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kaikun213 committed Feb 15, 2024
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## How it works

### Reliability
AgentKit attempts to solve the reliability issue of agents such as ReAct agents by constraining the potential routes the agent can take to a pre-configured sets of routes, or **Action Plans**. Since for many use cases the potential routes the agent can take are known, we can use our human domain expertise to steer the agent in the right direction, and reduce it going into unexpected directions or rabbit holes. This is achieved by combining a **Meta Agent** with **Action Plans**: A set of tools which are executed linearily and in parallel, similar to a Chain. The Meta Agent takes in the user prompt and outputs the most suited Action Plan to generate an answer. Note: implementing multiple Meta Agents is possible, generating a tree of possible routes.
AgentKit attempts to solve the reliability issue of agents such as ReAct agents by constraining the potential routes the agent can take to a pre-configured sets of routes, or **Action Plans**. Since for many use cases the potential routes the agent can take are known, we can use our human domain expertise to steer the agent in the right direction, and reduce it going into unexpected directions or rabbit holes. This is achieved by combining a **Meta Agent** with **Action Plans**: A set of tools which are executed linearly and in parallel, similar to a Chain. The Meta Agent takes in the user prompt and outputs the most suited Action Plan to generate an answer. Note: implementing multiple Meta Agents is possible, generating a tree of possible routes.

### User experience
To optimize user experience, the intermediary output of every step in the Action Plan can be shown to the user. For example, consider an Action Plan consisting of 2 toolsets: `[[sql_tool, pdf_tool], [generate_summary_tool, visualize_tool]]`. In the first action step, information from a SQL database and a vector database with embedded PDFs are retrieved in parallel. The retrieved data and most relevant PDF are streamed to the UI as soon as the first action step finishes. In the second action step, the output from step 1 is passed to a tool that generates a text summary and a tool that creates a JSX visualization from the data, which is streamed to the UI to create the final answer.
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The project spun of a combination of different templates. One great inspiration is [fastapi-alembic-sqlmodel-async](https://github.com/jonra1993/fastapi-alembic-sqlmodel-async), which provided the foundations for the FastAPI setup. Please check them out!

Great thanks to all the contributors:
[@kaikun213](https://github.com/kaikun213) [@drivian](https://github.com/drivian) [@ielmansouri](https://github.com/ielmansouri) [@mastersplinter](https://github.com/mastersplinter) [@tanmaygupta9](https://github.com/tanmaygupta9) [@sofglide](https://github.com/sofglide) [@harticode](https://github.com/harticode) [@edenbd](https://github.com/edenbd) [@benhowt](https://github.com/benhowt) [@carelschw](https://github.com/carelschw) [@gustafvh](https://github.com/gustafvh) [@casper321](https://github.com/casper321) [@modvinden1](https://github.com/modvinden1) [@valerie-jzr](https://github.com/valerie-jzr) [@ispoljari](https://github.com/ispoljari) [martinthenext](https://github.com/martinthenext)
[@kaikun213](https://github.com/kaikun213) [@drivian](https://github.com/drivian) [@ielmansouri](https://github.com/ielmansouri) [@mastersplinter](https://github.com/mastersplinter) [@tanmaygupta9](https://github.com/tanmaygupta9) [@sofglide](https://github.com/sofglide) [@harticode](https://github.com/harticode) [@edenbd](https://github.com/edenbd) [@benhowt](https://github.com/benhowt) [@carelschw](https://github.com/carelschw) [@gustafvh](https://github.com/gustafvh) [@casper321](https://github.com/casper321) [@modvinden1](https://github.com/modvinden1) [@valerie-jzr](https://github.com/valerie-jzr) [@ispoljari](https://github.com/ispoljari) [@martinthenext](https://github.com/martinthenext)

Please read `CONTRIBUTING.md` for more details on how to contribute.
PRs are welcome ❤️
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