources and dependencies. Primary Functions are expected to fully or partially fulfill an objective provided by users. - - - **Secondary Functions** are Agent Sub-functions providing secondary services that likely need additional context or information to carry out the Primary Function. Secondary Functions are executed in combination with the Objective task. The AI Engine would see that the Agent Primary Function can be fulfilled by executing a Secondary Function, thus, it will contact this latter one which may or may not require gaining context directly from the user. - -In this context, a **Primary function** refers to an agent function that provides a specific action or information requested by the user that is directly accessible via DeltaV. In contrast, a **Secondary function** also responds to user requests within DeltaV, but typically provides additional or complementary functions that often rely on a prior context or additional information for their execution. For example, while a Primary function might be an agent that provides the user's current account balance, a Secondary function might involve converting the account balance to a different currency, which requires additional context or user input. - -## Deconstructing tasks: context building and smart routing - - - -Finding new information is a key focus of the AI Engine to significantly improve the user journey. This is crucial for the execution of Agent Functions, such as booking a hotel room for your holiday in a specific city. In an environment where reservations are centralized, this seems like a simple process. However, for the booking to be successful, the AI Engine must be able to understand the user's input and objectives and communicate with multiple agents. At this stage, the AI Engine's ability to **understand and plan** is very important: the user's goal is broken down into a series of smaller primary and secondary functions, each representing an integral step towards the desired end result. This coordination may be automatic, or in certain situations where the AI Engine is unsure, it may require user input to confirm the function selection. - -**Context building** plays a crucial role, allowing the AI Engine to continuously improve its understanding by transforming data. Context building is an ongoing process within the AI Engine that involves the continuous improvement of the knowledge base during the AI Engine session. In other words, context building is the continuous act of collecting and/or transforming new knowledge to complete a task. - - - -The final step of the AI Engine is **smart routing**, that is the ongoing process within the AI Engine that makes it aware of all registered Agents and Agent Function according to the objective for which they are best suited for. This process takes into account the context and past performance history of these agents to guide the AI Engine's decision-making process. In this way, the AI Engine selects the most suitable agents, taking into account the agents' functions and their past performance metrics. **Trust** becomes a key factor, favoring agents with a track record of reliable behavior. Smart routing not only ensures the completion of objectives, but also creates a sense of reliability and efficiency in the operations. diff --git a/pages/concepts/fetch-network/_meta.json b/pages/concepts/fetch-network/_meta.json deleted file mode 100644 index 25e555241..000000000 --- a/pages/concepts/fetch-network/_meta.json +++ /dev/null @@ -1,12 +0,0 @@ -{ - "intro-fetch-network": { - "title": "Fetch Network Introduction", - "timestamp": true - }, - "native-and-erc20-fet-tokens": { - "title": "Native and ERC-20 FET tokens", - "timestamp": true - }, - "almanac": { "title": "The Almanac contract", "timestamp": true }, - "ledger": { "title": "Ledger", "timestamp": true } -} diff --git a/pages/concepts/fetch-network/almanac.mdx b/pages/concepts/fetch-network/almanac.mdx deleted file mode 100644 index c08345c9a..000000000 --- a/pages/concepts/fetch-network/almanac.mdx +++ /dev/null @@ -1,35 +0,0 @@ -import { Callout } from 'nextra/components' - -# The Almanac - -The **Almanac** contract is a critical component within the Fetch.ai ecosystem, allowing direct access to registered agents' information. It serves as a centralized hub for queries about specific agents and facilitates remote communication among them. - -Agents must register within the Almanac to enable remote interactions and be found via the [Agentverse Marketplace ↗️](/concepts/agent-services/agent-explorer). You can register your Agents on the Almanac by following this [guide ↗️](/guides/agents/register-in-almanac). You can also explore the [Communicating with other agents ↗️](/guides/agents/communicating-with-other-agents) guide to understand how Agents leverage the Almanac to communicate remotely. - -Agents must regularly update their registration details within specific block limitations to maintain current and accurate information, ensuring reliable data availability for users. - -Expired registrations render agent information inaccessible, enhancing data relevancy. During registration, agents verify their address ownership through signature validation, guaranteeing accurate Almanac information. - - - Head over to the [Almanac contract overview ↗️](/references/contracts/uagents-almanac/almanac-overview) and the [Registration and endpoints weighting ↗️](/references/contracts/uagents-almanac/endpoints) resources for a better overview of the Almanac, its features and how to register agents on it. - - -## Public and private agents: the role of protocols and Almanac - -Agents offer the flexibility of being designated as either public or private during their development, adapting to your specific requirements. This flexibility is made possible thanks to the Almanac and protocols within the uAgents Framework - - - Checkout the [public and private agents ↗️](/concepts/agents/public-private-agents) resource for a better clarification on this topic. - - -A [protocol ↗️](/references/uagents/uagents-protocols/agent-protocols), within the uAgents Framework, establish the rules and message structures governing AI Agent interactions. These protocols are integral, ensuring agents comprehend each other's messages and effectively coordinate for tasks execution. - -Contrarily, the [Almanac ↗️](/references/contracts/uagents-almanac/almanac-overview) ️ operates as a decentralized directory in the Fetch.ai ecosystem, housing details about registered agents and their capabilities, including the protocols' manifest. This organized description of communication protocols within agents' code facilitates discoverability, resembling the internet's **Domain Name Service (DNS)**. Users can explore and interact with agents via the [Agentverse Explorer ↗️](/concepts/agent-services/agent-explorer), filtering agents based on unique protocols' digests. - - - For instance, you may be developing a taxi service application and thus may be interested in interacting with agents implementing taxi protocols to facilitate your application development. - - - - For additional information on the Agentverse and its tools, visit our dedicated [concepts ↗️](/concepts/agent-services/agentverse-intro) and [guides ↗️](/guides) resources to start developing your Agents straightforwardly using the Agentverse **Agent Editor**. - diff --git a/pages/concepts/fetch-network/intro-fetch-network.mdx b/pages/concepts/fetch-network/intro-fetch-network.mdx deleted file mode 100644 index 3f69d2ced..000000000 --- a/pages/concepts/fetch-network/intro-fetch-network.mdx +++ /dev/null @@ -1,33 +0,0 @@ -# The Fetch Network - -## Introduction - -The **Fetch Network** represents the foundation of the Fetch.ai Ecosystem as it enables the decentralized digital economy driven by [Agents ↗️](/guides/agents/getting-started/whats-an-agent), [AI Engine ↗️](/concepts/ai-engine/ai-engine-intro), [Agentverse ↗️](/concepts/agent-services/agentverse-intro) and [DeltaV ↗️](/concepts/ai-engine/deltav). The Network provides integration with Fetch blockchain technology and ensures security, transparency, and scalability of transactions, and enhanced trust across the overall Ecosystem. - -### The Almanac Contract - -The [Almanac Contract ↗️](/concepts/fetch-network/almanac) is an important component within the Fetch Network. It connects together Agents, the Agentverse, and the AI Engine by working as decentralized registry and allowing for agents discoverability and coordination. Whenever agents are registered in the Almanac, they become accessible across the entire Fetch Ecosystem, allowing the AI Engine to dynamically locate and engage with them based on users' or agents' requests and queries. This ensures the accurate and reliable execution of objectives, as the Almanac supports the AI Engine in identifying and deploying the most appropriate agents for any given function being requested for execution, amongst all those registered agents in the Agentverse and Fetch Network. - -The Almanac facilitates remote communication between agents but also provides a layer of trust and verification, ensuring that accurate and up-to-date information is available at all times for everybody. By maintaining an organized directory of agents and their functions, the Almanac empowers the AI Engine to coordinate complex multi-agent workflows efficiently. - -### Fetch Name Service - FNS - -The [Fetch Name Service (FNS) ↗️](/guides/agents/advanced/name-service) is another key element providing human-readable names for interacting with Agents and Functions. The FNS simplifies resource identification and makes it easier for developers and users to access agents and functions and thus enhancing overall user accessibility. - -### Fetch Ledger - -The [Fetch Ledger ↗️](/concepts/fetch-network/ledger/intro) is an additional central component of the Fetch Network. It provides a secure, decentralized, and transparent record of all transactions and data exchanges that take place within the Fetch Ecosystem itself. The Ledger uses the [FET token ↗️](/concepts/fetch-network/native-and-erc20-fet-tokens) to facilitate transactions, agent interactions, and smart contracts execution, but it also to ensure that the integrity and efficiency of the Network is maintained. - -### Jenesis - -An additional tool is [Jenesis ↗️](/guides/fetch-network/jenesis/getting-started); it simplifies the development and deployment of smart contracts and decentralized applications (i.e., dApps) on the Fetch Network and other CosmWasm-enabled platforms. Jenesis offers a streamlined environment for developers that reduces the complexity of building blockchain-based solutions and accelerates the deployment of decentralized services and applications. - -### CosmPy - -As a complementary tool to the above ones, [CosmPy ↗️](/guides/fetch-network/cosmpy/install) is a Python-based library that facilitates interactions with Cosmos SDK-based blockchains, including the Fetch Network. CosmPy provides developers with a straightforward way to manage blockchain transactions, write and test smart contracts but also interact with agents; all within the familiar Python environment. - -### Conclusions - -These components together constitute the backbone structure of the Fetch Network. These tools are essential in enabling a decentralized economy of autonomous Agents and AI-driven Agent Functions. By leveraging the Fetch Ledger, Almanac Contract, FNS, Jenesis, and CosmPy, the Fetch Network focuses on creating an environment where agents can autonomously manage tasks, interact with each other, and create value in a secure and scalable way. - -The FET token empowers the Fetch Ecosystem, providing the economic incentive and governance framework necessary for the sustainability and evolution of the Network itself. The token acts both as the medium of exchange and the incentive structure for participants, while supporting the Network's governance and staking mechanisms. \ No newline at end of file diff --git a/pages/concepts/fetch-network/ledger/_meta.json b/pages/concepts/fetch-network/ledger/_meta.json deleted file mode 100644 index e683007fe..000000000 --- a/pages/concepts/fetch-network/ledger/_meta.json +++ /dev/null @@ -1,4 +0,0 @@ -{ - "intro": { "title": "Introduction", "timestamp": true }, - "validators": { "title": "Validators", "timestamp": true } -} diff --git a/pages/concepts/fetch-network/ledger/intro.mdx b/pages/concepts/fetch-network/ledger/intro.mdx deleted file mode 100644 index 7c9b4b715..000000000 --- a/pages/concepts/fetch-network/ledger/intro.mdx +++ /dev/null @@ -1,27 +0,0 @@ -import { Callout } from 'nextra/components' - -# Fetch Ledger - -## Introduction - -A **ledger** refers to a decentralized and distributed digital book that records all transactions across a network. This is used to ensure transparency and security of transactions and operations undertaken on that network. - -Within this context, the **Fetch Ledger** developed by Fetch.ai constitutes the underlying infrastructure for various decentralized applications and contracts. It employs a consensus mechanism where [validators ↗️](/concepts/fetch-network/ledger/validators) are responsible for validating transactions and creating new blocks in the [blockchain ↗️](/concepts/fetch-network/ledger/validators#overview-blockchains-consensus-and-validators). The ledger utilizes Fetch native cryptocurrency, FET, which is used for various activities within the network, including transaction fees and staking. The ledger also supports features such as [multi-signature keys ↗️](/guides/fetch-network/ledger/cli/multisig-keys), allowing users to control [keys ↗️](/guides/fetch-network/ledger/cli/keys) in different configurations. - -The fetchhub [mainnet ↗️](/concepts/fetch-network/ledger/validators#test-network-testnet-vs-main-network-mainnet) forms the core of the Fetch.ai ecosystem. In here, you will find all information to setup your client and connect on the network. - - - Head over to our [guides ↗️](/guides) section and get yourself started with the ledger [installation ↗️](/guides/fetch-network/ledger/installation) and different executable operations. Also, you can checkout our [GitHub repository ↗️](https://github.com/fetchai/fetchd) to further enhance your understanding of these topics. - - You can also visit the [references ↗️](/references) section for further information on ledger related topics, including [active networks ↗️](/references/ledger/active-networks) specifications, [ledger versions ↗️](/references/ledger/versions), and the [Command Line Interface (CLI) ↗️](/guides/fetch-network/ledger/cli/intro) section for guidance on how to install and configure the `fetchd` client and perform different operations within the ledger using the CLI. - - -This documentation covers the things you need to know in order to prepare yourself and start developing on the Fetch network. - -## Test networks - -The starting point for most users is [the test network ↗️](/references/ledger/active-networks#test-nets). Our test network (testnet) provides you with test tokens with no value, that you can safely experiment with through the [faucet ↗️](/guides/fetch-network/ledger/faucet). - - - This documentation is currently under construction, and the content may not be up-to-date. - diff --git a/pages/concepts/fetch-network/ledger/validators.mdx b/pages/concepts/fetch-network/ledger/validators.mdx deleted file mode 100644 index 268d342cb..000000000 --- a/pages/concepts/fetch-network/ledger/validators.mdx +++ /dev/null @@ -1,81 +0,0 @@ -import { Callout } from 'nextra/components' - -# Validators - -## Overview: blockchains, consensus and validators - -A **blockchain** is a series of data records that functions as a distributed, replicated digital ledger of transactions across a network of computer systems. On blockchains, the records of transactions are compiled into **blocks** which are linked together to form a chain. Thus, blockchains consists of a stable chain of blocks and each one of these blocks stores a list of previously confirmed transactions. - -These transactions take place inside a peer-to-peer (P2P) global network, thus, blockchains are considered minimize and immune to censorship. A blockchain network serves as a decentralized ledger since it is maintained by several computers located all over the world. This implies that each participant, namely a **node**, keeps a copy of the blockchain data and interacts with other participants to make sure that everyone is aware of the same information stored in the block. - -A blockchain, including the **Fetch.ai Ledger**, provides a secure and transparent way to record transactions, enabling trustless interactions between parties and removing the need for a central authority to overlook transactions. - - - This is especially crucial in decentralized systems in which multiple parties need to engage in secure and verifiable transactions. Despite the absence of a central authority to confirm and authenticate the transactions, every blockchain transaction is considered totally safe and validated. - - -Only the presence of a **consensus protocol** makes this feasible. A consensus algorithm allows every node in the blockchain network to agree on the distributed ledger's current state. The consensus protocol ensures that all nodes in the network reach a common agreement on the order and validity of transactions. - -More specifically, a **node** is any device or computer that participates in the network by maintaining a copy of the blockchain ledger, validating transactions, and broadcasting them to other nodes. Nodes can be categorized into different types, including **full** and **validator nodes**. These latter ones are specific type of node responsible for participating in the consensus process. These validate transactions, create new blocks, and contribute to the security and operation of the blockchain network. Validator nodes typically require a significant amount of cryptocurrency to be staked and which serves as collateral and as an incentive for them to act honestly. - -**The most well-known consensus mechanisms** are: - - - **Proof of Work (PoW)**: this is the original consensus protocol used by Bitcoin. It requires nodes (i.e. miners) to perform computationally intensive tasks to validate transactions and create new blocks. The first miner to solve the mathematical puzzle gets to add a block to the blockchain. - - - **Proof of Stake (PoS)**: in this protocol, nodes (i.e. validators) are chosen based on the amount of cryptocurrency they hold and are willing to stake as collateral. Validators take turns proposing and validating blocks, and they earn rewards for their participation in the form of transaction fees and block. - -**Compensation and incentives for validators** can take the form of: - - - **Block rewards**: in PoW and some PoS systems, validators are rewarded with newly created cryptocurrency tokens for successfully adding a new block to the blockchain. - - - **Transaction fees**: validators may receive transaction fees paid by users for including their transactions in a block. - - - **Delegation rewards**: in PoS networks, validators who receive delegated stakes from token holders may share a portion of the rewards with their delegators. This encourages token holders to delegate their stakes to reputable validators. - - - **Slashing penalties**: while not a form of compensation, validators can be penalized (i.e. slashed) for malicious behavior or violations of network rules. The penalties are typically deducted from the validator's committed stake. - -In this context, the Fetch.ai Ledger relies on a set of validators that are responsible for committing new blocks in the blockchain. These validators participate in the consensus protocol by broadcasting votes which contain cryptographic signatures signed by each validator's private key. As previously highlighted, validator candidates can have FET delegated or staked to them by token holders. The validators are determined by who has the most stake delegated to them. The top validator candidates with the most stake become **active validators** within the network. - - - If validators double sign, are frequently offline or do not participate in governance, their staked FET (including FET of users that delegated to them) can be slashed. The penalty depends on the severity of the violation. - - -### Test network (Testnet) vs Main Network (Mainnet) - -We can distinguish between: - - - **Testnet**: it is a separate blockchain environment that developers and users can use to test new features or applications without risking real tokens. It allows for experimentation in a controlled environment. - - - **Mainnet**: it is the actual production blockchain where real transactions occur with real tokens. It is the live version of the blockchain. - - - By setting up and experimenting on a testnet first, developers can ensure that everything works as intended before deploying it on the mainnet. This helps in avoiding potential issues or vulnerabilities in a live environment. - - -## Set up a validator node - -If you are willing to set up a validator node on the Fetch network, visit our dedicated [guide ↗️](/guides/fetch-network/ledger/setup-validator-node). - -### Hardware requirements - -The hardware resources for running a validator node largely depend on the network load. As a _recommended configuration_, we suggest the following requirements: - - - 2 x CPU, either Intel or AMD, with the SSE4.1, SSE4.2 and AVX flags (use lscpu to verify). - - 8 GB RAM. - - 500 GB SSD. - - 100 Mbit/s always-on internet connection. - - Linux OS (Ubuntu 18.04 or 20.04 recommended)/MacOS. - -Up-time is incredibly important for being a validator. It is expected that validators will have appropriate redundancies for compute, power, connectivity and so on. While the blockchain itself is highly replicated, it is also expected that validators will perform local storage backups in order to minimize validator down-time. - -### Set up a website for your validator - -Set up a dedicated validator's website and signal your intention to become a validator on our [Discord ↗️](https://discord.gg/fetchai) server. This is important since delegators will want to have information about the entity they are delegating their FET to. - -This is not necessary, however, it is recommended given that as a validator on the network, you will want to get other community users to delegate stake to your validator. The higher the delegated stake to a specific validator, the greater the share of the block rewards it will take. - -## Community - -We highly recommend to check out the validator community on the discord channel for more information and to check the latest announcements about becoming a validator within the Fetch.ai network: - - - [Discord ↗️](https://discord.gg/fetchai). diff --git a/pages/concepts/fetch-network/native-and-erc20-fet-tokens.mdx b/pages/concepts/fetch-network/native-and-erc20-fet-tokens.mdx deleted file mode 100644 index 6bbdd68b3..000000000 --- a/pages/concepts/fetch-network/native-and-erc20-fet-tokens.mdx +++ /dev/null @@ -1,11 +0,0 @@ -## Native and ERC-20 FET tokens - -The Fetch.ai (FET) token is the utility token and the key medium of exchange on the Fetch.ai network. FET can be used to pay for services in the Fetch ecosystem and network transaction fees. Users can also choose to stake FET to participate in securing the network via its Proof-of-Stake (PoS) consensus mechanism and earn rewards in return for contributing to [validator ↗️](/concepts/fetch-network/ledger/validators) nodes. - -The Fetch.ai team initially developed the FET utility token on an [ERC-20 contract ↗️](https://etherscan.io/token/0xaea46A60368A7bD060eec7DF8CBa43b7EF41Ad85) on the Ethereum network while finishing the work on the Fetch.ai native main network (Main-net). This helped developers across the world get their hands on the FET tokens earlier and kickstart the process of developing innovative solutions within the Fetch.ai ecosystem. FET, as an ERC-20 token on the Ethereum contract has never been Fetch.ai's end game because the Ethereum chain does not offer the degree of scalability needed by the kinds of applications the Fetch.ai ecosystem aims for. - -With the launch of the Fetch.ai Mainnet, the native FET became available. This meant that users operating on the Fetch.ai network no longer needed to hold any token (e.g. ETH or BTC) associated with any other network. It is only the native FET token that fuels the Fetch.ai ecosystem and its applications. - -ERC-20 FET tokens are still in circulation and currently co-exist with native FET tokens and can be [transferred from one to the other ↗️](/guides/fetch-network/how-to-convert-fet-to-and-from-erc20) easily on the Fetch.ai network. All of the ERC-20 FET tokens will ultimately become native FET tokens, but in the foreseeable future both will live side by side. FET tokens can be purchased from different [centralized or decentralized exchanges ↗️](https://coinmarketcap.com/currencies/fetch/#Markets). - -However, keep in mind that certain exchanges may buy or sell one type of FET or the other. diff --git a/pages/concepts/introducing-fetchai.mdx b/pages/concepts/introducing-fetchai.mdx deleted file mode 100644 index 9b2b41f72..000000000 --- a/pages/concepts/introducing-fetchai.mdx +++ /dev/null @@ -1,99 +0,0 @@ -import { ImageByTheme } from "../../components/mdx"; -import HighLevelDiagram from 'src/images/concepts/about/High-level-system-diagram.png'; -import DarkHighLevelDiagram from 'src/images/concepts/about/Dark-high-level-system-diagram.svg'; -import AgentsInteracting from 'src/images/concepts/ai-agents/Agents_interacting.png'; -import DarkAgentsInteracting from 'src/images/concepts/ai-agents/Dark_agents_interacting.svg'; -import DecentralisedNetwork from 'src/images/concepts/ai-agents/decentralised_network.png'; -import DarkDecentralisedNetwork from 'src/images/concepts/ai-agents/Dark_decentralised_network.svg'; - -# Introducing Fetch.ai: pioneering an AI powered decentralized digital economy - -**Fetch.ai** is developing a platform to enable the development of an AI empowered decentralized digital economy. _Agents_ are programs that can make choices on their own for individuals, companies, and devices. Agents are the actors, and the heart of Fetch.ai ecosystem. - -Agents are flexible problem solvers, capable of not just completing tasks but also tackling difficult issues across several domains. Agents have the adaptability to handle different activities inside the decentralized economy, whether it's improving supply chain logistics, maintaining solid record-keeping systems, executing computational tasks, or enabling buying and selling interactions. They might even book a hotel room for you. - -We couple agents with AI-Engine, the AI system that understands human input and turns that into actionable events empowered by agents in the network. AI-engine is an intelligence system which create dynamic agent workflows. Agentverse offers cheap agent hosting and the Fetch Network provides an open layer of trust. - -These services make up the core architecture of Fetch.ai - -### The architecture - -**Agents**, **Agentverse**, **AI Engine**, and **Fetch network**. - -Agents register to Almanac so that they can be discovered in the network by other agents. Agents may register their functions to Agentverse so that AI-Engine can index these agents so that they can be called by AI-Engine. The Fetch network offers a layer of truth and trust by inherently being open. - - - -### Agents: the core - -**Agents** are programs designed to operate freely and communicate with whomever they're programmed to. Agents can connect, search, and transact in order to create dynamic markets, and they can be programmed with logic to interact both within their environment and with other agents in the network. Because they're siloed, and decentralized they can safely accomplish particular activities and objectives without requiring human participation. Our documentation gets your started on building an agent to be part [of the network ↗️](/guides/agents/getting-started/create-a-uagent) - -Agents can come together to become multi-agent workflows, single agents which call one another to complete a task. This can be done natively, or with AI-Engine. - -Agents are built with the **uAgents Framework**, a lightweight library designed to facilitate the development of decentralized **Agents**. At the uAgents core is an open sourced communication protocol for agents. - - - -Agents can fundamentally change the way we see complicated systems. For example, supply chain management could deploy Agents using the uAgents Framework to improve operations at various stages. Demand forecasting, inventory control, logistics optimization, supplier relationships monitoring, quality control and risk mitigation in all areas can be done with their help. Agents could transform supply chain operations by increasing efficiency, reducing costs, improving accuracy and providing real-time visibility. - -These agents are the building blocks that allow developers to gain access to the tools and resources provided by the uAgents Framework, enabling them to create and participate in intelligent and self-managed systems that can be used in various real-world domains. - - - -Agents can wrap and cannibalize LLMs to create personalized agents for any task. With the rise of Large Language Models (LLMs) and AI-related products, autonomous intelligent agents have become the link between these models and tools. They are revolutionizing the way we solve problems, make decisions and collaborate with each other. - -The concept of agents refers to autonomous, decentralized micro-systems that overcome conventional limitations. Agents provide a gateway to a future where intelligent agents alongside the Fetch network and the [AI Engine ↗️](/concepts/ai-engine/ai-engine-intro), can communicate, negotiate and collaborate to streamline complex tasks, solve complicated problems and improve decision-making processes in various fields. - -### The Agentverse: your gateway to Agents - -The **Agentverse** is a Software as a Service (SaaS) platform built primarily for the creation and registration of Agents solutions. This platform enables the smooth deployment and management of agents, as well as their development and registration. This is an easy approach for managing and hosting your agents all in one place. - -The Agentverse provides multiple use cases ranging from simple "Hello World" to AI-driven recommendation systems. These use cases are only a click away from being edited, tweaked, and deployed for yourself. - -You can post your agent(s) and their functions on Agentverse so that the AI Engine can quickly find them and promote them to other users or agents via DeltaV. - -### DeltaV and the AI Engine: enabling user interactions - -**DeltaV** is a chat interface that acts as a link between users and registered agents in the Agentverse. It streamlines connections to these agents and wraps agent functions in a human-readable way, allowing everyone to easily obtain and query for different types of Functionalities. DeltaV is primarily a developer tool to interact with your deployed agents. - -The **AI Engine** is at the heart of DeltaV's functionalities; the AI Engine's aim is to parse, comprehend, and link human input to agents by facilitating natural language interactions. The AI Engine reads user inputs, converts them into actionable objectives, and selects the most suitable Agent registered in the Agentverse for objective task execution. - -### The Fetch.ai Network: the foundations - -The **Fetch.ai network** serves as the foundation of Fetch.ai's entire ecosystem, underpinning and empowering the functionalities of Agents, the Agentverse, DeltaV, and the AI Engine. This is the structural framework that enables the decentralized digital economy envisioned by Fetch.ai. - -The Fetch.ai network is composed of multiple essential elements; at the networks core is the [Almanac contract ↗️](/concepts/fetch-network/almanac), the [Fetch Name Service ↗️](/guides/agents/advanced/name-service), the [Fetch ledger ↗️](/concepts/fetch-network/ledger/intro), and the [FET Token ↗️](/concepts/fetch-network/native-and-erc20-fet-tokens). These web3 components are essential for a decentralized network for AI agents, and enable an easier path to developing your ideas and solutions and making them discoverable to a wider audience. - -At the heart of the Fetch.ai network lies the **Almanac contract**. It operates as a comprehensive repository, storing critical information about Agents, and it is crucial for the execution of various functionalities. The Almanac is a point of truth and a place to search for all registered agents. This contract enables the smooth exchange of data and ensures the efficient functioning of Agents within the Fetch.ai ecosystem. - -The **Fetch Name Service** works as a decentralized naming system which simplifies resource identification within the network. This service offers human-readable naming conventions and facilitates easy access and interaction with decentralized services and Agents. - -The backbone of Fetch.ai decentralized infrastructure is represented by the **Fetch ledger**. It acts as a secure and immutable record-keeping system and provides a transparent record of transactions, fostering trust and reliability across the network. The Fetch ledger supports the decentralized economy, ensuring secure data sharing and transactional integrity. - -The overall system we depicted runs on a specific fuel: **FET tokens**. These tokens hold intrinsic value and utility, drive transactions, promote active participation, and empower various decentralized services within the Fetch network. FET serves as a medium of exchange and facilitates interactions among users, Agents, and Functions within the Fetch ecosystem. - -### Next steps - -The foundational structure set by the Fetch network serves as a launchpad for the creation, cooperation, and integration of the many tools and technologies available inside the Fetch.ai ecosystem. The integration of the Fetch.ai network with Agents, the Agentverse, and DeltaV propels the Fetch.ai ecosystem to propose a new paradigm in how operations are carried out and Agent functions are provided within a decentralized digital economy environment. - -This way, Fetch.ai presents a shift towards a future where the benefits of AI and technology are available to everybody! - -For a deeper dive into Fetch.ai's concepts, tools, and components building up this vision, have a look at the following resources: - - - [Agents ↗️](/concepts/agents/agents) - - [The AI Engine ↗️](/concepts/ai-engine/ai-engine-intro) - - [The Agentverse ↗️](/concepts/agent-services/agentverse-intro) - - [DeltaV ↗️](/concepts/ai-engine/deltav) - - [Fetch Network ↗️](/concepts#fetch-network) diff --git a/src/images/concepts/tech/I1.svg b/src/images/concepts/tech/I1.svg new file mode 100644 index 000000000..d4c86d6e0 --- /dev/null +++ b/src/images/concepts/tech/I1.svg @@ -0,0 +1,286 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/src/images/concepts/tech/I2.svg b/src/images/concepts/tech/I2.svg new file mode 100644 index 000000000..85bd8ec03 --- /dev/null +++ b/src/images/concepts/tech/I2.svg @@ -0,0 +1,89 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +