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Merge pull request #2364 from valory-xyz/chore/update-docs
Chore (docs): New naming convention
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.github/PULL_REQUEST_TEMPLATE.md

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@@ -26,7 +26,7 @@ _Put an `x` in the boxes that apply._
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- [ ] I am making a pull request against the `main` branch (left side). Also you should start your branch off our `main`.
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- [ ] Lint and unit tests pass locally with my changes
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- [ ] I have added tests that prove my fix is effective or that my feature works
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- [ ] I have locally run services that could be impacted and they do not present failures derived from my changes
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- [ ] I have locally run AI agents that could be impacted and they do not present failures derived from my changes
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- [ ] Public-facing documentation has been updated with the changes affected by this PR. Even if the provided contents are not in their final form, all significant information must be included.
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- [ ] Any backwards-incompatible/breaking change has been clearly documented in the upgrading document.
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CONTRIBUTING.md

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- Always use guard clauses where possible. This leads to more efficient code that has less nesting and is much easier to read.
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### Agent development
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### Agent blueprint development
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You can find several general recommendations in the **Considerations to Develop FSM Apps** section in our documentation [here](https://stack.olas.network/open-autonomy/key_concepts/fsm_app_introduction/).
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You can find several general recommendations in the **Considerations to Develop FSM Apps** section in our documentation [here](https://stack.olas.network/open-autonomy/key_concepts/fsm_app_introduction/).

README.md

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</a>
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</p>
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**Open Autonomy** is a framework for the creation of **agent services**: off-chain
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autonomous services which run as a multi-agent-system (MAS) and offer enhanced functionalities
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on-chain. Agent services expand the range of operations that traditional
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**Open Autonomy** is a framework for the creation of **AI agents**: off-chain
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autonomous AI agents which run as a multi-agent-system (MAS) and offer enhanced functionalities
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on-chain. AI agents expand the range of operations that traditional
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smart contracts provide, making it possible to execute **arbitrarily complex operations**
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(such as machine-learning algorithms). Most importantly, agent services are
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(such as machine-learning algorithms). Most importantly, AI agents are
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**decentralized**, **trust-minimized**, **transparent**, and **robust**.
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## Get started developing agent services
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## Get started developing AI agents
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Read the [Open Autonomy documentation](https://stack.olas.network/open-autonomy/) to learn more about agent services. Follow the [set up](https://stack.olas.network/open-autonomy/guides/set_up/) and [quick start](https://stack.olas.network/open-autonomy/guides/quick_start/) guides to start building your own services.
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Read the [Open Autonomy documentation](https://stack.olas.network/open-autonomy/) to learn more about AI agents. Follow the [set up](https://stack.olas.network/open-autonomy/guides/set_up/) and [quick start](https://stack.olas.network/open-autonomy/guides/quick_start/) guides to start building your own AI agents.
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## For developers contributing to the framework: install from source

docs/advanced_reference/commands/autonomy_analyse.md

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Tools for analysing and verifying agent services.
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Tools for analysing and verifying AI agents.
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This command group consists of a number of functionalities to analyse and verify agent services, including {{fsm_app}} skill consistency checks. See the appropriate subcommands for more information.
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This command group consists of a number of functionalities to analyse and verify AI agents, including {{fsm_app}} skill consistency checks. See the appropriate subcommands for more information.
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??? example
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The docstring corresponding to the [Hello World agent service](https://stack.olas.network/demos/hello-world/) is
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The docstring corresponding to the [Hello World AI agent](https://stack.olas.network/demos/hello-world/) is
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```python
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Since the command will automatically append the `_dialogues` postfix if not provided by the user.
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## `autonomy analyse logs`
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Parse logs of an agent service.
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Parse logs of an AI agent.
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### Usage
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```bash
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autonomy analyse logs --from-dir ./abci_build_hAsH/persistent_data/logs -a 'aea_0' -ir ".*consensus.*" -er ".*debug.*"
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```
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These examples demonstrate various ways to filter and analyze agent service logs. You can combine multiple options to narrow down the log output to exactly what you need for debugging or analysis.
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These examples demonstrate various ways to filter and analyze AI agent logs. You can combine multiple options to narrow down the log output to exactly what you need for debugging or analysis.
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## `autonomy analyse benchmarks`
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Aggregate benchmark results from agent service deployments.
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Aggregate benchmark results from AI agent deployments.
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This tool requires the benchmark data generated from service agent's runtime.
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This tool requires the benchmark data generated from agent blueprint's runtime.
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By default the tool will aggregate the output for all the periods and code block types but you can restrict the aggregation to a specific period and/or a specific block type.
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Read the [guide on how to use the benchmarking tool](../developer_tooling/benchmarking.md) for more information.
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## `autonomy analyse service`
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Analyse if the service is ready to be deployed or not.
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Analyse if the AI agent is ready to be deployed or not.
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This tool can be used to analyse a service definition and see if there are any potential issues with configuration which can cause issues when running the deployment.
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This tool can be used to analyse an AI agent definition and see if there are any potential issues with configuration which can cause issues when running the deployment.
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Read the [guide on deployment readiness](../../configure_service/on-chain_deployment_checklist.md) for more information.
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### Options
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`--token-id INTEGER`
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: Token ID of the service
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: Token ID of the AI agent
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`--public-id PUBLIC_ID_OR_HASH`
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: Public ID of the service
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: Public ID of the AI agent
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`--use-celo` 
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### Examples
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Analyse the service `valory/hello_world` using
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Analyse the AI agent `valory/hello_world` using
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```bash
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autonomy analyse service --public-id valory/hello_world
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```
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Analyse an on-chain service with token ID `1` using
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Analyse an on-chain AI agent with token ID `1` using
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```bash
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autonomy analyse service --token-id 1

docs/advanced_reference/commands/autonomy_build-image.md

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Builds the agent image for a service.
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Builds the agent blueprint image for an AI agent.
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This command builds the Docker runtime images for the agent defined in a service configuration file `service.yaml`. By default, the command tags the generated images as
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This command builds the Docker runtime images for the agent blueprint defined in an AI agent configuration file `service.yaml`. By default, the command tags the generated images as
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```
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where `<author>` is the author name from the local CLI config (specified with `autonomy init`), `oar` stands for "Open Autonomy Runtime", and `<agent_package>:<package_hash>` is the `PUBLIC_ID` of the agent. These default tags can be modified using certain options described below.
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where `<author>` is the author name from the local CLI config (specified with `autonomy init`), `oar` stands for "Open Autonomy Runtime", and `<agent_package>:<package_hash>` is the `PUBLIC_ID` of the agent blueprint. These default tags can be modified using certain options described below.
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## Options
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: Specify custom `Dockerfile` for building the agent blueprint
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* Build the runtime image for an AI agent located in the folder `your_ai_agent`:
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autonomy build-image --service-dir /your_ai_agent
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* Build an agent blueprint image with a custom version tag:
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