Anatomy of a solution
This chapter presents the high level concepts and constructs of the Owl Agent framework and how it is used in the context of a custom solution.
Agent is a deployable unit built up by choreographing one or more llm, each with its own workflow that can leverage external tools, and guided by prompts.
A typical solution includes: 1/ a front end to let a human interact with the system, 2/ a backend to manage the life cycle of agents integrated with a LLM running as a service, with dynamic integration to tools and functions, vector store retrievers, and decision services. 3/ Decision service with inference rules to control the decision to be made.
4/ The conversation is stateful, persisted and integrated with the different agents defined in the solution.
The Owl Agent backend may manage multiple concurrent conversations and multiple agents instances. It can scale horizontally too.
Key concepts
The main concepts the framework defines and uses are:
- An Agent manages a co-ordinated set of calls to a Large Language Model, with a prompt and tools, to accomplish a subtask.
- Prompts, are
System promptsin the Generative AI context. They define what the LLM should do
The following diagram presents, one agent that integrate one LLM, with a set of tools. One tool is helping to access a client given its name, queries a database, one tool is to compute the next best action is send structured data to a decision service, to get better decsion, and finally one is a retriever to access collections in a vector database to support Retrieved Augmented Generation use cases.
Tools can be any python function, ot proxies to remote business service.
Agents
An agent is an interactive application or solution that supports a specific business use case, like helping a worker performing a specific task of a business process. The execution of the agent involves the coordination of one or more LLMs. Agents may be stateful to preserve the state of a conversation using snapshot capabilities.
Agent management has two parts: 1/ the management of the OwlAgent entity definitions with REST resources and a persistence repository, and 2/ the agent runner instance which manages conversations:
In any solution the conversation manager service use one agent runner.
Prompts
Documents
Tools
Agentic workflow
A customizable agent backend
Backend APIs
Hooks to custom code
Coming soon